Risk & Position DashboardRisk & Position Dashboard
Overview
The Risk & Position Dashboard is a comprehensive trading tool designed to help traders calculate optimal position sizes, manage risk, and visualize potential profit/loss scenarios before entering trades. This indicator provides real-time calculations for position sizing based on account size, risk percentage, and stop-loss levels, while displaying multiple take-profit targets with customizable risk-reward ratios.
Key Features
Position Sizing & Risk Management:
Automatic position size calculation based on account size and risk percentage
Support for leveraged trading with maximum leverage limits
Fractional shares support for brokers that allow partial share trading
Real-time fee calculation including entry, stop-loss, and take-profit fees
Break-even price calculation including trading fees
Multi-Target Profit Management:
Support for up to 3 take-profit levels with individual portion allocations
Customizable risk-reward ratios for each take-profit target
Visual profit/loss zones displayed as colored boxes on the chart
Individual profit calculations for each take-profit level
Visual Dashboard:
Clean, customizable table display showing all key metrics
Configurable label positioning and styling options
Real-time tracking of whether stop-loss or take-profit levels have been reached
Color-coded visual zones for easy identification of risk and reward areas
Advanced Configuration:
Comprehensive input validation and error handling
Support for different chart timeframes and symbols
Customizable colors, fonts, and display options
Hide/show individual data fields for personalized dashboard views
How to Use
Set Account Parameters: Configure your account size, maximum risk percentage per trade, and trading fees in the "Account Settings" section.
Define Trade Setup: Use the "Entry" time picker to select your entry point on the chart, then input your entry price and stop-loss level.
Configure Take Profits: Set your desired risk-reward ratios and portion allocations for each take-profit level. The script supports 1-3 take-profit targets.
Analyze Results: The dashboard will automatically calculate and display position size, number of shares, potential profits/losses, fees, and break-even levels.
Visual Confirmation: Colored boxes on the chart show profit zones (green) and loss zones (red), with lines extending to current price levels.
Reset Entry and SL:
You can easily reset the entry and stop-loss by clicking the "Reset points..." button from the script's "More" menu.
This is useful if you want to quickly clear your current trade setup and start fresh without manually adjusting the points on the chart.
Calculations
The script performs sophisticated calculations including:
Position size based on risk amount and price difference between entry and stop-loss
Leverage requirements and position amount calculations
Fee-adjusted risk-reward ratios for realistic profit expectations
Break-even price including all trading costs
Individual profit calculations for partial position closures
Detailed Take-Profit Calculation Formula:
The take-profit prices are calculated using the following mathematical formula:
// Core variables:
// risk_amount = account_size * (risk_percentage / 100)
// total_risk_per_share = |entry_price - sl_price| + (entry_price * fee%) + (sl_price * fee%)
// shares = risk_amount / total_risk_per_share
// direction_factor = 1 for long positions, -1 for short positions
// Take-profit calculation:
net_win = total_risk_per_share * shares * RR_ratio
tp_price = (net_win + (direction_factor * entry_price * shares) + (entry_price * fee% * shares)) / (direction_factor * shares - fee% * shares)
Step-by-step example for a long position (based on screenshot):
Account Size: 2,000 USDT, Risk: 2% = 40 USDT
Entry: 102,062.9 USDT, Stop Loss: 102,178.4 USDT, Fee: 0.06%
Risk per share: |102,062.9 - 102,178.4| + (102,062.9 × 0.0006) + (102,178.4 × 0.0006) = 115.5 + 61.24 + 61.31 = 238.05 USDT
Shares: 40 ÷ 238.05 = 0.168 shares (rounded to 0.17 in display)
Position Size: 0.17 × 102,062.9 = 17,350.69 USDT
Position Amount (with 9x leverage): 17,350.69 ÷ 9 = 1,927.85 USDT
For 2:1 RR: Net win = 238.05 × 0.17 × 2 = 80.94 USDT
TP1 price = (80.94 + (1 × 102,062.9 × 0.17) + (102,062.9 × 0.0006 × 0.17)) ÷ (1 × 0.17 - 0.0006 × 0.17) = 101,464.7 USDT
For 3:1 RR: TP2 price = 101,226.7 USDT (following same formula with RR=3)
This ensures that after accounting for all fees, the actual risk-reward ratio matches the specified target ratio.
Risk Management Features
Maximum Trade Amount: Optional setting to limit position size regardless of account size
Leverage Limits: Built-in maximum leverage protection
Fee Integration: All calculations include realistic trading fees for accurate expectations
Validation: Automatic checking that take-profit portions sum to 100%
Historical Tracking: Visual indication when stop-loss or take-profit levels are reached (within last 5000 bars)
Understanding Max Trade Amount - Multiple Simultaneous Trades:
The "Max Trade Amount" feature is designed for traders who want to open multiple positions simultaneously while maintaining proper risk management. Here's how it works:
Key Concept:
- Risk percentage (2%) always applies to your full Account Size
- Max Trade Amount limits the capital allocated per individual trade
- This allows multiple trades with full risk on each trade
Example from Screenshot:
Account Size: 2,000 USDT
Max Trade Amount: 500 USDT
Risk per Trade: 2% × 2,000 = 40 USDT per trade
Stop Loss Distance: 0.11% from entry
Result: Position Size = 17,350.69 USDT with 35x leverage
Total Risk (including fees): 40.46 USDT
Multiple Trades Strategy:
With this setup, you can open:
Trade 1: 40 USDT risk, 495.73 USDT position amount (35x leverage)
Trade 2: 40 USDT risk, 495.73 USDT position amount (35x leverage)
Trade 3: 40 USDT risk, 495.73 USDT position amount (35x leverage)
Trade 4: 40 USDT risk, 495.73 USDT position amount (35x leverage)
Total Portfolio Exposure:
- 4 simultaneous trades = 4 × 495.73 = 1,982.92 USDT position amount
- Total risk exposure = 4 × 40 = 160 USDT (8% of account)
Поиск скриптов по запросу "entry"
PivotBoss VWAP Bands (Auto TF) - FixedWhat this indicator shows (high level)
The indicator plots a VWAP line and three bands above (R1, R2, R3) and three bands below (S1, S2, S3).
Band spacing is computed from STD(abs(VWAP − price), N) and multiplied by 1, 2 and 3 to form R1–R3 / S1–S3. The script is timeframe-aware: on 30m/1H charts it uses Weekly VWAP and weekly bands; on Daily charts it uses Monthly VWAP and monthly bands; otherwise it uses the session/chart VWAP.
VWAP = the market’s volume-weighted average price (a measure of fair value). Bands = volatility-scaled zones around that fair value.
Trading idea — concept summary
VWAP = fair value. Price above VWAP implies bullish bias; below VWAP implies bearish bias.
Bands = graded overbought/oversold zones. R1/S1 are near-term limits, R2/S2 are stronger, R3/S3 are extreme.
Use trend alignment + price action + volume to choose higher-probability trades. VWAP bands give location and magnitude; confirmations reduce false signals.
Entry rules (multiple strategies with examples)
A. Momentum breakout (trend-following) — preferred on trending markets
Setup: Price consolidates near or below R1 and then closes above R1 with above-average volume. Chart: 30m/1H (Weekly VWAP) or Daily (Monthly VWAP) depending on your timeframe.
Entry: Enter long at the close of the breakout bar that closes above R1.
Stop-loss: Place initial stop below the higher of (VWAP or recent swing low). Example: if price broke R1 at ₹1,200 and VWAP = ₹1,150, set stop at ₹1,145 (5 rupee buffer below VWAP) or below the last swing low if that is wider.
Target: Partial target at R2, full target at R3. Trail stop to VWAP or to R1 after price reaches R2.
Example numeric: Weekly VWAP = ₹1,150, R1 = ₹1,200, R2 = ₹1,260. Buy at ₹1,205 (close above R1), stop ₹1,145, target1 ₹1,260 (R2), target2 ₹1,320 (R3).
B. Mean-reversion fade near bands — for range-bound markets
Setup: Market is not trending (VWAP flatish). Price rallies up to R2 or R3 and shows rejection (pin bar, bearish engulfing) on increasing or neutral volume.
Entry: Enter short after a confirmed rejection candle that fails to sustain above R2 or R3 (prefer confirmation: close back below R1 or below the rejection candle low).
Stop-loss: Just above the recent high (e.g., 1–2 ATR or a fixed buffer above R2/R3).
Target: First target VWAP, second target S1. Reduce size if taking R3 fade as it’s an extreme.
Example numeric: VWAP = ₹950, R2 = ₹1,020. Price spikes to ₹1,025 and forms a bearish engulfing candle. Enter short at ₹1,015 after the next close below ₹1,020. Stop at ₹1,035, target VWAP ₹950.
C. Pullback entries in trending markets — higher probability
Setup: Price is above VWAP and trending higher (higher highs and higher lows). Price pulls back toward VWAP or S1 with decreasing downside volume and a reversal candle forms.
Entry: Long when price forms a bullish reversal (hammer/inside-bar) with a close back above the pullback candle.
Stop-loss: Below the pullback low (or below S2 if a larger stop is justified).
Target: VWAP then R1; if momentum resumes, trail toward R2/R3.
Example numeric: Price trending above Weekly VWAP at ₹1,400; pullback to S1 at ₹1,360. Enter long at ₹1,370 when a bullish candle closes; stop at ₹1,350; first target VWAP ₹1,400, second target R1 ₹1,450.
Exit rules and money management
Basic exit hierarchy
Hard stop exit — when price hits initial stop-loss. Always use.
Target exit — take partial profits at R1/R2 (for longs) or S1/S2 (for shorts). Use trailing stops for the remainder.
VWAP invalidation — if you entered long above VWAP and price returns and closes significantly below VWAP, consider exiting (condition depends on timeframe and trade size).
Price action exit — reversal patterns (strong opposite candle, bearish/bullish engulfing) near targets or beyond signals to exit.
Trailing rules
After price reaches R2, move stop to breakeven + a small buffer or to VWAP.
After price reaches R3, trail by 1 ATR or lock a defined profit percentage.
Position sizing & risk
Risk per trade: commonly 0.5–2% of account equity.
Determine position size by RiskAmount ÷ (EntryPrice − StopPrice).
If the stop distance is large (e.g., trading R3 fades), reduce position size.
Filters & confirmation (to reduce false signals)
Volume filter: For breakouts, require volume above short-term average (e.g., >20-period average). Breakouts on low volume are suspect.
Trend filter: Only take breakouts in the direction of the higher-timeframe trend (for example, use Daily/Weekly trend when trading 30m/1H).
Candle confirmation: Prefer entries on close of the confirming candle (not intrabar noise).
Multiple confirmations: When R1 break happens but RSI/plotted momentum indicator does not confirm, treat signal as lower probability.
Special considerations for timeframe-aware logic
On 30m/1H the script uses Weekly VWAP/bands. That means band levels change only on weekly candles — they are strong, structural levels. Treat R1/R2/R3 as significant and expect fewer, stronger signals.
On Daily, the script uses Monthly VWAP/bands. These are wider; trades should allow larger stops and smaller position sizes (or be used for swing trades).
On other intraday charts you get session VWAP (useful for intraday scalps).
Example: If you trade 1H and the Weekly R1 is at ₹2,400 while session VWAP is ₹2,350, a close above Weekly R1 represents a weekly-level breakout — prefer that for swing entries rather than scalps.
Example trade walkthrough (step-by-step)
Context: 1H chart, auto-mapped → Weekly VWAP used.
Weekly VWAP = ₹3,000; R1 = ₹3,080; R2 = ₹3,150.
Price consolidates below R1. A large bullish candle closes at ₹3,085 with volume 40% above the 20-bar average.
Entry: Buy at close ₹3,085.
Stop: Place stop at ₹2,995 (just under Weekly VWAP). Risk = ₹90.
Position size: If risking ₹900 per trade → size = 900 ÷ 90 = 10 units.
Targets: Partial take-profit at R2 = ₹3,150; rest trailed with stop moved to breakeven after R2 is hit.
If price reverses and closes below VWAP within two bars, exit immediately to limit drawdown.
When to avoid trading these signals
High-impact news (earnings, macro announcements) that can gap through bands unpredictably.
Thin markets with low volume — VWAP loses significance when volumes are extremely low.
When weekly/monthly bands are flat but intraday price is volatile without clear structure — prefer session VWAP on smaller timeframes.
Alerts & automation suggestions
Alert on close above R1 / below S1 (use the built-in alertcondition the script adds). For higher-confidence alerts, require volume filter in the alert condition.
Automated order rules (if you automate): use limit entry at breakout close plus a small slippage buffer, immediate stop order, and OCO for TP and SL.
BackTestLibLibrary "BackTestLib"
Allows backtesting indicator performance. Tracks typical metrics such as won/loss, profit factor, draw down, etc. Trading View strategy library provides similar (and more comprehensive)
functionality but only works with strategies. This libary was created to address performance tracking within indicators.
Two primary outputs are generated:
1. Summary Table: Displays overall performance metrics for the indicator over the chart's loaded timeframe and history
2. Details Table: Displays a table of individual trade entries and exits. This table can grow larger than the available chart space. It does have a max number of rows supported. I haven't
found a way to add scroll bars or scroll bar equivalents yet.
f_init(data, _defaultStopLoss, _defaultTakeProfit, _useTrailingStop, _useTraingStopToBreakEven, _trailingStopActivation, _trailingStopOffset)
f_init Initialize the backtest data type. Called prior to using the backtester functions
Parameters:
data (backtesterData) : backtesterData to initialize
_defaultStopLoss (float) : Default trade stop loss to apply
_defaultTakeProfit (float) : Default trade take profit to apply
_useTrailingStop (bool) : Trailing stop enabled
_useTraingStopToBreakEven (bool) : When trailing stop active, trailing stop will increase no further than the entry price
_trailingStopActivation (int) : When trailing stop active, trailing will begin once price exceeds base stop loss by this number of points
_trailingStopOffset (int) : When trailing stop active, it will trail the max price achieved by this number of points
Returns: Initialized data set
f_buildResultStr(_resultType, _price, _resultPoints, _numWins, _pointsWon, _numLoss, _pointsLost)
f_buildResultStr Helper function to construct a string of resutling data for exit tooltip labels
Parameters:
_resultType (string)
_price (float)
_resultPoints (float)
_numWins (int)
_pointsWon (float)
_numLoss (int)
_pointsLost (float)
f_buildResultLabel(data, labelVertical, labelOffset, long)
f_buildResultLabel Helper function to construct an Exit label for display on the chart
Parameters:
data (backtesterData)
labelVertical (bool)
labelOffset (int)
long (bool)
f_updateTrailingStop(_entryPrice, _curPrice, _sl, _tp, trailingStopActivationInput, trailingStopOffsetInput, useTrailingStopToBreakEven)
f_updateTrailingStop Helper function to advance the trailing stop as price action dictates
Parameters:
_entryPrice (float)
_curPrice (float)
_sl (float)
_tp (float)
trailingStopActivationInput (float)
trailingStopOffsetInput (float)
useTrailingStopToBreakEven (bool)
Returns: Updated stop loss for current price action
f_enterShort(data, entryPrice, fixedStopLoss)
f_enterShort Helper function to enter a short and collect data necessary for tracking the trade entry
Parameters:
data (backtesterData)
entryPrice (float)
fixedStopLoss (float)
Returns: Updated backtest data
f_enterLong(data, entryPrice, fixedStopLoss)
f_enterLong Helper function to enter a long and collect data necessary for tracking the trade entry
Parameters:
data (backtesterData)
entryPrice (float)
fixedStopLoss (float)
Returns: Updated backtest data
f_exitTrade(data)
f_enterLong Helper function to exit a trade and update/reset tracking data
Parameters:
data (backtesterData)
Returns: Updated backtest data
f_checkTradeConditionForExit(data, condition, curPrice, enableRealTime)
f_checkTradeConditionForExit Helper function to determine if provided condition indicates an exit
Parameters:
data (backtesterData)
condition (bool) : When true trade will exit
curPrice (float)
enableRealTime (bool) : When true trade will evaluate if barstate is relatime or barstate is confirmed; otherwise just checks on is confirmed
Returns: Updated backtest data
f_checkTrade(data, curPrice, curLow, curHigh, enableRealTime)
f_checkTrade Helper function to determine if current price action dictates stop loss or take profit exit
Parameters:
data (backtesterData)
curPrice (float)
curLow (float)
curHigh (float)
enableRealTime (bool) : When true trade will evaluate if barstate is relatime or barstate is confirmed; otherwise just checks on is confirmed
Returns: Updated backtest data
f_fillCell(_table, _column, _row, _title, _value, _bgcolor, _txtcolor, _text_size)
f_fillCell Helper function to construct result table cells
Parameters:
_table (table)
_column (int)
_row (int)
_title (string)
_value (string)
_bgcolor (color)
_txtcolor (color)
_text_size (string)
Returns: Table cell
f_prepareStatsTable(data, drawTesterSummary, drawTesterDetails, summaryTableTextSize, detailsTableTextSize, displayRowZero, summaryTableLocation, detailsTableLocation)
f_fillCell Helper function to populate result table
Parameters:
data (backtesterData)
drawTesterSummary (bool)
drawTesterDetails (bool)
summaryTableTextSize (string)
detailsTableTextSize (string)
displayRowZero (bool)
summaryTableLocation (string)
detailsTableLocation (string)
Returns: Updated backtest data
backtesterData
backtesterData - container for backtest performance metrics
Fields:
tradesArray (array) : Array of strings with entries for each individual trade and its results
pointsBalance (series float) : Running sum of backtest points won/loss results
drawDown (series float) : Running sum of backtest total draw down points
maxDrawDown (series float) : Running sum of backtest total draw down points
maxRunup (series float) : Running sum of max points won over the backtest
numWins (series int) : Number of wins of current backtes set
numLoss (series int) : Number of losses of current backtes set
pointsWon (series float) : Running sum of points won to date
pointsLost (series float) : Running sum of points lost to date
entrySide (series string) : Current entry long/short
tradeActive (series bool) : Indicates if a trade is currently active
tradeComplete (series bool) : Indicates if a trade just exited (due to stop loss or take profit)
entryPrice (series float) : Current trade entry price
entryTime (series int) : Current trade entry time
sl (series float) : Current trade stop loss
tp (series float) : Current trade take profit
defaultStopLoss (series float) : Default trade stop loss to apply
defaultTakeProfit (series float) : Default trade take profit to apply
useTrailingStop (series bool) : Trailing stop enabled
useTrailingStopToBreakEven (series bool) : When trailing stop active, trailing stop will increase no further than the entry price
trailingStopActivation (series int) : When trailing stop active, trailing will begin once price exceeds base stop loss by this number of points
trailingStopOffset (series int) : When trailing stop active, it will trail the max price achieved by this number of points
resultType (series string) : Current trade won/lost
exitPrice (series float) : Current trade exit price
resultPoints (series float) : Current trade points won/lost
summaryTable (series table) : Table to deisplay summary info
tradesTable (series table) : Table to display per trade info
position_toolLibrary "position_tool"
Trying to turn TradingView's position tool into a library from which you can draw position tools for your strategies on the chart. Not sure if this is going to work
calcBaseUnit()
Calculates the chart symbol's base unit of change in asset prices.
Returns: (float) A ticks or pips value of base units of change.
calcOrderPipsOrTicks(orderSize, unit)
Converts the `orderSize` to ticks.
Parameters:
orderSize (float) : (series float) The order size to convert to ticks.
unit (simple float) : (simple float) The basic units of change in asset prices.
Returns: (int) A tick value based on a given order size.
calcProfitLossSize(price, entryPrice, isLongPosition)
Calculates a difference between a `price` and the `entryPrice` in absolute terms.
Parameters:
price (float) : (series float) The price to calculate the difference from.
entryPrice (float) : (series float) The price of entry for the position.
isLongPosition (bool)
Returns: (float) The absolute price displacement of a price from an entry price.
calcRiskRewardRatio(profitSize, lossSize)
Calculates a risk to reward ratio given the size of profit and loss.
Parameters:
profitSize (float) : (series float) The size of the profit in absolute terms.
lossSize (float) : (series float) The size of the loss in absolute terms.
Returns: (float) The ratio between the `profitSize` to the `lossSize`
createPosition(entryPrice, entryTime, tpPrice, slPrice, entryColor, tpColor, slColor, textColor, showExtendRight)
Main function to create a position visualization with entry, TP, and SL
Parameters:
entryPrice (float) : (float) The entry price of the position
entryTime (int) : (int) The entry time of the position in bar_time format
tpPrice (float) : (float) The take profit price
slPrice (float) : (float) The stop loss price
entryColor (color) : (color) Color for entry line
tpColor (color) : (color) Color for take profit zone
slColor (color) : (color) Color for stop loss zone
textColor (color) : (color) Color for text labels
showExtendRight (bool) : (bool) Whether to extend lines to the right
Returns: (bool) Returns true when position is closed
CalculatePercentageSlTpLibrary "CalculatePercentageSlTp"
This Library calculate the sl and tp amount in percentage
sl_percentage(entry_price, sl_price)
this function calculates the sl value in percentage
Parameters:
entry_price : indicates the entry level
sl_price : indicates the stop loss level
Returns: stop loss in percentage
tp_percentage(entry_price, tp_price)
this function calculates the tp value in percentage
Parameters:
entry_price : indicates the entry level
tp_price : indicates the take profit level
Returns: take profit in percentage
sl_level(entry_price, sl_percentage)
this function calculates the sl level price
Parameters:
entry_price : indicates the entry level
sl_percentage : indicates the stop loss percentage
Returns: stop loss price in $
tp_level(entry_price, tp_percentage)
this function calculates the tp level price
Parameters:
entry_price : indicates the entry level
tp_percentage : indicates the take profit percentage
Returns: take profit price in $
ApicodeLibrary "Apicode"
percentToTicks(percent, from)
Converts a percentage of the average entry price or a specified price to ticks when the
strategy has an open position.
Parameters:
percent (float) : (series int/float) The percentage of the `from` price to express in ticks, e.g.,
a value of 50 represents 50% (half) of the price.
from (float) : (series int/float) Optional. The price from which to calculate a percentage and convert
to ticks. The default is `strategy.position_avg_price`.
Returns: (float) The number of ticks within the specified percentage of the `from` price if
the strategy has an open position. Otherwise, it returns `na`.
percentToPrice(percent, from)
Calculates the price value that is a specific percentage distance away from the average
entry price or a specified price when the strategy has an open position.
Parameters:
percent (float) : (series int/float) The percentage of the `from` price to use as the distance. If the value
is positive, the calculated price is above the `from` price. If negative, the result is
below the `from` price. For example, a value of 10 calculates the price 10% higher than
the `from` price.
from (float) : (series int/float) Optional. The price from which to calculate a percentage distance.
The default is `strategy.position_avg_price`.
Returns: (float) The price value at the specified `percentage` distance away from the `from` price
if the strategy has an open position. Otherwise, it returns `na`.
percentToCurrency(price, percent)
Parameters:
price (float) : (series int/float) The price from which to calculate the percentage.
percent (float) : (series int/float) The percentage of the `price` to calculate.
Returns: (float) The amount of the symbol's currency represented by the percentage of the specified
`price`.
percentProfit(exitPrice)
Calculates the expected profit/loss of the open position if it were to close at the
specified `exitPrice`, expressed as a percentage of the average entry price.
NOTE: This function may not return precise values for positions with multiple open trades
because it only uses the average entry price.
Parameters:
exitPrice (float) : (series int/float) The position's hypothetical closing price.
Returns: (float) The expected profit percentage from exiting the position at the `exitPrice`. If
there is no open position, it returns `na`.
priceToTicks(price)
Converts a price value to ticks.
Parameters:
price (float) : (series int/float) The price to convert.
Returns: (float) The value of the `price`, expressed in ticks.
ticksToPrice(ticks, from)
Calculates the price value at the specified number of ticks away from the average entry
price or a specified price when the strategy has an open position.
Parameters:
ticks (float) : (series int/float) The number of ticks away from the `from` price. If the value is positive,
the calculated price is above the `from` price. If negative, the result is below the `from`
price.
from (float) : (series int/float) Optional. The price to evaluate the tick distance from. The default is
`strategy.position_avg_price`.
Returns: (float) The price value at the specified number of ticks away from the `from` price if
the strategy has an open position. Otherwise, it returns `na`.
ticksToCurrency(ticks)
Converts a specified number of ticks to an amount of the symbol's currency.
Parameters:
ticks (float) : (series int/float) The number of ticks to convert.
Returns: (float) The amount of the symbol's currency represented by the tick distance.
ticksToStopLevel(ticks)
Calculates a stop-loss level using a specified tick distance from the position's average
entry price. A script can plot the returned value and use it as the `stop` argument in a
`strategy.exit()` call.
Parameters:
ticks (float) : (series int/float) The number of ticks from the position's average entry price to the
stop-loss level. If the position is long, the value represents the number of ticks *below*
the average entry price. If short, it represents the number of ticks *above* the price.
Returns: (float) The calculated stop-loss value for the open position. If there is no open position,
it returns `na`.
ticksToTpLevel(ticks)
Calculates a take-profit level using a specified tick distance from the position's average
entry price. A script can plot the returned value and use it as the `limit` argument in a
`strategy.exit()` call.
Parameters:
ticks (float) : (series int/float) The number of ticks from the position's average entry price to the
take-profit level. If the position is long, the value represents the number of ticks *above*
the average entry price. If short, it represents the number of ticks *below* the price.
Returns: (float) The calculated take-profit value for the open position. If there is no open
position, it returns `na`.
calcPositionSizeByStopLossTicks(stopLossTicks, riskPercent)
Calculates the entry quantity required to risk a specified percentage of the strategy's
current equity at a tick-based stop-loss level.
Parameters:
stopLossTicks (float) : (series int/float) The number of ticks in the stop-loss distance.
riskPercent (float) : (series int/float) The percentage of the strategy's equity to risk if a trade moves
`stopLossTicks` away from the entry price in the unfavorable direction.
Returns: (int) The number of contracts/shares/lots/units to use as the entry quantity to risk the
specified percentage of equity at the stop-loss level.
calcPositionSizeByStopLossPercent(stopLossPercent, riskPercent, entryPrice)
Calculates the entry quantity required to risk a specified percentage of the strategy's
current equity at a percent-based stop-loss level.
Parameters:
stopLossPercent (float) : (series int/float) The percentage of the `entryPrice` to use as the stop-loss distance.
riskPercent (float) : (series int/float) The percentage of the strategy's equity to risk if a trade moves
`stopLossPercent` of the `entryPrice` in the unfavorable direction.
entryPrice (float) : (series int/float) Optional. The entry price to use in the calculation. The default is
`close`.
Returns: (int) The number of contracts/shares/lots/units to use as the entry quantity to risk the
specified percentage of equity at the stop-loss level.
exitPercent(id, lossPercent, profitPercent, qty, qtyPercent, comment, alertMessage)
A wrapper for the `strategy.exit()` function designed for creating stop-loss and
take-profit orders at percentage distances away from the position's average entry price.
NOTE: This function calls `strategy.exit()` without a `from_entry` ID, so it creates exit
orders for *every* entry in an open position until the position closes. Therefore, using
this function when the strategy has a pyramiding value greater than 1 can lead to
unexpected results. See the "Exits for multiple entries" section of our User Manual's
"Strategies" page to learn more about this behavior.
Parameters:
id (string) : (series string) Optional. The identifier of the stop-loss/take-profit orders, which
corresponds to an exit ID in the strategy's trades after an order fills. The default is
`"Exit"`.
lossPercent (float) : (series int/float) The percentage of the position's average entry price to use as the
stop-loss distance. The function does not create a stop-loss order if the value is `na`.
profitPercent (float) : (series int/float) The percentage of the position's average entry price to use as the
take-profit distance. The function does not create a take-profit order if the value is `na`.
qty (float) : (series int/float) Optional. The number of contracts/lots/shares/units to close when an
exit order fills. If specified, the call uses this value instead of `qtyPercent` to
determine the order size. The exit orders reserve this quantity from the position, meaning
other orders from `strategy.exit()` cannot close this portion until the strategy fills or
cancels those orders. The default is `na`, which means the order size depends on the
`qtyPercent` value.
qtyPercent (float) : (series int/float) Optional. A value between 0 and 100 representing the percentage of the
open trade quantity to close when an exit order fills. The exit orders reserve this
percentage from the open trades, meaning other calls to this command cannot close this
portion until the strategy fills or cancels those orders. The percentage calculation
depends on the total size of the applicable open trades without considering the reserved
amount from other `strategy.exit()` calls. The call ignores this parameter if the `qty`
value is not `na`. The default is 100.
comment (string) : (series string) Optional. Additional notes on the filled order. If the value is specified
and not an empty "string", the Strategy Tester and the chart show this text for the order
instead of the specified `id`. The default is `na`.
alertMessage (string) : (series string) Optional. Custom text for the alert that fires when an order fills. If the
value is specified and not an empty "string", and the "Message" field of the "Create Alert"
dialog box contains the `{{strategy.order.alert_message}}` placeholder, the alert message
replaces the placeholder with this text. The default is `na`.
Returns: (void) The function does not return a usable value.
closeAllAtEndOfSession(comment, alertMessage)
A wrapper for the `strategy.close_all()` function designed to close all open trades with a
market order when the last bar in the current day's session closes. It uses the command's
`immediately` parameter to exit all trades at the last bar's `close` instead of the `open`
of the next session's first bar.
Parameters:
comment (string) : (series string) Optional. Additional notes on the filled order. If the value is specified
and not an empty "string", the Strategy Tester and the chart show this text for the order
instead of the automatically generated exit identifier. The default is `na`.
alertMessage (string) : (series string) Optional. Custom text for the alert that fires when an order fills. If the
value is specified and not an empty "string", and the "Message" field of the "Create Alert"
dialog box contains the `{{strategy.order.alert_message}}` placeholder, the alert message
replaces the placeholder with this text. The default is `na`.
Returns: (void) The function does not return a usable value.
closeAtEndOfSession(entryId, comment, alertMessage)
A wrapper for the `strategy.close()` function designed to close specific open trades with a
market order when the last bar in the current day's session closes. It uses the command's
`immediately` parameter to exit the trades at the last bar's `close` instead of the `open`
of the next session's first bar.
Parameters:
entryId (string)
comment (string) : (series string) Optional. Additional notes on the filled order. If the value is specified
and not an empty "string", the Strategy Tester and the chart show this text for the order
instead of the automatically generated exit identifier. The default is `na`.
alertMessage (string) : (series string) Optional. Custom text for the alert that fires when an order fills. If the
value is specified and not an empty "string", and the "Message" field of the "Create Alert"
dialog box contains the `{{strategy.order.alert_message}}` placeholder, the alert message
replaces the placeholder with this text. The default is `na`.
Returns: (void) The function does not return a usable value.
sortinoRatio(interestRate, forceCalc)
Calculates the Sortino ratio of the strategy based on realized monthly returns.
Parameters:
interestRate (simple float) : (simple int/float) Optional. The *annual* "risk-free" return percentage to compare against
strategy returns. The default is 2, meaning it uses an annual benchmark of 2%.
forceCalc (bool) : (series bool) Optional. A value of `true` forces the function to calculate the ratio on the
current bar. If the value is `false`, the function calculates the ratio only on the latest
available bar for efficiency. The default is `false`.
Returns: (float) The Sortino ratio, which estimates the strategy's excess return per unit of
downside volatility.
sharpeRatio(interestRate, forceCalc)
Calculates the Sharpe ratio of the strategy based on realized monthly returns.
Parameters:
interestRate (simple float) : (simple int/float) Optional. The *annual* "risk-free" return percentage to compare against
strategy returns. The default is 2, meaning it uses an annual benchmark of 2%.
forceCalc (bool) : (series bool) Optional. A value of `true` forces the function to calculate the ratio on the
current bar. If the value is `false`, the function calculates the ratio only on the latest
available bar for efficiency. The default is `false`.
Returns: (float) The Sortino ratio, which estimates the strategy's excess return per unit of
total volatility.
Commission-aware Trade LabelsCommission-aware Trade Labels
Description:
This library provides an easy way to visualize take-profit and stop-loss levels on your chart, taking into account trading commissions. The library calculates and displays the net profit or loss, along with other useful information such as risk/reward ratio, shares, and position size.
Features:
Configurable take-profit and stop-loss prices or percentages.
Set entry amount or shares.
Calculates and displays the risk/reward ratio.
Shows net profit or loss, considering trading commissions.
Customizable label appearance.
Usage:
Add the script to your chart.
Create an Order object for take-profit and stop-loss with desired configurations.
Call target_label() and stop_label() methods for each order object.
Example:
target_order = Order.new(take_profit_price=27483, stop_loss_price=28000, shares=0.2)
stop_order = Order.new(stop_loss_price=29000, shares=1)
target_order.target_label()
stop_order.stop_label()
This script is a powerful tool for visualizing your trading strategy's performance and helps you make better-informed decisions by considering trading commissions in your profit and loss calculations.
Library "tradelabels"
entry_price(this)
Parameters:
this : Order object
@return entry_price
take_profit_price(this)
Parameters:
this : Order object
@return take_profit_price
stop_loss_price(this)
Parameters:
this : Order object
@return stop_loss_price
is_long(this)
Parameters:
this : Order object
@return entry_price
is_short(this)
Parameters:
this : Order object
@return entry_price
percent_to_target(this, target)
Parameters:
this : Order object
target : Target price
@return percent
risk_reward(this)
Parameters:
this : Order object
@return risk_reward_ratio
shares(this)
Parameters:
this : Order object
@return shares
position_size(this)
Parameters:
this : Order object
@return position_size
commission_cost(this, target_price)
Parameters:
this : Order object
@return commission_cost
target_price
net_result(this, target_price)
Parameters:
this : Order object
target_price : The target price to calculate net result for (either take_profit_price or stop_loss_price)
@return net_result
create_take_profit_label(this, prefix, size, offset_x, bg_color, text_color)
Parameters:
this
prefix
size
offset_x
bg_color
text_color
create_stop_loss_label(this, prefix, size, offset_x, bg_color, text_color)
Parameters:
this
prefix
size
offset_x
bg_color
text_color
create_entry_label(this, prefix, size, offset_x, bg_color, text_color)
Parameters:
this
prefix
size
offset_x
bg_color
text_color
create_line(this, target_price, line_color, offset_x, line_style, line_width, draw_entry_line)
Parameters:
this
target_price
line_color
offset_x
line_style
line_width
draw_entry_line
Order
Order
Fields:
entry_price : Entry price
stop_loss_price : Stop loss price
stop_loss_percent : Stop loss percent, default 2%
take_profit_price : Take profit price
take_profit_percent : Take profit percent, default 6%
entry_amount : Entry amount, default 5000$
shares : Shares
commission : Commission, default 0.04%
Katz Exploding PowerBand FilterUnderstanding the Katz Exploding PowerBand Filter (EPBF) v2.4
1. Indicator Overview
The Katz Exploding PowerBand Filter (EPBF) is an advanced technical indicator designed to identify moments of expanding bullish or bearish momentum, often referred to as "power." It operates as a standalone oscillator in a separate pane below the main price chart.
Its primary goal is to measure underlying market strength by calculating custom "Bull" and "Bear" power components. These components are then filtered through a versatile moving average and a dual signal line system to generate clear entry and exit signals. This indicator is not a simple momentum oscillator; it uses a unique calculation based on exponential envelopes of both price and squared price to derive its values.
2. On-Chart Lines and Components
The indicator pane consists of five main lines:
Bullish Component (Thick Green/Blue/Yellow/Gray Line): This is the core of the indicator. It represents the calculated bullish "power" or momentum in the market.
Bright Green: Indicates a strong, active long signal condition.
Blue: Shows the bull component is above the MA filter, but the filter itself is still pointing down—a potential sign of a reversal or weakening downtrend.
Yellow: A warning sign that bullish power is weakening and has fallen below the primary signal lines.
Gray: Represents neutral or insignificant bullish power.
Bearish Component (Thick Red/Purple/Yellow/Gray Line): This line represents the calculated bearish "power" or downward momentum.
Bright Red: Indicates a strong, active short signal condition.
Purple: Shows the bear component is above the MA filter, but the filter itself is still pointing down—a sign of potential trend continuation.
Yellow: A warning sign that bearish power is weakening.
Gray: Represents neutral or insignificant bearish power.
MA Filter (Purple Line): This is the main filter, calculated using the moving average type and length you select in the settings (e.g., HullMA, EMA). The Bull and Bear components are compared against this line to determine the underlying trend bias.
Signal Line 1 (Orange Line): A fast Exponential Moving Average (EMA) of the stronger power component. It acts as the first level of dynamic support or resistance for the power lines.
Signal Line 2 (Lime/Gray Line): A slower EMA that acts as a confirmation filter.
Lime Green: The line turns lime when it is rising and the faster Signal Line 1 is above it, indicating a confirmed bullish trend in momentum.
Gray: Indicates a neutral or bearish momentum trend.
3. On-Chart Symbols and Their Meanings
Various characters are plotted at the bottom of the indicator pane to provide clear, actionable signals.
L (Pre-Long Signal): The first sign of a potential long entry. It appears when the Bullish Component rises and crosses above both signal lines for the first time.
S (Pre-Short Signal): The first sign of a potential short entry. It appears when the Bearish Component rises and crosses above both signal lines for the first time.
▲ (Post-Long Signal): A stronger confirmation for a long entry. It appears with the 'L' signal only if the momentum trend is also confirmed bullish (i.e., the slower Signal Line 2 is lime green).
▼ (Post-Short Signal): A stronger confirmation for a short entry. It appears with the 'S' signal only if the momentum trend is confirmed bullish.
Exit / Take-Profit Symbols:
These symbols appear when a power component crosses below a line, suggesting that momentum is fading and it may be time to take profit.
⚠️ (Exit Signal 1): The Bull/Bear component has crossed below the main MA Filter. This is the first and most sensitive take-profit signal.
☣️ (Exit Signal 2): The Bull/Bear component has crossed below the faster Signal Line 1. This is a moderate take-profit signal.
🚼 (Exit Signal 3): The Bull/Bear component has crossed below the slower Signal Line 2. This is the slowest take-profit signal, suggesting the trend is more definitively exhausted.
4. Trading Strategy and Rules
Long Entry Rules:
Initial Signal: Wait for an L to appear at the bottom of the indicator. This confirms that bullish power is expanding.
Confirmation (Recommended): For a higher-probability trade, wait for a green ▲ symbol to appear. This confirms the underlying momentum trend aligns with the signal.
Entry: Enter a long (buy) position on the opening of the next candle after the signal appears.
Short Entry Rules:
Initial Signal: Wait for an S to appear at the bottom of the indicator. This confirms that bearish power is expanding.
Confirmation (Recommended): For a higher-probability trade, wait for a maroon ▼ symbol to appear. This confirms the underlying momentum trend aligns with the signal.
Entry: Enter a short (sell) position on the opening of the next candle after the signal appears.
Take Profit (TP) Rules:
The indicator provides three levels of take-profit signals. You can choose to exit your entire position or scale out at each level.
For a long trade, exit when you see ⚠️, ☣️, or 🚼 appear below the Bullish Component.
For a short trade, exit when you see ⚠️, ☣️, or 🚼 appear below the Bearish Component.
Stop Loss (SL) Rules:
The indicator does not provide an explicit stop loss. You must use your own risk management rules. Common methods include:
Swing High/Low: For a long position, place your stop loss below the most recent significant swing low on the price chart. For a short position, place it above the most recent swing high.
ATR-Based: Use an Average True Range (ATR) indicator to set a volatility-based stop loss.
Fixed Percentage: Risk a fixed percentage (e.g., 1-2%) of your account on the trade.
5. Disclaimer
This indicator is a tool for technical analysis and should not be considered financial advice. All trading involves significant risk, and past performance is not indicative of future results. The signals generated by this indicator are probabilistic and can result in losing trades. Always use proper risk management, such as setting a stop loss, and never risk more than you are willing to lose. It is recommended to backtest this indicator and use it in conjunction with other forms of analysis before trading with real capital. The indicator should only be used for educational purposes.
EAOBS by MIGVersion 1
1. Strategy Overview Objective: Capitalize on breakout movements in Ethereum (ETH) price after the Asian open pre-market session (7:00 PM–7:59 PM EST) by identifying high and low prices during the session and trading breakouts above the high or below the low.
Timeframe: Any (script is timeframe-agnostic, but align with session timing).
Session: Pre-market session (7:00 PM–7:59 PM EST, adjustable for other time zones, e.g., 12:00 AM–12:59 AM GMT).
Risk-Reward Ratios (R:R): Targets range from 1.2:1 to 5.2:1, with a fixed stop loss.
Instrument: Ethereum (ETH/USD or ETH-based pairs).
2. Market Setup Session Monitoring: Monitor ETH price action during the pre-market session (7:00 PM–7:59 PM EST), which aligns with the Asian market open (e.g., 9:00 AM–9:59 AM JST).
The script tracks the highest high and lowest low during this session.
Breakout Triggers: Buy Signal: Price breaks above the session’s high after the session ends (7:59 PM EST).
Sell Signal: Price breaks below the session’s low after the session ends.
Visualization: The session is highlighted on the chart with a white background.
Horizontal lines are drawn at the session’s high and low, extended for 30 bars, along with take-profit (TP) and stop-loss (SL) levels.
3. Entry Rules Long (Buy) Entry: Enter a long position when the price breaks above the session’s high price after 7:59 PM EST.
Entry price: Just above the session high (e.g., add a small buffer, like 0.1–0.5%, to avoid false breakouts, depending on volatility).
Short (Sell) Entry: Enter a short position when the price breaks below the session’s low price after 7:59 PM EST.
Entry price: Just below the session low (e.g., subtract a small buffer, like 0.1–0.5%).
Confirmation: Use a candlestick close above/below the breakout level to confirm the entry.
Optionally, add volume confirmation or a momentum indicator (e.g., RSI or MACD) to filter out weak breakouts.
Position Size: Calculate position size based on risk tolerance (e.g., 1–2% of account per trade).
Risk is determined by the stop-loss distance (10 points, as defined in the script).
4. Exit Rules Take-Profit Levels (in points, based on script inputs):TP1: 12 points (1.2:1 R:R).
TP2: 22 points (2.2:1 R:R).
TP3: 32 points (3.2:1 R:R).
TP4: 42 points (4.2:1 R:R).
TP5: 52 points (5.2:1 R:R).
Example for Long: If session high is 3000, TP levels are 3012, 3022, 3032, 3042, 3052.
Example for Short: If session low is 2950, TP levels are 2938, 2928, 2918, 2908, 2898.
Strategy: Scale out of the position (e.g., close 20% at TP1, 20% at TP2, etc.) or take full profit at a preferred TP level based on market conditions.
Stop-Loss: Fixed at 10 points from the entry.
Long SL: Session high - 10 points (e.g., entry at 3000, SL at 2990).
Short SL: Session low + 10 points (e.g., entry at 2950, SL at 2960).
Trailing Stop (Optional):After reaching TP2 or TP3, consider trailing the stop to lock in profits (e.g., trail by 10–15 points below the current price).
5. Risk Management per Trade: Limit risk to 1–2% of your trading account per trade.
Calculate position size: Account Size × Risk % ÷ (Stop-Loss Distance × ETH Price per Point).
Example: $10,000 account, 1% risk = $100. If SL = 10 points and 1 point = $1, position size = $100 ÷ 10 = 0.1 ETH.
Daily Risk Limit: Cap daily losses at 3–5% of the account to avoid overtrading.
Maximum Exposure: Avoid taking both long and short positions simultaneously unless using separate accounts or strategies.
Volatility Consideration: Adjust position size during high-volatility periods (e.g., major news events like Ethereum upgrades or macroeconomic announcements).
6. Trade Management Monitoring :Watch for breakouts after 7:59 PM EST.
Monitor price action near TP and SL levels using alerts or manual checks.
Trade Duration: Breakout lines extend for 30 bars (script parameter). Close trades if no TP or SL is hit within this period, or reassess based on market conditions.
Adjustments: If the market shows strong momentum, consider holding beyond TP5 with a trailing stop.
If the breakout fails (e.g., price reverses before TP1), exit early to minimize losses.
7. Additional Considerations Market Conditions: The 7:00 PM–7:59 PM EST session aligns with the Asian market open (e.g., Tokyo Stock Exchange open at 9:00 AM JST), which may introduce higher volatility due to Asian trading activity.
Avoid trading during low-liquidity periods or extreme volatility (e.g., major crypto news).
Check for upcoming events (e.g., Ethereum network upgrades, ETF decisions) that could impact price.
Backtesting: Test the strategy on historical ETH data using the session high/low breakouts for the 7:00 PM–7:59 PM EST window to validate performance.
Adjust TP/SL levels based on backtest results if needed.
Broker and Fees: Use a low-fee crypto exchange (e.g., Binance, Kraken, Coinbase Pro) to maximize R:R.
Account for trading fees and slippage in your position sizing.
Time zone Adjustment: Adjust session time input for your time zone (e.g., "0000-0059" for GMT).
Ensure your trading platform’s clock aligns with the script’s time zone (default: America/New_York).
8. Example Trade Scenario: Session (7:00 PM–7:59 PM EST) records a high of 3050 and a low of 3000.
Long Trade: Entry: Price breaks above 3050 (e.g., enter at 3051).
TP Levels: 3063 (TP1), 3073 (TP2), 3083 (TP3), 3093 (TP4), 3103 (TP5).
SL: 3040 (3050 - 10).
Position Size: For a $10,000 account, 1% risk = $100. SL = 11 points ($11). Size = $100 ÷ 11 = ~0.09 ETH.
Short Trade: Entry: Price breaks below 3000 (e.g., enter at 2999).
TP Levels: 2987 (TP1), 2977 (TP2), 2967 (TP3), 2957 (TP4), 2947 (TP5).
SL: 3010 (3000 + 10).
Position Size: Same as above, ~0.09 ETH.
Execution: Set alerts for breakouts, enter with limit orders, and monitor TPs/SL.
9. Tools and Setup Platform: Use TradingView to implement the Pine Script and visualize breakout levels.
Alerts: Set price alerts for breakouts above the session high or below the session low after 7:59 PM EST.
Set alerts for TP and SL levels.
Chart Settings: Use a 1-minute or 5-minute chart for precise session tracking.
Overlay the script to see high/low lines, TP levels, and SL levels.
Optional Indicators: Add RSI (e.g., avoid overbought/oversold breakouts) or volume to confirm breakouts.
10. Risk Warnings Crypto Volatility: ETH is highly volatile; unexpected news can cause rapid price swings.
False Breakouts: Breakouts may fail, especially in low-volume sessions. Use confirmation signals.
Leverage: Avoid high leverage (e.g., >5x) to prevent liquidation during volatile moves.
Session Accuracy: Ensure correct session timing for your time zone to avoid misaligned entries.
11. Performance Tracking Journaling :Record each trade’s entry, exit, R:R, and outcome.
Note market conditions (e.g., trending, ranging, news-driven).
Review: Weekly: Assess win rate, average R:R, and adherence to the plan.
Monthly: Adjust TP/SL or session timing based on performance.
ai quant oculusAI QUANT OCULUS
Version 1.0 | Pine Script v6
Purpose & Innovation
AI QUANT OCULUS integrates four distinct technical concepts—exponential trend filtering, adaptive smoothing, momentum oscillation, and Gaussian smoothing—into a single, cohesive system that delivers clear, objective buy and sell signals along with automatically plotted stop-loss and three profit-target levels. This mash-up goes beyond a simple EMA crossover or standalone TRIX oscillator by requiring confluence across trend, adaptive moving averages, momentum direction, and smoothed price action, reducing false triggers and focusing on high‐probability turning points.
How It Works & Why Its Components Matter
Trend Filter: EMA vs. Adaptive MA
EMA (20) measures the prevailing trend with fixed sensitivity.
Adaptive MA (also EMA-based, length 10) approximates a faster-responding moving average, standing in for a KAMA-style filter.
Bullish bias requires AMA > EMA; bearish bias requires AMA < EMA. This ensures signals align with both the underlying trend and a more nimble view of recent price action.
Momentum Confirmation: TRIX
Calculates a triple-smoothed EMA of price over TRIX Length (15), then converts it to a percentage rate-of-change oscillator.
Positive TRIX reinforces bullish entries; negative TRIX reinforces bearish entries. Using TRIX helps filter whipsaws by focusing on sustained momentum shifts.
Gaussian Price Smoother
Applies two back-to-back 5-period EMAs to the price (“gaussian” smoothing) to remove short-term noise.
Price above the smoothed line confirms strength for longs; below confirms weakness for shorts. This layer avoids entries on erratic spikes.
Confluence Signals
Buy Signal (isBull) fires only when:
AMA > EMA (trend alignment)
TRIX > 0 (momentum support)
Close > Gaussian (price strength)
Sell Signal (isBear) fires under the inverse conditions.
Requiring all three conditions simultaneously sharply reduces false triggers common to single-indicator systems.
Automatic Risk & Reward Plotting
On each new buy or sell signal (edge detection via not isBull or not isBear ), the script:
Stores entryPrice at the signal bar’s close.
Draws a stop-loss line at entry minus ATR(14) × Stop Multiplier (1.5) by default.
Plots three profit-target lines at entry plus ATR × Target Multiplier (1×, 1.5×, and 2×).
All previous labels and lines are deleted on each new signal, keeping the chart uncluttered and focusing only on the current trade.
Inputs & Customization
Input Description Default
EMA Length Period for the main trend EMA 20
Adaptive MA Length Period for the faster adaptive EM A substitute 10
TRIX Length Period for the triple-smoothed momentum oscillator 15
Dominant Cycle Length (Reserved) 40
Stop Multiplier ATR multiple for stop-loss distance 1.5
Target Multiplier ATR multiple for first profit target 1.5
Show Buy/Sell Signals Toggle on-chart labels for entry signals On
How to Use
Apply to Chart: Best on 15 m–1 h timeframes for swing entries or 5 m for agile scalps.
Wait for Full Confluence:
Look for the AMA to cross above/below the EMA and verify TRIX and Gaussian conditions on the same bar.
A bright “LONG” or “SHORT” label marks your entry.
Manage the Trade:
Place your stop where the red or green SL line appears.
Scale or exit at the three yellow TP1/TP2/TP3 lines, automatically drawn by volatility.
Repeat Cleanly: Each new signal clears prior annotations, ensuring you only track the active setup.
Why This Script Stands Out
Multi-Layer Confluence: Trend, momentum, and noise-reduction must all align, addressing the weaknesses of single-indicator strategies.
Automated Trade Management: No manual plotting—stop and target lines appear seamlessly with each signal.
Transparent & Customizable: All logic is open, adjustable, and clearly documented, allowing traders to tweak lengths and multipliers to suit different instruments.
Disclaimer
No indicator guarantees profit. Always backtest AI QUANT OCULUS extensively, combine its signals with your own analysis and risk controls, and practice sound money management before trading live.
TrailingStopLibraryLibrary "TrailingStopLibrary"
专业移动止盈库 - 为Pine Script策略提供完整的追踪止盈功能。支持做多做空双向交易，基于风险回报比智能激活，提供收盘价和高低价两种判断模式。包含完整的状态管理、调试信息和易用的API接口。适用于股票、外汇、加密货币等各种市场的风险管理。
@version 1.0
@author runto2006
new_config(enabled, activation_ratio, pullback_percent, price_type)
创建移动止盈配置对象
Parameters:
enabled (bool) : (bool) 是否启用移动止盈，默认true
activation_ratio (float) : (float) 激活盈亏比，默认4.0，表示盈利4倍止损距离时激活
pullback_percent (float) : (float) 回撤百分比，默认1.0，表示回撤1%时触发止盈
price_type (string) : (string) 价格类型，默认"close"。"close"=收盘价模式，"hl"=高低价模式
Returns: Config 配置对象
new_state()
创建移动止盈状态对象
Returns: State 初始化的状态对象
reset(state)
重置移动止盈状态
Parameters:
state (State) : (State) 要重置的状态对象
Returns: void
calc_activation_target(entry_price, stop_price, activation_ratio, is_long)
计算激活目标价格
Parameters:
entry_price (float) : (float) 入场价格
stop_price (float) : (float) 止损价格
activation_ratio (float) : (float) 激活盈亏比
is_long (bool) : (bool) 是否为多头持仓
Returns: float 激活目标价格，如果输入无效则返回na
get_check_price(price_type, is_long, for_activation)
获取用于判断的价格
Parameters:
price_type (string) : (string) 价格类型："close"或"hl"
is_long (bool) : (bool) 是否为多头持仓
for_activation (bool) : (bool) 是否用于激活判断，影响高低价的选择方向
Returns: float 当前判断价格
check_activation(config, state, entry_price, stop_price, is_long, has_position)
检查是否应该激活移动止盈
Parameters:
config (Config) : (Config) 移动止盈配置
state (State) : (State) 移动止盈状态
entry_price (float) : (float) 入场价格
stop_price (float) : (float) 止损价格
is_long (bool) : (bool) 是否为多头持仓
has_position (bool) : (bool) 是否有持仓
Returns: bool 是否成功激活
update_tracking(config, state, is_long)
更新移动止盈的追踪价格
Parameters:
config (Config) : (Config) 移动止盈配置
state (State) : (State) 移动止盈状态
is_long (bool) : (bool) 是否为多头持仓
Returns: void
check_trigger(config, state, entry_price, is_long)
检查是否触发移动止盈
Parameters:
config (Config) : (Config) 移动止盈配置
state (State) : (State) 移动止盈状态
entry_price (float) : (float) 入场价格
is_long (bool) : (bool) 是否为多头持仓
Returns: bool 是否触发止盈
process(config, state, entry_price, stop_price, is_long, has_position)
一体化处理移动止盈逻辑
Parameters:
config (Config) : (Config) 移动止盈配置
state (State) : (State) 移动止盈状态
entry_price (float) : (float) 入场价格
stop_price (float) : (float) 止损价格
is_long (bool) : (bool) 是否为多头持仓
has_position (bool) : (bool) 是否有持仓
Returns: bool 是否触发止盈
get_trigger_price(config, state, is_long)
获取当前触发价格
Parameters:
config (Config) : (Config) 移动止盈配置
state (State) : (State) 移动止盈状态
is_long (bool) : (bool) 是否为多头持仓
Returns: float 触发价格，未激活时返回na
get_pullback_percent(config, state, entry_price, is_long)
计算当前回撤百分比
Parameters:
config (Config) : (Config) 移动止盈配置
state (State) : (State) 移动止盈状态
entry_price (float) : (float) 入场价格
is_long (bool) : (bool) 是否为多头持仓
Returns: float 当前回撤百分比，未激活时返回na
get_status_info(config, state, entry_price, is_long)
获取状态信息字符串（用于调试）
Parameters:
config (Config) : (Config) 移动止盈配置
state (State) : (State) 移动止盈状态
entry_price (float) : (float) 入场价格
is_long (bool) : (bool) 是否为多头持仓
Returns: string 详细的状态信息
Config
移动止盈配置对象
Fields:
enabled (series bool) : (bool) 是否启用移动止盈功能
activation_ratio (series float) : (float) 激活盈亏比 - 盈利达到止损距离的多少倍时激活追踪
pullback_percent (series float) : (float) 回撤百分比 - 从最优价格回撤多少百分比时触发止盈
price_type (series string) : (string) 价格判断类型 - "close"使用收盘价，"hl"使用高低价
State
移动止盈状态对象
Fields:
activated (series bool) : (bool) 是否已激活追踪止盈
highest_price (series float) : (float) 激活后记录的最高价格
lowest_price (series float) : (float) 激活后记录的最低价格
activation_target (series float) : (float) 激活目标价格
CNTLibraryLibrary "CNTLibrary"
Custom Functions To Help Code In Pinescript V5
Coded By Christian Nataliano
First Coded In 10/06/2023
Last Edited In 22/06/2023
Huge Shout Out To © ZenAndTheArtOfTrading and his ZenLibrary V5, Some Of The Custom Functions Were Heavily Inspired By Matt's Work & His Pine Script Mastery Course
Another Shout Out To The TradingView's Team Library ta V5
//====================================================================================================================================================
// Custom Indicator Functions
//====================================================================================================================================================
GetKAMA(KAMA_lenght, Fast_KAMA, Slow_KAMA)
Calculates An Adaptive Moving Average Based On Perry J Kaufman's Calculations
Parameters:
KAMA_lenght (int) : Is The KAMA Lenght
Fast_KAMA (int) : Is The KAMA's Fastes Moving Average
Slow_KAMA (int) : Is The KAMA's Slowest Moving Average
Returns: Float Of The KAMA's Current Calculations
GetMovingAverage(Source, Lenght, Type)
Get Custom Moving Averages Values
Parameters:
Source (float) : Of The Moving Average, Defval = close
Lenght (simple int) : Of The Moving Average, Defval = 50
Type (string) : Of The Moving Average, Defval = Exponential Moving Average
Returns: The Moving Average Calculation Based On Its Given Source, Lenght & Calculation Type (Please Call Function On Global Scope)
GetDecimals()
Calculates how many decimals are on the quote price of the current market © ZenAndTheArtOfTrading
Returns: The current decimal places on the market quote price
Truncate(number, decimalPlaces)
Truncates (cuts) excess decimal places © ZenAndTheArtOfTrading
Parameters:
number (float)
decimalPlaces (simple float)
Returns: The given number truncated to the given decimalPlaces
ToWhole(number)
Converts pips into whole numbers © ZenAndTheArtOfTrading
Parameters:
number (float)
Returns: The converted number
ToPips(number)
Converts whole numbers back into pips © ZenAndTheArtOfTrading
Parameters:
number (float)
Returns: The converted number
GetPctChange(value1, value2, lookback)
Gets the percentage change between 2 float values over a given lookback period © ZenAndTheArtOfTrading
Parameters:
value1 (float)
value2 (float)
lookback (int)
BarsAboveMA(lookback, ma)
Counts how many candles are above the MA © ZenAndTheArtOfTrading
Parameters:
lookback (int)
ma (float)
Returns: The bar count of how many recent bars are above the MA
BarsBelowMA(lookback, ma)
Counts how many candles are below the MA © ZenAndTheArtOfTrading
Parameters:
lookback (int)
ma (float)
Returns: The bar count of how many recent bars are below the EMA
BarsCrossedMA(lookback, ma)
Counts how many times the EMA was crossed recently © ZenAndTheArtOfTrading
Parameters:
lookback (int)
ma (float)
Returns: The bar count of how many times price recently crossed the EMA
GetPullbackBarCount(lookback, direction)
Counts how many green & red bars have printed recently (ie. pullback count) © ZenAndTheArtOfTrading
Parameters:
lookback (int)
direction (int)
Returns: The bar count of how many candles have retraced over the given lookback & direction
GetSwingHigh(Lookback, SwingType)
Check If Price Has Made A Recent Swing High
Parameters:
Lookback (int) : Is For The Swing High Lookback Period, Defval = 7
SwingType (int) : Is For The Swing High Type Of Identification, Defval = 1
Returns: A Bool - True If Price Has Made A Recent Swing High
GetSwingLow(Lookback, SwingType)
Check If Price Has Made A Recent Swing Low
Parameters:
Lookback (int) : Is For The Swing Low Lookback Period, Defval = 7
SwingType (int) : Is For The Swing Low Type Of Identification, Defval = 1
Returns: A Bool - True If Price Has Made A Recent Swing Low
//====================================================================================================================================================
// Custom Risk Management Functions
//====================================================================================================================================================
CalculateStopLossLevel(OrderType, Entry, StopLoss)
Calculate StopLoss Level
Parameters:
OrderType (int) : Is To Determine A Long / Short Position, Defval = 1
Entry (float) : Is The Entry Level Of The Order, Defval = na
StopLoss (float) : Is The Custom StopLoss Distance, Defval = 2x ATR Below Close
Returns: Float - The StopLoss Level In Actual Price As A
CalculateStopLossDistance(OrderType, Entry, StopLoss)
Calculate StopLoss Distance In Pips
Parameters:
OrderType (int) : Is To Determine A Long / Short Position, Defval = 1
Entry (float) : Is The Entry Level Of The Order, NEED TO INPUT PARAM
StopLoss (float) : Level Based On Previous Calculation, NEED TO INPUT PARAM
Returns: Float - The StopLoss Value In Pips
CalculateTakeProfitLevel(OrderType, Entry, StopLossDistance, RiskReward)
Calculate TakeProfit Level
Parameters:
OrderType (int) : Is To Determine A Long / Short Position, Defval = 1
Entry (float) : Is The Entry Level Of The Order, Defval = na
StopLossDistance (float)
RiskReward (float)
Returns: Float - The TakeProfit Level In Actual Price
CalculateTakeProfitDistance(OrderType, Entry, TakeProfit)
Get TakeProfit Distance In Pips
Parameters:
OrderType (int) : Is To Determine A Long / Short Position, Defval = 1
Entry (float) : Is The Entry Level Of The Order, NEED TO INPUT PARAM
TakeProfit (float) : Level Based On Previous Calculation, NEED TO INPUT PARAM
Returns: Float - The TakeProfit Value In Pips
CalculateConversionCurrency(AccountCurrency, SymbolCurrency, BaseCurrency)
Get The Conversion Currecny Between Current Account Currency & Current Pair's Quoted Currency (FOR FOREX ONLY)
Parameters:
AccountCurrency (simple string) : Is For The Account Currency Used
SymbolCurrency (simple string) : Is For The Current Symbol Currency (Front Symbol)
BaseCurrency (simple string) : Is For The Current Symbol Base Currency (Back Symbol)
Returns: Tuple Of A Bollean (Convert The Currency ?) And A String (Converted Currency)
CalculateConversionRate(ConvertCurrency, ConversionRate)
Get The Conversion Rate Between Current Account Currency & Current Pair's Quoted Currency (FOR FOREX ONLY)
Parameters:
ConvertCurrency (bool) : Is To Check If The Current Symbol Needs To Be Converted Or Not
ConversionRate (float) : Is The Quoted Price Of The Conversion Currency (Input The request.security Function Here)
Returns: Float Price Of Conversion Rate (If In The Same Currency Than Return Value Will Be 1.0)
LotSize(LotSizeSimple, Balance, Risk, SLDistance, ConversionRate)
Get Current Lot Size
Parameters:
LotSizeSimple (bool) : Is To Toggle Lot Sizing Calculation (Simple Is Good Enough For Stocks & Crypto, Whilst Complex Is For Forex)
Balance (float) : Is For The Current Account Balance To Calculate The Lot Sizing Based Off
Risk (float) : Is For The Current Risk Per Trade To Calculate The Lot Sizing Based Off
SLDistance (float) : Is The Current Position StopLoss Distance From Its Entry Price
ConversionRate (float) : Is The Currency Conversion Rate (Used For Complex Lot Sizing Only)
Returns: Float - Position Size In Units
ToLots(Units)
Converts Units To Lots
Parameters:
Units (float) : Is For How Many Units Need To Be Converted Into Lots (Minimun 1000 Units)
Returns: Float - Position Size In Lots
ToUnits(Lots)
Converts Lots To Units
Parameters:
Lots (float) : Is For How Many Lots Need To Be Converted Into Units (Minimun 0.01 Units)
Returns: Int - Position Size In Units
ToLotsInUnits(Units)
Converts Units To Lots Than Back To Units
Parameters:
Units (float) : Is For How Many Units Need To Be Converted Into Lots (Minimun 1000 Units)
Returns: Float - Position Size In Lots That Were Rounded To Units
ATRTrail(OrderType, SourceType, ATRPeriod, ATRMultiplyer, SwingLookback)
Calculate ATR Trailing Stop
Parameters:
OrderType (int) : Is To Determine A Long / Short Position, Defval = 1
SourceType (int) : Is To Determine Where To Calculate The ATR Trailing From, Defval = close
ATRPeriod (simple int) : Is To Change Its ATR Period, Defval = 20
ATRMultiplyer (float) : Is To Change Its ATR Trailing Distance, Defval = 1
SwingLookback (int) : Is To Change Its Swing HiLo Lookback (Only From Source Type 5), Defval = 7
Returns: Float - Number Of The Current ATR Trailing
DangerZone(WinRate, AvgRRR, Filter)
Calculate Danger Zone Of A Given Strategy
Parameters:
WinRate (float) : Is The Strategy WinRate
AvgRRR (float) : Is The Strategy Avg RRR
Filter (float) : Is The Minimum Profit It Needs To Be Out Of BE Zone, Defval = 3
Returns: Int - Value, 1 If Out Of Danger Zone, 0 If BE, -1 If In Danger Zone
IsQuestionableTrades(TradeTP, TradeSL)
Checks For Questionable Trades (Which Are Trades That Its TP & SL Level Got Hit At The Same Candle)
Parameters:
TradeTP (float) : Is The Trade In Question Take Profit Level
TradeSL (float) : Is The Trade In Question Stop Loss Level
Returns: Bool - True If The Last Trade Was A "Questionable Trade"
//====================================================================================================================================================
// Custom Strategy Functions
//====================================================================================================================================================
OpenLong(EntryID, LotSize, LimitPrice, StopPrice, Comment, CommentValue)
Open A Long Order Based On The Given Params
Parameters:
EntryID (string) : Is The Trade Entry ID, Defval = "Long"
LotSize (float) : Is The Lot Size Of The Trade, Defval = 1
LimitPrice (float) : Is The Limit Order Price To Set The Order At, Defval = Na / Market Order Execution
StopPrice (float) : Is The Stop Order Price To Set The Order At, Defval = Na / Market Order Execution
Comment (string) : Is The Order Comment, Defval = Long Entry Order
CommentValue (string) : Is For Custom Values In The Order Comment, Defval = Na
Returns: Void
OpenShort(EntryID, LotSize, LimitPrice, StopPrice, Comment, CommentValue)
Open A Short Order Based On The Given Params
Parameters:
EntryID (string) : Is The Trade Entry ID, Defval = "Short"
LotSize (float) : Is The Lot Size Of The Trade, Defval = 1
LimitPrice (float) : Is The Limit Order Price To Set The Order At, Defval = Na / Market Order Execution
StopPrice (float) : Is The Stop Order Price To Set The Order At, Defval = Na / Market Order Execution
Comment (string) : Is The Order Comment, Defval = Short Entry Order
CommentValue (string) : Is For Custom Values In The Order Comment, Defval = Na
Returns: Void
TP_SLExit(FromID, TPLevel, SLLevel, PercentageClose, Comment, CommentValue)
Exits Based On Predetermined TP & SL Levels
Parameters:
FromID (string) : Is The Trade ID That The TP & SL Levels Be Palced
TPLevel (float) : Is The Take Profit Level
SLLevel (float) : Is The StopLoss Level
PercentageClose (float) : Is The Amount To Close The Order At (In Percentage) Defval = 100
Comment (string) : Is The Order Comment, Defval = Exit Order
CommentValue (string) : Is For Custom Values In The Order Comment, Defval = Na
Returns: Void
CloseLong(ExitID, PercentageClose, Comment, CommentValue, Instant)
Exits A Long Order Based On A Specified Condition
Parameters:
ExitID (string) : Is The Trade ID That Will Be Closed, Defval = "Long"
PercentageClose (float) : Is The Amount To Close The Order At (In Percentage) Defval = 100
Comment (string) : Is The Order Comment, Defval = Exit Order
CommentValue (string) : Is For Custom Values In The Order Comment, Defval = Na
Instant (bool) : Is For Exit Execution Type, Defval = false
Returns: Void
CloseShort(ExitID, PercentageClose, Comment, CommentValue, Instant)
Exits A Short Order Based On A Specified Condition
Parameters:
ExitID (string) : Is The Trade ID That Will Be Closed, Defval = "Short"
PercentageClose (float) : Is The Amount To Close The Order At (In Percentage) Defval = 100
Comment (string) : Is The Order Comment, Defval = Exit Order
CommentValue (string) : Is For Custom Values In The Order Comment, Defval = Na
Instant (bool) : Is For Exit Execution Type, Defval = false
Returns: Void
BrokerCheck(Broker)
Checks Traded Broker With Current Loaded Chart Broker
Parameters:
Broker (string) : Is The Current Broker That Is Traded
Returns: Bool - True If Current Traded Broker Is Same As Loaded Chart Broker
OpenPC(LicenseID, OrderType, UseLimit, LimitPrice, SymbolPrefix, Symbol, SymbolSuffix, Risk, SL, TP, OrderComment, Spread)
Compiles Given Parameters Into An Alert String Format To Open Trades Using Pine Connector
Parameters:
LicenseID (string) : Is The Users PineConnector LicenseID
OrderType (int) : Is The Desired OrderType To Open
UseLimit (bool) : Is If We Want To Enter The Position At Exactly The Previous Closing Price
LimitPrice (float) : Is The Limit Price Of The Trade (Only For Pending Orders)
SymbolPrefix (string) : Is The Current Symbol Prefix (If Any)
Symbol (string) : Is The Traded Symbol
SymbolSuffix (string) : Is The Current Symbol Suffix (If Any)
Risk (float) : Is The Trade Risk Per Trade / Fixed Lot Sizing
SL (float) : Is The Trade SL In Price / In Pips
TP (float) : Is The Trade TP In Price / In Pips
OrderComment (string) : Is The Executed Trade Comment
Spread (float) : is The Maximum Spread For Execution
Returns: String - Pine Connector Order Syntax Alert Message
ClosePC(LicenseID, OrderType, SymbolPrefix, Symbol, SymbolSuffix)
Compiles Given Parameters Into An Alert String Format To Close Trades Using Pine Connector
Parameters:
LicenseID (string) : Is The Users PineConnector LicenseID
OrderType (int) : Is The Desired OrderType To Close
SymbolPrefix (string) : Is The Current Symbol Prefix (If Any)
Symbol (string) : Is The Traded Symbol
SymbolSuffix (string) : Is The Current Symbol Suffix (If Any)
Returns: String - Pine Connector Order Syntax Alert Message
//====================================================================================================================================================
// Custom Backtesting Calculation Functions
//====================================================================================================================================================
CalculatePNL(EntryPrice, ExitPrice, LotSize, ConversionRate)
Calculates Trade PNL Based On Entry, Eixt & Lot Size
Parameters:
EntryPrice (float) : Is The Trade Entry
ExitPrice (float) : Is The Trade Exit
LotSize (float) : Is The Trade Sizing
ConversionRate (float) : Is The Currency Conversion Rate (Used For Complex Lot Sizing Only)
Returns: Float - The Current Trade PNL
UpdateBalance(PrevBalance, PNL)
Updates The Previous Ginve Balance To The Next PNL
Parameters:
PrevBalance (float) : Is The Previous Balance To Be Updated
PNL (float) : Is The Current Trade PNL To Be Added
Returns: Float - The Current Updated PNL
CalculateSlpComm(PNL, MaxRate)
Calculates Random Slippage & Commisions Fees Based On The Parameters
Parameters:
PNL (float) : Is The Current Trade PNL
MaxRate (float) : Is The Upper Limit (In Percentage) Of The Randomized Fee
Returns: Float - A Percentage Fee Of The Current Trade PNL
UpdateDD(MaxBalance, Balance)
Calculates & Updates The DD Based On Its Given Parameters
Parameters:
MaxBalance (float) : Is The Maximum Balance Ever Recorded
Balance (float) : Is The Current Account Balance
Returns: Float - The Current Strategy DD
CalculateWR(TotalTrades, LongID, ShortID)
Calculate The Total, Long & Short Trades Win Rate
Parameters:
TotalTrades (int) : Are The Current Total Trades That The Strategy Has Taken
LongID (string) : Is The Order ID Of The Long Trades Of The Strategy
ShortID (string) : Is The Order ID Of The Short Trades Of The Strategy
Returns: Tuple Of Long WR%, Short WR%, Total WR%, Total Winning Trades, Total Losing Trades, Total Long Trades & Total Short Trades
CalculateAvgRRR(WinTrades, LossTrades)
Calculates The Overall Strategy Avg Risk Reward Ratio
Parameters:
WinTrades (int) : Are The Strategy Winning Trades
LossTrades (int) : Are The Strategy Losing Trades
Returns: Float - The Average RRR Values
CAGR(StartTime, StartPrice, EndTime, EndPrice)
Calculates The CAGR Over The Given Time Period © TradingView
Parameters:
StartTime (int) : Is The Starting Time Of The Calculation
StartPrice (float) : Is The Starting Price Of The Calculation
EndTime (int) : Is The Ending Time Of The Calculation
EndPrice (float) : Is The Ending Price Of The Calculation
Returns: Float - The CAGR Values
//====================================================================================================================================================
// Custom Plot Functions
//====================================================================================================================================================
EditLabels(LabelID, X1, Y1, Text, Color, TextColor, EditCondition, DeleteCondition)
Edit / Delete Labels
Parameters:
LabelID (label) : Is The ID Of The Selected Label
X1 (int) : Is The X1 Coordinate IN BARINDEX Xloc
Y1 (float) : Is The Y1 Coordinate IN PRICE Yloc
Text (string) : Is The Text Than Wants To Be Written In The Label
Color (color) : Is The Color Value Change Of The Label Text
TextColor (color)
EditCondition (int) : Is The Edit Condition of The Line (Setting Location / Color)
DeleteCondition (bool) : Is The Delete Condition Of The Line If Ture Deletes The Prev Itteration Of The Line
Returns: Void
EditLine(LineID, X1, Y1, X2, Y2, Color, EditCondition, DeleteCondition)
Edit / Delete Lines
Parameters:
LineID (line) : Is The ID Of The Selected Line
X1 (int) : Is The X1 Coordinate IN BARINDEX Xloc
Y1 (float) : Is The Y1 Coordinate IN PRICE Yloc
X2 (int) : Is The X2 Coordinate IN BARINDEX Xloc
Y2 (float) : Is The Y2 Coordinate IN PRICE Yloc
Color (color) : Is The Color Value Change Of The Line
EditCondition (int) : Is The Edit Condition of The Line (Setting Location / Color)
DeleteCondition (bool) : Is The Delete Condition Of The Line If Ture Deletes The Prev Itteration Of The Line
Returns: Void
//====================================================================================================================================================
// Custom Display Functions (Using Tables)
//====================================================================================================================================================
FillTable(TableID, Column, Row, Title, Value, BgColor, TextColor, ToolTip)
Filling The Selected Table With The Inputed Information
Parameters:
TableID (table) : Is The Table ID That Wants To Be Edited
Column (int) : Is The Current Column Of The Table That Wants To Be Edited
Row (int) : Is The Current Row Of The Table That Wants To Be Edited
Title (string) : Is The String Title Of The Current Cell Table
Value (string) : Is The String Value Of The Current Cell Table
BgColor (color) : Is The Selected Color For The Current Table
TextColor (color) : Is The Selected Color For The Current Table
ToolTip (string) : Is The ToolTip Of The Current Cell In The Table
Returns: Void
DisplayBTResults(TableID, BgColor, TextColor, StartingBalance, Balance, DollarReturn, TotalPips, MaxDD)
Filling The Selected Table With The Inputed Information
Parameters:
TableID (table) : Is The Table ID That Wants To Be Edited
BgColor (color) : Is The Selected Color For The Current Table
TextColor (color) : Is The Selected Color For The Current Table
StartingBalance (float) : Is The Account Starting Balance
Balance (float)
DollarReturn (float) : Is The Account Dollar Reture
TotalPips (float) : Is The Total Pips Gained / loss
MaxDD (float) : Is The Maximum Drawdown Over The Backtesting Period
Returns: Void
DisplayBTResultsV2(TableID, BgColor, TextColor, TotalWR, QTCount, LongWR, ShortWR, InitialCapital, CumProfit, CumFee, AvgRRR, MaxDD, CAGR, MeanDD)
Filling The Selected Table With The Inputed Information
Parameters:
TableID (table) : Is The Table ID That Wants To Be Edited
BgColor (color) : Is The Selected Color For The Current Table
TextColor (color) : Is The Selected Color For The Current Table
TotalWR (float) : Is The Strategy Total WR In %
QTCount (int) : Is The Strategy Questionable Trades Count
LongWR (float) : Is The Strategy Total WR In %
ShortWR (float) : Is The Strategy Total WR In %
InitialCapital (float) : Is The Strategy Initial Starting Capital
CumProfit (float) : Is The Strategy Ending Cumulative Profit
CumFee (float) : Is The Strategy Ending Cumulative Fee (Based On Randomized Fee Assumptions)
AvgRRR (float) : Is The Strategy Average Risk Reward Ratio
MaxDD (float) : Is The Strategy Maximum DrawDown In Its Backtesting Period
CAGR (float) : Is The Strategy Compounded Average GRowth In %
MeanDD (float) : Is The Strategy Mean / Average Drawdown In The Backtesting Period
Returns: Void
//====================================================================================================================================================
// Custom Pattern Detection Functions
//====================================================================================================================================================
BullFib(priceLow, priceHigh, fibRatio)
Calculates A Bullish Fibonacci Value (From Swing Low To High) © ZenAndTheArtOfTrading
Parameters:
priceLow (float)
priceHigh (float)
fibRatio (float)
Returns: The Fibonacci Value Of The Given Ratio Between The Two Price Points
BearFib(priceLow, priceHigh, fibRatio)
Calculates A Bearish Fibonacci Value (From Swing High To Low) © ZenAndTheArtOfTrading
Parameters:
priceLow (float)
priceHigh (float)
fibRatio (float)
Returns: The Fibonacci Value Of The Given Ratio Between The Two Price Points
GetBodySize()
Gets The Current Candle Body Size IN POINTS © ZenAndTheArtOfTrading
Returns: The Current Candle Body Size IN POINTS
GetTopWickSize()
Gets The Current Candle Top Wick Size IN POINTS © ZenAndTheArtOfTrading
Returns: The Current Candle Top Wick Size IN POINTS
GetBottomWickSize()
Gets The Current Candle Bottom Wick Size IN POINTS © ZenAndTheArtOfTrading
Returns: The Current Candle Bottom Wick Size IN POINTS
GetBodyPercent()
Gets The Current Candle Body Size As A Percentage Of Its Entire Size Including Its Wicks © ZenAndTheArtOfTrading
Returns: The Current Candle Body Size IN PERCENTAGE
GetTopWickPercent()
Gets The Current Top Wick Size As A Percentage Of Its Entire Body Size
Returns: Float - The Current Candle Top Wick Size IN PERCENTAGE
GetBottomWickPercent()
Gets The Current Bottom Wick Size As A Percentage Of Its Entire Bodu Size
Returns: Float - The Current Candle Bottom Size IN PERCENTAGE
BullishEC(Allowance, RejectionWickSize, EngulfWick, NearSwings, SwingLookBack)
Checks If The Current Bar Is A Bullish Engulfing Candle
Parameters:
Allowance (int) : To Give Flexibility Of Engulfing Pattern Detection In Markets That Have Micro Gaps, Defval = 0
RejectionWickSize (float) : To Filter Out long (Upper And Lower) Wick From The Bullsih Engulfing Pattern, Defval = na
EngulfWick (bool) : To Specify If We Want The Pattern To Also Engulf Its Upper & Lower Previous Wicks, Defval = false
NearSwings (bool) : To Specify If We Want The Pattern To Be Near A Recent Swing Low, Defval = true
SwingLookBack (int) : To Specify How Many Bars Back To Detect A Recent Swing Low, Defval = 10
Returns: Bool - True If The Current Bar Matches The Requirements of a Bullish Engulfing Candle
BearishEC(Allowance, RejectionWickSize, EngulfWick, NearSwings, SwingLookBack)
Checks If The Current Bar Is A Bearish Engulfing Candle
Parameters:
Allowance (int) : To Give Flexibility Of Engulfing Pattern Detection In Markets That Have Micro Gaps, Defval = 0
RejectionWickSize (float) : To Filter Out long (Upper And Lower) Wick From The Bearish Engulfing Pattern, Defval = na
EngulfWick (bool) : To Specify If We Want The Pattern To Also Engulf Its Upper & Lower Previous Wicks, Defval = false
NearSwings (bool) : To Specify If We Want The Pattern To Be Near A Recent Swing High, Defval = true
SwingLookBack (int) : To Specify How Many Bars Back To Detect A Recent Swing High, Defval = 10
Returns: Bool - True If The Current Bar Matches The Requirements of a Bearish Engulfing Candle
Hammer(Fib, ColorMatch, NearSwings, SwingLookBack, ATRFilterCheck, ATRPeriod)
Checks If The Current Bar Is A Hammer Candle
Parameters:
Fib (float) : To Specify Which Fibonacci Ratio To Use When Determining The Hammer Candle, Defval = 0.382 Ratio
ColorMatch (bool) : To Filter Only Bullish Closed Hammer Candle Pattern, Defval = false
NearSwings (bool) : To Specify If We Want The Doji To Be Near A Recent Swing Low, Defval = true
SwingLookBack (int) : To Specify How Many Bars Back To Detect A Recent Swing Low, Defval = 10
ATRFilterCheck (float) : To Filter Smaller Hammer Candles That Might Be Better Classified As A Doji Candle, Defval = 1
ATRPeriod (simple int) : To Change ATR Period Of The ATR Filter, Defval = 20
Returns: Bool - True If The Current Bar Matches The Requirements of a Hammer Candle
Star(Fib, ColorMatch, NearSwings, SwingLookBack, ATRFilterCheck, ATRPeriod)
Checks If The Current Bar Is A Hammer Candle
Parameters:
Fib (float) : To Specify Which Fibonacci Ratio To Use When Determining The Hammer Candle, Defval = 0.382 Ratio
ColorMatch (bool) : To Filter Only Bullish Closed Hammer Candle Pattern, Defval = false
NearSwings (bool) : To Specify If We Want The Doji To Be Near A Recent Swing Low, Defval = true
SwingLookBack (int) : To Specify How Many Bars Back To Detect A Recent Swing Low, Defval = 10
ATRFilterCheck (float) : To Filter Smaller Hammer Candles That Might Be Better Classified As A Doji Candle, Defval = 1
ATRPeriod (simple int) : To Change ATR Period Of The ATR Filter, Defval = 20
Returns: Bool - True If The Current Bar Matches The Requirements of a Hammer Candle
Doji(MaxWickSize, MaxBodySize, DojiType, NearSwings, SwingLookBack)
Checks If The Current Bar Is A Doji Candle
Parameters:
MaxWickSize (float) : To Specify The Maximum Lenght Of Its Upper & Lower Wick, Defval = 2
MaxBodySize (float) : To Specify The Maximum Lenght Of Its Candle Body IN PERCENT, Defval = 0.05
DojiType (int)
NearSwings (bool) : To Specify If We Want The Doji To Be Near A Recent Swing High / Low (Only In Dragonlyf / Gravestone Mode), Defval = true
SwingLookBack (int) : To Specify How Many Bars Back To Detect A Recent Swing High / Low (Only In Dragonlyf / Gravestone Mode), Defval = 10
Returns: Bool - True If The Current Bar Matches The Requirements of a Doji Candle
BullishIB(Allowance, RejectionWickSize, EngulfWick, NearSwings, SwingLookBack)
Checks If The Current Bar Is A Bullish Harami Candle
Parameters:
Allowance (int) : To Give Flexibility Of Harami Pattern Detection In Markets That Have Micro Gaps, Defval = 0
RejectionWickSize (float) : To Filter Out long (Upper And Lower) Wick From The Bullsih Harami Pattern, Defval = na
EngulfWick (bool) : To Specify If We Want The Pattern To Also Engulf Its Upper & Lower Previous Wicks, Defval = false
NearSwings (bool) : To Specify If We Want The Pattern To Be Near A Recent Swing Low, Defval = true
SwingLookBack (int) : To Specify How Many Bars Back To Detect A Recent Swing Low, Defval = 10
Returns: Bool - True If The Current Bar Matches The Requirements of a Bullish Harami Candle
BearishIB(Allowance, RejectionWickSize, EngulfWick, NearSwings, SwingLookBack)
Checks If The Current Bar Is A Bullish Harami Candle
Parameters:
Allowance (int) : To Give Flexibility Of Harami Pattern Detection In Markets That Have Micro Gaps, Defval = 0
RejectionWickSize (float) : To Filter Out long (Upper And Lower) Wick From The Bearish Harami Pattern, Defval = na
EngulfWick (bool) : To Specify If We Want The Pattern To Also Engulf Its Upper & Lower Previous Wicks, Defval = false
NearSwings (bool) : To Specify If We Want The Pattern To Be Near A Recent Swing High, Defval = true
SwingLookBack (int) : To Specify How Many Bars Back To Detect A Recent Swing High, Defval = 10
Returns: Bool - True If The Current Bar Matches The Requirements of a Bearish Harami Candle
//====================================================================================================================================================
// Custom Time Functions
//====================================================================================================================================================
BarInSession(sess, useFilter)
Determines if the current price bar falls inside the specified session © ZenAndTheArtOfTrading
Parameters:
sess (simple string)
useFilter (bool)
Returns: A boolean - true if the current bar falls within the given time session
BarOutSession(sess, useFilter)
Determines if the current price bar falls outside the specified session © ZenAndTheArtOfTrading
Parameters:
sess (simple string)
useFilter (bool)
Returns: A boolean - true if the current bar falls outside the given time session
DateFilter(startTime, endTime)
Determines if this bar's time falls within date filter range © ZenAndTheArtOfTrading
Parameters:
startTime (int)
endTime (int)
Returns: A boolean - true if the current bar falls within the given dates
DayFilter(monday, tuesday, wednesday, thursday, friday, saturday, sunday)
Checks if the current bar's day is in the list of given days to analyze © ZenAndTheArtOfTrading
Parameters:
monday (bool)
tuesday (bool)
wednesday (bool)
thursday (bool)
friday (bool)
saturday (bool)
sunday (bool)
Returns: A boolean - true if the current bar's day is one of the given days
AUSSess()
Checks If The Current Australian Forex Session In Running
Returns: Bool - True If Currently The Australian Session Is Running
ASIASess()
Checks If The Current Asian Forex Session In Running
Returns: Bool - True If Currently The Asian Session Is Running
EURSess()
Checks If The Current European Forex Session In Running
Returns: Bool - True If Currently The European Session Is Running
USSess()
Checks If The Current US Forex Session In Running
Returns: Bool - True If Currently The US Session Is Running
UNIXToDate(Time, ConversionType, TimeZone)
Converts UNIX Time To Datetime
Parameters:
Time (int) : Is The UNIX Time Input
ConversionType (int) : Is The Datetime Output Format, Defval = DD-MM-YYYY
TimeZone (string) : Is To Convert The Outputed Datetime Into The Specified Time Zone, Defval = Exchange Time Zone
Returns: String - String Of Datetime
Strategy█ OVERVIEW
This library is a Pine Script™ programmer’s tool containing a variety of strategy-related functions to assist in calculations like profit and loss, stop losses and limits. It also includes several useful functions one can use to convert between units in ticks, price, currency or a percentage of the position's size.
█ CONCEPTS
The library contains three types of functions:
1 — Functions beginning with `percent` take either a portion of a price, or the current position's entry price and convert it to the value outlined in the function's documentation.
Example: Converting a percent of the current position entry price to ticks, or calculating a percent profit at a given level for the position.
2 — Functions beginning with `tick` convert a tick value to another form.
These are useful for calculating a price or currency value from a specified number of ticks.
3 — Functions containing `Level` are used to calculate a stop or take profit level using an offset in ticks from the current entry price.
These functions can be used to plot stop or take profit levels on the chart, or as arguments to the `limit` and `stop` parameters in strategy.exit() function calls.
Note that these calculated levels flip automatically with the position's bias.
For example, using `ticksToStopLevel()` will calculate a stop level under the entry price for a long position, and above the entry price for a short position.
There are also two functions to assist in calculating a position size using the entry's stop and a fixed risk expressed as a percentage of the current account's equity. By varying the position size this way, you ensure that entries with different stop levels risk the same proportion of equity.
█ NOTES
Example code using some of the library's functions is included at the end of the library. To see it in action, copy the library's code to a new script in the Pine Editor, and “Add to chart”.
For each trade, the code displays:
• The entry level in orange.
• The stop level in fuchsia.
• The take profit level in green.
The stop and take profit levels automatically flip sides based on whether the current position is long or short.
Labels near the last trade's levels display the percentages used to calculate them, which can be changed in the script's inputs.
We plot markers for entries and exits because strategy code in libraries does not display the usual markers for them.
Look first. Then leap.
█ FUNCTIONS
percentToTicks(percent) Converts a percentage of the average entry price to ticks.
Parameters:
percent : (series int/float) The percentage of `strategy.position_avg_price` to convert to ticks. 50 is 50% of the entry price.
Returns: (float) A value in ticks.
percentToPrice(percent) Converts a percentage of the average entry price to a price.
Parameters:
percent : (series int/float) The percentage of `strategy.position_avg_price` to convert to price. 50 is 50% of the entry price.
Returns: (float) A value in the symbol's quote currency (USD for BTCUSD).
percentToCurrency(price, percent) Converts the percentage of a price to money.
Parameters:
price : (series int/float) The symbol's price.
percent : (series int/float) The percentage of `price` to calculate.
Returns: (float) A value in the symbol's currency.
percentProfit(exitPrice) Calculates the profit (as a percentage of the position's `strategy.position_avg_price` entry price) if the trade is closed at `exitPrice`.
Parameters:
exitPrice : (series int/float) The potential price to close the position.
Returns: (float) Percentage profit for the current position if closed at the `exitPrice`.
priceToTicks(price) Converts a price to ticks.
Parameters:
price : (series int/float) Price to convert to ticks.
Returns: (float) A quantity of ticks.
ticksToPrice(price) Converts ticks to a price offset from the average entry price.
Parameters:
price : (series int/float) Ticks to convert to a price.
Returns: (float) A price level that has a distance from the entry price equal to the specified number of ticks.
ticksToCurrency(ticks) Converts ticks to money.
Parameters:
ticks : (series int/float) Number of ticks.
Returns: (float) Money amount in the symbol's currency.
ticksToStopLevel(ticks) Calculates a stop loss level using a distance in ticks from the current `strategy.position_avg_price` entry price. This value can be plotted on the chart, or used as an argument to the `stop` parameter of a `strategy.exit()` call. NOTE: The stop level automatically flips based on whether the position is long or short.
Parameters:
ticks : (series int/float) The distance in ticks from the entry price to the stop loss level.
Returns: (float) A stop loss level for the current position.
ticksToTpLevel(ticks) Calculates a take profit level using a distance in ticks from the current `strategy.position_avg_price` entry price. This value can be plotted on the chart, or used as an argument to the `limit` parameter of a `strategy.exit()` call. NOTE: The take profit level automatically flips based on whether the position is long or short.
Parameters:
ticks : (series int/float) The distance in ticks from the entry price to the take profit level.
Returns: (float) A take profit level for the current position.
calcPositionSizeByStopLossTicks(stopLossTicks, riskPercent) Calculates the position size needed to implement a given stop loss (in ticks) corresponding to `riskPercent` of equity.
Parameters:
stopLossTicks : (series int) The stop loss (in ticks) that will be used to protect the position.
riskPercent : (series int/float) The maximum risk level as a percent of current equity (`strategy.equity`).
Returns: (int) A quantity of contracts.
calcPositionSizeByStopLossPercent(stopLossPercent, riskPercent, entryPrice) Calculates the position size needed to implement a given stop loss (%) corresponding to `riskPercent` of equity.
Parameters:
stopLossPercent : (series int/float) The stop loss in percent that will be used to protect the position.
riskPercent : (series int/float) The maximum risk level as a percent of current equity (`strategy.equity`).
entryPrice : (series int/float) The entry price of the position.
Returns: (int) A quantity of contracts.
exitPercent(id, lossPercent, profitPercent, qty, qtyPercent, comment, when, alertMessage) A wrapper of the `strategy.exit()` built-in which adds the possibility to specify loss & profit in as a value in percent. NOTE: this function may work incorrectly with pyramiding turned on due to the use of `strategy.position_avg_price` in its calculations of stop loss and take profit offsets.
Parameters:
id : (series string) The order identifier of the `strategy.exit()` call.
lossPercent : (series int/float) Stop loss as a percent of the entry price.
profitPercent : (series int/float) Take profit as a percent of the entry price.
qty : (series int/float) Number of contracts/shares/lots/units to exit a trade with. The default value is `na`.
qtyPercent : (series int/float) The percent of the position's size to exit a trade with. If `qty` is `na`, the default value of `qty_percent` is 100.
comment : (series string) Optional. Additional notes on the order.
when : (series bool) Condition of the order. The order is placed if it is true.
alertMessage : (series string) An optional parameter which replaces the {{strategy.order.alert_message}} placeholder when it is used in the "Create Alert" dialog box's "Message" field.
Contrarian Period High & LowContrarian Period High & Low
This indicator pairs nicely with the Contrarian 100 MA and can be located here:
Overview
The "Contrarian Period High & Low" indicator is a powerful technical analysis tool designed for traders seeking to identify key support and resistance levels and capitalize on contrarian trading opportunities. By tracking the highest highs and lowest lows over user-defined periods (Daily, Weekly, or Monthly), this indicator plots historical levels and generates buy and sell signals when price breaks these levels in a contrarian manner. A unique blue dot counter and action table enhance decision-making, making it ideal for swing traders, trend followers, and those trading forex, stocks, or cryptocurrencies. Optimized for daily charts, it can be adapted to other timeframes with proper testing.
How It Works
The indicator identifies the highest high and lowest low within a specified period (e.g., daily, weekly, or monthly) and draws horizontal lines for the previous period’s extremes on the chart. These levels act as dynamic support and resistance zones. Contrarian signals are generated when the price crosses below the previous period’s low (buy signal) or above the previous period’s high (sell signal), indicating potential reversals. A blue dot counter tracks consecutive buy signals, and a table displays the count and recommended action, helping traders decide whether to hold or flip positions.
Key Components
Period High/Low Levels: Tracks the highest high and lowest low for each period, plotting red lines for highs and green lines for lows from the bar where they occurred, extending for a user-defined length (default: 200 bars).
Contrarian Signals: Generates buy signals (blue circles) when price crosses below the previous period’s low and sell signals (white circles) when price crosses above the previous period’s high, designed to capture potential reversals.
Blue Dot Tracker: Counts consecutive buy signals (“blue dots”). If three or more occur, it suggests a stronger trend, with the table recommending whether to “Hold Investment” or “Flip Investment.”
Action Table: A 2x2 table in the bottom-right corner displays the blue dot count and action (“Hold Investment” if count ≥ 4, else “Flip Investment”) for quick reference.
Mathematical Concepts
Period Detection: Uses an approximate bar count to define periods (1 bar for Daily, 5 bars for Weekly, 20 bars for Monthly on a daily chart). When a new period starts, the previous period’s high/low is finalized and plotted.
High/Low Tracking:
Highest high (periodHigh) and lowest low (periodLow) are updated within the period.
Lines are drawn at these levels when the period ends, starting from the bar where the extreme occurred (periodHighBar, periodLowBar).
Signal Logic:
Buy signal: ta.crossunder(close , prevPeriodLow) and not lowBroken and barstate.isconfirmed
Sell signal: ta.crossover(close , prevPeriodHigh) and not highBroken and barstate.isconfirmed
Flags (highBroken, lowBroken) prevent multiple signals for the same level within a period.
Blue Dot Counter: Increments on each buy signal, resets on a sell signal or if price exceeds the entry price after three or more buy signals.
Entry and Exit Rules
Buy Signal (Blue Circle): Triggered when the price crosses below the previous period’s low, suggesting a potential oversold condition and buying opportunity. The signal appears as a blue circle below the price bar.
Sell Signal (White Circle): Triggered when the price crosses above the previous period’s high, indicating a potential overbought condition and selling opportunity. The signal appears as a white circle above the price bar.
Blue Dot Tracker:
Increments blueDotCount on each buy signal and sets an entryPrice on the first buy.
Resets on a sell signal or if price exceeds entryPrice after three or more buy signals.
If blueDotCount >= 3, the table suggests holding; if >= 4, it reinforces “Hold Investment.”
Exit Rules: Exit a buy position on a sell signal or when price exceeds the entry price after three or more buy signals. Combine with other tools (e.g., trendlines, support/resistance) for additional confirmation. Always apply proper risk management.
Recommended Usage
The "Contrarian Period High & Low" indicator is optimized for daily charts but can be adapted to other timeframes (e.g., 1H, 4H) with adjustments to the period bar count. It excels in markets with clear support/resistance levels and potential reversal zones. Traders should:
Backtest the indicator on their chosen asset and timeframe to validate signal reliability.
Combine with other technical tools (e.g., moving averages, Fibonacci levels) for stronger trade confirmation.
Adjust barsPerPeriod (e.g., ~120 bars for Weekly on hourly charts) based on the chart timeframe and market volatility.
Monitor the action table to guide position management based on blue dot counts.
Customization Options
Period Type: Choose between Daily, Weekly, or Monthly periods (default: Monthly).
Line Length: Set the length of high/low lines in bars (default: 200).
Show Highs/Lows: Toggle visibility of period high (red) and low (green) lines.
Max Lines to Keep: Limit the number of historical lines displayed (default: 10).
Hide Signals: Toggle buy/sell signal visibility for a cleaner chart.
Table Display: A fixed table in the bottom-right corner shows the blue dot count and action, with yellow (Hold) or green (Flip) backgrounds based on the count.
Why Use This Indicator?
The "Contrarian Period High & Low" indicator offers a unique blend of support/resistance visualization and contrarian signal generation, making it a versatile tool for identifying potential reversals. Its clear visual cues (lines and signals), blue dot tracker, and actionable table provide traders with an intuitive way to monitor market structure and manage trades. Whether you’re a beginner or an experienced trader, this indicator enhances your ability to spot key levels and time entries/exits effectively.
Tips for Users
Test the indicator thoroughly on your chosen market and timeframe to optimize settings (e.g., adjust barsPerPeriod for non-daily charts).
Use in conjunction with price action or other indicators for stronger trade setups.
Monitor the action table to decide whether to hold or flip positions based on blue dot counts.
Ensure your chart timeframe aligns with the selected period type (e.g., daily chart for Monthly periods).
Apply strict risk management to protect against false breakouts.
Happy trading with the Contrarian Period High & Low indicator! Share your feedback and strategies in the TradingView community!
Momentum Long + Short Strategy (BTC 3H)Momentum Long + Short Strategy (BTC 3H)
🔍 How It Works, Step by Step
Detect the Trend (📈/📉)
Calculate two moving averages (100-period and 500-period), either EMA or SMA.
For longs, we require MA100 > MA500 (uptrend).
For shorts, we block entries if MA100 exceeds MA500 by more than a set percentage (to avoid fading a powerful uptrend).
Apply Momentum Filters (⚡️)
RSI Filter: Measures recent strength—only allow longs when RSI crosses above its smoothed average, and shorts when RSI dips below the oversold threshold.
ADX Filter: Gauges trend strength—ensures we only enter when a meaningful trend exists (optional).
ATR Filter: Confirms volatility—avoids choppy, low-volatility conditions by requiring ATR to exceed its smoothed value (optional).
Confirm Entry Conditions (✅)
Long Entry:
Price is above both MAs
Trend alignment & optional filters pass ✅
Short Entry:
Price is below both MAs and below the lower Bollinger Band
RSI is sufficiently oversold
Trend-blocker & ATR filter pass ✅
Position Sizing & Risk (💰)
Each trade uses 100 % of account equity by default.
One pyramid addition allowed, so you can scale in if the move continues.
Commission and slippage assumptions built in for realistic backtests.
Stops & Exits (🛑)
Long Stop-Loss: e.g. 3 % below entry.
Long Auto-Exit: If price falls back under the 500-period MA.
Short Stop-Loss: e.g. 3 % above entry.
Short Take-Profit: e.g. 4 % below entry.
🎨 Why It’s Powerful & Customizable
Modular Filters: Turn on/off RSI, ADX, ATR filters to suit different market regimes.
Adjustable Thresholds: Fine-tune stop-loss %, take-profit %, RSI lengths, MA gaps and more.
Multi-Timeframe Potential: Although coded for 3 h BTC, you can adapt it to stocks, forex or other cryptos—just recalibrate!
Backtest Fine-Tuned: Default settings were optimized via backtesting on historical BTC data—but they’re not guarantees of future performance.
⚠️ Warning & Disclaimer
This strategy is for educational purposes only and designed for a toy fund. Crypto markets are highly volatile—you can lose 100 % of your capital. It is not a predictive “holy grail” but a rules-based framework using past data. The parameters have been fine-tuned on historical data and are not valid for future trades without fresh calibration. Always practice with paper-trading first, use proper risk management, and do your own research before risking real money. 🚨🔒
Good luck exploring and experimenting! 🚀📊
1h Liquidity Swings Strategy with 1:2 RRLuxAlgo Liquidity Swings (Simulated):
Uses ta.pivothigh and ta.pivotlow to detect 1h swing highs (resistance) and swing lows (support).
The lookback parameter (default 5) controls swing point sensitivity.
Entry Logic:
Long: Uptrend, price crosses above 1h swing low (ta.crossover(low, support1h)), and price is below recent swing high (close < resistance1h).
Short: Downtrend, price crosses below 1h swing high (ta.crossunder(high, resistance1h)), and price is above recent swing low (close > support1h).
Take Profit (1:2 Risk-Reward):
Risk:
Long: risk = entryPrice - initialStopLoss.
Short: risk = initialStopLoss - entryPrice.
Take-profit price:
Long: takeProfitPrice = entryPrice + 2 * risk.
Short: takeProfitPrice = entryPrice - 2 * risk.
Set via strategy.exit’s limit parameter.
Stop-Loss:
Initial Stop-Loss:
Long: slLong = support1h * (1 - stopLossBuffer / 100).
Short: slShort = resistance1h * (1 + stopLossBuffer / 100).
Breakout Stop-Loss:
Long: close < support1h.
Short: close > resistance1h.
Managed via strategy.exit’s stop parameter.
Visualization:
Plots:
50-period SMA (trendMA, blue solid line).
1h resistance (resistance1h, red dashed line).
1h support (support1h, green dashed line).
Marks buy signals (green triangles below bars) and sell signals (red triangles above bars) using plotshape.
Usage Instructions
Add the Script:
Open TradingView’s Pine Editor, paste the code, and click “Add to Chart”.
Set Timeframe:
Use the 1-hour (1h) chart for intraday trading.
Adjust Parameters:
lookback: Swing high/low lookback period (default 5). Smaller values increase sensitivity; larger values reduce noise.
stopLossBuffer: Initial stop-loss buffer (default 0.5%).
maLength: Trend SMA period (default 50).
Backtesting:
Use the “Strategy Tester” to evaluate performance metrics (profit, win rate, drawdown).
Optimize parameters for your target market.
Notes on Limitations
LuxAlgo Liquidity Swings:
Simulated using ta.pivothigh and ta.pivotlow. LuxAlgo may include proprietary logic (e.g., volume or visit frequency filters), which requires the indicator’s code or settings for full integration.
Action: Please provide the Pine Script code or specific LuxAlgo settings if available.
Stop-Loss Breakout:
Uses closing price breakouts to reduce false signals. For more sensitive detection (e.g., high/low-based), I can modify the code upon request.
Market Suitability:
Ideal for high-liquidity markets (e.g., BTC/USD, EUR/USD). Choppy markets may cause false breakouts.
Action: Backtest in your target market to confirm suitability.
Fees:
Take-profit/stop-loss calculations exclude fees. Adjust for trading costs in live trading.
Swing Detection:
Swing high/low detection depends on market volatility. Optimize lookback for your market.
Verification
Tested in TradingView’s Pine Editor (@version=5):
plot function works without errors.
Entries occur strictly at 1h support (long) or resistance (short) in the trend direction.
Take-profit triggers at 1:2 risk-reward.
Stop-loss triggers on initial settings or 1h support/resistance breakouts.
Backtesting performs as expected.
Next Steps
Confirm Functionality:
Run the script and verify entries, take-profit (1:2), stop-loss, and trend filtering.
If issues occur (e.g., inaccurate signals, premature stop-loss), share backtest results or details.
LuxAlgo Liquidity Swings:
Provide the Pine Script code, settings, or logic details (e.g., volume filters) for LuxAlgo Liquidity Swings, and I’ll integrate them precisely.
IU Higher Timeframe MA Cross StrategyIU Higher Timeframe MA Cross Strategy
The IU Higher Timeframe MA Cross Strategy is a versatile trading tool designed to identify trend by utilizing two customizable moving averages (MAs) across different timeframes and types. This strategy includes detailed entry and exit rules with fully configurable inputs, offering flexibility to suit various trading styles.
Key Features:
- Two moving averages (MA1 and MA2) with customizable types, lengths, sources, and timeframes.
- Both long and short trade setups based on MA crossovers.
- Integrated risk management with adjustable stop-loss and take-profit levels based on a user-defined risk-to-reward (RTR) ratio.
- Clear visualization of MAs, entry points, stop-loss, and take-profit zones.
Inputs:
1. Risk-to-Reward Ratio (RTR):
- Defines the take-profit level in relation to the stop-loss distance. Default is 2.
2. MA1 Settings:
- Source: Select the data source for calculating MA1 (e.g., close, open, high, low). Default is close.
- Timeframe: Specify the timeframe for MA1 calculation. Default is 60 (60-minute chart).
- Length: Set the lookback period for MA1 calculation. Default is 20.
- Type: Choose the type of moving average (options: SMA, EMA, SMMA, WMA, VWMA). Default is EMA.
- Smooth: Option to enable or disable smoothing of MA1 to merge gaps. Default is true.
3. MA2 Settings:
- Source: Select the data source for calculating MA2 (e.g., close, open, high, low). Default is close.
- Timeframe: Specify the timeframe for MA2 calculation. Default is 60 (60-minute chart).
- Length: Set the lookback period for MA2 calculation. Default is 50.
- Type: Choose the type of moving average (options: SMA, EMA, SMMA, WMA, VWMA). Default is EMA.
- Smooth: Option to enable or disable smoothing of MA2 to merge gaps. Default is true.
Entry Rules:
- Long Entry:
- Triggered when MA1 crosses above MA2 (crossover).
- Entry is confirmed only when the bar is closed and no existing position is active.
- Short Entry:
- Triggered when MA1 crosses below MA2 (crossunder).
- Entry is confirmed only when the bar is closed and no existing position is active.
Exit Rules:
- Stop-Loss:
- For long positions: Set at the low of the bar preceding the entry.
- For short positions: Set at the high of the bar preceding the entry.
- Take-Profit:
- For long positions: Calculated as (Entry Price - Stop-Loss) * RTR + Entry Price.
- For short positions: Calculated as Entry Price - (Stop-Loss - Entry Price) * RTR.
Visualization:
- Plots MA1 and MA2 on the chart with distinct colors for easy identification.
- Highlights stop-loss and take-profit levels using shaded zones for clear visual representation.
- Displays the entry level for active positions.
This strategy provides a robust framework for traders to identify and act on trend reversals while maintaining strict risk management. The flexibility of its inputs allows for seamless customization to adapt to various market conditions and trading preferences.
SnowdexUtilsLibrary "SnowdexUtils"
the various function that often use when create a strategy trading.
f_backtesting_date(train_start_date, train_end_date, test_date, deploy_date)
Backtesting within a specific window based on deployment and testing dates.
Parameters:
train_start_date (int) : the start date for training the strategy.
train_end_date (int) : the end date for training the strategy.
test_date (bool) : if true, backtests within the period from `train_end_date` to the current time.
deploy_date (bool) : if true, the strategy backtests up to the current time.
Returns: given time falls within the specified window for backtesting.
f_init_ma(ma_type, source, length)
Initializes a moving average based on the specified type.
Parameters:
ma_type (simple string) : the type of moving average (e.g., "RMA", "EMA", "SMA", "WMA").
source (float) : the input series for the moving average calculation.
length (simple int) : the length of the moving average window.
Returns: the calculated moving average value.
f_init_tp(side, entry_price, rr, sl_open_position)
Calculates the target profit based on entry price, risk-reward ratio, and stop loss. The formula is `tp = entry price + (rr * (entry price - stop loss))`.
Parameters:
side (bool) : the trading side (true for long, false for short).
entry_price (float) : the entry price of the position.
rr (float) : the risk-reward ratio.
sl_open_position (float) : the stop loss price for the open position.
Returns: the calculated target profit value.
f_round_up(number, decimals)
Rounds up a number to a specified number of decimals.
Parameters:
number (float)
decimals (int)
Returns: The rounded-up number.
f_get_pip_size()
Calculates the pip size for the current instrument.
Returns: Pip size adjusted for Forex instruments or 1 for others.
f_table_get_position(value)
Maps a string to a table position constant.
Parameters:
value (string) : String representing the desired position (e.g., "Top Right").
Returns: The corresponding position constant or `na` for invalid values.
Position Size CalculatorThe provided Pine Script is a custom indicator titled "Position Size Calculator" designed to assist traders in calculating the appropriate size of a trading position based on predefined risk parameters. This script is intended to be overlaid on a trading chart, as indicated by `overlay=true`, allowing traders to visualize and adjust their risk and position size directly within the context of their trading strategy.
What It Does:
The core functionality of this script revolves around calculating the position size a trader should take based on three input parameters:
**Risk in USD (`Risk`)**: This represents the amount of money the trader is willing to risk on a single trade.
**Entry Price (`EntryPrice`)**: The price at which the trader plans to enter the market.
**Stop Loss (`StopLoss`)**: The price at which the trader plans to exit the market should the trade move against them, effectively limiting their loss.
The script calculates the position size using a function named `calculatePositionSize`, which performs the following steps:
It first calculates the `expectedLoss` by taking 90% (`0.9`) of the input risk. This implies that the script factors in a safety margin, assuming traders are willing to risk up to 90% of their stated risk amount per trade.
It then calculates the position size based on the distance between the Entry Price and the Stop Loss. This calculation adjusts based on whether the Entry Price is higher or lower than the Stop Loss, ensuring that the position size fits the risk profile regardless of trade direction.
The function returns several values: `risk`, `entryPrice`, `stopLoss`, `expectedLoss`, and `size`, which are then plotted on the chart.
How It Does It:
**Expected Loss Calculation**: By reducing the risk by 10% before calculating position size, the script provides a buffer to account for slippage or to ensure the trader does not fully utilize their risk budget on a single trade.
**Position Size Calculation**: The script calculates position size by dividing the adjusted risk (`expectedLoss`) by the price difference between the Entry Price and Stop Loss. This gives a quantitative measure of how many units of the asset can be bought or sold while staying within the risk parameters.
What Traders Can Use It For:
Traders can use this Position Size Calculator for several purposes:
- **Risk Management**: By determining the appropriate position size, traders can ensure that they do not overexpose themselves to market risk on a single trade.
- **Trade Planning**: Before entering a trade, the script allows traders to visualize their risk, entry, and exit points, helping them to make more informed decisions.
- **Consistency**: Using a standardized method for calculating position size helps traders maintain consistency in their trading approach, a key aspect of successful trading strategies.
- **Efficiency**: Automating the calculation of position size saves time and reduces the likelihood of manual calculation errors.
Overall, this Pine Script indicator is a practical tool for traders looking to implement strict risk management rules within their trading strategies, ensuring that each trade is sized appropriately according to their risk tolerance and market conditions.
CCI+EMA Strategy with Percentage or ATR TP/SL [Alifer]This is a momentum strategy based on the Commodity Channel Index (CCI), with the aim of entering long trades in oversold conditions and short trades in overbought conditions.
Optionally, you can enable an Exponential Moving Average (EMA) to only allow trading in the direction of the larger trend. Please note that the strategy will not plot the EMA. If you want, for visual confirmation, you can add to the chart an Exponential Moving Average as a second indicator, with the same settings used in the strategy’s built-in EMA.
The strategy also allows you to set internal Stop Loss and Take Profit levels, with the option to choose between Percentage-based TP/SL or ATR-based TP/SL.
The strategy can be adapted to multiple assets and timeframes:
Pick an asset and a timeframe
Zoom back as far as possible to identify meaningful positive and negative peaks of the CCI
Set Overbought and Oversold at a rough average of the peaks you identified
Adjust TP/SL according to your risk management strategy
Like the strategy? Give it a boost!
Have any questions? Leave a comment or drop me a message.
CAUTIONARY WARNING
Please note that this is a complex trading strategy that involves several inputs and conditions. Before using it in live trading, it is highly recommended to thoroughly test it on historical data and use risk management techniques to safeguard your capital. After backtesting, it's also highly recommended to perform a first live test with a small amount. Additionally, it's essential to have a good understanding of the strategy's behavior and potential risks. Only risk what you can afford to lose .
USED INDICATORS
1 — COMMODITY CHANNEL INDEX (CCI)
The Commodity Channel Index (CCI) is a technical analysis indicator used to measure the momentum of an asset. It was developed by Donald Lambert and first published in Commodities magazine (now Futures) in 1980. Despite its name, the CCI can be used in any market and is not just for commodities. The CCI compares current price to average price over a specific time period. The indicator fluctuates above or below zero, moving into positive or negative territory. While most values, approximately 75%, fall between -100 and +100, about 25% of the values fall outside this range, indicating a lot of weakness or strength in the price movement.
The CCI was originally developed to spot long-term trend changes but has been adapted by traders for use on all markets or timeframes. Trading with multiple timeframes provides more buy or sell signals for active traders. Traders often use the CCI on the longer-term chart to establish the dominant trend and on the shorter-term chart to isolate pullbacks and generate trade signals.
CCI is calculated with the following formula:
(Typical Price - Simple Moving Average) / (0.015 x Mean Deviation)
Some trading strategies based on CCI can produce multiple false signals or losing trades when conditions turn choppy. Implementing a stop-loss strategy can help cap risk, and testing the CCI strategy for profitability on your market and timeframe is a worthy first step before initiating trades.
2 — AVERAGE TRUE RANGE (ATR)
The Average True Range (ATR) is a technical analysis indicator that measures market volatility by calculating the average range of price movements in a financial asset over a specific period of time. The ATR was developed by J. Welles Wilder Jr. and introduced in his book “New Concepts in Technical Trading Systems” in 1978.
The ATR is calculated by taking the average of the true range over a specified period. The true range is the greatest of the following:
The difference between the current high and the current low.
The difference between the previous close and the current high.
The difference between the previous close and the current low.
The ATR can be used to set stop-loss orders. One way to use ATR for stop-loss orders is to multiply the ATR by a factor (such as 2 or 3) and subtract it from the entry price for long positions or add it to the entry price for short positions. This can help traders set stop-loss orders that are more adaptive to market volatility.
3 — EXPONENTIAL MOVING AVERAGE (EMA)
The Exponential Moving Average (EMA) is a type of moving average (MA) that places a greater weight and significance on the most recent data points.
The EMA is calculated by taking the average of the true range over a specified period. The true range is the greatest of the following:
The difference between the current high and the current low.
The difference between the previous close and the current high.
The difference between the previous close and the current low.
The EMA can be used by traders to produce buy and sell signals based on crossovers and divergences from the historical average. Traders often use several different EMA lengths, such as 10-day, 50-day, and 200-day moving averages.
The formula for calculating EMA is as follows:
Compute the Simple Moving Average (SMA).
Calculate the multiplier for weighting the EMA.
Calculate the current EMA using the following formula:
EMA = Closing price x multiplier + EMA (previous day) x (1-multiplier)
STRATEGY EXPLANATION
1 — INPUTS AND PARAMETERS
The strategy uses the Commodity Channel Index (CCI) with additional options for an Exponential Moving Average (EMA), Take Profit (TP) and Stop Loss (SL).
length : The period length for the CCI calculation.
overbought : The overbought level for the CCI. When CCI crosses above this level, it may signal a potential short entry.
oversold : The oversold level for the CCI. When CCI crosses below this level, it may signal a potential long entry.
useEMA : A boolean input to enable or disable the use of Exponential Moving Average (EMA) as a filter for long and short entries.
emaLength : The period length for the EMA if it is used.
2 — CCI CALCULATION
The CCI indicator is calculated using the following formula:
(src - ma) / (0.015 * ta.dev(src, length))
src is the typical price (average of high, low, and close) and ma is the Simple Moving Average (SMA) of src over the specified length.
3 — EMA CALCULATION
If the useEMA option is enabled, an EMA is calculated with the given emaLength .
4 — TAKE PROFIT AND STOP LOSS METHODS
The strategy offers two methods for TP and SL calculations: percentage-based and ATR-based.
tpSlMethod_percentage : A boolean input to choose the percentage-based method.
tpSlMethod_atr : A boolean input to choose the ATR-based method.
5 — PERCENTAGE-BASED TP AND SL
If tpSlMethod_percentage is chosen, the strategy calculates the TP and SL levels based on a percentage of the average entry price.
tp_percentage : The percentage value for Take Profit.
sl_percentage : The percentage value for Stop Loss.
6 — ATR-BASED TP AND SL
If tpSlMethod_atr is chosen, the strategy calculates the TP and SL levels based on Average True Range (ATR).
atrLength : The period length for the ATR calculation.
atrMultiplier : A multiplier applied to the ATR to set the SL level.
riskRewardRatio : The risk-reward ratio used to calculate the TP level.
7 — ENTRY CONDITIONS
The strategy defines two conditions for entering long and short positions based on CCI and, optionally, EMA.
Long Entry: CCI crosses below the oversold level, and if useEMA is enabled, the closing price should be above the EMA.
Short Entry: CCI crosses above the overbought level, and if useEMA is enabled, the closing price should be below the EMA.
8 — TP AND SL LEVELS
The strategy calculates the TP and SL levels based on the chosen method and updates them dynamically.
For the percentage-based method, the TP and SL levels are calculated as a percentage of the average entry price.
For the ATR-based method, the TP and SL levels are calculated using the ATR value and the specified multipliers.
9 — EXIT CONDITIONS
The strategy defines exit conditions for both long and short positions.
If there is a long position, it will be closed either at TP or SL levels based on the chosen method.
If there is a short position, it will be closed either at TP or SL levels based on the chosen method.
Additionally, positions will be closed if CCI crosses back above oversold in long positions or below overbought in short positions.
10 — PLOTTING
The script plots the CCI line along with overbought and oversold levels as horizontal lines.
The CCI line is colored red when above the overbought level, green when below the oversold level, and white otherwise.
The shaded region between the overbought and oversold levels is plotted as well.
swing tradeTHIS strategy is based on the
franklin ochao swing trade book
confirmed bullish - when ever stock closed above R2 (more bullish)
when ever stock closed between R1 AND R2 (moderatly bullish or consolidation phase with respect to previous trend)
entry1 for more bullish trend is buy at every dips means when ever price low below pivot when it open above the pivot
entry2 for more bullish trend is buy at low is below s1
keep strictly stoploss at s1 of previous day (r2 close day)
trend reversal is possible once stock close below s1 in 1hr time frame
virgin cpr or missed pivot is added a advantage
For bearish mode this vice verse
machine_learningLibrary "machine_learning"
euclidean(a, b)
Parameters:
a (array)
b (array)
manhattan(a, b)
Parameters:
a (array)
b (array)
cosine_similarity(a, b)
Parameters:
a (array)
b (array)
cosine_distance(a, b)
Parameters:
a (array)
b (array)
chebyshev(a, b)
Parameters:
a (array)
b (array)
minkowski(a, b, p)
Parameters:
a (array)
b (array)
p (float)
dot_product(a, b)
Parameters:
a (array)
b (array)
vector_norm(arr, p)
Parameters:
arr (array)
p (float)
sigmoid(x)
Parameters:
x (float)
sigmoid_derivative(x)
Parameters:
x (float)
tanh_derivative(x)
Parameters:
x (float)
relu(x)
Parameters:
x (float)
relu_derivative(x)
Parameters:
x (float)
leaky_relu(x, alpha)
Parameters:
x (float)
alpha (float)
leaky_relu_derivative(x, alpha)
Parameters:
x (float)
alpha (float)
elu(x, alpha)
Parameters:
x (float)
alpha (float)
gelu(x)
Parameters:
x (float)
swish(x, beta)
Parameters:
x (float)
beta (float)
softmax(arr)
Parameters:
arr (array)
apply_activation(arr, activation_type, alpha)
Parameters:
arr (array)
activation_type (string)
alpha (float)
normalize_minmax(arr, min_val, max_val)
Parameters:
arr (array)
min_val (float)
max_val (float)
normalize_zscore(arr, mean_val, std_val)
Parameters:
arr (array)
mean_val (float)
std_val (float)
normalize_matrix_cols(m)
Parameters:
m (matrix)
scaler_fit(arr, method)
Parameters:
arr (array)
method (string)
scaler_fit_matrix(m, method)
Parameters:
m (matrix)
method (string)
scaler_transform(scaler, arr)
Parameters:
scaler (ml_scaler)
arr (array)
scaler_transform_matrix(scaler, m)
Parameters:
scaler (ml_scaler)
m (matrix)
clip(x, lo, hi)
Parameters:
x (float)
lo (float)
hi (float)
clip_array(arr, lo, hi)
Parameters:
arr (array)
lo (float)
hi (float)
loss_mse(predicted, actual)
Parameters:
predicted (array)
actual (array)
loss_rmse(predicted, actual)
Parameters:
predicted (array)
actual (array)
loss_mae(predicted, actual)
Parameters:
predicted (array)
actual (array)
loss_binary_crossentropy(predicted, actual)
Parameters:
predicted (array)
actual (array)
loss_huber(predicted, actual, delta)
Parameters:
predicted (array)
actual (array)
delta (float)
gradient_step(weights, gradients, lr)
Parameters:
weights (array)
gradients (array)
lr (float)
adam_step(weights, gradients, m, v, lr, beta1, beta2, t, epsilon)
Parameters:
weights (array)
gradients (array)
m (array)
v (array)
lr (float)
beta1 (float)
beta2 (float)
t (int)
epsilon (float)
clip_gradients(gradients, max_norm)
Parameters:
gradients (array)
max_norm (float)
lr_decay(initial_lr, decay_rate, step)
Parameters:
initial_lr (float)
decay_rate (float)
step (int)
lr_cosine_annealing(initial_lr, min_lr, step, total_steps)
Parameters:
initial_lr (float)
min_lr (float)
step (int)
total_steps (int)
knn_create(k, distance_type)
Parameters:
k (int)
distance_type (string)
knn_fit(model, X, y)
Parameters:
model (ml_knn)
X (matrix)
y (array)
knn_predict(model, x)
Parameters:
model (ml_knn)
x (array)
knn_predict_proba(model, x)
Parameters:
model (ml_knn)
x (array)
knn_batch_predict(model, X)
Parameters:
model (ml_knn)
X (matrix)
linreg_fit(X, y)
Parameters:
X (matrix)
y (array)
ridge_fit(X, y, lambda)
Parameters:
X (matrix)
y (array)
lambda (float)
linreg_predict(model, x)
Parameters:
model (ml_linreg)
x (array)
linreg_predict_batch(model, X)
Parameters:
model (ml_linreg)
X (matrix)
linreg_score(model, X, y)
Parameters:
model (ml_linreg)
X (matrix)
y (array)
logreg_create(n_features, learning_rate, iterations)
Parameters:
n_features (int)
learning_rate (float)
iterations (int)
logreg_fit(model, X, y)
Parameters:
model (ml_logreg)
X (matrix)
y (array)
logreg_predict_proba(model, x)
Parameters:
model (ml_logreg)
x (array)
logreg_predict(model, x, threshold)
Parameters:
model (ml_logreg)
x (array)
threshold (float)
logreg_batch_predict(model, X, threshold)
Parameters:
model (ml_logreg)
X (matrix)
threshold (float)
nb_create(n_classes)
Parameters:
n_classes (int)
nb_fit(model, X, y)
Parameters:
model (ml_nb)
X (matrix)
y (array)
nb_predict_proba(model, x)
Parameters:
model (ml_nb)
x (array)
nb_predict(model, x)
Parameters:
model (ml_nb)
x (array)
nn_create(layers, activation)
Parameters:
layers (array)
activation (string)
nn_forward(model, x)
Parameters:
model (ml_nn)
x (array)
nn_predict_class(model, x)
Parameters:
model (ml_nn)
x (array)
accuracy(y_true, y_pred)
Parameters:
y_true (array)
y_pred (array)
precision(y_true, y_pred, positive_class)
Parameters:
y_true (array)
y_pred (array)
positive_class (int)
recall(y_true, y_pred, positive_class)
Parameters:
y_true (array)
y_pred (array)
positive_class (int)
f1_score(y_true, y_pred, positive_class)
Parameters:
y_true (array)
y_pred (array)
positive_class (int)
r_squared(y_true, y_pred)
Parameters:
y_true (array)
y_pred (array)
mse(y_true, y_pred)
Parameters:
y_true (array)
y_pred (array)
rmse(y_true, y_pred)
Parameters:
y_true (array)
y_pred (array)
mae(y_true, y_pred)
Parameters:
y_true (array)
y_pred (array)
confusion_matrix(y_true, y_pred, n_classes)
Parameters:
y_true (array)
y_pred (array)
n_classes (int)
sliding_window(data, window_size)
Parameters:
data (array)
window_size (int)
train_test_split(X, y, test_ratio)
Parameters:
X (matrix)
y (array)
test_ratio (float)
create_binary_labels(data, threshold)
Parameters:
data (array)
threshold (float)
lag_matrix(data, n_lags)
Parameters:
data (array)
n_lags (int)
signal_to_position(prediction, threshold_long, threshold_short)
Parameters:
prediction (float)
threshold_long (float)
threshold_short (float)
confidence_sizing(probability, max_size, min_confidence)
Parameters:
probability (float)
max_size (float)
min_confidence (float)
kelly_sizing(win_rate, avg_win, avg_loss, max_fraction)
Parameters:
win_rate (float)
avg_win (float)
avg_loss (float)
max_fraction (float)
sharpe_ratio(returns, risk_free_rate)
Parameters:
returns (array)
risk_free_rate (float)
sortino_ratio(returns, risk_free_rate)
Parameters:
returns (array)
risk_free_rate (float)
max_drawdown(equity)
Parameters:
equity (array)
atr_stop_loss(entry_price, atr, multiplier, is_long)
Parameters:
entry_price (float)
atr (float)
multiplier (float)
is_long (bool)
risk_reward_take_profit(entry_price, stop_loss, ratio)
Parameters:
entry_price (float)
stop_loss (float)
ratio (float)
ensemble_vote(predictions)
Parameters:
predictions (array)
ensemble_weighted_average(predictions, weights)
Parameters:
predictions (array)
weights (array)
smooth_prediction(current, previous, alpha)
Parameters:
current (float)
previous (float)
alpha (float)
regime_classifier(volatility, trend_strength, vol_threshold, trend_threshold)
Parameters:
volatility (float)
trend_strength (float)
vol_threshold (float)
trend_threshold (float)
ml_knn
Fields:
k (series int)
distance_type (series string)
X_train (matrix)
y_train (array)
ml_linreg
Fields:
coefficients (array)
intercept (series float)
lambda (series float)
ml_logreg
Fields:
weights (array)
bias (series float)
learning_rate (series float)
iterations (series int)
ml_nn
Fields:
layers (array)
weights (matrix)
biases (array)
weight_offsets (array)
bias_offsets (array)
activation (series string)
ml_nb
Fields:
class_priors (array)
means (matrix)
variances (matrix)
n_classes (series int)
ml_scaler
Fields:
min_vals (array)
max_vals (array)
means (array)
stds (array)
method (series string)
ml_train_result
Fields:
loss_history (array)
final_loss (series float)
converged (series bool)
iterations_run (series int)
ml_prediction
Fields:
class_label (series int)
probability (series float)
probabilities (array)
value (series float)
Impulse Reactor RSI-SMA Trend Indicator [ApexLegion]Impulse Reactor RSI-SMA Trend Indicator
Introduction and Theoretical Background
Design Rationale
Standard indicators frequently generate binary 'BUY' or 'SELL' signals without accounting for the broader market context. This often results in erratic "Flip-Flop" behavior, where signals are triggered indiscriminately regardless of the prevailing volatility regime.
Impulse Reactor was engineered to address this limitation by unifying two critical requirements: Quantitative Rigor and Execution Flexibility.
The Solution
Composite Analytical Framework This script is not a simple visual overlay of existing indicators. It is an algorithmic synthesis designed to function as a unified decision-making engine. The primary objective was to implement rigorous quantitative analysis (Volatility Normalization, Structural Filtering) directly within an alert-enabled framework. This architecture is designed to process signals through strict, multi-factor validation protocols before generating real-time notifications, allowing users to focus on structurally validated setups without manual monitoring.
How It Works
This is not a simple visual mashup. It utilizes a cross-validation algorithm where the Trend Structure acts as a gatekeeper for Momentum signals:
Logic over Lag: Unlike simple moving average crossovers, this script uses a 15-layer Gradient Ribbon to detect "Laminar Flow." If the ribbon is knotted (Compression), the system mathematically suppresses all signals.
Volatility Normalization: The core calculation adapts to ATR (Average True Range). This means the indicator automatically expands in volatile markets and contracts in quiet ones, maintaining accuracy without constant manual tweaking.
Adaptive Signal Thresholding: It incorporates an 'Anti-Greed' algorithm (Dynamic Thresholding) that automatically adjusts entry criteria based on trend duration. This logic aims to mitigate the risk of entering positions during periods of statistical trend exhaustion.
Why Use It?
Market State Decoding: The gradient Ribbon visualizes the underlying trend phase in real-time.
◦ Cyan/Blue Flow: Strong Bullish Trend (Laminar Flow).
◦ Magenta/Pink Flow: Strong Bearish Trend.
◦ Compressed/Knotted: When the ribbon lines are tightly squeezed or overlapping, it signals Consolidation. The system filters signals here to avoid chop.
Noise Reduction: The goal is not to catch every pivot, but to isolate high-confidence setups. The logic explicitly filters out minor fluctuations to help maintain position alignment with the broader trend.
⚖️ Chapter 1: System Architecture
Introduction: Composite Analytical Framework
System Overview
Impulse Reactor serves as a comprehensive technical analysis engine designed to synthesize three distinct market dimensions—Momentum, Volatility, and Trend Structure—into a unified decision-making framework. Unlike traditional methods that analyze these metrics in isolation, this system functions as a central processing unit that integrates disparate data streams to construct a coherent model of market behavior.
Operational Objective
The primary objective is to transition from single-dimensional signal generation to a multi-factor assessment model. By fusing data from the Impulse Core (Volatility), Gradient Oscillator (Momentum), and Structural Baseline (Trend), the system aims to filter out stochastic noise and identify high-probability trade setups grounded in quantitative confluence.
Market Microstructure Analysis: Limitations of Conventional Models
Extensive backtesting and quantitative analysis have identified three critical inefficiencies in standard oscillator-based strategies:
• Bounded Oscillator Limitations (The "Oscillation Trap"): Traditional indicators such as RSI or Stochastics are mathematically constrained between fixed values (0 to 100). In strong trending environments, these metrics often saturate in "overbought" or "oversold" zones. Consequently, traders relying on static thresholds frequently exit structurally valid positions prematurely or initiate counter-trend trades against prevailing momentum, resulting in suboptimal performance.
• Quantitative Blindness to Quality: Standard moving averages and trend indicators often fail to distinguish the qualitative nature of price movement. They treat low-volume drift and high-velocity expansion identically. This inability to account for "Volatility Quality" leads to delayed responsiveness during critical market events.
• Fractal Dissonance (Timeframe Disconnect): Financial markets exhibit fractal characteristics where trends on lower timeframes may contradict higher timeframe structures. Manual integration of multi-timeframe analysis increases cognitive load and susceptibility to human error, often resulting in conflicting biases at the point of execution.
Core Design Principles
To mitigate the aforementioned systemic inefficiencies, Impulse Reactor employs a modular architecture governed by three foundational principles:
Principle A:
Volatility Precursor Analysis Market mechanics demonstrate that volatility expansion often functions as a leading indicator for directional price movement. The system is engineered to detect "Volatility Deviation" — specifically, the divergence between short-term and long-term volatility baselines—prior to its manifestation in price action. This allows for entry timing aligned with the expansion phase of market volatility.
Principle B:
Momentum Density Visualization The system replaces singular momentum lines with a "Momentum Density" model utilizing a 15-layer Simple Moving Average (SMA) Ribbon.
• Concept: This visualization represents the aggregate strength and consistency of the trend.
• Application: A fully aligned and expanded ribbon indicates a robust trend structure ("Laminar Flow") capable of withstanding minor counter-trend noise, whereas a compressed ribbon signals consolidation or structural weakness.
Principle C:
Adaptive Confluence Protocols Signal validity is strictly governed by a multi-dimensional confluence logic. The system suppresses signal generation unless there is synchronized confirmation across all three analytical vectors:
1. Volatility: Confirmed expansion via the Impulse Core.
2. Momentum: Directional alignment via the Hybrid Oscillator.
3. Structure: Trend validation via the Baseline. This strict filtering mechanism significantly reduces false positives in non-trending (choppy) environments while maintaining sensitivity to genuine breakouts.
🔍 Chapter 2: Core Modules & Algorithmic Logic
Module A: Impulse Core (Normalized Volatility Deviation)
Operational Logic The Impulse Core functions as a volatility-normalized momentum gauge rather than a standard oscillator. It is designed to identify "Volatility Contraction" (Squeeze) and "Volatility Expansion" phases by quantifying the divergence between short-term and long-term volatility states.
Volatility Z-Score Normalization
The formula implements a custom normalization algorithm. Unlike standard oscillators that rely on absolute price changes, this logic calculates the Z-Score of the Volatility Spread.
◦ Numerator: (atr_f - atr_s) captures the raw momentum of volatility expansion.
◦ Denominator: (std_f + 1e-6) standardizes this value against historical variance.
◦ Result: This allows the indicator scales consistently across assets (e.g., Bitcoin vs. Euro) without manual recalibration.
f_impulse() =>
atr_f = ta.atr(fastLen) // Fast Volatility Baseline
atr_s = ta.atr(slowLen) // Slow Volatility Baseline
std_f = ta.stdev(atr_f, devLen) // Volatility Standard Deviation
(atr_f - atr_s) / (std_f + 1e-6) // Normalized Differential Calculation
Algorithmic Framework
• Differential Calculation: The system computes the spread between a Fast Volatility Baseline (ATR-10) and a Slow Volatility Baseline (ATR-30).
• Normalization Protocol: To standardize consistency across diverse asset classes (e.g., Forex vs. Crypto), the raw differential is divided by the standard deviation of the volatility itself over a 30-period lookback.
• Signal Generation:
◦ Contraction (Squeeze): When the Fast ATR compresses below the Slow ATR, it registers a potential volatility buildup phase.
◦ Expansion (Release): A rapid divergence of the Fast ATR above the Slow ATR signals a confirmed volatility expansion, validating the strength of the move.
Module B: Gradient Oscillator (RSI-SMA Hybrid)
Design Rationale To mitigate the "noise" and "false reversal" signals common in single-line oscillators (like standard RSI), this module utilizes a 15-Layer Gradient Ribbon to visualize momentum density and persistence.
Technical Architecture
• Ribbon Array: The system generates 15 sequential Simple Moving Averages (SMA) applied to a volatility-adjusted RSI source. The length of each layer increases incrementally.
• State Analysis:
Momentum Alignment (Laminar Flow): When all 15 layers are expanded and parallel, it indicates a robust trend where buying/selling pressure is distributed evenly across multiple timeframes. This state helps filter out premature "overbought/oversold" signals.
• Consolidation (Compression): When the distance between the fastest layer (Layer 1) and the slowest layer (Layer 15) approaches zero or the layers intersect, the system identifies a "Non-Tradable Zone," preventing entries during choppy market conditions.
// Laminar Flow Validation
f_validate_trend() =>
// Calculate spread between Ribbon layers
ribbon_spread = ta.stdev(ribbon_array, 15)
// Only allow signals if Ribbon is expanded (Laminar Flow)
is_flowing = ribbon_spread > min_expansion_threshold
// If compressed (Knotted), force signal to false
is_flowing ? signal : na
Module C: Adaptive Signal Filtering (Behavioral Bias Mitigation)
This subsystem, operating as an algorithmic "Anti-Greed" Mechanism, addresses the statistical tendency for signal degradation following prolonged trends.
Dynamic Threshold Adjustment
• Win Streak Detection: The algorithm internally tracks the outcome of closed trade cycles.
• Sensitivity Multiplier: Upon detecting consecutive successful signals in the same direction, a Penalty_Factor is applied to the entry logic.
• Operational Impact: This effectively raises the Required_Slope threshold for subsequent signals. For example, after three consecutive bullish signals, the system requires a 30% steeper trend angle to validate a fourth entry. This enforces stricter discipline during extended trends to reduce the probability of entering at the point of trend exhaustion.
Anti-Greed Logic: Dynamic Threshold Calculation
f_adjust_threshold(base_slope, win_streak) =>
// Adds a 10% penalty to the difficulty for every consecutive win
penalty_factor = 0.10
risk_scaler = 1 + (win_streak * penalty_factor)
// Returns the new, harder-to-reach threshold
base_slope * risk_scaler
Module D: Trend Baseline (Triple-Smoothed Structure)
The Trend Baseline serves as the structural filter for all signals. It employs a Triple-Smoothed Hybrid Algorithm designed to balance lag reduction with noise filtration.
Smoothing Stages
1. Volatility Banding: Utilizes a SuperTrend-based calculation to establish the upper and lower boundaries of price action.
2. Weighted Filter: Applies a Weighted Moving Average (WMA) to prioritize recent price data.
3. Exponential Smoothing: A final Exponential Moving Average (EMA) pass is applied to create a seamless baseline curve.
Functionality
This "Heavy" baseline resists minor intraday volatility spikes while remaining responsive to sustained structural shifts. A signal is only considered valid if the price action maintains structural integrity relative to this baseline
🚦 Chapter 3: Risk Management & Exit Protocols
Quantitative Risk Management (TP/SL & Trailing)
Foundational Architecture: Volatility-Adjusted Geometry Unlike strategies relying on static nominal values, Impulse Reactor establishes dynamic risk boundaries derived from quantitative volatility metrics. This design aligns trade invalidation levels mathematically with the current market regime.
• ATR-Based Dynamic Bracketing:
The protocol calculates Stop-Loss and Take-Profit levels by applying Fibonacci coefficients (Default: 0.786 for SL / 1.618 for TP) to the Average True Range (ATR).
◦ High Volatility Environments: The risk bands automatically expand to accommodate wider variance, preventing premature exits caused by standard market noise.
◦ Low Volatility Environments: The bands contract to tighten risk parameters, thereby dynamically adjusting the Risk-to-Reward (R:R) geometry.
• Close-Validation Protocol ("Soft Stop"):
Institutional algorithms frequently execute liquidity sweeps—driving prices briefly below key support levels to accumulate inventory.
◦ Mechanism: When the "Soft Stop" feature is enabled, the system filters out intraday volatility spikes. The stop-loss is conditional; execution is triggered only if the candle closes beyond the invalidation threshold.
◦ Strategic Advantage: This logic distinguishes between momentary price wicks and genuine structural breakdowns, preserving positions during transient volatility.
• Step-Function Trailing Mechanism:
To protect unrealized PnL while allowing for normal price breathing, a two-phase trailing methodology is employed:
◦ Phase 1 (Activation): The trailing function remains dormant until the price advances by a pre-defined percentage threshold.
◦ Phase 2 (Dynamic Floor): Once armed, the stop level creates a moving floor, adjusting relative to price action while maintaining a volatility-based (ATR) buffer to systematically protect unrealized PnL.
• Algorithmic Exit Protocols (Dynamic Liquidity Analysis)
◦ Rationale: Inefficiencies of Static Targets Static "Take Profit" levels often result in suboptimal exits. They compel traders to close positions based on arbitrary figures rather than evolving market structure, potentially capping upside during significant trends or retaining positions while the underlying trend structure deteriorates.
◦ Solution: Structural Integrity Assessment The system utilizes a Dynamic Liquidity Engine to continuously audit the validity of the position. Instead of targeting a specific price point, the algorithm evaluates whether the trend remains statistically robust.
Multi-Factor Exit Logic (The Tri-Vector System)
The Smart Exit protocol executes only when specific algorithmic invalidation criteria are met:
• 1. Momentum Exhaustion (Confluence Decay): The system monitors a 168-hour rolling average of the Confluence Score. A significant deviation below this historical baseline indicates momentum exhaustion, signaling that the driving force behind the trend has dissipated prior to a price reversal. This enables preemptive exits before a potential drawdown.
• 2. Statistical Over-Extension (Mean Reversion): Utilizing the core volatility logic, the system identifies instances where price deviates beyond 2.0 standard deviations from the mean. While the trend may be technically bullish, this statistical anomaly suggests a high probability of mean reversion (elastic snap-back), triggering a defensive exit to capitalize on peak valuation.
• 3. Oscillator Rejection (Immediate Pivot): To manage sudden V-shaped volatility, the system monitors RSI pivots. If a sharp "Pivot High" or divergence is detected, the protocol triggers an immediate "Peak Exit," bypassing standard trend filters to secure liquidity during high-velocity reversals.
🎨 Chapter 4: Visualization Guide
Gradient Oscillator Ribbon
The 15-layer SMA ribbon visualized via plot(r1...r15) represents the "Momentum Density" of the market.
• Visuals:
◦ Cyan/Blue Ribbon: Indicates Bullish Momentum.
◦ Pink/Magenta Ribbon: Indicates Bearish Momentum.
• Interpretation:
◦ Laminar Flow: When the ribbon expands widely and flows in parallel, it signifies a robust trend where momentum is distributed evenly across timeframes. This is the ideal state for trend-following.
◦ Compression (Consolidation): If the ribbon becomes narrow, twisted, or knotted, it indicates a "Non-Tradable Zone" where the market lacks a unified direction. Traders are advised to wait for clarity.
◦ Over-Extension: If the top layer crosses the Overbought (85) or Oversold (15) lines, it visually warns of potential market overheating.
Trend Baseline
The thick, color-changing line plotted via plot(baseline) represents the Structural Backbone of the market.
• Visuals: Changes color based on the trend direction (Blue for Bullish, Pink for Bearish).
• Interpretation:
Structural Filter: Long positions are statistically favored only when price action sustains above this baseline, while short positions are favored below it.
Dynamic Support/Resistance: The baseline acts as a dynamic support level during uptrends and resistance during downtrends.
Entry Signals & Labels
Text labels ("Long Entry", "Short Entry") appear when the system detects high-probability setups grounded in quantitative confluence.
• Visuals: Labeled signals appear above/below specific candles.
• Interpretation:
These signals represent moments where Volatility (Expansion), Momentum (Alignment), and Structure (Trend) are synchronized.
Smart Exit: Labels such as "Smart Exit" or "Peak Exit" appear when the system detects momentum exhaustion or structural decay, prompting a defensive exit to preserve capital.
Dynamic TP/SL Boxes
The semi-transparent colored zones drawn via fill() represent the risk management geometry.
• Visuals: Colored boxes extending from the entry point to the Take Profit (TP) and Stop Loss (SL) levels.
• Function:
Volatility-Adjusted Geometry: Unlike static price targets, these boxes expand during high volatility (to prevent wicks from stopping you out) and contract during low volatility (to optimize Risk-to-Reward ratios).
SAR + MACD Glow
Small glowing shapes appearing above or below candles.
• Visuals: Triangle or circle glows near the price bars.
• Interpretation:
This visual indicates a secondary confirmation where Parabolic SAR and MACD align with the main trend direction. It serves as an additional confluence factor to increase confidence in the trade setup.
Support/Resistance Table
A small table located at the bottom-right of the chart.
• Function: Automatically identifies and displays recent Pivot Highs (Resistance) and Pivot Lows (Support).
• Interpretation: These levels can be used as potential targets for Take Profit or invalidation points for manual Stop Loss adjustments.
🖥️ Chapter 5: Dashboard & Operational Guide
Integrated Analytics Panel (Dashboard Overview)
To facilitate rapid decision-making without manual calculation, the system aggregates critical market dimensions into a unified "Heads-Up Display" (HUD). This panel monitors real-time metrics across multiple timeframes and analytical vectors.
A. Intermediate Structure (12H Trend)
• Function: Anchors the intraday analysis to the broader market structure using a 12-hour rolling window.
• Interpretation:
◦ Bullish (> +0.5%): Indicates a positive structural bias. Long setups align with the macro flow.
◦ Bearish (< -0.5%): Indicates structural weakness. Short setups are statistically favored.
◦ Neutral: Represents a ranging environment where the Confluence Score becomes the primary weighting factor.
B. Composite Confluence Score (Signal Confidence)
• Definition: A probability metric derived from the synchronization of Volatility (Impulse Core), Momentum (Ribbon), and Trend (Baseline).
• Grading Scale:
Strong Buy/Sell (> 7.0 / < 3.0): Indicates full alignment across all three vectors. Represents a "Prime Setup" eligible for standard position sizing.
Buy/Sell (5.0–7.0 / 3.0–5.0): Indicates a valid trend but with moderate volatility confirmation.
Neutral: Signals conflicting data (e.g., Bullish Momentum vs. Bearish Structure). Trading is not recommended ("No-Trade Zone").
C. Statistical Deviation Status (Mean Reversion)
• Logic: Utilizes Bollinger Band deviation principles to quantify how far price has stretched from the statistical mean (20 SMA).
• Alert States:
Over-Extended (> 2.0 SD): Warning that price is statistically likely to revert to the mean (Elastic Snap-back), even if the trend remains technically valid. New entries are discouraged in this zone.
Normal: Price is within standard distribution limits, suitable for trend-following entries.
D. Volatility Regime Classification
• Metric: Compares current ATR against a 100-period historical baseline to categorize the market state.
• Regimes:
Low Volatility (Lvl < 1.0): Market Compression. Often precedes volatility expansion events.
Mid Volatility (Lvl 1.0 - 1.5): Standard operating environment.
High Volatility (Lvl > 1.5): Elevated market stress. Risk parameters should be adjusted (e.g., reduced position size) to account for increased variance.
E. Performance Telemetry
• Function: Displays the historical reliability of the Trend Baseline for the current asset and timeframe.
• Operational Threshold: If the displayed Win Rate falls below 40%, it suggests the current market behavior is incoherent (choppy) and does not respect trend logic. In such cases, switching assets or timeframes is recommended.
Operational Protocols & Signal Decoding
Visual Interpretation Standards
• Laminar Flow (Trade Confirmation): A valid trend is visually confirmed when the 15-layer SMA Ribbon is fully expanded and parallel. This indicates distributed momentum across timeframes.
• Consolidation (No-Trade): If the ribbon appears twisted, knotted, or compressed, the market lacks a unified directional vector.
• Baseline Interaction: The Triple-Smoothed Baseline acts as a dynamic support/resistance filter. Long positions remain valid only while price sustains above this structure.
System Calibration (Settings)
• Adaptive Signal Filtering (Prev. Anti-Greed): Enabled by default. This logic automatically raises the required trend slope threshold following consecutive wins to mitigate behavioral bias.
• Impulse Sensitivity: Controls the reactivity of the Volatility Core. Higher settings capture faster moves but may introduce more noise.
⚙️ Chapter 6: System Configuration & Alert Guide
This section provides a complete breakdown of every adjustable setting within Impulse Reactor to assist you in tailoring the engine to your specific needs.
🌐 LANGUAGE SETTINGS (Localization)
◦ Select Language (Default: English):
Function: Instantly translates all chart labels, dashboard texts into your preferred language.
Supported: English, Korean, Chinese, Spanish
⚡ IMPULSE CORE SETTINGS (Volatility Engine)
◦ Deviation Lookback (Default: 30): The period used to calculate the standard deviation of volatility.
Role: Sets the baseline for normalizing momentum. Higher values make the core smoother but slower to react.
◦ Fast Pulse Length (Default: 10): The short-term ATR period.
Role: Detects rapid volatility expansion.
◦ Slow Pulse Length (Default: 30): The long-term ATR baseline.
Role: Establishes the background volatility level. The core signal is derived from the divergence between Fast and Slow pulses.
🎯 TP/SL SETTINGS (Risk Management)
◦ SL/TP Fibonacci (Default: 0.786 / 1.618): Selects the Fibonacci ratio used for risk calculation.
◦ SL/TP Multiplier (Default: 1.5 / 2): Applies a multiplier to the ATR-based bands.
Role: Expands or contracts the Take Profit and Stop Loss boxes. Increase these values for higher volatility assets (like Altcoins) to avoid premature stop-outs.
◦ ATR Length (Default: 14): The lookback period for calculating the Average True Range used in risk geometry.
◦ Use Soft Stop (Close Basis):
Role: If enabled, Stop Loss alerts only trigger if a candle closes beyond the invalidation level. This prevents being stopped out by wick manipulations.
🔊 RIBBON SETTINGS (Momentum Visualization)
◦ Show SMA Ribbon: Toggles the visibility of the 15-layer gradient ribbon.
◦ Ribbon Line Count (Default: 15): The number of SMA lines in the ribbon array.
◦ Ribbon Start Length (Default: 2) & Step (Default: 1): Defines the spread of the ribbon.
Role: Controls the "thickness" of the momentum density visualization. A wider step creates a broader ribbon, useful for higher timeframes.
📎 DISPLAY OPTIONS
◦ Show Entry Lines / TP/SL Box / Position Labels / S/R Levels / Dashboard: Toggles individual visual elements on the chart to reduce clutter.
◦ Show SAR+MACD Glow: Enables the secondary confirmation shapes (triangles/circles) above/below candles.
📈 TREND BASELINE (Structural Filter)
◦ Supertrend Factor (Default: 12) & ATR Period (Default: 90): Controls the sensitivity of the underlying Supertrend algorithm used for the baseline calculation.
◦ WMA Length (40) & EMA Length (14): The smoothing periods for the Triple-Smoothed Baseline.
◦ Min Trend Duration (Default: 10): The minimum number of bars the trend must be established before a signal is considered valid.
🧠 SMART EXIT (Dynamic Liquidity)
◦ Use Smart Exit: Enables the momentum exhaustion logic.
◦ Exit Threshold Score (Default: 3): The sensitivity level for triggering a Smart Exit. Lower values trigger earlier exits.
◦ Average Period (168) & Min Hold Bars (5): Defines the rolling window for momentum decay analysis and the minimum duration a trade must be held before Smart Exit logic activates.
🛡️ TRAILING STOP (Step)
◦ Use Trailing Stop: Activates the step-function trailing mechanism.
◦ Step 1 Activation % (0.5) & Offset % (0.5): The price must move 0.5% in your favor to arm the first trail level, which sets a stop 0.5% behind price.
◦ Step 2 Activation % (1) & Offset % (0.2): Once price moves 1%, the trail tightens to 0.2%, securing the position.
🌀 SAR & MACD SETTINGS (Secondary Confirmation)
◦ SAR Start/Increment/Max: Standard Parabolic SAR parameters.
◦ SAR Score Scaling (ATR): Adjusts how much weight the SAR signal has in the overall confluence score.
◦ MACD Fast/Slow/Signal: Standard MACD parameters used for the "Glow" signals.
🔄 ANTI-GREED LOGIC (Behavioral Bias)
◦ Strict Entry after Win: Enables the negative feedback loop.
◦ Strict Multiplier (Default: 1.1): Increases the entry difficulty by 10% after each win.
Role: Prevents overtrading and entering at the top of an extended trend.
🌍 HTF FILTER (Multi-Timeframe)
◦ Use Auto-Adaptive HTF Filter: Automatically selects a higher timeframe (e.g., 1H -> 4H) to filter signals.
◦ Bypass HTF on Steep Trigger: Allows an entry even against the HTF trend if the local momentum slope is exceptionally steep (catch powerful reversals).
📉 RSI PEAK & CHOPPINESS
◦ RSI Peak Exit (Instant): Triggers an immediate exit if a sharp RSI pivot (V-shape) is detected.
◦ Choppiness Filter: Suppresses signals if the Choppiness Index is above the threshold (Default: 60), indicating a flat market.
📐 SLOPE TRIGGER LOGIC
◦ Force Entry on Steep Slope: Overrides other filters if the price angle is extremely vertical (high velocity).
◦ Slope Sensitivity (1.5): The angle required to trigger this override.
⛔ FLAT MARKET FILTER (ADX & ATR)
◦ Use ADX Filter: Blocks signals if ADX is below the threshold (Default: 20), indicating no trend.
◦ Use ATR Flat Filter: Blocks signals if volatility drops below a critical level (dead market).
🔔 Alert Configuration Guide
Impulse Reactor is designed with a comprehensive suite of alert conditions, allowing you to automate your trading or receive real-time notifications for specific market events.
How to Set Up:
Click the "Alert" (Clock) icon in the TradingView toolbar.
Select "Impulse Reactor " from the Condition dropdown.
Choose one of the specific trigger conditions below:
🚀 Entry Signals (Trend Initiation)
Long Entry:
Trigger: Fires when a confirmed Bullish Setup is detected (Momentum + Volatility + Structure align).
Usage: Use this to enter new Long positions.
Short Entry:
Trigger: Fires when a confirmed Bearish Setup is detected.
Usage: Use this to enter new Short positions.
🎯 Profit Taking (Target Levels)
Long TP:
Trigger: Fires when price hits the calculated Take Profit level for a Long trade.
Usage: Automate partial or full profit taking.
Short TP:
Trigger: Fires when price hits the calculated Take Profit level for a Short trade.
Usage: Automate partial or full profit taking.
🛡️ Defensive Exits (Risk Management)
Smart Exit:
Trigger: Fires when the system detects momentum decay or statistical exhaustion (even if the trend hasn't fully reversed).
Usage: Recommended for tightening stops or closing positions early to preserve gains.
Overbought / Oversold:
Trigger: Fires when the ribbon extends into extreme zones.
Usage: Warning signal to prepare for a potential reversal or pullback.
💡 Secondary Confirmation (Confluence)
SAR+MACD Bullish:
Trigger: Fires when Parabolic SAR and MACD align bullishly with the main trend.
Usage: Ideal for Pyramiding (adding to an existing winning position).
SAR+MACD Bearish:
Trigger: Fires when Parabolic SAR and MACD align bearishly.
Usage: Ideal for adding to short positions.
⚠️ Chapter 7: Conclusion & Risk Disclosure
Methodological Synthesis
Impulse Reactor represents a shift from reactive price tracking to proactive energy analysis. By decomposing market activity into its atomic components — Volatility, Momentum, and Structure — and reconstructing them into a coherent decision model, the system aims to provide a quantitative framework for market engagement. It is designed not to predict the future, but to identify high-probability conditions where kinetic energy and trend structure align.
Disclaimer & Risk Warnings
◦ Educational Purpose Only
This indicator, including all associated code, documentation, and visual outputs, is provided strictly for educational and informational purposes. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments.
◦ No Guarantee of Performance
Past performance is not indicative of future results. All metrics displayed on the dashboard (including "Win Rate" and "P&L") are theoretical calculations based on historical data. These figures do not account for real-world trading factors such as slippage, liquidity gaps, spread costs, or broker commissions.
◦ High-Risk Warning
Trading cryptocurrencies, futures, and leveraged financial products involves a substantial risk of loss. The use of leverage can amplify both gains and losses. Users acknowledge that they are solely responsible for their trading decisions and should conduct independent due diligence before executing any trades.
◦ Software Limitations
The software is provided "as is" without warranty. Users should be aware that market data feeds on analysis platforms may experience latency or outages, which can affect signal generation accuracy.
