ATR Trailing Stop (EMA Filter) with Adjustable ShiftATR and ema plotted to visualize best stop losses for scalping.
Индикаторы и стратегии
Nifty DTR CE/PE AlertsHow to use this for Nifty Options:
The "Safety" Zone (< 70%): If the dashboard is Green, Nifty still has fuel. This is when "Scalping" or "Trend Following" in options usually works best.
The "Caution" Zone (70% - 90%): The dashboard turns Orange. Be careful buying "Out of the Money" (OTM) calls/puts here; the move is likely reaching its peak.
The "Exhaustion" Zone (> 90%): The dashboard turns Red. Statistically, Nifty rarely exceeds its ATR significantly without a reversal.
Action: Stop adding new buy positions. Consider booking profits on your Nifty Options or look for "Mean Reversion" (shorting the peak).
FINRA Pressure Index - FixIndicator Description : works on tickers from NYSE / NYSE ARCA / NASDAQ
This indicator measures the intensity of short-selling speculation on a stock or ETF. By comparing the daily Short Volume to its moving average (typically 20 days), it calculates a relative strength ratio:
Ratio = 1.0: Short-selling activity is at its normal baseline.
Ratio > 1.5: An abnormally high level of short-selling activity is detected.
Unlike standard volume, it specifically isolates market participants betting on a price decline.
How to Use It
Short Squeeze (Counter-trend Buy Signal): If the price hits a historical support level while the indicator shows a significant spike (e.g., > 1.8), the market is considered "over-shorted." Even a minor bounce will force short sellers to cover their positions urgently, triggering a violent rally.
Distribution (Caution Signal): If the price stagnates near a resistance level while the FINRA pressure increases day after day, it indicates that "smart money" is accumulating short positions. The uptrend is likely losing steam.
OHLC an der Kerze: Hover-Tooltip + Live-Anzeige (v6)Moin Moin.
This Pine-script is helping to show the OHLC-data as tooltipps, effectively eliminationg the need to wander of/avert with the eyes' point of view to the left upper corner.
this helps to avoid a flush of the ultrashort-term-memory due to the aversion of the point of view, which neurologically interrupts the thought-processes. (You ma be noticing this effect if Your ultrashort-term-memory has been flushed for taking too long for an in-my-head caluclation like 1/7=0,14255... oh crap I lost it... again effect)
_Tschüß,
__Michael.
Trader Baboo Aanaa V 1.2this script uses ema five to generate bullish signal. it is comprised only of 5 ema
Vwap by EVThis indicator provides a complete multi-VWAP framework designed for traders who rely on price acceptance, value areas, and mean reversion across different market horizons. It plots Session, Daily, and Weekly VWAPs simultaneously, allowing users to understand short-term, intraday, and higher-timeframe value in a single, uncluttered view.
The Session VWAP supports custom trading hours and timezones, making it adaptable to equities, indices, forex, and crypto markets. All VWAP calculations are volume-weighted and non-repainting, with optional standard deviation bands based on true volume dispersion rather than fixed offsets. This ensures that each VWAP reflects genuine market participation and volatility.
Daily and Weekly VWAPs act as higher-timeframe equilibrium references, helping traders identify premium and discount zones, dynamic support and resistance, and directional bias. Optional band visibility and independent styling allow the indicator to remain clean while still providing depth when needed.
Volume SMA 9 / 20 / 50This is real time volume average lines having option to select period of volume lines . it not only provides volume with respect to price action but also we can find out real picture of price action pressure. use it with ADX and MACD wisely . only volume spike is not confirmation some times fake breakout , so wait for confirmation and participate at breakout confirmation.
Orion Time Matrix | ICT Macros [by AK]ORION TIME MATRIX | ICT MACRO SUITE
The Orion Time Matrix is a precision timing instrument designed to decipher the algorithmic "Heartbeat" and the timing of institutional order flow in US Index Futures markets, specifically Nasdaq (NQ) and S&P 500 (ES).
Inspired by the "Time & Price" teachings of Michael J. Huddleston (The Inner Circle Trader), this tool maps out the specific time windows where algorithms seek liquidity and price delivery is most efficient.
HelperScriptA Personal Helper Script based on FFriZz/Holiday/2
Only change the font size and language
Al Brooks_BarCount_Start from Opening🔹 Key Features
Counts from the RTH open every trading day
Stocks: 09:30–16:00 (New York Time)
Futures: 08:30–15:15 (Chicago Time)
Automatically detects stocks vs futures
Always displays the first bar of the session
Optional display every N bars to reduce chart clutter
Custom highlight rules
Highlight specific bar numbers (e.g. bar 18)
Highlight bar multiples (e.g. every 12 bars)
Fully customizable label size and colors
🔹 Why count from the open?
In Al Brooks’ Price Action framework:
The first 30–60 bars after the open often define the day’s structure
Trends, failed breakouts, and trading ranges frequently align with specific bar counts
Counting across overnight or pre-market sessions can distort intraday analysis
👉 This indicator resets precisely at the RTH open, keeping the count aligned with real trading decisions.
🔹 Inputs Overview
Display at every X bars
Show bar numbers at fixed intervals (bar 1 is always shown)
Count From RTH Open (Session Filter)
Limits counting strictly to regular trading hours (recommended ON)
Special Color Multiple
Highlights every N-th bar
Special Number 1 / 2
Highlights specific bar numbers
Label Size / Colors
Visual customization options
🔹 Markets Supported
✅ US index futures (ES, MES, NQ, MNQ, GC, CL – RTH)
✅ US stocks and indices (NYSE / NASDAQ)
❗ Not intended for 24h markets (e.g. crypto)
🔹 Usage Tips (Al Brooks Style)
Observe price behavior around early session bars (5–10)
Watch key counts like 12, 18, 24 for acceleration or failure
Combine with EMAs, trend lines, and trading-range highs/lows
Sector Momentum Dashboard (Pure 3M / 6M / 12M)Script Description (Simple + Accurate)
This script builds a sector‑momentum dashboard that ranks major U.S. sector ETFs based on their pure trailing performance over a selected lookback period. Instead of using academic momentum windows like 3‑1M or 12‑1M, it measures straight returns over the past 3, 6, or 12 months, using daily closing prices.
The script:
Pulls daily price data for 11 sector ETFs (XLK, XLC, XLI, XLF, XLB, XLV, XLU, XLY, XLE, XLP, XLRE)
Calculates each ETF’s return over the chosen lookback window:
3M = 63 trading days
6M = 126 trading days
12M = 252 trading days
Sorts the ETFs from strongest momentum to weakest
Displays the ranked list in a compact table on the chart
Highlights:
Top 3 sectors in green
Bottom 3 sectors in red
The intention is to give traders a quick, visual snapshot of sector leadership, making it easier to:
Identify which sectors are outperforming
Spot rotation trends
Build or adjust a sector‑rotation strategy
Compare relative strength across the market
It’s designed to be simple, fast, and reliable — ideal for anyone who wants a clean momentum‑based view of the U.S. sector landscape.
Bullish, Bearish, & Normal RSI1. Identifying "True" Momentum (The Aqua/Fuchsia Logic)The most useful part of this script is the comparison between the three lines.Bullish Conviction (Aqua): When both the Bullish and Bearish lines are above the Normal RSI, it suggests that even on "down" candles (red candles), the price isn't losing significant ground. The overall structure is buoyant.Bearish Conviction (Fuchsia): When both are below the Normal RSI, it indicates that even when you get "up" candles (green candles), they lack the strength to lift the average momentum. The sellers are effectively "smothering" the bounces.
2. Spotting Hidden Weakness/Strength (Spread Analysis)The "Spread" (the gap between rsiBull and rsiBear) provides a unique utility:ScenarioInterpretationUtilityWide SpreadHigh volatility and indecision. Green candles are very strong, but red candles are also very weak.Avoid trend-following; wait for a "squeeze" or narrowing.Tight SpreadHigh agreement in price action. Most candles are moving in a similar direction or with similar intensity.Great for identifying stable, trending moves with low noise.Bull/Bear CrossIf the Bullish RSI crosses above the Bearish RSI significantly.Can act as an early entry signal before the Standard RSI hits the 50-midline.
3. Practical Strategy Use CasesFilter for Breakouts: If you see a price breakout but the RSI color remains Gray, the move might lack "conviction." You ideally want to see the color flip to Aqua (for long) or Fuchsia (for short) as the breakout occurs.Exhaustion Signal: If the Normal RSI is overbought ($>70$) but the rsiBull begins to dip toward the rsiNormal, it suggests that the "green candle strength" is waning even if the price is staying high—a potential warning of a reversal.Potential Drawbacks to WatchLag: Like all RSI-based indicators, this is lagging. Because you are using a 14-period lookback on three different calculations, it may take a few bars to confirm a sentiment shift.Whipsaw in Sideways Markets: In a tight range-bound market, the color may flip between Aqua and Fuchsia rapidly, creating "noise."Pro-Tip: This indicator would be most effective when used in conjunction with Volume. If you get an "Aqua" signal on rising volume, the probability of a sustained trend is significantly higher.
Spearman Correlation🔗 Spearman Correlation – Ranked Relationship Tracker
Overview:
This indicator calculates and plots the Spearman Rank Correlation Coefficient between the current chart’s asset and a custom comparison ticker (the example shown is BTC vs the OTHERS market cap for crypto). Unlike Pearson correlation, which measures linear relationships, Spearman correlation captures monotonic (ranked) relationships—making it better suited for analysing assets that move in sync but not necessarily in a linear fashion.
🧠 What It Does:
Computes ranked correlation between two assets over a user-defined lookback period
Smooths the correlation curve for better readability
Visually shades the background by correlation strength and direction:
🟩 Strong Positive (+0.5 to +1)
🟨 Weak Positive (+0.1 to +0.5)
⬜ No Correlation (–0.1 to +0.1)
🟧 Weak Negative (–0.5 to –0.1)
🟥 Strong Negative (–1 to –0.5)
⚙️ User Inputs:
Lookback Period: Number of bars used to calculate correlation
Comparison Ticker: Choose any asset to compare against
Shading Toggles: Customize which correlation zones are highlighted
📈 Use Cases:
Identify evolving relationships between assets (e.g., BTC vs DXY, ETH vs SPX)
Spot when assets become inversely correlated or lose correlation entirely
Track regime shifts where traditional relationships break down or re-align
Use alongside trend or momentum strategies to add a cross-asset confirmation layer
🔍 Interpreting the Correlation:
+1 → Perfect positive (ranks match exactly)
+0.5 to +1 → Strong positive relationship
+0.1 to +0.5 → Weak but positive relationship
–0.1 to +0.1 → Essentially uncorrelated
–0.5 to –0.1 → Weak negative correlation
–1 to –0.5 → Strong inverse relationship
–1 → Perfect negative (rankings are completely opposite)
🧪 Technical Notes:
Calculation uses ranked returns to better reflect monotonic relationships
Smoothed with a simple moving average (SMA) for stability
Arrays are managed internally to maintain performance and adaptability
This script is ideal for traders seeking deeper insight into cross-asset dynamics, portfolio hedging, or timing divergence-based strategies.
Directional Comparisons - Two Tickers📊 Directional Comparisons – Two Tickers
Overview:
This tool allows you to visually and statistically compare the directional behaviour of any two assets on any chart timeframe. It identifies and color-codes each bar based on how both the current asset and your chosen comparison asset performed in that period (e.g., both up, both down, diverging). A statistical summary table dynamically updates in the corner of your chart, tracking the probability and streak performance of each condition.
🛠 How It Works:
Each candle is analysed and color-coded based on the relationship between the current chart's asset and a comparison asset of your choice:
✅ Green – Both tickers closed higher (bullish alignment)
🔻 Red – Both tickers closed lower (bearish alignment)
🔷 Blue – Current ticker up, comparison ticker down (positive divergence)
🟧 Orange – Current ticker down, comparison ticker up (negative divergence)
You can toggle each colour condition on/off independently.
📈 Statistical Table (Top Right):
For the candles in the visible chart range, the indicator displays:
The frequency (probability) of each condition
Longest, shortest, and average streaks for each condition
Average % change for both the current and comparison asset under each scenario
All stats auto-update as you zoom or scroll through the chart.
🔧 User Inputs:
Comparison Ticker: Choose any ticker symbol to compare against the current chart
Toggle Conditions: Enable or disable individual directional conditions (color-coded)
✅ Use Cases:
Spot high-probability alignment zones between two assets (e.g., BTC vs ETH, SPX vs VIX)
Identify divergence opportunities for trading signals
Analyse historical relationships and co-movements between assets
Perform correlation streak studies directly on the chart
🔍 Notes:
The script works across all timeframes (1min to monthly).
Stats only consider visible bars on your chart for responsiveness.
Ideal for pair traders, macro analysts, or anyone interested in cross-asset relationships.
Micro Futures Risk Calculator (Minimal)risk calculator based off of stop distance. to keep risk consistent for consistent growth
Crypto Session Range 📄 INDICATOR DESCRIPTION (ENGLISH)
Crypto Session Range (Custom Timezone) is a lightweight and accurate session-based indicator designed specifically for cryptocurrency markets (24/7).
This indicator allows traders to define custom trading time windows using any global timezone, solving common issues found in traditional session indicators that are built for stock markets.
🔹 Key Features
Custom timezone support (e.g. America/Puerto_Rico, America/New_York, UTC)
Up to 3 configurable trading sessions
Visual background highlighting during active sessions
Automatic High & Low range tracking for each session
Optional range extension after the session ends
Works on all crypto pairs and timeframes
🔹 Who Is This For?
Crypto traders who want precise session control
Day traders, scalpers, and session-based strategies
Traders who operate during specific market windows (London / NY / custom)
🔹 Notes
This indicator is not restricted to exchange trading hours and is fully compatible with 24/7 markets like crypto, unlike many default session tools.
Trap longs - Hamza Naveed// This source code is subject to the terms of the Mozilla Public License 2.0 at mozilla.org
//@version=5
indicator("Trap Longs - Hamza Naveed", max_labels_count = 500, overlay = false, format = format.volume)
g1 = '📊 Net Positions '
g2 = '📈 Moving Averages (VWMA/EMA) '
g3 = '⚙️ Additional Settings '
g4 = '🎚️ Profile '
g5 = '🖥️ Statistics '
g6 = '⚖️ Divergences'
// User inputs - General settings
dtype = input.string('Net Positions', 'Type', options = )
disp = input.string('Candles', 'Display as', options = )
cumu = input.string('Full Data', 'Cumulation', options = )
denom = input.string('Quote Currency', 'Quoted in', options = )
// User inputs - Data Source Settings
binance = input.bool(true, 'Binance USDT.P', inline = 'src')
binance2 = input.bool(true, 'Binance USD.P', inline = 'src')
binance3 = input.bool(true, 'Binance BUSD.P', inline = 'src2')
bitmex = input.bool(true, 'BitMEX USD.P', inline = 'src2')
bitmex2 = input.bool(true, 'BitMEX USDT.P ', inline = 'src3')
kraken = input.bool(true, 'Kraken USD.P', inline = 'src3')
// User inputs - Net Positions
showL = input.bool(true, 'NET LONGS ►', group = g1, inline='l')
showS = input.bool(false, 'NET SHORTS ►', group = g1, inline='s')
showD = input.bool(false, 'NET DELTA ►', group = g1, inline='d')
showR = input.bool(false, 'NET RATIO ►', group = g1, inline='r')
pcolL = input.color(#a5d6a7, '', group = g1, inline = 'l')
ncolL = input.color(#f77c80, '', group = g1, inline = 'l')
lcolL = input.color(#a5d6a7, '━', group = g1, inline = 'l')
pcolS = input.color(#a5d6a7, '', group = g1, inline = 's')
ncolS = input.color(#f77c80, '', group = g1, inline = 's')
lcolS = input.color(#faa1a4, '━', group = g1, inline = 's')
pcolD = input.color(#a5d6a7, '', group = g1, inline = 'd')
ncolD = input.color(#f77c80, '', group = g1, inline = 'd')
lcolD = input.color(#90bff9, '━', group = g1, inline = 'd')
pcolR = input.color(#a5d6a7, '', group = g1, inline = 'r')
ncolR = input.color(#f77c80, '', group = g1, inline = 'r')
lcolR = input.color(#f9d690, '━', group = g1, inline = 'r')
// User inputs - Net Positions EMAs
mat = input.string('VWMA', 'Type', options= , group=g2)
emaL = input.bool(false, 'LONGS ', group=g2, inline='emal')
emaS = input.bool(false, 'SHORTS ', group=g2, inline='emas')
emaD = input.bool(false, 'DELTA ',group=g2, inline='emad')
emaR = input.bool(false, 'RATIO ',group=g2, inline='emar')
emaLl = input.int(100, '', group=g2, inline='emal')
emaSl = input.int(100, '', group=g2, inline='emas')
emaDl = input.int(100, '', group=g2, inline='emad')
emaRl = input.int(100, '', group=g2, inline='emar')
emaLc = input.color(color.rgb(165, 214, 167, 60), '', group=g2, inline='emal')
emaSc = input.color(color.rgb(250, 161, 164, 60), '', group=g2, inline='emas')
emaDc = input.color(color.rgb(144, 191, 249, 60), '', group=g2, inline='emad')
emaRc = input.color(color.rgb(249, 214, 144, 60), '', group=g2, inline='emar')
// User inputs - Additional settings
volhm = input.bool(false, 'Volume HM', group=g3, inline='vol')
volc2 = input.color(color.rgb(49, 121, 245),'', group=g3, inline = 'vol')
offs = input.int (10, 'Label Offset', group=g3)
length = input.int (14, 'Position RSI Length', group=g3)
vlbl = input.bool(true, 'Value Labels', group=g3, inline='lv')
nlbl = input.bool(true, 'Data Labels', group=g3, inline='lv')
wick = input.bool(false, 'Show Candle Wicks', group=g3)
// User inputs - Profile settings
prof = input.bool (false, 'Generate a profile', group=g4)
profsrc = input.string('Net Longs', 'Profile Data', options = , group=g4)
vapct = input.float (70, 'Value Area %', minval = 5, maxval = 95, group = g4)
ori = input.string("Left", 'Position', options = , group = g4)
profSize = input.int (2, 'Node Size', minval = 1, group = g4)
rows = input.int (40, 'Rows', minval = 6, maxval = 500, step = 25, group = g4) - 1
vancol = input.color (color.new(color.blue, 75), 'Node Colors ', group = g4, inline = 'nc')
nvancol = input.color (color.new(color.gray, 75), '━', group = g4, inline = 'nc')
poc = input.bool (false, 'POC', group = g4, inline = 'POC'),
poccol = input.color (color.new(color.red, 50), ' ', group = g4, inline = "POC")
val = input.bool (false, 'VA', group = g4, inline = "VA")
vafill = input.color (color.new(color.blue, 95), ' ', group = g4, inline = 'VA')
// User inputs - Statistics
stats = input.bool(false, 'Show Stats', group = g5)
chg_b = input.int(50, 'Bars Back', group = g5)
tablevpos = input.string('Horizontal', 'Orientation', options= , group = g5)
tablepos = input.string('Bottom Center', 'Position', options= , group = g5)
stat_oi = input.bool(true, 'OI ━', group = g5, inline = 'oi')
stat_nl = input.bool(true, 'NL ━', group = g5, inline = 'nl')
stat_ns = input.bool(true, 'NS ━', group = g5, inline = 'ns')
stat_nd = input.bool(true, 'ND ━', group = g5, inline = 'nd')
stat_oi_c = input.bool(true, 'OI Change ━', group = g5, inline = 'oi')
stat_nl_c = input.bool(true, 'NL Change ━', group = g5, inline = 'nl')
stat_ns_c = input.bool(true, 'NS Change ━', group = g5, inline = 'ns')
stat_nd_c = input.bool(true, 'ND Change ━', group = g5, inline = 'nd')
stat_oi_r = input.bool(true, 'OI RSI', group = g5, inline = 'oi')
stat_nl_r = input.bool(true, 'NL RSI', group = g5, inline = 'nl')
stat_ns_r = input.bool(true, 'NS RSI', group = g5, inline = 'ns')
stat_nd_r = input.bool(true, 'ND RSI', group = g5, inline = 'nd')
// User inputs - Divergence Finder
showdiv = input.bool(false, 'Divergence finder', group = g6)
divsrc = input.string('Net Longs', 'Source', options = , group=g6)
pivotDistance = input.int(5, 'Maximum Distance', minval=0, group=g6)
leftPivot = input.int(8, 'Lookback Bars Left', minval=1, group=g6)
rightPivot = input.int(8, 'Lookback Bars Right', minval=1, group=g6)
pHH_npLH = input.bool(true, 'Price HH + Data LH', group = g6, inline='div1')
pLH_npHH = input.bool(true, 'Price LH + Data HH', group = g6, inline='div2')
pLL_npHL = input.bool(true, 'Price LL + Data HL ', group = g6, inline='div3')
pHL_npLL = input.bool(true, 'Price HL + Data LL ', group = g6, inline='div4')
pHH_npLHcol = input.color(color.red, '', group = g6, inline='div1')
pLH_npHHcol = input.color(color.red, '', group = g6, inline='div2')
pLL_npHLcol = input.color(color.green, '', group = g6, inline='div3')
pHL_npLLcol = input.color(color.green, '', group = g6, inline='div4')
// Getting OI data
mex = syminfo.basecurrency=='BTC' ? 'XBT' : string(syminfo.basecurrency)
= request.security('BINANCE' + ":" + string(syminfo.basecurrency) + 'USDT.P_OI', timeframe.period, [close-close , close], ignore_invalid_symbol = true)
= request.security('BINANCE' + ":" + string(syminfo.basecurrency) + 'USD.P_OI', timeframe.period, [close-close , close], ignore_invalid_symbol = true)
= request.security('BINANCE' + ":" + string(syminfo.basecurrency) + 'BUSD.P_OI', timeframe.period, [close-close , close], ignore_invalid_symbol = true)
= request.security('BITMEX' + ":" + mex + 'USD.P_OI', timeframe.period, [close-close , close], ignore_invalid_symbol = true)
= request.security('BITMEX' + ":" + mex + 'USDT.P_OI', timeframe.period, [close-close , close], ignore_invalid_symbol = true)
= request.security('KRAKEN' + ":" + string(syminfo.basecurrency) + 'USD.P_OI', timeframe.period, [close-close , close], ignore_invalid_symbol = true)
deltaOI = (binance ? nz(oid1,0) : 0) + (binance2 ? nz(oid2,0)/close : 0) + (binance3 ? nz(oid3,0) : 0) + (bitmex ? nz(oid4,0)/close : 0) + (bitmex2 ? nz(oid5,0)/close : 0) + (kraken ? nz(oid6,0)/close : 0)
OI = (binance ? nz(oi1,0) : 0) + (binance2 ? nz(oi2,0)/close : 0) + (binance3 ? nz(oi3,0) : 0) + (bitmex ? nz(oi4,0)/close : 0) + (bitmex2 ? nz(oi5,0)/close : 0) + (kraken ? nz(oi6,0)/close : 0)
// Conditions for positions entering and exiting
priceUP = close>open
priceDOWN = close0
oiDOWN = deltaOI<0
newlongs = oiUP and priceUP
rektlongs = oiDOWN and priceDOWN
newshorts = oiUP and priceDOWN
rektshorts = oiDOWN and priceUP
// Visible range
vrc = cumu=='Visible Range' ? time > chart.left_visible_bar_time and time <= chart.right_visible_bar_time : true
// Cumulation of positions entering and exiting
longs_entering = ta.cum(newlongs and vrc ? (denom=='Base Currency' ? deltaOI : deltaOI * close) : 0)
longs_exiting = ta.cum(rektlongs and vrc ? (denom=='Base Currency' ? deltaOI : deltaOI * close) : 0)
shorts_entering = ta.cum(newshorts and vrc ? (denom=='Base Currency' ? deltaOI : deltaOI * close) : 0)
shorts_exiting = ta.cum(rektshorts and vrc ? (denom=='Base Currency' ? deltaOI : deltaOI * close) : 0)
// Output data
net_longs = longs_entering - math.abs(longs_exiting)
net_shorts = shorts_entering - math.abs(shorts_exiting)
net_delta = net_longs - net_shorts
net_ratio = net_longs / net_shorts
// Calculating Relative Strength
longs_strength = ta.rsi(net_longs, length)
shorts_strength = ta.rsi(net_shorts, length)
delta_strength = ta.rsi(net_delta, length)
ratio_strength = ta.rsi(net_ratio, length)
oi_strength = ta.rsi(OI, length)
// Calculating candle OHLC
src = dtype=='Net Positions' ? net_longs : longs_strength
OpenL = wick ? ta.sma(src , 2) : src
HighL = ta.highest(src, 1)
LowL = ta.lowest(src, 1)
CloseL = wick ? ta.sma(src, 2) : src
src2 = dtype=='Net Positions' ? net_shorts : shorts_strength
OpenS = wick ? ta.sma(src2 , 2) : src2
HighS = ta.highest(src2, 1)
LowS = ta.lowest(src2, 1)
CloseS = wick ? ta.sma(src2, 2) : src2
src3 = dtype=='Net Positions' ? net_delta : delta_strength
OpenD = wick ? ta.sma(src3 , 2) : src3
HighD = ta.highest(src3, 1)
LowD = ta.lowest(src3, 1)
CloseD = wick ? ta.sma(src3, 2) : src3
src4 = dtype=='Net Positions' ? net_ratio : ratio_strength
OpenR = wick ? ta.sma(src4 , 2) : src4
HighR = ta.highest(src4, 1)
LowR = ta.lowest(src4, 1)
CloseR = wick ? ta.sma(src4, 2) : src4
// Calculating EMAs
Lema = mat=='EMA' ? ta.ema(src, emaLl) : ta.vwma(src, emaLl)
Sema = mat=='EMA' ? ta.ema(src2, emaSl) : ta.vwma(src2, emaSl)
Dema = mat=='EMA' ? ta.ema(src3, emaDl) : ta.vwma(src3, emaDl)
Rema = mat=='EMA' ? ta.ema(src4, emaRl) : ta.vwma(src4, emaRl)
// Conditions
lcondL = showL and (disp=='Line' or disp=='Columns'), ccondL = showL and disp=='Candles'
lcondS = showS and (disp=='Line' or disp=='Columns'), ccondS = showS and disp=='Candles'
lcondD = showD and (disp=='Line' or disp=='Columns'), ccondD = showD and disp=='Candles'
lcondR = showR and (disp=='Line' or disp=='Columns'), ccondR = showR and disp=='Candles'
// Plotting Lines
plot(lcondL ? src : na, title="Net Longs", color=disp=='Line' ? lcolL : (net_longs >0 ? pcolL : ncolL), linewidth=1, style = disp=='Line' ? plot.style_line : disp=='Columns' ? plot.style_columns : na, editable = false)
plot(lcondS ? src2 : na, title="Net Shorts", color=disp=='Line' ? lcolS : (net_shorts >0 ? pcolS : ncolS), linewidth=1, style = disp=='Line' ? plot.style_line : disp=='Columns' ? plot.style_columns : na, editable = false)
plot(lcondD ? src3 : na, title="Net Shorts", color=disp=='Line' ? lcolD : (net_delta >0 ? pcolD : ncolD), linewidth=1, style = disp=='Line' ? plot.style_line : disp=='Columns' ? plot.style_columns : na, editable = false)
plot(lcondR ? src4 : na, title="Net Ratio", color=disp=='Line' ? lcolR : (net_ratio >0 ? pcolR : ncolR), linewidth=1, style = disp=='Line' ? plot.style_line : disp=='Columns' ? plot.style_columns : na, editable = false)
// Plotting Candles
plotcandle(ccondL ? OpenL : na, ccondL ? HighL : na, ccondL ? LowL : na, ccondL ? CloseL : na, "Longs", CloseL>OpenL ? pcolL : ncolL, CloseL>OpenL ? pcolL : ncolL, false, bordercolor = CloseL>OpenL ? pcolL : ncolL)
plotcandle(ccondS ? OpenS : na, ccondS ? HighS : na, ccondS ? LowS : na, ccondS ? CloseS : na, "Shorts", CloseS>OpenS ? pcolS : ncolS, CloseS>OpenS ? pcolS : ncolS, false, bordercolor = CloseS>OpenS ? pcolS : ncolS)
plotcandle(ccondD ? OpenD : na, ccondD ? HighD : na, ccondD ? LowD : na, ccondD ? CloseD : na, "Delta", CloseD>OpenD ? pcolD : ncolD, CloseD>OpenD ? pcolD : ncolD, false, bordercolor = CloseD>OpenD ? pcolD : ncolD)
plotcandle(ccondR ? OpenR : na, ccondR ? HighR : na, ccondR ? LowR : na, ccondR ? CloseR : na, "Ratio", CloseR>OpenR ? pcolR : ncolR, CloseR>OpenR ? pcolR : ncolR, false, bordercolor = CloseR>OpenR ? pcolR : ncolR)
// Plotting EMAs
plot(emaL ? Lema : na, color=emaLc, editable = false)
plot(emaS ? Sema : na, color=emaSc, editable = false)
plot(emaD ? Dema : na, color=emaDc, editable = false)
plot(emaR ? Rema : na, color=emaRc, editable = false)
// Plotting Relative Strength
plot(dtype=='Position RSI' ? 100 : na, color=color.rgb(120, 123, 134, 90), title = 'RSI 100')
plot(dtype=='Position RSI' ? 70 : na, color=color.rgb(120, 123, 134, 72), title = 'RSI 70')
plot(dtype=='Position RSI' ? 50 : na, color=color.rgb(120, 123, 134, 90), title = 'RSI 50')
plot(dtype=='Position RSI' ? 30 : na, color=color.rgb(120, 123, 134, 72), title = 'RSI 30')
plot(dtype=='Position RSI' ? 0 : na, color=color.rgb(120, 123, 134, 90), title = 'RSI 0')
// Volume Heatmap
vol = volume
volmax = ta.highest(volume, 50)
col = color.from_gradient(volume, 0, volmax, chart.bg_color, volc2)
plotshape(time>chart.left_visible_bar_time and volhm, style=shape.square, size=size.normal,location = location.bottom, color=col, editable = false)
// Labels
if vlbl and disp=='Candles'
vLlabel = showL ? label.new(bar_index, CloseL>OpenL ? HighL : LowL, newlongs or rektlongs ? str.tostring(deltaOI, format.volume) : na, size = size.auto, color=color.rgb(255, 255, 255, 100), textcolor = chart.fg_color, style = CloseL>OpenL ? label.style_label_down : label.style_label_up) : na
vSlabel = showS ? label.new(bar_index, CloseS>OpenS ? HighS : LowS, newshorts or rektshorts ? str.tostring(deltaOI, format.volume) : na, size = size.auto, color=color.rgb(255, 255, 255, 100), textcolor = chart.fg_color, style = CloseS>OpenS ? label.style_label_down : label.style_label_up) : na
vDlabel = showD ? label.new(bar_index, CloseD>OpenD ? HighD : LowD, str.tostring(deltaOI, format.volume), size = size.auto, color=color.rgb(255, 255, 255, 100), textcolor = chart.fg_color, style = CloseD>OpenD ? label.style_label_down : label.style_label_up) : na
vRlabel = showR ? label.new(bar_index, CloseR>OpenR ? HighR : LowR, str.tostring(deltaOI, format.volume), size = size.auto, color=color.rgb(255, 255, 255, 100), textcolor = chart.fg_color, style = CloseR>OpenR ? label.style_label_down : label.style_label_up) : na
if nlbl and disp!='Columns'
Llabel = showL ? label.new(bar_index+offs, src, 'NET LONGS', size = size.tiny, color=lcolL, textcolor = color.black, style = label.style_label_left) : na
Slabel = showS ? label.new(bar_index+offs, src2, 'NET SHORTS', size = size.tiny, color=lcolS, textcolor = color.black, style = label.style_label_left) : na
Dlabel = showD ? label.new(bar_index+offs, src3, 'NET DELTA', size = size.tiny, color=lcolD, textcolor = color.black, style = label.style_label_left) : na
Rlabel = showR ? label.new(bar_index+offs, src4, 'NET RATIO', size = size.tiny, color=lcolR, textcolor = color.black, style = label.style_label_left) : na
label.delete(Llabel )
label.delete(Slabel )
label.delete(Dlabel )
label.delete(Rlabel )
// Generating a profile - Code from @KioseffTrading's "Profile Any Indicator" script (used with their permission)
srcp = profsrc=='Net Longs' ? src : profsrc=='Net Shorts' ? src2 : profsrc=='Net Delta' ? src3 : src4
var int timeArray = array.new_int()
var float dist = array.new_float()
var int x2 = array.new_int(rows + 1, 5)
var vh = matrix.new(1, 1)
array.unshift(timeArray, math.round(time))
if prof and time >= chart.left_visible_bar_time and time <= chart.right_visible_bar_time
matrix.add_col(vh)
matrix.set(vh, 0, matrix.columns(vh) - 1, srcp)
if prof and barstate.islast
= switch ori
"Left" =>
=>
calc = (matrix.max(vh) - matrix.min(vh)) / (rows + 1)
for i = 0 to rows
array.push(dist, matrix.min(vh) + (i * calc))
for i = 1 to matrix.columns(vh) - 1
for x = 0 to array.size(dist) - 1
if matrix.get(vh, 0, i) >= matrix.get(vh, 0, i - 1)
if array.get(dist, x) >= matrix.get(vh, 0, i - 1) and array.get(dist, x) <= matrix.get(vh, 0, i)
array.set(x2, x, array.get(x2, x) + profSize)
else
if array.get(dist, x) >= matrix.get(vh, 0, i) and array.get(dist, x) <= matrix.get(vh, 0, i - 1)
array.set(x2, x, array.get(x2, x) + profSize)
boc = array.new_box()
for i = 1 to rows
right = array.get(timeArray, n + array.get(x2, i))
if ori == "Left"
switch math.sign(n - array.get(x2, i))
-1 => right := chart.right_visible_bar_time
=> right := array.get(timeArray, n - array.get(x2, i))
array.push(boc, box.new(pos, array.get(dist, i - 1),
right, array.get(dist, i), xloc = xloc.bar_time, border_color =
nvancol, bgcolor = nvancol
))
if i == rows
array.push(boc, box.new(pos, array.get(dist, array.size(dist) - 1),
right, array.get(dist, array.size(dist) - 1) + calc, xloc = xloc.bar_time, border_color =
nvancol, bgcolor = nvancol
))
array.shift(x2), nx = array.indexof(x2, array.max(x2))
nz = nx - 1, nz2 = 0, nz3 = 0, nz4 = 0
for i = 0 to array.size(x2) - 1
if nz > -1 and nx <= array.size(x2) - 1
switch array.get(x2, nx) >= array.get(x2, nz)
true => nz2 += array.get(x2, nx), nx += 1
=> nz2 += array.get(x2, nz), nz -= 1
else if nz <= -1
nz2 += array.get(x2, nx), nx += 1
else if nx >= array.size(x2)
nz2 += array.get(x2, nz), nz -= 1
if nz2 >= array.sum(x2) * (vapct / 100)
nz3 := nx <= array.size(x2) - 1 ? nx : array.size(x2) - 1, nz4 := nz <= -1 ? 0 : nz
break
for i = nz3 to nz4
box.set_border_color(array.get(boc, i), vancol)
box.set_bgcolor(array.get(boc, i), vancol)
if poc
var pocL = line(na)
y = math.avg(box.get_top(array.get(boc, array.indexof(x2, array.max(x2)))), box.get_bottom(array.get(boc, array.indexof(x2, array.max(x2)))))
if na(pocL)
pocL := line.new(chart.left_visible_bar_time, y, chart.right_visible_bar_time, y, xloc = xloc.bar_time, color = poccol, width = 1)
else
line.set_xy1(pocL, chart.left_visible_bar_time, y)
line.set_xy2(pocL, chart.right_visible_bar_time, y)
if val
var vaup = line(na), var vadn = line(na)
ydn = box.get_bottom(array.get(boc, nz3)), yup = box.get_top(array.get(boc, nz4))
if na(vaup)
vadn := line.new(chart.left_visible_bar_time, ydn, chart.right_visible_bar_time, ydn, xloc = xloc.bar_time, color = vancol, width = 1)
vaup := line.new(chart.left_visible_bar_time, yup, chart.right_visible_bar_time, yup, xloc = xloc.bar_time, color = vancol, width = 1)
else
line.set_xy1(vadn, chart.left_visible_bar_time, ydn), line.set_xy2(vadn, chart.right_visible_bar_time, ydn)
line.set_xy1(vaup, chart.left_visible_bar_time, yup), line.set_xy2(vaup, chart.right_visible_bar_time, yup)
linefill.new(vadn, vaup, vafill)
//Generating tables for Stats
switchpos(tablepos) =>
switch tablepos
'Top Left' => position.top_left
'Top Center' => position.top_center
'Top Right' => position.top_right
'Bottom Left' => position.bottom_left
'Bottom Center' => position.bottom_center
'Bottom right' => position.bottom_right
dataTable = table.new(switchpos(tablepos), columns=15, rows=15, bgcolor=color.rgb(120, 123, 134, 56))
fill_rows(cond, txt, c, r) =>
if cond
table.cell(table_id=dataTable, column = tablevpos=='Horizontal' ? c : 0, row = tablevpos=='Horizontal' ? 0 : r, text = txt, height=0, text_color=color.white, text_halign=text.align_center, text_valign= text.align_center)
if barstate.islast and stats and dtype!='Position RSI'
txt = ' •𝗢𝗜: ' + (denom=='Quote Currency' ? '$' : '') + str.tostring(denom=='Base Currency' ? OI : OI*close, format = format.volume) + ' ' + (denom=='Base Currency' ? str.tostring(string(syminfo.basecurrency)) : '')
txt2 = ' •𝗡𝗟: ' + (denom=='Quote Currency' ? '$' : '') + str.tostring(net_longs, format = format.volume) + ' ' + (denom=='Base Currency' ? str.tostring(string(syminfo.basecurrency)) : '')
txt3 = ' •𝗡𝗦: ' + (denom=='Quote Currency' ? '$' : '') + str.tostring(net_shorts, format = format.volume) + ' ' + (denom=='Base Currency' ? str.tostring(string(syminfo.basecurrency)) : '')
txt4 = ' •𝗡𝗗: ' + (denom=='Quote Currency' ? '$' : '') + str.tostring(net_delta, format = format.volume) + ' ' + (denom=='Base Currency' ? str.tostring(string(syminfo.basecurrency)) : '')
txt5 = ' •𝗢𝗜𝗖: ' + (denom=='Quote Currency' ? '$' : '') + str.tostring(denom=='Base Currency' ? OI-OI : (OI-OI ) * close, format = format.volume) + ' ' + (denom=='Base Currency' ? str.tostring(string(syminfo.basecurrency)) : '')
txt6 = ' •𝗡𝗟𝗖: ' + (denom=='Quote Currency' ? '$' : '') + str.tostring(net_longs - net_longs , format = format.volume) + ' ' + (denom=='Base Currency' ? str.tostring(string(syminfo.basecurrency)) : '')
txt7 = ' •𝗡𝗦𝗖: ' + (denom=='Quote Currency' ? '$' : '') + str.tostring(net_shorts - net_shorts , format = format.volume) + ' ' + (denom=='Base Currency' ? str.tostring(string(syminfo.basecurrency)) : '')
txt8 = ' •𝗡𝗗𝗖: ' + (denom=='Quote Currency' ? '$' : '') + str.tostring(net_delta - net_delta , format = format.volume) + ' ' + (denom=='Base Currency' ? str.tostring(string(syminfo.basecurrency)) : '')
txt9 = ' •𝗢𝗜 𝗥𝗦𝗜: ' + str.tostring(math.round(oi_strength,1))
txt10 = ' •𝗡𝗟 𝗥𝗦𝗜: ' + str.tostring(math.round(longs_strength,1))
txt11 = ' •𝗡𝗦 𝗥𝗦𝗜: ' + str.tostring(math.round(shorts_strength, 1))
txt12 = ' •𝗡𝗗 𝗥𝗦𝗜: ' + str.tostring(math.round(delta_strength, 1))
fill_rows(stat_oi, txt, 0, 0)
fill_rows(stat_nl, txt2, 1, 1)
fill_rows(stat_ns, txt3, 2, 2)
fill_rows(stat_nd, txt4, 3, 3)
fill_rows(stat_oi_c, txt5, 4, 4)
fill_rows(stat_nl_c, txt6, 5, 5)
fill_rows(stat_ns_c, txt7, 6, 6)
fill_rows(stat_nd_c, txt8, 7, 7)
fill_rows(stat_oi_r, txt9, 8, 8)
fill_rows(stat_nl_r, txt10, 9, 9)
fill_rows(stat_ns_r, txt11, 10, 10)
fill_rows(stat_nd_r, txt12, 11, 11)
// Divergence Finder
switchdivsrc(divsrc) =>
switch divsrc
'Net Longs' => src
'Net Shorts' => src2
'Net Delta' => src3
'Net Ratio' => src4
np = switchdivsrc(divsrc)
var priceHigh = array.new_float(0), var priceLow = array.new_float(0)
var priceHighIndex = array.new_int (0), var priceLowIndex = array.new_int (0)
var npHigh = array.new_float(0), var npLow = array.new_float(0)
var npHighIndex = array.new_int (0), var npLowIndex = array.new_int (0)
var priceHighTrend = 0, var priceLowTrend = 0
var npHighTrend = 0, var npLowTrend = 0
bool closeRecentHighs = false, bool closeOldHighs = false
bool closeHighs = false, bool closeRecentLows = false
bool closeOldLows = false, bool closeLows = false
curPriceHigh = ta.pivothigh(close, leftPivot, rightPivot)
curPriceLow = ta.pivotlow (close, leftPivot, rightPivot)
curnpHigh = ta.pivothigh(np, leftPivot, rightPivot)
curnpLow = ta.pivotlow (np, leftPivot, rightPivot)
if not na(curPriceHigh)
array.push(priceHigh, curPriceHigh)
array.push(priceHighIndex, bar_index-rightPivot)
if not na(curPriceLow)
array.push(priceLow, curPriceLow)
array.push(priceLowIndex, bar_index-rightPivot)
if not na(curnpHigh)
array.push(npHigh, curnpHigh)
array.push(npHighIndex, bar_index-rightPivot)
if not na(curnpLow)
array.push(npLow, curnpLow)
array.push(npLowIndex, bar_index-rightPivot)
if showdiv
if array.size(priceHigh) >= 2 and not na(curPriceHigh)
if array.get(priceHigh, array.size(priceHigh)-1) >= array.get(priceHigh, array.size(priceHigh)-2)
priceHighTrend := 1
else
priceHighTrend := -1
if array.size(priceLow) >= 2 and not na(curPriceLow)
if array.get(priceLow, array.size(priceLow)-1) >= array.get(priceLow, array.size(priceLow)-2)
priceLowTrend := 1
else
priceLowTrend := -1
if array.size(npHigh) >= 2 and not na(curnpHigh)
if array.get(npHigh, array.size(npHigh)-1) >= array.get(npHigh, array.size(npHigh)-2)
npHighTrend := 1
else
npHighTrend := -1
if array.size(npLow) >= 2 and not na(curnpLow)
if array.get(npLow, array.size(npLow)-1) >= array.get(npLow, array.size(npLow)-2)
npLowTrend := 1
else
npLowTrend := -1
if array.size(priceHighIndex) >= 2 and array.size(npHighIndex) >=2
closeRecentHighs := math.abs(array.get(priceHighIndex, array.size(priceHighIndex)-1) - array.get(npHighIndex, array.size(npHighIndex)-1)) <= pivotDistance
closeOldHighs := math.abs(array.get(priceHighIndex, array.size(priceHighIndex)-2) - array.get(npHighIndex, array.size(npHighIndex)-2)) <= pivotDistance
closeHighs := closeRecentHighs and closeOldHighs
if array.size(priceLowIndex) >= 2 and array.size(npLowIndex) >=2
closeRecentLows := math.abs(array.get(priceLowIndex, array.size(priceLowIndex)-1) - array.get(npLowIndex, array.size(npLowIndex)-1)) <= pivotDistance
closeOldLows := math.abs(array.get(priceLowIndex, array.size(priceLowIndex)-2) - array.get(npLowIndex, array.size(npLowIndex)-2)) <= pivotDistance
closeLows := closeRecentLows and closeOldLows
bool uptrendExhuastion = closeHighs and priceHighTrend > 0 and npHighTrend < 0 and (not na(curnpHigh) or not na(curPriceHigh))
bool uptrendAbsorption = closeHighs and priceHighTrend < 0 and npHighTrend > 0 and (not na(curnpHigh) or not na(curPriceHigh))
bool downtrendExhuastion = closeLows and priceLowTrend < 0 and npLowTrend > 0 and (not na(curnpLow) or not na(curPriceLow))
bool downtrendAbsorption = closeLows and priceLowTrend > 0 and npLowTrend < 0 and (not na(curnpLow) or not na(curPriceLow))
drawDiv(time1, price1, time2, price2, type) =>
dcol = type == 'Uptrend Exhuastion' ? pHH_npLHcol : type == 'Uptrend Absorption' ? pLH_npHHcol : type == 'Downtrend Exhaustion' ? pLL_npHLcol : type == 'Downtrend Absorption' ? pHL_npLLcol : na
line.new(x1=time1, y1=price1, x2=time2, y2=price2, color=dcol, width=1)
if uptrendAbsorption or uptrendExhuastion and showdiv
highTime1 = array.get(npHighIndex, array.size(npHighIndex)-1)
highPrice1 = array.get(npHigh, array.size(npHigh)-1)
highTime2 = array.get(npHighIndex, array.size(npHighIndex)-2)
highPrice2 = array.get(npHigh, array.size(npHigh)-2)
if uptrendExhuastion and pHH_npLH
drawDiv(highTime1, highPrice1, highTime2, highPrice2, 'Uptrend Exhuastion')
if uptrendAbsorption and pLH_npHH
drawDiv(highTime1, highPrice1, highTime2, highPrice2, 'Uptrend Absorption')
if downtrendAbsorption or downtrendExhuastion and showdiv
lowTime1 = array.get(npLowIndex, array.size(npLowIndex)-1)
lowPrice1 = array.get(npLow, array.size(npLow)-1)
lowTime2 = array.get(npLowIndex, array.size(npLowIndex)-2)
lowPrice2 = array.get(npLow, array.size(npLow)-2)
if downtrendExhuastion and pLL_npHL
drawDiv(lowTime1, lowPrice1, lowTime2, lowPrice2, 'Downtrend Exhuastion')
if downtrendAbsorption and pHL_npLL
drawDiv(lowTime1, lowPrice1, lowTime2, lowPrice2, 'Downtrend Absorption')
Adaptive Log Trend Zones + Retest SignalsAdaptive Log Trend Zones + Retest Signals
Adaptive Log Trend Zones is a trend-following overlay built to identify high-probability breakout retests in strong market conditions. It combines logarithmic regression , volatility-adaptive behavior , and ATR-based trend zones to help traders stay aligned with dominant momentum while avoiding chop.
🔹 Core Features
Logarithmic Regression Midline
Uses linear regression on log price to better handle exponential market moves
Produces smoother, more realistic trend structure on higher timeframes
Volatility-Adaptive Lookback
Automatically expands or contracts the regression length based on ATR volatility
Reacts faster in high volatility, smoother in consolidation
Dynamic Trend Zones
Upper and lower bands are ATR-adjusted and trend-colored
Optional future projection for visual trend guidance
Breakout → Retest Signal Logic
Detects clean breakouts beyond the trend zone
Waits for a controlled pullback (retest) before signaling
Signals only trigger when trend strength is confirmed
Trend Quality Filter
Internal regime detection filters out low-quality, sideways conditions
Uses slope strength and volatility compression to validate entries
🔹 Signals
BUY : Bullish breakout followed by a valid retest in a trending regime
SELL : Bearish breakout followed by a valid retest in a trending regime
Signals are designed for trend continuation , not mean reversion.
🔹 Best Use Cases
Crypto, Forex, and Index markets
Higher timeframes (15m+ recommended)
Trend continuation and pullback strategies
⚠️ Notes
This indicator is not a standalone trading system . Always use proper risk management and confirm signals with structure, volume, or higher-timeframe context.
Designed for traders who prefer structure, patience, and momentum alignment.
TDPOWERSYS vs Market-Cap Weighted Peersfor QIC - UnCut Diamonds team..
to compare one company vs its peers bundled as basket.
editable..
Live Candle Range Position SizerThis script displays a fixed execution HUD on the chart that continuously measures the current candle range (high–low) and automatically calculates position size based on a fixed Risk Unit (RU).
Cloud Gold TrendTrend Filter (Ichimoku): If the price is above the cloud (Kumo), look only for "Long" signals. If it is below, look only for "Short" signals.
Entry Signal (Bollinger): When the price touches the Lower Band while you are above the Cloud, it could be a great buying point in an uptrend.
Volatility Confirmation: If the Bollinger Bands squeeze within the cloud, get ready for a strong directional move as soon as the price breaks one of the two levels.
Triple EMA + Stochastic/ADX# Triple EMA + Stochastic/ADX Breakout Indicator
A professional TradingView indicator designed for trend-following and momentum breakout trading. This system uses a hierarchical confirmation process to ensure high-probability entries and robust trend maintenance.
## 🚀 Core Trading Logic: "The Setup Cycle"
This indicator operates on a **Cycle-Based Logic** rather than simple crossovers. A trade cycle is defined as:
1. **The Setup (Priming)**: A Stochastic crossover (K > D for Long, D > K for Short) initiates a "Setup Mode." This is marked by a small dot (Blue for Long, Orange for Short).
2. **The Confirmation (Trend)**: The systems checks for hierarchical EMA alignment (Fast > Medium > Slow for Longs).
3. **The Trigger (Breakout)**: Once the Setup is active and EMAs are aligned, every **Price Breakout** above the previous high (X-period) triggers a continuous **BUY/SELL mark**.
4. **The Exit (Take Profit/Stop)**: The cycle and trade only end when the Fast EMA crosses back over the Medium EMA (EMA 9/21 crossover).
---
## 🛠 Features
### 1. Triple EMA System
* **Hierarchical Alignment**: Requires Fast > Medium > Slow (9, 21, 50 by default) for a confirmed trend direction.
* **Dynamic Trend Background**: Chart background changes color when a full EMA trend is established.
### 2. Dual Filter System (Stochastic & ADX)
* **Stochastic Setup**: Uses smoothed %K and %D to identify the start of momentum cycles.
* **ADX Filter**: Provides a trend-strength baseline. Default threshold is set to 20 to filter out choppy markets.
### 3. Price Breakout Confirmation
* Requires price to break above/below the previous High/Low of the last X bars (default 10).
* Allows for **continuous entries** within a single trend cycle.
### 4. Robust Exit Strategy
* **EMA Crossover Exit**: The primary exit method. Triggers an "EXIT" flag when the trend momentum shifts.
* **ATR Trailing Stop**: A secondary volatility-based stop that moves with the price. Can be set as the absolute exit or used for visual reference.
### 5. Mean Reversion Mode (Optional)
* Identifies overextended price action (percent deviation from EMA2).
* Signals potential "bounce" or "rejection" trades against the trend.
---
## 📊 Dashboard & Visuals
* **🟢 BUY / 🔴 SELL**: Trend continuation breakout signals.
* **🟠 EXIT / 🟣 EXIT**: Trend reversal/exit signals.
* **🔵/🟠 Small Dots**: Setup priming moments.
* **Real-time Dashboard**: Displays current Setup Status, EMA Alignment, Breakout status, ADX strength, and calculated Stop levels.
---
## ⚙️ How to Customize
| Parameter | Recommended Use |
| :--- | :--- |
| **Breakout Lookback** | Lower (3-5) for aggressive scalping, Higher (10-20) for conservative trends. |
| **Filter Mode** | Choose "Stochastic" for momentum or "ADX" for trend strength preference. |
| **ATR Multiplier** | Reduce (1.5) for tighter stops, Increase (3.0) for wider trend following. |
| **Exit ONLY on EMA** | Enable to stay in trades longer; Disable to exit immediately on ATR stop hits. |
---
## 📥 Installation
1. Open your **Pine Editor** in TradingView.
2. Create a new "Indicator."
3. Copy the code from `Triple_EMA_Stochastic_ADX.pine`.
4. Click **Save** and **Add to Chart**.
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*Developed for Dhan/MCX/Futures and general Asset Trading.*
GOLD TERTIUM MGC 1mThis indicator is a visual tool for TradingView designed to help you read trend structure using EMAs and highlight potential long and short entries on the MGC 1‑minute chart, while filtering pullbacks and avoiding trades when the 200 EMA is flat.
It calculates five EMAs (32, 50, 110, 200, 250) and plots them in different colors so you can clearly see the moving‑average stack and overall direction. The main trend is defined by the 200 EMA: bullish when price and the fast EMAs (32 and 50) are above it with a positive slope, and bearish when they are below it with a negative slope; if the 200 EMA is almost flat, signals are blocked to reduce trading in choppy markets.
Entry logic looks for a pullback into the 32–50 EMA zone on the previous candle, then requires a trend‑aligned candle to trigger a signal: long when the trend is up, the previous bar retested the EMA zone, and the current bar closes above EMA 32 with a bullish body; short when the trend is down, there was a valid retest, the current bar closes below EMA 32 with a bearish body and EMA 32 is below EMA 50. On the chart, you will see colored EMAs plus green “L” triangles under bars for potential long entries and red “S” triangles above bars for potential short entries, which are meant as visual cues rather than automatic trade instructions
