Price Log Regression (by Currency)1. Introduction
This indicator draws a logarithmic regression line directly on top of the price candles, showing the long‑term “average” growth path of any asset in the currency you select (for example USD). It is inspired by popular log‑regression studies used on assets like Bitcoin, where price is transformed to a log scale and a straight regression line is used to visualize macro trends and diminishing returns over time.
2. Key Features
- Currency‑aware trend line : Before calculating the regression, the script converts the asset’s price into the chosen currency, so the line represents the trend of “price in USD”, not just the original quote on the chart.
- Logarithmic regression : The script takes the logarithm (base 10) of the converted price, applies a linear regression to that log series, and then converts the result back to normal price; this produces a smooth line that follows the exponential character of many long‑term price moves.
- On‑chart overlay : Only the regression line is plotted and `overlay` is enabled, so the line appears directly over your existing candles, keeping the chart clean and making it easy to compare current price versus its long‑term log‑trend in the selected currency.
3. How to Use
- Add the script to any symbol and timeframe, then choose the Currency input (for example set it to “USD” if you want to see the trend of that asset measured in Dolars).
- Adjust the Regression length input: longer lengths give a slower, smoother macro line, while shorter lengths react more to recent price action; use what best matches the horizon you are analysing.
- Read the line as an analytical tool, not as guaranteed support or resistance: if price is far above the line, it may indicate an extended move relative to its long‑term path in that currency; if it is far below, it may indicate a cheaper zone relative to that same path, always remembering that this is educational analysis and not financial advice.
Note: This indicator focuses on long‑term logarithmic trends rather than short‑term noise, it is best suited for longer‑horizon approaches such as swing trading and position trading, rather than intraday scalping.
Индикаторы и стратегии
Korocham MA & SwingSMA 3Lines , Swing High Low
An indicator that displays 3 SMA lines and Swing Highs/Lows with 5 bars to the left and right.
AllinOne-ADR/ATR/LoDdist./MarketCap/EPStable&EPSTTM/SMA/ShortsHi guy's,
here's my 2025 Chrismas present: coco's "all in one" script.
First, what's missing:
Institutional ownership% and increase (Use MarketBeat)
Short Percent of Float (isn't working) (Use MarketBeat)
IBD EPS Ranking (Use IBD with an LLM)
Insider ownership % (Use MarketBeat)
Daily Volume (use another script)
VRVP (use another script)
RSI (use another script)
OVB (use another script)
Even if you follow the “keep it simple” approach and avoid using too many indicators, this one can consolidate several key metrics in one place.
a quarterly EPS/Sales table (Table or HeadBand mode) with earnings-event arrows
a mini stats table (ADR%/ATR/LoD dist./Market Cap/EPS TTM × multiple)
an SMA bundle
an integrated Shorts module (short-volume/short-interest metrics).
Long explanation:
This is a consolidated Pine Script v6 overlay indicator built from four functional blocks that run together in one script.
It plots a full quarterly fundamentals dashboard and optionally prints earnings markers on the chart. It pulls EPS (actual, standardized fallback, and estimates) via request.earnings() and revenue plus related fields via request.financial(). A quarter “event” is detected by changes in actual/standardized/estimate series, then historical values are reconstructed with ta.valuewhen() so the script can display multiple past quarters even if the chart timeframe is not quarterly. From those reconstructed series it calculates YoY EPS % change (MarketSurge/MarketSmith style), optional QoQ EPS % change, EPS surprise %, the same set for sales, and optional Gross Margin and ROE series. It supports display quirks such as “#” labeling when the YoY base quarter was negative, capping at ±999%, “avoid N/A” behavior, and a compare mode that prints “current vs year-ago” values inside cells.
The fundamentals are rendered into tables with two presentation modes. The “Table” mode is a larger multi-row quarterly grid showing date (MMM-yy), EPS, EPS % change, optional QoQ, optional surprise, sales (scaled to M or B), sales % change, optional QoQ, optional surprise, and optional GM/ROE columns. The “HeadBand” mode builds a compact daily-style panel for the most recent quarters with merged header cells and aligned text, intended for non-weekly timeframes. Both modes use configurable sizing, borders, frame width, and MarketSmith/MarketSurge styling presets.
On earnings-event bars it can place triangle labels beneath the price bars. The label can show EPS only or EPS plus sales, can switch between YoY and QoQ depending on the toggle, and colors the text based on positive/negative performance.
A separate mini stats table prints quick trading context metrics: ADR% (range/close over N daily bars), daily ATR (Wilder), LoD distance as a percent of daily ATR, market cap computed from outstanding shares times price (scaled K/M/B/T), and EPS TTM multiplied by a configurable x-multiple (default x20), where EPS TTM is the sum of the last four reported quarters reconstructed from the same earnings-event logic. This table is intended to stay fixed in a standard corner location and update only on the last bar.
The script also includes an SMA bundle that can plot up to ten simple moving averages, with optional computation forced to daily bars for consistency across intraday charts. Each SMA line is conditionally colored based on whether price is above or below the SMA.
Finally, it includes a Shorts block (the “Short Volume Stamper” section). That module is responsible for short-related metrics (short volume/ratio style outputs) and is integrated as an additional feature section within the same indicator rather than a separate script.
Credit goes to the following excellent works, which helped me compile this script:
Fred6724 for the EPS table:
TheScrutiniser for the ADR/ATR/LoD/MarketCap:
stocksinboxx for the SMA layout:
Hope this helps. I’d been looking for this for a while and couldn’t find it, so I combined several scripts into one. Please let me know if you spot any mistakes. Wishing you all some boring trading sessions!
Danny's Quarter Zones - CompleteThis is a very good indicator which can make anybody profitable even me. so that's why im sharing it with you all . it was made specifically for NQ. to use it on ES I would have to mess around and see what works best. as it is it is good for NQ.
Liquidity Sweep Pro [Whale Edition]Liquidity Sweep Pro is a next-generation trading tool that bridges the gap between Smart Money Concepts (SMC) and Quantitative Volume Analysis.
Traditional "Liquidity Sweep" indicators often generate false signals by marking every wick crossover as a trade setup. This indicator solves that problem by filtering setups through a Quant VSA Engine. It asks not just "Did price sweep a level?" but "Was there institutional money behind this move?"
🔬 How It Works
The indicator operates on three synchronized layers:
1. Market Structure (Liquidity Pools) It automatically identifies key pivot points where retail Stop Losses are likely clustered:
Buy Side Liquidity (BSL): Areas above swing highs.
Sell Side Liquidity (SSL): Areas below swing lows.
2. The Quant Engine (Whale Detection) Instead of using simple volume averages, we apply statistical modeling to detect anomalies:
Log-Normal Z-Score: Normalizes volume data to detect statistically significant outliers (Sigma > 2.5). This adapts to market volatility, filtering out noise.
Kaufman Efficiency Ratio (KER): Analyzes the quality of price movement to classify the "Whale" type:
❄️ Absorption (Iceberg): High Volume + Low Price Movement. Signals a potential reversal.
🚀 Propulsion (Drive): High Volume + High Price Efficiency. Signals an aggressive breakout.
3. The Trigger (Smart Entry) A trade signal is generated ONLY when:
Price sweeps a liquidity level (wicking below/above).
Price closes back within the range.
Institutional Activity is confirmed (High Z-Score Volume).
Trend (EMA 200) and Momentum (RSI) filters are aligned.
🛡️ Features
Intrabar Analysis: Uses request.security_lower_tf to analyze the internal volume delta of the candle for maximum precision.
Automated Risk Management: Plots Entry, Take Profit, and Stop Loss levels directly on the chart based on ATR (Average True Range) and your preferred Risk:Reward ratio.
Unified Alerts: Includes a single "ANY SWEEP" alert condition, allowing you to monitor both Long and Short setups with just one TradingView alert.
Visual Classification: Candles with institutional activity are marked with a 🐋 symbol, even if no sweep occurs, helping you read the narrative.
⚙️ Best Settings & Usage
Timeframes: Works best on 15m, 1h, and 4h charts.
LTF Interval (Input): This is crucial.
If trading on the 1h chart, set LTF to 1 minute.
If trading on the 4h chart, set LTF to 5 minutes.
Whale Threshold: Default is 2.5 Sigma. Increase to 3.0 for fewer, higher-confidence signals, or decrease to 2.0 for more frequency.
⚠️ Disclaimer
This tool is for educational purposes only. It identifies statistical probabilities, not certainties. Always manage your risk and do not rely solely on one indicator.
Relative Strength Index SmoothedDefinition
The Relative Strength Index (RSI) is a well versed momentum based oscillator which is used to measure the speed (velocity) as well as the change (magnitude) of directional price movements. Essentially RSI, when graphed, provides a visual mean to monitor both the current, as well as historical, strength and weakness of a particular market. The strength or weakness is based on closing prices over the duration of a specified trading period creating a reliable metric of price and momentum changes. Given the popularity of cash settled instruments (stock indexes) and leveraged financial products (the entire field of derivatives); RSI has proven to be a viable indicator of price movements.
History
J.Welles Wilder Jr. is the creator of the Relative Strength Index. A former Navy mechanic, Wilder would later go on to a career as a mechanical engineer. After a few years of trading commodities, Wilder focused his efforts on the study of technical analysis. In 1978 he published New Concepts in Technical Trading Systems. This work featured the debut of his new momentum oscillator, the Relative Strength Index, better known as RSI.
Over the years, RSI has remained quite popular and is now seen as one of the core, essential tools used by technical analysts the world over. Some practitioners of RSI have gone on to further build upon the work of Wilder. One rather notable example is Andrew Cardwell who used RSI for trend confirmation.
Calculation
RSI = 100 – 100/ (1 + RS)
RS = Average Gain of n days UP / Average Loss of n days DOWN
For a practical example, the built-in Pine Script function rsi(), could be replicated in long form as follows.
change = change(close)
gain = change >= 0 ? change : 0.0
loss = change < 0 ? (-1) * change : 0.0
avgGain = rma(gain, 14)
avgLoss = rma(loss, 14)
rs = avgGain / avgLoss
rsi = 100 - (100 / (1 + rs))
"rsi", above, is exactly equal to rsi(close, 14).
The basics
As previously mentioned, RSI is a momentum based oscillator. What this means is that as an oscillator, this indicator operates within a band or a set range of numbers or parameters. Specifically, RSI operates between a scale of 0 and 100. The closer RSI is to 0, the weaker the momentum is for price movements. The opposite is also true. An RSI closer to 100 indicates a period of stronger momentum.
- 14 days is likely the most popular period, however traders have been known to use a wide variety of numbers of days.
What to look for
Overbought/Oversold
Wilder believed that when prices rose very rapidly and therefore momentum was high enough, that the underlying financial instrument/commodity would have to eventually be considered overbought and a selling opportunity was possibly at hand. Likewise, when prices dropped rapidly and therefore momentum was low enough, the financial instrument would at some point be considered oversold presenting a possible buying opportunity.
There are set number ranges within RSI that Wilder consider useful and noteworthy in this regard. According to Wilder, any number above 70 should be considered overbought and any number below 30 should be considered oversold.
An RSI between 30 and 70 was to be considered neutral and an RSI around 50 signified “no trend”.
Some traders believe that Wilder’s overbought/oversold ranges are too wide and choose to alter those ranges. For example, someone might consider any number above 80 as overbought and anything below 20 as oversold. This is entirely at the trader’s discretion.
Divergence
RSI Divergence occurs when there is a difference between what the price action is indicating and what RSI is indicating. These differences can be interpreted as an impending reversal. Specifically there are two types of divergences, bearish and bullish.
Bullish RSI Divergence – When price makes a new low but RSI makes a higher low.
Bearish RSI Divergence – When price makes a new high but RSI makes a lower high.
Wilder believed that Bearish Divergence creates a selling opportunity while Bullish Divergence creates a buying opportunity.
Failure Swings
Failure swings are another occurrence which Wilder believed increased the likelihood of a price reversal. One thing to keep in mind about failure swings is that they are completely independent of price and rely solely on RSI. Failure swings consist of four “steps” and are considered to be either Bullish (buying opportunity) or Bearish (selling opportunity).
Bullish Failure Swing
RSI drops below 30 (considered oversold).
RSI bounces back above 30.
RSI pulls back but remains above 30 (remains above oversold)
RSI breaks out above its previous high.
Bearish Failure Swing
RSI rises above 70 (considered overbought)
RSI drops back below 70
RSI rises slightly but remains below 70 (remains below overbought)
RSI drops lower than its previous low.
Cardwell’s trend confirmations
Of course no one indicator is a magic bullet and almost nothing can be taken simply at face value. Andrew Cardwell, who was mentioned earlier, was one of those students who took Wilder’s RSI interpretations and built upon them. Cardwell’s work with RSI led to RSI being a great tool not just for anticipating reversals but also for confirming trends.
Uptrends/Downtrends
Cardwell made keen observations while studying Wilder’s ideas of divergence. Cardwell believed that:
Bullish Divergence only occurs in a Bearish Trend.
Bearish Divergence only occurs in an Bullish Trend.
Both Bullish and Bearish Divergence usually cause a brief price correction and not an actual trend reversal.
What this means is that essentially Divergence should be used as a way to confirm trends and not necessarily anticipate reversals.
Reversals
Cardwell also discovered what are referred to as Positive and Negative Reversals. Positive and Negative Reversals are basically the opposite of Divergence.
Positive Reversal occurs when price makes a higher low while RSI makes a lower low. Price proceeds to rise. Positive Reversals only occur in Bullish Trends.
Negative Reversal occurs when price makes a lower high while RSI makes a higher high. Price proceeds to fall. Negative Reversals only occur in Bearish Trends.
Positive and Negative Reversals can be boiled down to cases where price outperformed momentum. And because Positive and Negative Reversals only occur in their specified trends, they can be used as yet another tool for trend confirmation.
Summary
For more than four decades the Relative Strength Index (RSI) has been an extremely valuable tool for almost any serious technical analyst. Wilder’s work with momentum laid the groundwork for future chartists and analysts to dive in deeper to further explore the implications of his RSI modeling and its correlation with underlying price movements. As such, RSI is simply one of the best tools or indicators in a trader’s arsenal of market metrics to develop most any trading methodology. Only the novice will take one look at RSI and assume which direction the market will be heading next based off of one number. Wilder believed that a bullish divergence was a sign that the market would soon be on the rise, while Cardwell believed that such a divergence was merely a slight price correction on the continued road of a downward trend. As with any indicator, a trader should take the time to research and experiment with the indicator before relying on it as a sole source of information for any trading decision. When used in proper its perspective, RSI has proven to be a core indicator and reliable metric of price, velocity and depth of market.
Middle Candle High / LowMiddle Candle High / Low – Liquidity Pivot Lines
This indicator identifies middle-candle pivot highs and lows based on wick extremes and plots them as liquidity lines extending to the right .
A pivot is formed when the middle candle’s wick is higher (for highs) or lower (for lows) than both the left and right candles. These levels often act as liquidity pools , where price may later react or get mitigated.
HMA 9/50 Crossover + RSI 50 Filter1. The Core Indicators
HMA 9 (Fast): Acts as the primary trigger line. Its unique calculation minimizes lag compared to standard moving averages, allowing for faster entries.
HMA 50 (Slow): Defines the medium-term trend direction and acts as the "anchor" for crossover signals.
RSI 14: Serves as a "momentum gate." Instead of traditional overbought/oversold levels, we use the 50 midline to confirm that the directional strength supports the crossover.
2. Entry Conditions
Long Entry: Triggered when the HMA 9 crosses above the HMA 50 AND the RSI is greater than 50.
Short Entry: Triggered when the HMA 9 crosses below the HMA 50 AND the RSI is less than 50.
3. Execution & Reversal
This strategy is currently configured as an Always-in-the-Market system.
A "Long" position is automatically closed when a "Short" signal is triggered.
To prevent "pyramiding" (buying multiple positions in one direction), the script checks the current position_size before opening new entries.
How to Use
Timeframe: Optimized for 3-minute (3m) candles but can be tuned for 1m to 15m scalping.
Settings: Use the Inputs panel to adjust HMA lengths based on the volatility of your specific asset (e.g., shorter for stable stocks, longer for volatile crypto).
Visuals:
Aqua Line: HMA 9
Orange Line: HMA 50
Green Background: Bullish RSI Momentum (> 50)
Red Background: Bearish RSI Momentum (< 50)
Risk Disclosure
Whipsaws: This strategy is likely to underperform in sideways markets.
Backtesting: Past performance does not guarantee future results. Always test this strategy in the Strategy Tester with appropriate commission and slippage settings before live use.
CME Quarterly ShiftsCME Quarterly Shifts - Institutional Quarter Levels
Overview:
The CME Quarterly Shifts indicator tracks price action based on actual CME futures contract rollover dates, not calendar quarters. This indicator plots the Open, High, Low, and Close (OHLC) for each quarter, with quarters defined by the third Friday of March, June, September, and December - the exact dates when CME quarterly futures contracts expire and roll over.
Why CME Contract Dates Matter:
Institutional traders, hedge funds, and large market participants typically structure their positions around futures contract expiration cycles. By tracking quarters based on CME rollover dates rather than calendar months, this indicator aligns with how major institutional players view quarterly timeframes and position their capital.
Key Features:
✓ Automatic CME contract rollover date calculation (3rd Friday of Mar/Jun/Sep/Dec)
✓ Displays Quarter Open, High, Low, and Close levels
✓ Vertical break lines marking the start of each new quarter
✓ Quarter labels (Q1, Q2, Q3, Q4) for easy identification
✓ Adjustable history - show up to 20 previous quarters
✓ Fully customizable colors and line widths
✓ Works on any instrument and timeframe
✓ Toggle individual OHLC levels on/off
How to Use:
Quarter Open: The opening price when the new quarter begins (at CME rollover)
Quarter High: The highest price reached during the current quarter
Quarter Low: The lowest price reached during the current quarter
Quarter Close: The closing price from the previous quarter
These levels often act as key support/resistance zones as institutions reference them for quarterly performance, rebalancing, and position management.
Settings:
Display Options: Toggle quarterly break lines, OHLC levels, and labels
Max Quarters: Control how many historical quarters to display (1-20)
Colors: Customize colors for each level and break lines
Styles: Adjust line widths for OHLC levels and quarterly breaks
Best Practices:
Combine with other Smart Money Concepts (liquidity, order blocks, FVGs)
Watch for price reactions at quarterly Open levels
Monitor quarterly highs/lows as potential targets or stop levels
Use on higher timeframes (4H, Daily, Weekly) for clearer institutional perspective
Pairs well with monthly and yearly levels for multi-timeframe confluence
Perfect For:
ICT (Inner Circle Trader) methodology followers
Smart Money Concepts traders
Swing and position traders
Institutional-focused technical analysis
Traders tracking quarterly performance levels
Works on all markets: Forex, Indices, Commodities, Crypto, Stocks
Williams %R Smoothed (EMA colour & bar toggle)From TradingView's description:
Williams %R (%R) is a momentum-based oscillator used in technical analysis, primarily to identify overbought and oversold conditions. The %R is based on a comparison between the current close and the highest high for a user defined look back period. %R Oscillates between 0 and -100 (note the negative values) with readings closer to zero indicating more overbought conditions and readings closer to -100 indicating oversold. Typically %R can generate set ups based on overbought and oversold conditions as well overall changes in momentum.
What's special?
This indicator adds two additional EMA lines to the original Williams %R indicator. Default EMA lengths are 5 and 13. The result is 2 smoother average lines, which are easier to read.
This indicator includes:
- signals for EMA crosses. EMA crosses can help indicate confirmed trend changes. Default colors are green and red
- signals for trend reversals on the faster EMA line. Default colors are blue and orange
Alerts available for bullish/bearish crossovers and reversals.
Stochastic RSI (adjustable fast line color)Definition
The Stochastic RSI indicator (Stoch RSI) is essentially an indicator of an indicator. It is used in technical analysis to provide a stochastic calculation to the RSI indicator. This means that it is a measure of RSI relative to its own high/low range over a user defined period of time. The Stochastic RSI is an oscillator that calculates a value between 0 and 1 which is then plotted as a line. This indicator is primarily used for identifying overbought and oversold conditions.
History
The Stochastic RSI (Stoch RSI) indicator was developed by Tushard Chande and Stanley Kroll. They introduced their indicator in their 1994 book The New Technical Trader.
Calculation
In this example, a very common 14 Period Stoch RSI is used.
Stoch RSI = (RSI - Lowest Low RSI) / (Highest High RSI - Lowest Low RSI)
Here are some approximate benchmark levels:
14 Day Stoch RSI = 1 when RSI is at its highest level in 14 Days.
14 Day Stoch RSI = .8 when RSI is near the high of its 14 Day high/low range.
14 Day Stoch RSI = .5 when RSI is in the middle of its 14 Day high/low range.
14 Day Stoch RSI = .2 when RSI is near the low of its 14 Day high/low range.
14 Day Stoch RSI = 0 when RSI is at its lowest level in 14 Days.
The basics
It is important to remember that the Stoch RSI is an indicator of an indicator making it two steps away from price. RSI is one step away from price and therefore a stochastic calculation of the RSI is two steps away. This is important because as with any indicator that is multiple steps away from price, Stoch RSI can have brief disconnects from actual price movement. That being said, as a range bound indicator, the Stoch RSI's primary function is identifying crossovers as well as overbought and oversold conditions.
What to look for
Overbought/Oversold
Overbought and Oversold conditions are traditionally different than the RSI. While RSI overbought and oversold conditions are traditionally set at 70 for overbought and 30 for oversold, Stoch RSI are typically .80 and .20 respectively. When using the Stoch RSI, overbought and oversold work best when trading along with the underlying trend.
During an uptrend, look for oversold conditions for points of entry.
During a downtrend, look for overbought conditions for points of entry.
Summary
When using Stoch RSI in technical analysis, a trader should be careful. By adding the Stochastic calculation to RSI, speed is greatly increased. This can generate many more signals and therefore more bad signals as well as the good ones. Stoch RSI needs to be combined with additional tools or indicators in order to be at its most effective. Using trend lines or basic chart pattern analysis can help to identify major, underlying trends and increase the Stoch RSI's accuracy. Using Stoch RSI to make trades that go against the underlying trend is a dangerous proposition.
Inputs
K
The time period to be used in calculating the %K. 3 is the default.
D
% D = Percent of Deviation between price and the average of previous prices (Momentum). The time period to be used in calculating the %D. 3 is the default.
RSI Length
The time period to be used in calculating the RSI
Stochastic Length
The time period to be used in calculating the Stochastic
RSI Source
Determines what data from each bar will be used in calculations. Close is the default.
Stock Breakout (Liquidity + Breakout)//@version=5
indicator("Stock Breakout (Liquidity + Breakout)", overlay=true)
// ===== Inputs =====
lenRange = input.int(20, "Consolidation Length")
lenVol = input.int(20, "Volume MA")
lenMFI = input.int(14, "MFI Length")
// ===== Indicators =====
rangeHigh = ta.highest(high, lenRange)
volMA = ta.sma(volume, lenVol)
mfi = ta.mfi(hlc3, lenMFI)
vwapLine = ta.vwap(close)
// ===== Conditions =====
liquidityIn = mfi > 50 and volume > volMA
priceBreak = close > rangeHigh
aboveVWAP = close > vwapLine
breakout = liquidityIn and priceBreak and aboveVWAP
// ===== Plot =====
plotshape(breakout, title="BREAKOUT",
style=shape.labelup, location=location.belowbar,
color=color.new(color.green, 0), text="")
plot(vwapLine, color=color.orange, linewidth=2, title="VWAP")
12M Cumulative Volume Delta12M of CVD Data for those who need to detect major Divergences or whatever is in your needs
Cumulative Day-Over-Day VWAPDay Over Day VWAP "MultiDay VWAP" It keeps a log of session vwap and marks it as a day over day vwap on your chart
MA Alignment DetectorMA Alignment Detector : If it is bullish MA alignment, the color becomes red, if it is bearlish MA alignment, the color become green.
Volume Weighted Average Pricendicator(title="Volume Weighted Average Price", shorttitle="VWAP", overlay=true, timeframe="", timeframe_gaps=true)
hideonDWM = input(false, title="Hide VWAP on 1D or Above", group="VWAP Settings", display = display.data_window)
var anchor = input.string(defval = "Session", title="Anchor Period",
options= , group="VWAP Settings")
src = input(title = "Source", defval = hlc3, group="VWAP Settings", display = display.data_window)
offset = input.int(0, title="Offset", group="VWAP Settings", minval=0, display = display.data_window)
BANDS_GROUP = "Bands Settings"
CALC_MODE_TOOLTIP = "Determines the units used to calculate the distance of the bands. When 'Percentage' is selected, a multiplier of 1 means 1%."
calcModeInput = input.string("Standard Deviation", "Bands Calculation Mode", options = , group = BANDS_GROUP, tooltip = CALC_MODE_TOOLTIP, display = display.data_window)
showBand_1 = input(true, title = "", group = BANDS_GROUP, inline = "band_1", display = display.data_window)
bandMult_1 = input.float(1.0, title = "Bands Multiplier #1", group = BANDS_GROUP, inline = "band_1", step = 0.5, minval=0, display = display.data_window, active = showBand_1)
showBand_2 = input(false, title = "", group = BANDS_GROUP, inline = "band_2", display = display.data_window)
bandMult_2 = input.float(2.0, title = "Bands Multiplier #2", group = BANDS_GROUP, inline = "band_2", step = 0.5, minval=0, display = display.data_window, active = showBand_2)
showBand_3 = input(false, title = "", group = BANDS_GROUP, inline = "band_3", display = display.data_window)
bandMult_3 = input.float(3.0, title = "Bands Multiplier #3", group = BANDS_GROUP, inline = "band_3", step = 0.5, minval=0, display = display.data_window, active = showBand_3)
cumVolume = ta.cum(volume)
if barstate.islast and cumVolume == 0
runtime.error("No volume is provided by the data vendor.")
isNewPeriod = switch anchor
"Earnings" =>
new_earnings_actual = request.earnings(syminfo.tickerid, earnings.actual, barmerge.gaps_on, barmerge.lookahead_on, ignore_invalid_symbol=true)
new_earnings_standardized = request.earnings(syminfo.tickerid, earnings.standardized, barmerge.gaps_on, barmerge.lookahead_on, ignore_invalid_symbol=true)
not na(new_earnings_actual) or not na(new_earnings_standardized)
"Dividends" =>
new_dividends = request.dividends(syminfo.tickerid, dividends.gross, barmerge.gaps_on, barmerge.lookahead_on, ignore_invalid_symbol=true)
not na(new_dividends)
"Splits" =>
new_split = request.splits(syminfo.tickerid, splits.denominator, barmerge.gaps_on, barmerge.lookahead_on, ignore_invalid_symbol=true)
not na(new_split)
"Session" => timeframe.change("D")
"Week" => timeframe.change("W")
"Month" => timeframe.change("M")
"Quarter" => timeframe.change("3M")
"Year" => timeframe.change("12M")
"Decade" => timeframe.change("12M") and year % 10 == 0
"Century" => timeframe.change("12M") and year % 100 == 0
=> false
isEsdAnchor = anchor == "Earnings" or anchor == "Dividends" or anchor == "Splits"
if na(src ) and not isEsdAnchor
isNewPeriod := true
float vwapValue = na
float upperBandValue1 = na
float lowerBandValue1 = na
float upperBandValue2 = na
float lowerBandValue2 = na
float upperBandValue3 = na
float lowerBandValue3 = na
if not (hideonDWM and timeframe.isdwm)
= ta.vwap(src, isNewPeriod, 1)
vwapValue := _vwap
stdevAbs = _stdevUpper - _vwap
bandBasis = calcModeInput == "Standard Deviation" ? stdevAbs : _vwap * 0.01
upperBandValue1 := _vwap + bandBasis * bandMult_1
lowerBandValue1 := _vwap - bandBasis * bandMult_1
upperBandValue2 := _vwap + bandBasis * bandMult_2
lowerBandValue2 := _vwap - bandBasis * bandMult_2
upperBandValue3 := _vwap + bandBasis * bandMult_3
lowerBandValue3 := _vwap - bandBasis * bandMult_3
plot(vwapValue, title = "VWAP", color = #2962FF, offset = offset)
displayBand1 = showBand_1 ? display.all : display.none
upperBand_1 = plot(upperBandValue1, title="Upper Band #1", color = color.green, offset = offset, display = displayBand1, editable = showBand_1)
lowerBand_1 = plot(lowerBandValue1, title="Lower Band #1", color = color.green, offset = offset, display = displayBand1, editable = showBand_1)
fill(upperBand_1, lowerBand_1, title="Bands Fill #1", color = color.new(color.green, 95), display = displayBand1, editable = showBand_1)
displayBand2 = showBand_2 ? display.all : display.none
upperBand_2 = plot(upperBandValue2, title="Upper Band #2", color = color.olive, offset = offset, display = displayBand2, editable = showBand_2)
lowerBand_2 = plot(lowerBandValue2, title="Lower Band #2", color = color.olive, offset = offset, display = displayBand2, editable = showBand_2)
fill(upperBand_2, lowerBand_2, title="Bands Fill #2", color = color.new(color.olive, 95), display = displayBand2, editable = showBand_2)
displayBand3 = showBand_3 ? display.all : display.none
upperBand_3 = plot(upperBandValue3, title="Upper Band #3", color = color.teal, offset = offset, display = displayBand3, editable = showBand_3)
lowerBand_3 = plot(lowerBandValue3, title="Lower Band #3", color = color.teal, offset = offset, display = displayBand3, editable = showBand_3)
fill(upperBand_3, lowerBand_3, title="Bands Fill #3", color = color.new(color.teal, 95), display = displayBand3, editable = showBand_3)
ETH 1-2-3 Rigor Strategy Entry & 2:1 Risk-Rewar- By: Labaxuria Descrição em Inglês (Copy & Paste):
This script is a technical analysis tool designed specifically for ETH/USDT on Daily (1D) and Weekly (1W) timeframes. It identifies the classic 1-2-3 reversal pattern to provide high-probability entry points with a strictly disciplined risk management approach.
Core Features:
C3 Trigger Identification: The indicator highlights the "Candle 3" (Confirmation Candle) where the breakout of "Point 2" occurs, validating the market structure shift.
Automated 2:1 Risk-Reward: Upon a BUY or SELL signal, the script automatically plots a Red Line (Stop Loss) at the recent pivot and a Green Line (Take Profit) at a fixed 2:1 ratio. This ensures that every win is twice the size of a potential loss.
Trend Filtering (Gray Line): It includes a 20-period Moving Average to ensure trades are aligned with the prevailing market momentum.
Compression Detection (White Candles): Identifies "Inside Bars" by coloring the candle body or borders white. This warns the trader of price compression and potential volatility buildup before a breakout.
How to Use:
BUY + C3: Enter long when the price closes above Point 2, ideally while trading above the gray 20-SMA.
SELL + C3: Enter short when the price closes below Point 2, ideally while trading below the gray 20-SMA.
Exit Strategy: Follow the plotted levels strictly. Exit at the red line to protect capital or at the green line to book profits.
iQsFFTLibrary "iQsFFT"
TODO: add library description here
2. Summary
A high-performance mathematical library designed to bring advanced spectral analysis and signal processing to the Pine Script ecosystem. This tool allows traders and developers to decompose price action into its underlying cyclical components, helping to distinguish market noise from dominant periodic trends.
3. How It Works
The methodology behind this library is based on digital signal processing (DSP) principles, specifically focusing on frequency domain transformation. Instead of looking at price as a simple time-series, this script translates price data into a frequency spectrum to identify the "DNA" of market movement.
Spectral Decomposition: The algorithm utilizes a complex mathematical transform to break down price movements into various frequencies. This allows the user to see which cycles (short-term vs. long-term) are currently influencing the market most heavily.
Signal Reconstruction: By analyzing the real and imaginary components of price data, the library can assist in filtering out high-frequency noise while retaining the core directional "harmonics" of the asset.
Power Spectrum Analysis: The tool calculates the "energy" behind specific price cycles. This helps in identifying whether a recent price move is a significant structural shift or merely a low-energy fluctuation.
4. Key Features
Dual-Direction Transformation: Supports both forward analysis (time-to-frequency) and inverse reconstruction (frequency-to-time).
Advanced Noise Filtering: Conceptually designed to separate dominant market cycles from random volatility.
Power Density Estimation: Quantifies the strength of specific frequencies to identify market resonance.
Optimized Computation: Built using efficient array-handling logic to manage complex calculations within the TradingView environment.
5. How to Use
As this is a library, it is intended to be integrated into other indicators or strategies.
Step 1: Import the library into your script using the import statement.
Step 2: Prepare your input data (real and imaginary arrays) ensuring the sample size is a power of 2 (e.g., 64, 128, 256) for optimal processing.
Step 3: Call the transformation functions to extract the frequency components of your chosen asset.
Step 4: Utilize the power spectrum output to identify which cycles are currently "dominant" and use them to forecast potential turning points.
6. Settings & Configuration
Transform Direction: Choose between Forward (analysis) or Inverse (reconstruction) modes.
Data Arrays: Input fields for the real and imaginary price components.
Input Size: Configuration for the sample window (requires power-of-two lengths for mathematical validity).
ma_PPLibrary "ma_PP"
Summary
The Adaptive Multi-Algorithm Moving Average Suite is a professional-grade technical analysis library designed for traders who require precision and flexibility in trend identification. This tool consolidates over 40 distinct smoothing algorithms—ranging from classic statistical averages to advanced signal-processing filters—into a single, high-performance interface.
Theoretical Methodology
This suite operates on the principle that no single mathematical model can perfectly capture market trends across all volatility regimes. Instead of relying on a standard calculation, this script provides access to a diverse array of weighting methodologies.
Signal Processing Logic: Several algorithms within the suite, such as the Hybrid Convolution Filter and Damped Sine Wave Filter, treat price action as a digital signal, applying frequency-domain logic to isolate the underlying trend from market noise.
Adaptive Volatility Weighting: Advanced modules like the Fractal Adaptive MA and Kaufman Adaptive MA dynamically adjust their sensitivity based on market efficiency. When markets are trending efficiently, the filter tightens; during choppy consolidation, it increases smoothing to prevent false signals.
Zero-Lag and Corrective Estimations: The suite includes proprietary-style logic designed to reduce the inherent delay found in traditional indicators. By utilizing recursive error correction and polynomial regression, the algorithms aim to track price action closer to its current "real-time" value without overshooting.
Key Features
Extensive Algorithm Library: Includes 40+ smoothing types including Jurik, Ehlers, Hull, and Fractal-based logic.
Dynamic Sensitivity Controls: Specialized inputs for adaptive filters to define minimum and maximum smoothing thresholds.
Volume-Integrated Analysis: Features algorithms that weigh price action relative to volume participation for more robust trend confirmation.
Modular Architecture: Designed to be easily integrated as a core engine for broader trading strategies.
How to Use
Step 1: Select Your Logic: Use the "Moving Average Type" dropdown to choose a smoothing method that matches your trading style (e.g., JMA for low lag or FRAMA for adaptive trend following).
Step 2: Calibrate the Period: Adjust the "Length" parameter to align the indicator with your specific timeframe and the asset's typical cycle.
Step 3: Identify Trend Shifts: Look for price crossing the filter line or the slope of the line changing direction as a primary signal for trend momentum.
Step 4: Execute Strategy: Use the filter as a dynamic support/resistance level or as a trend-filter for your existing entry signals.
Settings & Configuration
Moving Average Type: Select from over 40 specific smoothing algorithms.
Length: The primary lookback period used for the majority of calculations.
Min/Max Length: Specific constraints for adaptive algorithms (like KAMA) to control how much the filter is allowed to speed up or slow down.
FPT - Harami FPT – Harami (Wick Included) is a clean and minimalist candlestick pattern indicator that highlights Harami reversal formations using full candle ranges (wicks included).
This version follows a strict and objective definition of Harami by requiring the entire range of the second candle (high–low) to be fully contained within the range of the first candle.
🔹 Patterns Detected
Bullish Harami
First candle: Bearish
Second candle: Bullish
Second candle’s high and low are completely inside the first candle’s range
Bearish Harami
First candle: Bullish
Second candle: Bearish
Second candle’s high and low are completely inside the first candle’s range
Only the pattern-forming candle (second candle) is highlighted to keep the chart clean and focused.
🎨 Customization
Highlight Bullish, Bearish, or Both Harami patterns
Separate and fully customizable colors for bullish and bearish patterns via Inputs → Colors
Style tab colors are intentionally not used
🎯 Design Philosophy
No indicators
No filters
No assumptions about trend or volatility
This tool is designed for traders who prefer pure price action and want to identify Harami patterns in combination with:
Key levels
Support & resistance
Market structure
Session-based or discretionary analysis
⚠️ This indicator is for visual analysis only and does not provide trade signals.
Always apply proper risk management.
