Godmode 4.0.0 [Oscillator]First off, a huge thank you to the following people:
LEGION:
LazyBear: www.tradingview.com
xSilas: www.tradingview.com
Ni6HTH4awK: www.tradingview.com
sco77m4r7and:
SNOW_CITY: www.tradingview.com
oh92: www.tradingview.com
alexgrover: www.tradingview.com
cI8DH: www.tradingview.com
DonovanWall: www.tradingview.com
Since I've been on TradingView I've become somewhat enthralled by Godmode and the collective work that goes in to it, so I decided to publish my own iteration, building off the ideas already present. (This is a great way to get familiar with Pine by the way, just in case there are any beginners reading this)
Changes
The first change I made was to allow the user to select whatever tickerid they wanted as a benchmark. If trading XBTUSD on BitMEX for example, the indicator will react to exchange-specific activity, which means it will respond to all the little whipsaws, whipsaws that can be especially present on a futures exchange. By typing CRYPTOCAP:BTC or CRYPTOCAP:TOTAL we endeavor to remove noise. It can also signal earlier. Less noise and less lag. Another idea would be to choose a benchmark that has a strong inverse relationship with the asset you're trading: try CRYPTOCAP:USDT as the benchmark against BTC to see what I mean.
I also added the ability to smooth the plot, yet again removing noise but adding considerable lag.
The linear regression of the wave-trend is calculated in place of the EMA. This is plotted as columns with the midline (50) as the base. This is just calculating the slope of the wave-trend and can signal a weakening trend before a reversal takes place.
Using cI8DH's True RSI script () as inspiration, I added a function for calculating the True TSI in an attempt to remove any bullish bias. Funnily enough, when I tried to do the same with the RSI I had some problems. I'll try to resolve this in the coming weeks.
Made slight changes to the aesthetics. Tried to bring the two main plots alive by making their bold, opaque colors stand off the subtle tones in the background.
To Do List
1. I would like to sort out the issue with the True RSI.
2. When the plots are smoothed, there's an issue with the green 'Caution!' dots appearing in the lower half of the indicator.
3. I'd like to adjust the code so that if the 'Benchmark' box is empty, that it will automatically register the current tickerid as the 'Benchmark'.
If anyone has any suggestions on other fixes or how to apply the fixes mentioned by me, please don't hesitate to reach out to me here or through other media platforms.
Want to Learn?
If you'd like the opportunity to learn Pine but you have difficulty finding resources to guide you, take a look at this rudimentary list: docs.google.com
The list will be updated in the future as more people share the resources that have helped, or continue to help, them. Follow me on Twitter to keep up-to-date with the growing list of resources.
Suggestions or Questions?
Don't even kinda hesitate to forward them to me. My (metaphorical) door is always open.
BITMEX:XBTUSD
CRYPTOCAP:BTC
CRYPTOCAP:TOTAL
CRYPTOCAP:USDT.D
Pesquisar nos scripts por "文华财经tick价格"
Simple Spread Simple spread between two tickers. Click format to set inputs for tickers. ex: "COINBASE:BTC:USD"
OHLC Volatility Estimators by @Xel_arjonaDISCLAIMER:
The Following indicator/code IS NOT intended to be a formal investment advice or recommendation by the author, nor should be construed as such. Users will be fully responsible by their use regarding their own trading vehicles/assets.
The embedded code and ideas within this work are FREELY AND PUBLICLY available on the Web for NON LUCRATIVE ACTIVITIES and must remain as is by Creative-Commons as TradingView's regulations. Any use, copy or re-use of this code should mention it's origin as it's authorship.
WARNING NOTICE!
THE INCLUDED FUNCTION MUST BE CONSIDERED AS DEBUGING CODE The models included in the function have been taken from openly sources on the web so they could have some errors as in the calculation scheme and/or in it's programatic scheme. Debugging are welcome.
WHAT'S THIS?
Here's a full collection of candle based (compressed tick) Volatility Estimators given as a function, openly available for free, it can print IMPLIED VOLATILITY by an external symbol ticker like INDEX:VIX.
Models included in the volatility calculation function:
CLOSE TO CLOSE: This is the classic estimator by rule, sometimes referred as HISTORICAL VOLATILITY and is the must common, accepted and widely used out there. Is based on traditional Standard Deviation method derived from the logarithm return of current close from yesterday's.
ELASTIC WEIGHTED MOVING AVERAGE: This estimator has been used by RiskMetriks®. It's calculation is based on an ElasticWeightedMovingAverage Standard Deviation method derived from the logarithm return of current close from yesterday's. It can be viewed or named as an EXPONENTIAL HISTORICAL VOLATILITY model.
PARKINSON'S: The Parkinson number, or High Low Range Volatility, developed by the physicist, Michael Parkinson, in 1980 aims to estimate the Volatility of returns for a random walk using the high and low in any particular period. IVolatility.com calculates daily Parkinson values. Prices are observed on a fixed time interval. n=10, 20, 30, 60, 90, 120, 150, 180 days.
ROGERS-SATCHELL: The Rogers-Satchell function is a volatility estimator that outperforms other estimators when the underlying follows a Geometric Brownian Motion (GBM) with a drift (historical data mean returns different from zero). As a result, it provides a better volatility estimation when the underlying is trending. However, this Rogers-Satchell estimator does not account for jumps in price (Gaps). It assumes no opening jump. The function uses the open, close, high, and low price series in its calculation and it has only one parameter, which is the period to use to estimate the volatility.
YANG-ZHANG: Yang and Zhang were the first to derive an historical volatility estimator that has a minimum estimation error, is independent of the drift, and independent of opening gaps. This estimator is maximally 14 times more efficient than the close-to-close estimator.
LOGARITHMIC GARMAN-KLASS: The former is a pinescript transcript of the model defined as in iVolatility . The metric used is a combination of the overnight, high/low and open/close range. Such a volatility metric is a more efficient measure of the degree of volatility during a given day. This metric is always positive.
920 Order Flow SATY ATR//@version=6
indicator("Order-Flow / Volume Signals (No L2)", overlay=true)
//======================
// Inputs
//======================
rvolLen = input.int(20, "Relative Volume Lookback", minval=5)
rvolMin = input.float(1.1, "Min Relative Volume (× avg)", step=0.1)
wrbLen = input.int(20, "Wide-Range Lookback", minval=5)
wrbMult = input.float(1, "Wide-Range Multiplier", step=0.1)
upperCloseQ = input.float(0.60, "Close near High (0-1)", minval=0.0, maxval=1.0)
lowerCloseQ = input.float(0.40, "Close near Low (0-1)", minval=0.0, maxval=1.0)
cdLen = input.int(25, "Rolling CumDelta Window", minval=5)
useVWAP = input.bool(true, "Use VWAP Bias Filter")
showSignals = input.bool(true, "Show Long/Short OF Triangles")
//======================
// Core helpers
//======================
rng = high - low
tr = ta.tr(true)
avgTR = ta.sma(tr, wrbLen)
wrb = rng > wrbMult * avgTR
// Relative Volume
volAvg = ta.sma(volume, rvolLen)
rvol = volAvg > 0 ? volume / volAvg : 0.0
// Close location in bar (0..1)
clo = rng > 0 ? (close - low) / rng : 0.5
// VWAP (session) + SMAs
vwap = ta.vwap(close)
sma9 = ta.sma(close, 9)
sma20 = ta.sma(close, 20)
sma200= ta.sma(close, 200)
// CumDelta proxy (uptick/downtick signed volume)
tickSign = close > close ? 1.0 : close < close ? -1.0 : 0.0
delta = volume * tickSign
cumDelta = ta.cum(delta)
rollCD = cumDelta - cumDelta
//======================
// Signal conditions
//======================
volActive = rvol >= rvolMin
effortBuy = wrb and clo >= upperCloseQ
effortSell = wrb and clo <= lowerCloseQ
cdUp = ta.crossover(rollCD, 0)
cdDown = ta.crossunder(rollCD, 0)
biasBuy = not useVWAP or close > vwap
biasSell = not useVWAP or close < vwap
longOF = barstate.isconfirmed and volActive and effortBuy and cdUp and biasBuy
shortOF = barstate.isconfirmed and volActive and effortSell and cdDown and biasSell
//======================
// Plot ONLY on price chart
//======================
// SMAs & VWAP
plot(sma9, title="9 SMA", color=color.orange, linewidth=3)
plot(sma20, title="20 SMA", color=color.white, linewidth=3)
plot(sma200, title="200 SMA", color=color.black, linewidth=3)
plot(vwap, title="VWAP", color=color.new(color.aqua, 0), linewidth=3)
// Triangles with const text (no extra pane)
plotshape(showSignals and longOF, title="LONG OF",
style=shape.triangleup, location=location.belowbar, size=size.tiny,
color=color.new(color.green, 0), text="LONG OF")
plotshape(showSignals and shortOF, title="SHORT OF",
style=shape.triangledown, location=location.abovebar, size=size.tiny,
color=color.new(color.red, 0), text="SHORT OF")
// Alerts
alertcondition(longOF, title="LONG OF confirmed", message="LONG OF confirmed")
alertcondition(shortOF, title="SHORT OF confirmed", message="SHORT OF confirmed")
//────────────────────────────
// End-of-line labels (offset to the right)
//────────────────────────────
var label label9 = na
var label label20 = na
var label label200 = na
var label labelVW = na
if barstate.islast
// delete old labels before drawing new ones
label.delete(label9)
label.delete(label20)
label.delete(label200)
label.delete(labelVW)
// how far to move the labels rightward (increase if needed)
offsetBars = input.int(3)
label9 := label.new(bar_index + offsetBars, sma9, "9 SMA", style=label.style_label_left, textcolor=color.white, color=color.new(color.orange, 0))
label20 := label.new(bar_index + offsetBars, sma20, "20 SMA", style=label.style_label_left, textcolor=color.black, color=color.new(color.white, 0))
label200 := label.new(bar_index + offsetBars, sma200, "200 SMA", style=label.style_label_left, textcolor=color.white, color=color.new(color.black, 0))
labelVW := label.new(bar_index + offsetBars, vwap, "VWAP", style=label.style_label_left, textcolor=color.black, color=color.new(color.aqua, 0))
//────────────────────────────────────────────────────────────────────
//────────────────────────────────────────────
// Overnight High/Low + HOD/LOD (no POC)
//────────────────────────────────────────────
sessionRTH = input.session("0930-1600", "RTH Session (exchange tz)")
levelWidth = input.int(2, "HL line width", minval=1, maxval=5)
labelOffsetH = input.int(10, "HL label offset (bars to right)", minval=0)
isRTH = not na(time(timeframe.period, sessionRTH))
rthOpen = isRTH and not isRTH
// --- Track Overnight High/Low during NON-RTH; freeze at RTH open
// --- Track Overnight High/Low during NON-RTH; freeze at RTH open
var float onHigh = na
var float onLow = na
var int onHighBar = na
var int onLowBar = na
var float onHighFix = na
var float onLowFix = na
var int onHighFixBar = na
var int onLowFixBar = na
if not isRTH
if na(onHigh) or high > onHigh
onHigh := high
onHighBar := bar_index
if na(onLow) or low < onLow
onLow := low
onLowBar := bar_index
if rthOpen
onHighFix := onHigh
onLowFix := onLow
onHighFixBar := onHighBar
onLowFixBar := onLowBar
onHigh := na, onLow := na
onHighBar := na, onLowBar := na
// ──────────────────────────────────────────
// Candle coloring + labels for 9/20/VWAP crosses
// ──────────────────────────────────────────
showCrossLabels = input.bool(true, "Show cross labels")
// Helpers
minAll = math.min(math.min(sma9, sma20), vwap)
maxAll = math.max(math.max(sma9, sma20), vwap)
// All three lines
goldenAll = open <= minAll and close >= maxAll
deathAll = open >= maxAll and close <= minAll
// 9/20 only (exclude cases that also crossed VWAP)
dcUpOnly = open <= math.min(sma9, sma20) and close >= math.max(sma9, sma20) and not goldenAll
dcDownOnly = open >= math.max(sma9, sma20) and close <= math.min(sma9, sma20) and not deathAll
// Candle colors (priority: all three > 9/20 only)
var color cCol = na
cCol := goldenAll ? color.yellow : deathAll ? color.black :dcUpOnly ? color.lime :dcDownOnly ? color.red : na
barcolor(cCol)
// Labels
plotshape(showCrossLabels and barstate.isconfirmed and goldenAll, title="GOLDEN CROSS",
style=shape.labelup, location=location.belowbar, text="GOLDEN CROSS",
color=color.new(color.yellow, 0), textcolor=color.black, size=size.tiny)
plotshape(showCrossLabels and barstate.isconfirmed and deathAll, title="DEATH CROSS",
style=shape.labeldown, location=location.abovebar, text="DEATH CROSS",
color=color.new(color.black, 0), textcolor=color.white, size=size.tiny)
plotshape(showCrossLabels and barstate.isconfirmed and dcUpOnly, title="DC UP",
style=shape.labelup, location=location.belowbar, text="DC UP",
color=color.new(color.lime, 0), textcolor=color.black, size=size.tiny)
plotshape(showCrossLabels and barstate.isconfirmed and dcDownOnly, title="DC DOWN",
style=shape.labeldown, location=location.abovebar, text="DC DOWN",
color=color.new(color.red, 0), textcolor=color.white, size=size.tiny)
// ──────────────────────────────────────────
// Audible + alert conditions
// ──────────────────────────────────────────
alertcondition(goldenAll, title="GOLDEN CROSS", message="GOLDEN CROSS detected")
alertcondition(deathAll, title="DEATH CROSS", message="DEATH CROSS detected")
alertcondition(dcUpOnly, title="DC UP", message="Dual Cross UP detected")
alertcondition(dcDownOnly,title="DC DOWN", message="Dual Cross DOWN detected")
Smart Margin Zone
SMART MARGIN ZONE - CME-BASED SUPPORT & RESISTANCE INDICATOR
TITLE FOR PUBLICATION:
Smart Margin Zone - CME Margin-Based Support and Resistance
CATEGORY:
Support and Resistance
SHORT DESCRIPTION (for preview):
Automatically plots margin zones based on CME Group requirements. These zones represent critical price levels where leveraged traders face margin calls, creating natural support and resistance through forced liquidations.
═══════════════════════════════════════════════════════════════
FULL DESCRIPTION FOR TRADINGVIEW:
═══════════════════════════════════════════════════════════════
📊 Smart Margin Zone - Professional Trading Zones Based on CME Data
This indicator automatically calculates and displays margin zones derived from official CME Group margin requirements. These zones represent critical price levels where traders using leverage receive margin calls, triggering forced position closures that create natural support and resistance levels.
═══════════════════════════════════════════════════════════════
🎯 CORE CONCEPT
═══════════════════════════════════════════════════════════════
When price reaches calculated margin zones, traders using 2:1 or 4:1 leverage on CME futures receive margin calls. Brokers automatically liquidate these positions, creating waves of buying or selling pressure that form strong support and resistance levels.
This is not theoretical - it's based on actual margin requirements from CME Group, the world's largest derivatives marketplace.
═══════════════════════════════════════════════════════════════
📐 CALCULATION METHODOLOGY
═══════════════════════════════════════════════════════════════
The indicator uses the following formula to calculate zone sizes:
Zone Size = (Margin Requirement / Tick Value) × Tick Size × 1.10
Where:
• Margin Requirement = Official CME initial margin (updated November 2024)
• Tick Value = Dollar value of minimum price movement
• Tick Size = Minimum price increment
• 1.10 = 10% buffer for realistic zone width
SUPPORTED INSTRUMENTS WITH CME DATA:
Currency Pairs:
• EURUSD: $2,100 margin → 0.0168 zone size
• GBPUSD: $1,800 margin → 0.0144 zone size
• AUDUSD: $1,300 margin → 0.0065 zone size
• NZDUSD: $1,100 margin → 0.0055 zone size
• USDJPY: $3,200 margin → custom calculation
• USDCAD: $950 margin → calculated
• USDCHF: $1,650 margin → calculated
Commodities:
• Gold (XAUUSD): $8,000 margin → 80 points zone size
• Silver (XAGUSD): $6,500 margin → calculated
• WTI Crude Oil: $4,500 margin → calculated
═══════════════════════════════════════════════════════════════
🔍 HOW IT WORKS
═══════════════════════════════════════════════════════════════
1. SWING POINT DETECTION
The indicator automatically identifies swing highs and swing lows using a configurable lookback period (default 10 bars). These become anchor points for zone calculations.
2. FIVE ZONE LEVELS
From each swing point, five zone levels are calculated:
• Zone 1/4 (25%) - First correction level
• Zone 1/2 (50%) - KEY ZONE for trend determination
• Zone 3/4 (75%) - Intermediate level
• Zone 1/1 (100%) - Full margin zone (strongest level)
• Zone 5/4 (125%) - Extended zone
3. TREND IDENTIFICATION
• Close above Zone 1/2 resistance = Bullish trend
• Close below Zone 1/2 support = Bearish trend
• Between zones = Range/consolidation
4. HISTORICAL CONTEXT
Current zones are displayed prominently with fills and labels. Historical zones appear as thin, semi-transparent lines for context without cluttering the chart.
═══════════════════════════════════════════════════════════════
⚙️ FEATURES
═══════════════════════════════════════════════════════════════
AUTOMATED CALCULATION:
✅ Auto-detection of swing highs and lows
✅ Real-time zone updates as new swings form
✅ CME margin data built-in for major instruments
✅ Manual override option for custom calculations
VISUAL CLARITY:
✅ Color-coded zones (red=resistance, green=support)
✅ Adjustable transparency for fills and lines
✅ Current zones bold with fills and price labels
✅ Historical zones thin and transparent
✅ Swing point markers show calculation origins
CUSTOMIZATION:
✅ Show/hide individual zone levels (1/4, 1/2, 3/4, 1/1, 5/4)
✅ Toggle historical zones on/off
✅ Adjustable lookback period (5-50 bars)
✅ Customizable colors for all elements
✅ Line width and transparency controls
✅ Zone extension options (none/right/both)
TREND ANALYSIS:
✅ Optional trend background coloring
✅ Customizable trend colors and transparency
✅ Real-time trend identification display
STATISTICS:
✅ Live statistics table showing:
- Current instrument
- Active zone size
- Calculation mode
- Current trend direction
- Number of zones displayed
ALERTS:
✅ Zone 1/2 breakout (up/down)
✅ Full margin zone 1/1 reached
✅ Customizable alert messages
═══════════════════════════════════════════════════════════════
📈 TRADING APPLICATIONS
═══════════════════════════════════════════════════════════════
ENTRY SIGNALS:
• Bounces from zone levels = potential entry points
• Zone 1/2 breakouts = trend continuation entries
• Zone rejections = reversal opportunities
RISK MANAGEMENT:
• Zone levels = logical stop-loss placement
• Zone 1/1 = maximum risk level
• Zone spacing = position sizing guide
PROFIT TARGETS:
• Next zone level = first target
• Zone 1/1 = full profit target
• Zone breakouts = extended targets
TREND CONFIRMATION:
• Price above Zone 1/2 resistance = confirmed uptrend
• Price below Zone 1/2 support = confirmed downtrend
• Consolidation between zones = wait for breakout
═══════════════════════════════════════════════════════════════
📚 USAGE INSTRUCTIONS
═══════════════════════════════════════════════════════════════
GETTING STARTED:
1. Add indicator to chart of any supported instrument
2. Zones automatically calculate and display
3. Adjust swing detection period if needed (default 10 works well)
4. Customize colors and visibility to your preference
OPTIMAL SETTINGS:
• Best timeframes: H1, H4, Daily, Weekly
• Default swing length (10) suitable for most markets
• Show 2-3 historical zones for context
• Enable swing point markers to see calculation origins
INTERPRETATION:
• Watch for price reactions at zone boundaries
• Strong bounces = respect for margin level
• Clean breaks = momentum continuation
• Multiple touches = zone strength confirmation
SET ALERTS:
• Zone 1/2 breakouts for trend entries
• Zone 1/1 reaches for profit-taking
• Custom alerts for your specific strategy
═══════════════════════════════════════════════════════════════
⚠️ IMPORTANT NOTES
═══════════════════════════════════════════════════════════════
DATA ACCURACY:
• CME margin requirements updated November 2024
• Margins change periodically - check CME Group website
• Manual mode available for latest margin data
• Indicator provides analysis tool, not financial advice
STATISTICAL PERFORMANCE:
• Historical data shows >60% probability of continued movement after Zone 1/2 breakout
• Zone effectiveness varies by market conditions
• Best results in trending markets with clear swings
LIMITATIONS:
• Margin requirements change - monitor CME updates
• Works best on liquid instruments with clear swings
• Not a standalone trading system
• Should be combined with additional analysis
═══════════════════════════════════════════════════════════════
🔧 METHODOLOGY CREDIT
═══════════════════════════════════════════════════════════════
This indicator is based on the margin zones concept developed by Alexander Bazylev (BTrade indicator for MetaTrader platforms).
The TradingView implementation has been completely rewritten with original enhancements:
• Multiple zone levels instead of single level
• Automatic swing point detection algorithm
• Direct CME data integration
• Historical zone visualization
• Advanced customization options
• Comprehensive statistics and alerts
All code is original and specifically designed for TradingView's Pine Script v5 environment.
═══════════════════════════════════════════════════════════════
💡 BEST PRACTICES
═══════════════════════════════════════════════════════════════
COMBINE WITH:
• Volume analysis for confirmation
• Trend indicators for direction bias
• Price action patterns at zones
• Higher timeframe analysis
AVOID:
• Trading against strong trends at minor zones
• Over-leveraging based solely on zone placement
• Ignoring broader market context
• Expecting perfect bounces every time
OPTIMIZE:
• Adjust swing length for different timeframes
• Shorter period (5-7) for intraday trading
• Longer period (15-20) for swing trading
• Test historical effectiveness on your instruments
═══════════════════════════════════════════════════════════════
📖 EDUCATIONAL VALUE
═══════════════════════════════════════════════════════════════
This indicator helps traders understand:
• How institutional margin requirements affect price
• Where forced liquidations create pressure
• Natural support and resistance formation
• Relationship between leverage and price levels
• Market structure and key technical levels
═══════════════════════════════════════════════════════════════
🔄 VERSION HISTORY
═══════════════════════════════════════════════════════════════
Version 1.0 (Initial Release):
• CME-based zone calculation for 10 instruments
• Automatic swing high/low detection
• 5 zone levels with customizable display
• Historical zones with transparency control
• Swing point markers
• Trend background indicator
• Live statistics table
• Multiple alert conditions
• Fully customizable colors and styles
• English language interface
═══════════════════════════════════════════════════════════════
📞 SUPPORT & FEEDBACK
═══════════════════════════════════════════════════════════════
Questions or suggestions? Leave a comment below!
If you find this indicator useful:
⭐ Please leave a like
💬 Share your experience in comments
🔔 Follow for updates and new indicators
═══════════════════════════════════════════════════════════════
⚖️ DISCLAIMER
═══════════════════════════════════════════════════════════════
This indicator is provided for educational and analytical purposes only. It is not financial advice and should not be the sole basis for trading decisions.
• Past performance does not guarantee future results
• Trading involves substantial risk of loss
• CME margin requirements subject to change
• Always do your own research and risk management
• Consult a financial advisor for investment advice
The creator is not responsible for any trading losses incurred through use of this indicator.
Market Breadth Decision HelperMarket Breadth Decision Helper (NYSE/NASDAQ VOLD, ADD, TICK)
Combines NYSE VOLD, NASDAQ VOLD (VOLDQ), NYSE/NASDAQ ADD, and TICK into a single intraday dashboard for tactical bias and risk management.
Tiered pressure scale (sign shows direction, abs(tier) shows intensity): 0 = Neutral, 1 = Mild, 2 = Strong, 3 = Severe, 4 = Panic. On-chart legend makes this explicit.
Table view highlights value, tier, bull/bear point contributions, and notes (PANIC, OVERRIDE, DIVERGENCE). VOLD and ADD panic trigger “stand down”; VOLD ±2 triggers bull/bear overrides; NYSE vs NASDAQ ADD divergence triggers “scalp only.”
Bull/bear points: VOLD 2 pts, ADD NYSE 2 pts, ADD NASDAQ 1 pt, TICK 1 pt. ≥3 pts on a side lifts that side’s multiplier to 1.5. Bias flips Bullish/Bearish only if a side leads and has ≥2 pts; otherwise Neutral.
Breadth modes: PANIC_NO_TRADE → DIVERGENCE_SCALP_ONLY → VOLD_OVERRIDE_BULL/BEAR → NORMAL/NO_EDGE.
Intraday context: tracks current session day_high / day_low for the chart symbol.
JSON/Alert export (optional) sends raw values plus *_tier and *_tier_desc labels (NEUTRAL/MILD/STRONG/SEVERE/PANIC) with sign/magnitude hints, so agents/bots never have to guess what “1 vs 2 vs 3 vs 4” mean.
Customizable bands for VOLD/ADD/TICK, table styling, label placement, and dashboard bias input to align with higher-timeframe context.
Best use
Quick read on internal participation and pressure magnitude.
Guardrails: respect PANIC and overrides; treat divergence as “scalp only.”
Pair with your strategy entries; let breadth govern when to press, scale back, or stand down.
Symbols (defaults)
VOLD (NYSE volume diff), VOLDQ (NASDAQ volume diff), ADD (NYSE), ADDQ (NASDAQ), TICK (NYSE). Adjust in Inputs as needed.
Alerts
Panic, divergence, strong bullish/bearish breadth. Enable JSON export to feed algo/agent workflows.
Algorithm Predator - ML-liteAlgorithm Predator - ML-lite
This indicator combines four specialized trading agents with an adaptive multi-armed bandit selection system to identify high-probability trade setups. It is designed for swing and intraday traders who want systematic signal generation based on institutional order flow patterns , momentum exhaustion , liquidity dynamics , and statistical mean reversion .
Core Architecture
Why These Components Are Combined:
The script addresses a fundamental challenge in algorithmic trading: no single detection method works consistently across all market conditions. By deploying four independent agents and using reinforcement learning algorithms to select or blend their outputs, the system adapts to changing market regimes without manual intervention.
The Four Trading Agents
1. Spoofing Detector Agent 🎭
Detects iceberg orders through persistent volume at similar price levels over 5 bars
Identifies spoofing patterns via asymmetric wick analysis (wicks exceeding 60% of bar range with volume >1.8× average)
Monitors order clustering using simplified Hawkes process intensity tracking (exponential decay model)
Signal Logic: Contrarian—fades false breakouts caused by institutional manipulation
Best Markets: Consolidations, institutional trading windows, low-liquidity hours
2. Exhaustion Detector Agent ⚡
Calculates RSI divergence between price movement and momentum indicator over 5-bar window
Detects VWAP exhaustion (price at 2σ bands with declining volume)
Uses VPIN reversals (volume-based toxic flow dissipation) to identify momentum failure
Signal Logic: Counter-trend—enters when momentum extreme shows weakness
Best Markets: Trending markets reaching climax points, over-extended moves
3. Liquidity Void Detector Agent 💧
Measures Bollinger Band squeeze (width <60% of 50-period average)
Identifies stop hunts via 20-bar high/low penetration with immediate reversal and volume spike
Detects hidden liquidity absorption (volume >2× average with range <0.3× ATR)
Signal Logic: Breakout anticipation—enters after liquidity grab but before main move
Best Markets: Range-bound pre-breakout, volatility compression zones
4. Mean Reversion Agent 📊
Calculates price z-scores relative to 50-period SMA and standard deviation (triggers at ±2σ)
Implements Ornstein-Uhlenbeck process scoring (mean-reverting stochastic model)
Uses entropy analysis to detect algorithmic trading patterns (low entropy <0.25 = high predictability)
Signal Logic: Statistical reversion—enters when price deviates significantly from statistical equilibrium
Best Markets: Range-bound, low-volatility, algorithmically-dominated instruments
Adaptive Selection: Multi-Armed Bandit System
The script implements four reinforcement learning algorithms to dynamically select or blend agents based on performance:
Thompson Sampling (Default - Recommended):
Uses Bayesian inference with beta distributions (tracks alpha/beta parameters per agent)
Balances exploration (trying underused agents) vs. exploitation (using proven winners)
Each agent's win/loss history informs its selection probability
Lite Approximation: Uses pseudo-random sampling from price/volume noise instead of true random number generation
UCB1 (Upper Confidence Bound):
Calculates confidence intervals using: average_reward + sqrt(2 × ln(total_pulls) / agent_pulls)
Deterministic algorithm favoring agents with high uncertainty (potential upside)
More conservative than Thompson Sampling
Epsilon-Greedy:
Exploits best-performing agent (1-ε)% of the time
Explores randomly ε% of the time (default 10%, configurable 1-50%)
Simple, transparent, easily tuned via epsilon parameter
Gradient Bandit:
Uses softmax probability distribution over agent preference weights
Updates weights via gradient ascent based on rewards
Best for Blend mode where all agents contribute
Selection Modes:
Switch Mode: Uses only the selected agent's signal (clean, decisive)
Blend Mode: Combines all agents using exponentially weighted confidence scores controlled by temperature parameter (smooth, diversified)
Lock Agent Feature:
Optional manual override to force one specific agent
Useful after identifying which agent dominates your specific instrument
Only applies in Switch mode
Four choices: Spoofing Detector, Exhaustion Detector, Liquidity Void, Mean Reversion
Memory System
Dual-Layer Architecture:
Short-Term Memory: Stores last 20 trade outcomes per agent (configurable 10-50)
Long-Term Memory: Stores episode averages when short-term reaches transfer threshold (configurable 5-20 bars)
Memory Boost Mechanism: Recent performance modulates agent scores by up to ±20%
Episode Transfer: When an agent accumulates sufficient results, averages are condensed into long-term storage
Persistence: Manual restoration of learned parameters via input fields (alpha, beta, weights, microstructure thresholds)
How Memory Works:
Agent generates signal → outcome tracked after 8 bars (performance horizon)
Result stored in short-term memory (win = 1.0, loss = 0.0)
Short-term average influences agent's future scores (positive feedback loop)
After threshold met (default 10 results), episode averaged into long-term storage
Long-term patterns (weighted 30%) + short-term patterns (weighted 70%) = total memory boost
Market Microstructure Analysis
These advanced metrics quantify institutional order flow dynamics:
Order Flow Toxicity (Simplified VPIN):
Measures buy/sell volume imbalance over 20 bars: |buy_vol - sell_vol| / (buy_vol + sell_vol)
Detects informed trading activity (institutional players with non-public information)
Values >0.4 indicate "toxic flow" (informed traders active)
Lite Approximation: Uses simple open/close heuristic instead of tick-by-tick trade classification
Price Impact Analysis (Simplified Kyle's Lambda):
Measures market impact efficiency: |price_change_10| / sqrt(volume_sum_10)
Low values = large orders with minimal price impact ( stealth accumulation )
High values = retail-dominated moves with high slippage
Lite Approximation: Uses simplified denominator instead of regression-based signed order flow
Market Randomness (Entropy Analysis):
Counts unique price changes over 20 bars / 20
Measures market predictability
High entropy (>0.6) = human-driven, chaotic price action
Low entropy (<0.25) = algorithmic trading dominance (predictable patterns)
Lite Approximation: Simple ratio instead of true Shannon entropy H(X) = -Σ p(x)·log₂(p(x))
Order Clustering (Simplified Hawkes Process):
Tracks self-exciting event intensity (coordinated order activity)
Decays at 0.9× per bar, spikes +1.0 when volume >1.5× average
High intensity (>0.7) indicates clustering (potential spoofing/accumulation)
Lite Approximation: Simple exponential decay instead of full λ(t) = μ + Σ α·exp(-β(t-tᵢ)) with MLE
Signal Generation Process
Multi-Stage Validation:
Stage 1: Agent Scoring
Each agent calculates internal score based on its detection criteria
Scores must exceed agent-specific threshold (adjusted by sensitivity multiplier)
Agent outputs: Signal direction (+1/-1/0) and Confidence level (0.0-1.0)
Stage 2: Memory Boost
Agent scores multiplied by memory boost factor (0.8-1.2 based on recent performance)
Successful agents get amplified, failing agents get dampened
Stage 3: Bandit Selection/Blending
If Adaptive Mode ON:
Switch: Bandit selects single best agent, uses only its signal
Blend: All agents combined using softmax-weighted confidence scores
If Adaptive Mode OFF:
Traditional consensus voting with confidence-squared weighting
Signal fires when consensus exceeds threshold (default 70%)
Stage 4: Confirmation Filter
Raw signal must repeat for consecutive bars (default 3, configurable 2-4)
Minimum confidence threshold: 0.25 (25%) enforced regardless of mode
Trend alignment check: Long signals require trend_score ≥ -2, Short signals require trend_score ≤ 2
Stage 5: Cooldown Enforcement
Minimum bars between signals (default 10, configurable 5-15)
Prevents over-trading during choppy conditions
Stage 6: Performance Tracking
After 8 bars (performance horizon), signal outcome evaluated
Win = price moved in signal direction, Loss = price moved against
Results fed back into memory and bandit statistics
Trading Modes (Presets)
Pre-configured parameter sets:
Conservative: 85% consensus, 4 confirmations, 15-bar cooldown
Expected: 60-70% win rate, 3-8 signals/week
Best for: Swing trading, capital preservation, beginners
Balanced: 70% consensus, 3 confirmations, 10-bar cooldown
Expected: 55-65% win rate, 8-15 signals/week
Best for: Day trading, most traders, general use
Aggressive: 60% consensus, 2 confirmations, 5-bar cooldown
Expected: 50-58% win rate, 15-30 signals/week
Best for: Scalping, high-frequency trading, active management
Elite: 75% consensus, 3 confirmations, 12-bar cooldown
Expected: 58-68% win rate, 5-12 signals/week
Best for: Selective trading, high-conviction setups
Adaptive: 65% consensus, 2 confirmations, 8-bar cooldown
Expected: Varies based on learning
Best for: Experienced users leveraging bandit system
How to Use
1. Initial Setup (5 Minutes):
Select Trading Mode matching your style (start with Balanced)
Enable Adaptive Learning (recommended for automatic agent selection)
Choose Thompson Sampling algorithm (best all-around performance)
Keep Microstructure Metrics enabled for liquid instruments (>100k daily volume)
2. Agent Tuning (Optional):
Adjust Agent Sensitivity multipliers (0.5-2.0):
<0.8 = Highly selective (fewer signals, higher quality)
0.9-1.2 = Balanced (recommended starting point)
1.3 = Aggressive (more signals, lower individual quality)
Monitor dashboard for 20-30 signals to identify dominant agent
If one agent consistently outperforms, consider using Lock Agent feature
3. Bandit Configuration (Advanced):
Blend Temperature (0.1-2.0):
0.3 = Sharp decisions (best agent dominates)
0.5 = Balanced (default)
1.0+ = Smooth (equal weighting, democratic)
Memory Decay (0.8-0.99):
0.90 = Fast adaptation (volatile markets)
0.95 = Balanced (most instruments)
0.97+ = Long memory (stable trends)
4. Signal Interpretation:
Green triangle (▲): Long signal confirmed
Red triangle (▼): Short signal confirmed
Dashboard shows:
Active agent (highlighted row with ► marker)
Win rate per agent (green >60%, yellow 40-60%, red <40%)
Confidence bars (█████ = maximum confidence)
Memory size (short-term buffer count)
Colored zones display:
Entry level (current close)
Stop-loss (1.5× ATR)
Take-profit 1 (2.0× ATR)
Take-profit 2 (3.5× ATR)
5. Risk Management:
Never risk >1-2% per signal (use ATR-based stops)
Signals are entry triggers, not complete strategies
Combine with your own market context analysis
Consider fundamental catalysts and news events
Use "Confirming" status to prepare entries (not to enter early)
6. Memory Persistence (Optional):
After 50-100 trades, check Memory Export Panel
Record displayed alpha/beta/weight values for each agent
Record VPIN and Kyle threshold values
Enable "Restore From Memory" and input saved values to continue learning
Useful when switching timeframes or restarting indicator
Visual Components
On-Chart Elements:
Spectral Layers: EMA8 ± 0.5 ATR bands (dynamic support/resistance, colored by trend)
Energy Radiance: Multi-layer glow boxes at signal points (intensity scales with confidence, configurable 1-5 layers)
Probability Cones: Projected price paths with uncertainty wedges (15-bar projection, width = confidence × ATR)
Connection Lines: Links sequential signals (solid = same direction continuation, dotted = reversal)
Kill Zones: Risk/reward boxes showing entry, stop-loss, and dual take-profit targets
Signal Markers: Triangle up/down at validated entry points
Dashboard (Configurable Position & Size):
Regime Indicator: 4-level trend classification (Strong Bull/Bear, Weak Bull/Bear)
Mode Status: Shows active system (Adaptive Blend, Locked Agent, or Consensus)
Agent Performance Table: Real-time win%, confidence, and memory stats
Order Flow Metrics: Toxicity and impact indicators (when microstructure enabled)
Signal Status: Current state (Long/Short/Confirming/Waiting) with confirmation progress
Memory Panel (Configurable Position & Size):
Live Parameter Export: Alpha, beta, and weight values per agent
Adaptive Thresholds: Current VPIN sensitivity and Kyle threshold
Save Reminder: Visual indicator if parameters should be recorded
What Makes This Original
This script's originality lies in three key innovations:
1. Genuine Meta-Learning Framework:
Unlike traditional indicator mashups that simply display multiple signals, this implements authentic reinforcement learning (multi-armed bandits) to learn which detection method works best in current conditions. The Thompson Sampling implementation with beta distribution tracking (alpha for successes, beta for failures) is statistically rigorous and adapts continuously. This is not post-hoc optimization—it's real-time learning.
2. Episodic Memory Architecture with Transfer Learning:
The dual-layer memory system mimics human learning patterns:
Short-term memory captures recent performance (recency bias)
Long-term memory preserves historical patterns (experience)
Automatic transfer mechanism consolidates knowledge
Memory boost creates positive feedback loops (successful strategies become stronger)
This architecture allows the system to adapt without retraining , unlike static ML models that require batch updates.
3. Institutional Microstructure Integration:
Combines retail-focused technical analysis (RSI, Bollinger Bands, VWAP) with institutional-grade microstructure metrics (VPIN, Kyle's Lambda, Hawkes processes) typically found in academic finance literature and professional trading systems, not standard retail platforms. While simplified for Pine Script constraints, these metrics provide insight into informed vs. uninformed trading , a dimension entirely absent from traditional technical analysis.
Mashup Justification:
The four agents are combined specifically for risk diversification across failure modes:
Spoofing Detector: Prevents false breakout losses from manipulation
Exhaustion Detector: Prevents chasing extended trends into reversals
Liquidity Void: Exploits volatility compression (different regime than trending)
Mean Reversion: Provides mathematical anchoring when patterns fail
The bandit system ensures the optimal tool is automatically selected for each market situation, rather than requiring manual interpretation of conflicting signals.
Why "ML-lite"? Simplifications and Approximations
This is the "lite" version due to necessary simplifications for Pine Script execution:
1. Simplified VPIN Calculation:
Academic Implementation: True VPIN uses volume bucketing (fixed-volume bars) and tick-by-tick buy/sell classification via Lee-Ready algorithm or exchange-provided trade direction flags
This Implementation: 20-bar rolling window with simple open/close heuristic (close > open = buy volume)
Impact: May misclassify volume during ranging/choppy markets; works best in directional moves
2. Pseudo-Random Sampling:
Academic Implementation: Thompson Sampling requires true random number generation from beta distributions using inverse transform sampling or acceptance-rejection methods
This Implementation: Deterministic pseudo-randomness derived from price and volume decimal digits: (close × 100 - floor(close × 100)) + (volume % 100) / 100
Impact: Not cryptographically random; may have subtle biases in specific price ranges; provides sufficient variation for agent selection
3. Hawkes Process Approximation:
Academic Implementation: Full Hawkes process uses maximum likelihood estimation with exponential kernels: λ(t) = μ + Σ α·exp(-β(t-tᵢ)) fitted via iterative optimization
This Implementation: Simple exponential decay (0.9 multiplier) with binary event triggers (volume spike = event)
Impact: Captures self-exciting property but lacks parameter optimization; fixed decay rate may not suit all instruments
4. Kyle's Lambda Simplification:
Academic Implementation: Estimated via regression of price impact on signed order flow over multiple time intervals: Δp = λ × Δv + ε
This Implementation: Simplified ratio: price_change / sqrt(volume_sum) without proper signed order flow or regression
Impact: Provides directional indicator of impact but not true market depth measurement; no statistical confidence intervals
5. Entropy Calculation:
Academic Implementation: True Shannon entropy requires probability distribution: H(X) = -Σ p(x)·log₂(p(x)) where p(x) is probability of each price change magnitude
This Implementation: Simple ratio of unique price changes to total observations (variety measure)
Impact: Measures diversity but not true information entropy with probability weighting; less sensitive to distribution shape
6. Memory System Constraints:
Full ML Implementation: Neural networks with backpropagation, experience replay buffers (storing state-action-reward tuples), gradient descent optimization, and eligibility traces
This Implementation: Fixed-size array queues with simple averaging; no gradient-based learning, no state representation beyond raw scores
Impact: Cannot learn complex non-linear patterns; limited to linear performance tracking
7. Limited Feature Engineering:
Advanced Implementation: Dozens of engineered features, polynomial interactions (x², x³), dimensionality reduction (PCA, autoencoders), feature selection algorithms
This Implementation: Raw agent scores and basic market metrics (RSI, ATR, volume ratio); minimal transformation
Impact: May miss subtle cross-feature interactions; relies on agent-level intelligence rather than feature combinations
8. Single-Instrument Data:
Full Implementation: Multi-asset correlation analysis (sector ETFs, currency pairs, volatility indices like VIX), lead-lag relationships, risk-on/risk-off regimes
This Implementation: Only OHLCV data from displayed instrument
Impact: Cannot incorporate broader market context; vulnerable to correlated moves across assets
9. Fixed Performance Horizon:
Full Implementation: Adaptive horizon based on trade duration, volatility regime, or profit target achievement
This Implementation: Fixed 8-bar evaluation window
Impact: May evaluate too early in slow markets or too late in fast markets; one-size-fits-all approach
Performance Impact Summary:
These simplifications make the script:
✅ Faster: Executes in milliseconds vs. seconds (or minutes) for full academic implementations
✅ More Accessible: Runs on any TradingView plan without external data feeds, APIs, or compute servers
✅ More Transparent: All calculations visible in Pine Script (no black-box compiled models)
✅ Lower Resource Usage: <500 bars lookback, minimal memory footprint
⚠️ Less Precise: Approximations may reduce statistical edge by 5-15% vs. academic implementations
⚠️ Limited Scope: Cannot capture tick-level dynamics, multi-order-book interactions, or cross-asset flows
⚠️ Fixed Parameters: Some thresholds hardcoded rather than dynamically optimized
When to Upgrade to Full Implementation:
Consider professional Python/C++ versions with institutional data feeds if:
Trading with >$100K capital where precision differences materially impact returns
Operating in microsecond-competitive environments (HFT, market making)
Requiring regulatory-grade audit trails and reproducibility
Backtesting with tick-level precision for strategy validation
Need true real-time adaptation with neural network-based learning
For retail swing/day trading and position management, these approximations provide sufficient signal quality while maintaining usability, transparency, and accessibility. The core logic—multi-agent detection with adaptive selection—remains intact.
Technical Notes
All calculations use standard Pine Script built-in functions ( ta.ema, ta.atr, ta.rsi, ta.bb, ta.sma, ta.stdev, ta.vwap )
VPIN and Kyle's Lambda use simplified formulas optimized for OHLCV data (see "Lite" section above)
Thompson Sampling uses pseudo-random noise from price/volume decimal digits for beta distribution sampling
No repainting: All calculations use confirmed bar data (no forward-looking)
Maximum lookback: 500 bars (set via max_bars_back parameter)
Performance evaluation: 8-bar forward-looking window for reward calculation (clearly disclosed)
Confidence threshold: Minimum 0.25 (25%) enforced on all signals
Memory arrays: Dynamic sizing with FIFO queue management
Limitations and Disclaimers
Not Predictive: This indicator identifies patterns in historical data. It cannot predict future price movements with certainty.
Requires Human Judgment: Signals are entry triggers, not complete trading strategies. Must be confirmed with your own analysis, risk management rules, and market context.
Learning Period Required: The adaptive system requires 50-100 bars minimum to build statistically meaningful performance data for bandit algorithms.
Overfitting Risk: Restoring memory parameters from one market regime to a drastically different regime (e.g., low volatility to high volatility) may cause poor initial performance until system re-adapts.
Approximation Limitations: Simplified calculations (see "Lite" section) may underperform academic implementations by 5-15% in highly efficient markets.
No Guarantee of Profit: Past performance, whether backtested or live-traded, does not guarantee future performance. All trading involves risk of loss.
Forward-Looking Bias: Performance evaluation uses 8-bar forward window—this creates slight look-ahead for learning (though not for signals). Real-time performance may differ from indicator's internal statistics.
Single-Instrument Limitation: Does not account for correlations with related assets or broader market regime changes.
Recommended Settings
Timeframe: 15-minute to 4-hour charts (sufficient volatility for ATR-based stops; adequate bar volume for learning)
Assets: Liquid instruments with >100k daily volume (forex majors, large-cap stocks, BTC/ETH, major indices)
Not Recommended: Illiquid small-caps, penny stocks, low-volume altcoins (microstructure metrics unreliable)
Complementary Tools: Volume profile, order book depth, market breadth indicators, fundamental catalysts
Position Sizing: Risk no more than 1-2% of capital per signal using ATR-based stop-loss
Signal Filtering: Consider external confluence (support/resistance, trendlines, round numbers, session opens)
Start With: Balanced mode, Thompson Sampling, Blend mode, default agent sensitivities (1.0)
After 30+ Signals: Review agent win rates, consider increasing sensitivity of top performers or locking to dominant agent
Alert Configuration
The script includes built-in alert conditions:
Long Signal: Fires when validated long entry confirmed
Short Signal: Fires when validated short entry confirmed
Alerts fire once per bar (after confirmation requirements met)
Set alert to "Once Per Bar Close" for reliability
Taking you to school. — Dskyz, Trade with insight. Trade with anticipation.
TopBot [CHE] TopBot — Structure pivots with buffered acceptance and gradient trend visualization
Summary
TopBot detects swing structure from confirmed pivot highs and lows, derives support and resistance levels, and switches trend only after a buffered and accepted break. It renders labels for recent structure points, maintains dynamic support and resistance lines that freeze on contact, and colors candles using a gradient that reflects consecutive trend persistence. The gradient communicates strength without extra panels, while the buffered acceptance reduces fragile flips around key levels. Everything runs in the main chart for immediate context.
Motivation: Why this design?
Classical swing tools often flip on single-bar spikes and produce lines that extend forever without acknowledging when price invalidates them. This script addresses that by requiring a user-controlled buffer and a run of consecutive closes before changing trend, while also freezing lines once price interacts with them. The gradient color layer communicates regime persistence so users can quickly judge whether a move is maturing or just starting.
What’s different vs. standard approaches?
Baseline reference: Simple pivot labeling and unbuffered break-of-structure tools.
Architecture differences:
Buffered level testing using ticks, percent, or ATR.
Acceptance logic that requires multiple consecutive closes.
Synchronized structure labeling with a single Top and Bottom within the active set.
Progressive support and resistance management that freezes lines on first contact.
Gradient candle and wick coloring driven by consecutive trend counts with windowed normalization and gamma control.
Practical effect: Fewer whipsaw flips, clearer status of active levels, and visual feedback about trend persistence without a secondary pane.
How it works (technical)
The script confirms swing points using left and right bar pivots, then forms a current structure window to classify each pivot as higher high, lower high, higher low, or lower low. Recent labels are trimmed to a user cap, and a postprocess step ensures one highest and one lowest label while preserving side information for the others. Support updates on higher low events, resistance on lower high events. Trend flips only after the close has moved beyond the active level by a chosen buffer and this condition holds for a chosen number of consecutive bars. Lines for new levels extend to the right and freeze once price touches them. A running count of consecutive trend bars produces a strength score, which is normalized over a rolling window, shaped by gamma, and mapped to user-defined dark and neon colors for both up and down regimes. Wick coloring uses `plotcandle`; fallback bar coloring uses `barcolor`. No higher-timeframe data is requested. Signals confirm only after the right-bar lookback of the pivot function.
Parameter Guide
Left Bars / Right Bars (default five each): Pivot sensitivity. Larger values confirm later and reduce noise; smaller values respond faster with more noise.
Draw S/R Lines (default true): Enables support and resistance line creation and updates.
Support / Resistance Colors (lime, red): Line colors for each side.
Line Style (Solid, Dashed, Dotted; default Dotted) and Width (default three): Visual style of S/R lines.
Max Labels & Lines (default ten): Cap for objects to control clutter and resource usage.
Change Bar Color (default true), Up/Down colors (blue, black): Fallback bar coloring when gradients or wick coloring are disabled.
Show Neutral Candles (default false): Optional coloring when no trend is active.
Enable Gradient Bar Colors (default true): Turns on gradient body coloring from the strength score.
Enable Wick Coloring (default true): Colors wicks and borders using `plotcandle`.
Collection Period (default one hundred): Rolling window used to scale the strength score. Shorter windows react faster but vary more.
Gamma Bars / Gamma Plots (defaults zero point seven and zero point eight): Shapes perceived contrast of bar and wick gradients. Lower values brighten early; higher values compress until stronger runs appear.
Gradient Transparency / Wick Transparency (default zero): Visual transparency for bodies and wicks.
Up/Down Trend Dark and Neon Colors: Endpoints for gradient mapping in each regime.
Acceptance closes (n) (default two): Number of consecutive closes beyond a level required before trend flips. Larger values reduce false breaks but react later.
Break buffer (None, Ticks, Percent, ATR; default ATR) and Value (default zero point five) and ATR Len (default fourteen): Defines the safety margin beyond the level. ATR mode adapts to volatility; Percent and Ticks are static.
Reading & Interpretation
Labels: “Top” and “Bottom” mark the most extreme points in the active set; “LT” and “HB” indicate side labels for lower top and higher bottom.
Lines: New support or resistance is drawn when structure confirms. A line freezes once price touches it, signaling that the dynamic phase ended.
Trend: Internal state switches to up or down only after buffered acceptance.
Colors: Brighter neon tones indicate stronger and more persistent runs; darker tones suggest early or weakening runs. When gradients are off, fallback bar colors indicate trend sign.
Practical Workflows & Combinations
Trend following: Wait for a buffered and accepted break through the most recent level, then use gradient intensity to stage entries or scale-ins.
Structure-first filtering: Trade only in the direction of the last accepted trend while price remains above support or below resistance.
Exits and stops: Consider exiting on loss of gradient intensity combined with a return through the most recent structure level.
Multi-asset / Multi-timeframe: Works on liquid symbols across common timeframes. Use larger pivot bars and higher acceptance on lower timeframes. No built-in higher-timeframe aggregation is used.
Behavior, Constraints & Performance
Repaint/confirmation: Pivot confirmation waits for the right bar window; trend acceptance is based on closes and can change during a live bar. Final signals stabilize on bar close.
security/HTF: Not used. No cross-timeframe data.
Resources: Arrays and loops are used for labels, lines, and structure search up to a capped historical span. Object counts are clamped by user input and platform limits.
Known limits: Delayed confirmation at sharp turns due to pivot windows; rapid gaps can jump over buffers; gradient scaling depends on the chosen collection period.
Sensible Defaults & Quick Tuning
Start with the defaults: pivot windows at five, ATR buffer with value near one half, acceptance at two, collection period near one hundred, gamma near zero point seven to zero point eight.
Too many flips: increase acceptance, increase buffer value, or increase pivot windows.
Too sluggish: reduce acceptance, reduce buffer value, or reduce pivot windows.
Colors too flat: lower gamma or shorten the collection period.
Visual clutter: reduce the max labels and lines cap or disable wicks.
What this indicator is—and isn’t
This is a visualization and signal layer that encodes swing structure, level state, and regime persistence. It is not a complete trading system, not predictive, and does not manage orders. Use it with broader context such as higher timeframe structure, session behavior, and defined risk controls.
Disclaimer
The content provided, including all code and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell any financial instrument, or an offer of any financial product or service. All strategies, tools, and examples discussed are provided for illustrative purposes to demonstrate coding techniques and the functionality of Pine Script within a trading context.
Any results from strategies or tools provided are hypothetical, and past performance is not indicative of future results. Trading and investing involve high risk, including the potential loss of principal, and may not be suitable for all individuals. Before making any trading decisions, please consult with a qualified financial professional to understand the risks involved.
By using this script, you acknowledge and agree that any trading decisions are made solely at your discretion and risk.
Do not use this indicator on Heikin-Ashi, Renko, Kagi, Point-and-Figure, or Range charts, as these chart types can produce unrealistic results for signal markers and alerts.
Best regards and happy trading
Chervolino
Acknowledgment
Thanks to LonesomeTheBlue for the fantastic and inspiring "Higher High Lower Low Strategy" .
Original script:
Credit for the original concept and implementation goes to the author; any adaptations or errors here are mine.
Turtles StrategyBorn from the 1980s "Turtle" experiment, this method of trading captures breakouts and places or closes trades with intrabar entries or exits and realized-equity risk controls.
How It Works
The strategy buys/sells on breakouts from recent highs/lows, using ATR for volatility-adjusted stops and sizing. It risks a fixed % (default 1%) of realized equity per trade—initial capital plus closed P&L, ignoring open positions for conservatism. Drawdown protection auto-reduces risk by 20% at 10% drops (up to three times), resetting only on full peak recovery. Single positions only, with 1-tick slippage simulated for realistic fills. Best for trending assets like forex,commodities, crypto, stocks. Backtest for optimal parameters.
Main Operations
The strategy works on any timeframe but it's meant to be used on daily charts.
Entry Signals:
Long: Buy-stop 1 tick above 20-bar high (default "Entry Period") when no position—enters intrabar on breakout.
Short: Sell-stop 1 tick below 20-bar low. OCA cancels opposites.
Size: (Realized equity × adjusted risk %) ÷ (2× ATR stop distance), scaled by point value.
Exit Signals:
Longs: Stop at tighter of (entry - 2× ATR) or (10-bar low - 1 tick trailing, default "Exit Period").
Shorts: Stop at tighter of (entry + 2× ATR) or (10-bar high + 1 tick trailing).
Locks profits in trends, exits fast on fades.
Risk Controls:
Tracks realized equity peak.
10% drawdown: Risk ×0.8; 20%/30%: Further ×0.8 (max 3x).
Full reset above peak—preserves capital in slumps.
DRACO Tomas Delta (Custom/Monthly)🐉 DRACO Delta SessionBox (Custom / Monthly)
Overview
The DRACO Delta SessionBox is an advanced visual and analytical tool designed to measure and display cumulative buying and selling pressure (Δ — delta) within a user-defined time window, such as a specific custom date range, a recurring monthly period, or the entire current month.
It visually represents market accumulation or distribution phases by calculating an approximate delta — the imbalance between bullish and bearish volume — and then aggregates it inside a dynamic “box” that spans only the selected time window.
Core Concept
Delta in this context is an approximation of the real order-flow delta (buy vs sell volume difference).
Since TradingView doesn’t provide raw tick-by-tick trade direction data, this indicator uses a proxy formula based on OHLC and volume data:
Δ per bar
=
Volume
×
(
Close
−
Open
)
max
(
High
−
Low
,
Tick Size
)
Δ per bar=Volume×
max(High−Low,Tick Size)
(Close−Open)
This gives a very effective approximation of intrabar directional pressure — whether volume was dominated by buyers (Δ > 0) or sellers (Δ < 0).
Modes
The indicator can operate in three distinct modes:
🕒 Custom DateTime
The user manually sets an exact date & time range (From – To).
The box only measures delta and volume accumulation within this window.
Ideal for analyzing specific events, like FOMC weeks, quarterly earnings, or macro periods.
📆 Monthly Window
The user selects start and end days of the month (e.g. 5–20).
The same window repeats automatically every month.
Useful for identifying recurring accumulation or distribution cycles within months.
🧭 Whole Month
Automatically measures and visualizes delta for the entire current calendar month.
The box resets when a new month begins.
Provides a macro-level view of monthly directional bias.
Zero Lag Trend Signals (MTF) [Quant Trading] V7Overview
The Zero Lag Trend Signals (MTF) V7 is a comprehensive trend-following strategy that combines Zero Lag Exponential Moving Average (ZLEMA) with volatility-based bands to identify high-probability trade entries and exits. This strategy is designed to reduce lag inherent in traditional moving averages while incorporating dynamic risk management through ATR-based stops and multiple exit mechanisms.
This is a longer term horizon strategy that takes limited trades. It is not a high frequency trading and therefore will also have limited data and not > 100 trades.
How It Works
Core Signal Generation:
The strategy uses a Zero Lag EMA (ZLEMA) calculated by applying an EMA to price data that has been adjusted for lag:
Calculate lag period: floor((length - 1) / 2)
Apply lag correction: src + (src - src )
Calculate ZLEMA: EMA of lag-corrected price
Volatility bands are created using the highest ATR over a lookback period multiplied by a band multiplier. These bands are added to and subtracted from the ZLEMA line to create upper and lower boundaries.
Trend Detection:
The strategy maintains a trend variable that switches between bullish (1) and bearish (-1):
Long Signal: Triggers when price crosses above ZLEMA + volatility band
Short Signal: Triggers when price crosses below ZLEMA - volatility band
Optional ZLEMA Trend Confirmation:
When enabled, this filter requires ZLEMA to show directional momentum before entry:
Bullish Confirmation: ZLEMA must increase for 4 consecutive bars
Bearish Confirmation: ZLEMA must decrease for 4 consecutive bars
This additional filter helps avoid false signals in choppy or ranging markets.
Risk Management Features:
The strategy includes multiple stop-loss and take-profit mechanisms:
Volatility-Based Stops: Default stop-loss is placed at ZLEMA ± volatility band
ATR-Based Stops: Dynamic stop-loss calculated as entry price ± (ATR × multiplier)
ATR Trailing Stop: Ratcheting stop-loss that follows price but never moves against position
Risk-Reward Profit Target: Take-profit level set as a multiple of stop distance
Break-Even Stop: Moves stop to entry price after reaching specified R:R ratio
Trend-Based Exit: Closes position when price crosses EMA in opposite direction
Performance Tracking:
The strategy includes optional features for monitoring and analyzing trades:
Floating Statistics Table: Displays key metrics including win rate, GOA (Gain on Account), net P&L, and max drawdown
Trade Log Labels: Shows entry/exit prices, P&L, bars held, and exit reason for each closed trade
CSV Export Fields: Outputs trade data for external analysis
Default Strategy Settings
Commission & Slippage:
Commission: 0.1% per trade
Slippage: 3 ticks
Initial Capital: $1,000
Position Size: 100% of equity per trade
Main Calculation Parameters:
Length: 70 (range: 70-7000) - Controls ZLEMA calculation period
Band Multiplier: 1.2 - Adjusts width of volatility bands
Entry Conditions (All Disabled by Default):
Use ZLEMA Trend Confirmation: OFF - Requires ZLEMA directional momentum
Re-Enter on Long Trend: OFF - Allows multiple entries during sustained trends
Short Trades:
Allow Short Trades: OFF - Strategy is long-only by default
Performance Settings (All Disabled by Default):
Use Profit Target: OFF
Profit Target Risk-Reward Ratio: 2.0 (when enabled)
Dynamic TP/SL (All Disabled by Default):
Use ATR-Based Stop-Loss & Take-Profit: OFF
ATR Length: 14
Stop-Loss ATR Multiplier: 1.5
Profit Target ATR Multiplier: 2.5
Use ATR Trailing Stop: OFF
Trailing Stop ATR Multiplier: 1.5
Use Break-Even Stop-Loss: OFF
Move SL to Break-Even After RR: 1.5
Use Trend-Based Take Profit: OFF
EMA Exit Length: 9
Trade Data Display (All Disabled by Default):
Show Floating Stats Table: OFF
Show Trade Log Labels: OFF
Enable CSV Export: OFF
Trade Label Vertical Offset: 0.5
Backtesting Date Range:
Start Date: January 1, 2018
End Date: December 31, 2069
Important Usage Notes
Default Configuration: The strategy operates in its most basic form with default settings - using only ZLEMA crossovers with volatility bands and volatility-based stop-losses. All advanced features must be manually enabled.
Stop-Loss Priority: If multiple stop-loss methods are enabled simultaneously, the strategy will use whichever condition is hit first. ATR-based stops override volatility-based stops when enabled.
Long-Only by Default: Short trading is disabled by default. Enable "Allow Short Trades" to trade both directions.
Performance Monitoring: Enable the floating stats table and trade log labels to visualize strategy performance during backtesting.
Exit Mechanisms: The strategy can exit trades through multiple methods: stop-loss hit, take-profit reached, trend reversal, or trailing stop activation. The trade log identifies which exit method was used.
Re-Entry Logic: When "Re-Enter on Long Trend" is enabled with ZLEMA trend confirmation, the strategy can take multiple long positions during extended uptrends as long as all entry conditions remain valid.
Capital Efficiency: Default setting uses 100% of equity per trade. Adjust "default_qty_value" to manage position sizing based on risk tolerance.
Realistic Backtesting: Strategy includes commission (0.1%) and slippage (3 ticks) to provide realistic performance expectations. These values should be adjusted based on your broker and market conditions.
Recommended Use Cases
Trending Markets: Best suited for markets with clear directional moves where trend-following strategies excel
Medium to Long-Term Trading: The default length of 70 makes this strategy more appropriate for swing trading rather than scalping
Risk-Conscious Traders: Multiple stop-loss options allow traders to customize risk management to their comfort level
Backtesting & Optimization: Comprehensive performance tracking features make this strategy ideal for testing different parameter combinations
Limitations & Considerations
Like all trend-following strategies, performance may suffer in choppy or ranging markets
Default 100% position sizing means full capital exposure per trade - consider reducing for conservative risk management
Higher length values (70+) reduce signal frequency but may improve signal quality
Multiple simultaneous risk management features may create conflicting exit signals
Past performance shown in backtests does not guarantee future results
Customization Tips
For more aggressive trading:
Reduce length parameter (minimum 70)
Decrease band multiplier for tighter bands
Enable short trades
Use lower profit target R:R ratios
For more conservative trading:
Increase length parameter
Enable ZLEMA trend confirmation
Use wider ATR stop-loss multipliers
Enable break-even stop-loss
Reduce position size from 100% default
For optimal choppy market performance:
Enable ZLEMA trend confirmation
Increase band multiplier
Use tighter profit targets
Avoid re-entry on trend continuation
Visual Elements
The strategy plots several elements on the chart:
ZLEMA line (color-coded by trend direction)
Upper and lower volatility bands
Long entry markers (green triangles)
Short entry markers (red triangles, when enabled)
Stop-loss levels (when positions are open)
Take-profit levels (when enabled and positions are open)
Trailing stop lines (when enabled and positions are open)
Optional ZLEMA trend markers (triangles at highs/lows)
Optional trade log labels showing complete trade information
Exit Reason Codes (for CSV Export)
When CSV export is enabled, exit reasons are coded as:
0 = Manual/Other
1 = Trailing Stop-Loss
2 = Profit Target
3 = ATR Stop-Loss
4 = Trend Change
Conclusion
Zero Lag Trend Signals V7 provides a robust framework for trend-following with extensive customization options. The strategy balances simplicity in its core logic with sophisticated risk management features, making it suitable for both beginner and advanced traders. By reducing moving average lag while incorporating volatility-based signals, it aims to capture trends earlier while managing risk through multiple configurable exit mechanisms.
The modular design allows traders to start with basic trend-following and progressively add complexity through ZLEMA confirmation, multiple stop-loss methods, and advanced exit strategies. Comprehensive performance tracking and export capabilities make this strategy an excellent tool for systematic testing and optimization.
Note: This strategy is provided for educational and backtesting purposes. All trading involves risk. Past performance does not guarantee future results. Always test thoroughly with paper trading before risking real capital, and adjust position sizing and risk parameters according to your risk tolerance and account size.
================================================================================
TAGS:
================================================================================
trend following, ZLEMA, zero lag, volatility bands, ATR stops, risk management, swing trading, momentum, trend confirmation, backtesting
================================================================================
CATEGORY:
================================================================================
Strategies
================================================================================
CHART SETUP RECOMMENDATIONS:
================================================================================
For optimal visualization when publishing:
Use a clean chart with no other indicators overlaid
Select a timeframe that shows multiple trade signals (4H or Daily recommended)
Choose a trending asset (crypto, forex major pairs, or trending stocks work well)
Show at least 6-12 months of data to demonstrate strategy across different market conditions
Enable the floating stats table to display key performance metrics
Ensure all indicator lines (ZLEMA, bands, stops) are clearly visible
Use the default chart type (candlesticks) - avoid Heikin Ashi, Renko, etc.
Make sure symbol information and timeframe are clearly visible
================================================================================
COMPLIANCE NOTES:
================================================================================
✅ Open-source publication with complete code visibility
✅ English-only title and description
✅ Detailed explanation of methodology and calculations
✅ Realistic commission (0.1%) and slippage (3 ticks) included
✅ All default parameters clearly documented
✅ Performance limitations and risks disclosed
✅ No unrealistic claims about performance
✅ No guaranteed results promised
✅ Appropriate for public library (original trend-following implementation with ZLEMA)
✅ Educational disclaimers included
✅ All features explained in detail
================================================================================
Smart Money Support/Resistance - LiteSmart Money Support/Resistance — Lite
Overview & Methodology
This indicator identifies support and resistance as zones derived from concentrated buying and selling pressure, rather than relying solely on traditional swing highs/lows. Its design focuses on transparency: how data is sourced, how zones are computed, and how the on‑chart display should be interpreted.
Lower‑Timeframe (LTF) Data
The script requests Up Volume, Down Volume, and Volume Delta from a lower timeframe to expose intrabar order‑flow structure that the chart’s native timeframe cannot show. In practical terms, this lets you see where buyers or sellers briefly dominated inside the body of a higher‑timeframe bar.
bool use_custom_tf_input = input.bool(true, title="Use custom lower timeframe", tooltip="Override the automatically chosen lower timeframe for volume calculations.", group=grpVolume)
string custom_tf_input = input. Timeframe("1", title="Lower timeframe", tooltip="Lower timeframe used for up/down volume calculations (default 5 seconds).", group=grpVolume)
import TradingView/ta/10 as tvta
resolve_lower_tf(useCustom, customTF) =>
useCustom ? customTF :
timeframe.isseconds ? "1S" :
timeframe.isintraday ? "1" :
timeframe.isdaily ? "5" : "60"
get_up_down_volume(lowerTf) =>
= tvta.requestUpAndDownVolume(lowerTf)
var float upVolume = na
var float downVolume = na
var float deltaVolume = na
string lower_tf = resolve_lower_tf(use_custom_tf_input, custom_tf_input)
= get_up_down_volume(lower_tf)
upVolume := u_tmp
downVolume := d_tmp
deltaVolume := dl_tmp
• Data source: TradingView’s ta.requestUpAndDownVolume(lowerTf) via the official TA library.
• Plan capabilities: higher‑tier subscriptions unlock seconds‑based charts and allow more historical bars per chart. This expands both the temporal depth of LTF data and the precision of short‑horizon analysis, while base tiers provide minute‑level data suitable for day/short‑swing studies.
• Coverage clarity: a small on‑chart Coverage Panel reports the active lower timeframe, the number of bars covered, and the latest computed support/resistance ranges so you always know the bounds of valid LTF input.
Core Method
1) Data acquisition (LTF)
The script retrieves three series from the chosen lower timeframe:
– Up Volume (buyers)
– Down Volume (sellers)
– Delta (Up – Down)
2) Rolling window & extrema
Over a user‑defined lookback (Global Volume Period), the algorithm builds rolling arrays of completed bars and scans for extrema:
– Buyers_max / Buyers_min from Up Volume
– Sellers_max / Sellers_min from Down Volume
Only completed bars are considered; the current bar is excluded for stability.
3) Price mapping
The extrema are mapped back to their source candles to obtain price bounds:
– For “maximum” roles the algorithm uses the relevant candle highs.
– For “minimum” roles it uses the relevant candle lows.
These pairs define candidate resistance (max‑based) and support (min‑based) zones or vice versa.
4) Zone construction & minimum width
To ensure practicality on all symbols, zones enforce a minimum vertical thickness of two ticks. This prevents visually invisible or overly thin ranges on instruments with tight ticks.
5) Vertical role resolution
When both max‑ and min‑based zones exist, the script compares their midpoints. If, due to local price structure, the min‑based zone sits above the max‑based zone, display roles are swapped so the higher zone is labeled Resistance and the lower zone Support. Colors/widths are updated accordingly to keep the visual legend consistent.
6) Rendering & panel
Two horizontal lines and a filled box represent each active zone. The Coverage Panel (bottom‑right by default) prints:
– Lower‑timeframe in use
– Number of bars covered by LTF data
– Current Support and Resistance ranges
If the two zones overlap, an additional “Range Market” note is shown.
Key Inputs
• Global Volume Period: shared lookback window for the extrema search.
• Lower timeframe: user‑selectable override of the automatically resolved lower timeframe.
• Visualization toggles: independent show/hide controls and colors for maximum (resistance) and minimum (support) zones.
• Coverage Panel: enable/disable the single‑cell table and its readout.
Operational Notes
• The algorithm aligns all lookups to completed bars (no peeking). Price references are shifted appropriately to avoid using the still‑forming bar in calculations.
• Second‑based lower timeframes improve granularity for scalping and very short‑term entries. Minute‑based lower timeframes provide broader coverage for intraday and short‑swing contexts.
• Use the Coverage Panel to confirm the true extent of available LTF history on your symbol/plan before drawing conclusions from very deep lookbacks.
Visual Walkthrough
A step‑by‑step image sequence accompanies this description. Each figure demonstrates how the indicator reads LTF volume, locates extrema, builds price‑mapped zones, and updates labels/colors when vertical order requires it.
Chart Interpretation
This chart illustrates two distinct perspectives of the Smart Money Support/Resistance — Lite indicator, each derived from different lookback horizons and lower-timeframe (LTF) resolutions.
1- Short-term view (43 bars, 10-second LTF)
Using the most recent 43 completed bars with 10-second intrabar data, the algorithm detects that both maximum and minimum volume extrema fall within a narrow range. The result is a clearly identified range market: resistance between 178.15–184.55 and support between 175.02–179.38.
The Coverage Panel (bottom-right) confirms the scope of valid input: the lower timeframe used, number of bars covered, and the resulting zones. This short-term scan highlights how the indicator adapts to limited data depth, flagging sideways structure where neither side dominates.
2 - Long-term view (120 bars, 30-second LTF)
Over a wider 120-bar lookback with higher-granularity 30-second data, broader supply and demand zones emerge.
– The long-term resistance zone captures the concentration of buyers and sellers at the upper boundary of recent price history.
– The long-term support zone anchors to the opposite side of the distribution, derived from maxima and minima of both buying and selling pressure.
These zones reflect deeper structural levels where market participants previously committed significant volume.
Combined Perspective
By aligning the short-term and long-term outputs, the chart shows how the indicator distinguishes immediate consolidation (range market) from more durable support and resistance levels derived from extended history. This dual resolution approach makes clear that support and resistance are not static lines but dynamic zones, dependent on both timeframe depth and the resolution of intrabar volume data.
Heikin Ashi Overlay SuiteHeikin Ashi Overlay Suite is designed to give traders more control and clarity when working with Heikin Ashi candles — whether you're analyzing trend strength, reducing chart noise, or simply improving your visual read of market momentum. It works by layering multiple types of HA overlays and color systems on top of your standard candlestick chart — without switching chart types. With dynamic gradient coloring, smoothing options, and a predictive line tool, this script helps you see not just what the current trend is, but how strong it is, and what it would take to reverse it.
Heikin Ashi candles help reduce noise but this script goes further by:
➡️adding color intelligence that shows trend strength using a streak counter
➡️uses smoothing logic to clean up chop and whipsaws
➡️introduces a predictive close line — a subtle but powerful guide for anticipating trend flips before they happen
Everything is configurable: colors, candle sources, overlays, predictive tools, and line styles. It’s built for traders who want visual speed, but don’t want to sacrifice signal quality.
At its core, the script offers two powerful dropdown controls:
💥HA Color Scheme (Colors Regular Candles) — Applies Heikin Ashi-derived coloring to your regular candles based on trend direction or streak strength. This gives you instant visual context without switching to a separate chart type.
💥HA Candle Overlay Mode — Overlays actual Heikin Ashi-style candles directly on top of your chart, using your preferred source:
➡️Custom HA candles using internal formula logic
➡️TradingView’s built-in Heikin Ashi source with your own colors
➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖
🎨 Custom + Gradient HA Coloring🎨
See trend strength at a glance:
➡️1–4 bar streaks → lighter tone
➡️5–8 bars → medium tone
➡️9+ bars → bold tone, ideal for momentum-based entries, exits, or scaling strategies
→ Choose from:
➡️Your own custom color set
➡️A simple 2-color base mode
➡️Or a 3-level gradient for progressive trend analysis (using the streak counter)
🏛️ TradingView Official Heikin Ashi Overlay
Prefer native HA candles but want your own colors?
This mode plots TradingView's Heikin Ashi source, with your personal bullish/bearish color scheme.
➡️Ensures consistency with built-in charts while still leveraging your visual style.
🌊 Smoothed Heikin Ashi Candles — Clarity in Chaos🌊
These aren’t your standard HA candles. Smoothed Heikin Ashi uses a two-step EMA process to transform chaotic price action into a cleaner, slower-moving trend structure:
🔹 First, it smooths the raw OHLC data using EMA — filtering out minor price fluctuations.
🔹 Then, it applies the Heikin Ashi transformation on top of the smoothed data.
🔹 Finally, it applies a second EMA smoothing pass to the HA values — creating ultra-smooth candles.
📈 What You See:
Trends appear more fluid and consistent.
Choppy ranges and fakeouts are visually suppressed.
Minor pullbacks within a trend are de-emphasized, helping you avoid premature exits.
🎯 Best For:
Swing traders looking to stay in positions longer.
Intraday traders dealing with volatile or noisy instruments.
Anyone who wants a "trend map" overlay without the distractions of raw price action.
✅ Reduces whipsaws
✅ Delivers high-contrast trend zones
✅ Makes reversals more visually apparent (but with a slight lag)
📍 Predictive Close Line📍
Shows where the real close must land to flip the current HA candle's color.
✅ Use it like predictive support/resistance
✅ Know if the trend is actually at risk
✅Visualize potential fakeouts or confirmation
Color-coded based on current HA direction (bullish, bearish, or neutral).
📈 Tick by tick & bar-to-bar Plots📈
Provides 2 plot types:
1)1 plot that tracks a bar tick by tick
2)another plot that tracks the close from bar to bar
For the bar to bar plot, you can choose between 2 options:
✅Full Plot — continuous line colored by HA trend
✅Recent Segments — color just the last few bars (configurable) to reduce chart clutter
✅ Customize width, number of bars, and visibility
➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖
📘 How to Use this script📘
Imagine you're watching a choppy 15-minute chart on a volatile crypto pair — price action is messy, and it’s hard to tell if a trend is forming or just noise.
Here’s how to cut through the chaos using Heikin Ashi Overlay Suite:
🔹 Step 1: Enable "Smoothed HA Candles"
Start by turning on the smoothed candles. You’ll immediately notice the noise fades, and broader directional moves become easier to follow. It's like switching from static to clean trend zones.
🧠 Why: Smoothed HA uses a double EMA process that filters out small reversals and lets larger moves stand out. Perfect for sideways or jittery charts.
🔹 Step 2: Watch the Color Gradient Build
As the smoothed candles begin to align in one direction, the gradient coloring (1–4, 5–8, 9+ streaks) gives you an at-a-glance visual of how strong the trend is.
✅ If you see 9+ same-colored candles? You’re likely in a mature trend.
✅ If it resets often? You’re in chop — consider staying out.
🔹 Step 3: Use the Predictive Close Line for Anticipation
Now here’s the edge — this line tells you where the candle would have to close to flip colors.
📉 If price is hovering just above it during a bullish run — momentum may be weakening.
📈 If price bounces off it — the trend may be strengthening.
This is excellent for confirming entries, exits, or spotting early warning signs.
🔹 Step 4: Switch Between Candle Modes as Needed
You can flip between:
✅ Custom HA: Gradient candles with your colors
✅ TradingView HA: The official source with your styling
✅ None: Just color regular candles using the HA logic
Use what fits your style — everything is modular.
🔹 Step 5: Tune It to Your Chart
Lastly, tweak streak thresholds (currently only can do this within the source code), smoothing lengths, and line styles to match your timeframe and strategy.
🎯 Tailor The Settings to Fit Your Trading Style🎯
🔹 🧪 Scalper (1–5 min charts)
If you’re trading fast intraday moves, you want quicker responsiveness and less lag.
Try these settings:
🔸Smoothing Lengths: Use lower values (e.g. len = 3, len2 = 5)
🔸Candle Mode: Use Custom HA or TV’s HA for real-time color flips
🔸Predictive Close Line: Great for ultra-fast anticipation of color reversals
🔸Line Mode: Use Recent Segments mode to track short bursts of trend
🔸Colors: Use high-contrast, opaque colors for clarity
✅ These settings help you catch micro-trends and flip signals faster, while still filtering out the worst of the noise.
🔹 🧪 Swing Trader (30m–4h charts and beyond)
If you’re looking for multi-hour or multi-day trend confirmation, prioritize clarity and staying in moves longer.
Recommended setup:
🔸Smoothing Lengths: Medium to high values (e.g. len = 8, len2 = 21)
🔸Candle Mode: Use Smoothed HA Candles to block out intrabar chop
🔸Gradient Colors: Enable to visualize trend maturity and strength
🔸Predictive Close Line: Helps confirm trend continuation or spot early reversals
🔸Line Mode: Use Full Plot Line for clean HA-based trend tracking
✅ These settings give you a calm, clean view of the bigger picture — ideal for holding positions longer and avoiding early exits.
🔧 This script isn’t just a chart overlay — it’s a visual trend engine.🔧
Ideal For:
🔶 Trend-followers who want clean, color-coded confirmation
🔶 Reversal traders spotting exhaustion via predictive flips
🔶 Scalpers filtering noise with lighter smoothing
🔶 Swing traders using smoothed visuals to hold longer
📌 Final Note
Heikin Ashi Overlay Pro is designed to help you see momentum, trend shifts, and market structure with greater clarity — not to predict price on its own. For best results:
✔️ Combine with support/resistance, moving averages, or price action patterns
✔️ Use Predictive Close as a confirmation tool, not a signal generator
✔️ Pair gradient colors with structure to gauge trend maturity
✔️ Always zoom out and check higher timeframes for context
🧠 Use this as part of a layered approach — not a standalone system.
🙏 Credits🙏
⚡HA logic based on SimpleCryptoLife
⚡Smoothed HA concept adapted from a script by Jackvmk
💡💡💡Turn logic into clarity. Structure into trades. And uncertainty into confidence.💡💡💡
Deadband Hysteresis Supertrend [BackQuant]Deadband Hysteresis Supertrend
A two-stage trend tool that first filters price with a deadband baseline, then runs a Supertrend around that baseline with optional flip hysteresis and ATR-based adverse exits.
What this is
A hybrid of two ideas:
Deadband Hysteresis Baseline that only advances when price pulls far enough from the baseline to matter. This suppresses micro noise and gives you a stable centerline.
Supertrend bands wrapped around that baseline instead of raw price. Flips are further gated by an extra margin so side changes are more deliberate.
The goal is fewer whipsaws in chop and clearer regime identification during trends.
How it works (high level)
Deadband step — compute a per-bar “deadband” size from one of four modes: ATR, Percent of price, Ticks, or Points. If price deviates from the baseline by more than this amount, move the baseline forward by a fraction of the excess. If not, hold the line.
Centered Supertrend — build upper and lower bands around the baseline using ATR and a user factor. Track the usual trailing logic that tightens a band while price moves in its favor.
Flip hysteresis — require price to exceed the active band by an extra flip offset × ATR before switching sides. This adds stickiness at the boundary.
Adverse exit — once a side is taken, trigger an exit if price moves against the entry by K × ATR .
If you would like to check out the filter by itself:
What it plots
DBHF baseline (optional) as a smooth centerline.
DBHF Supertrend as the active trailing band.
Candle coloring by trend side for quick read.
Signal markers 𝕃 and 𝕊 at flips plus ✖ on adverse exits.
Inputs that matter
Price Source — series being filtered. Close is typical. HL2 or HLC3 can be steadier.
Deadband mode — ATR, Percent, Ticks, or Points. This defines the “it’s big enough to matter” zone.
ATR Length / Mult (DBHF) — only used when mode = ATR. Larger values widen the do-nothing zone.
Percent / Ticks / Points — alternatives to ATR; pick what fits your market’s convention.
Enter Mult — scales the deadband you must clear before the baseline moves. Increase to filter more noise.
Response — fraction of the excess applied to baseline movement. Higher responds faster; lower is smoother.
Supertrend ATR Period & Factor — traditional band size controls; higher factor widens and flips less often.
Flip Offset ATR — extra ATR buffer required to flip. Useful in choppy regimes.
Adverse Stop K·ATR — per-trade danger brake that forces an exit if price moves K×ATR against entry.
UI — toggle baseline, supertrend, signals, and bar painting; choose long and short colors.
How to read it
Green regime — candles painted long and the Supertrend running below price. Pullbacks toward the baseline that fail to breach the opposite band often resume higher.
Red regime — candles painted short and the Supertrend running above price. Rallies that cannot reclaim the band may roll over.
Frequent side swaps — reduce sensitivity by increasing Enter Mult, using ATR mode, raising the Supertrend factor, or adding Flip Offset ATR.
Use cases
Bias filter — allow entries only in the direction of the current side. Use your preferred triggers inside that bias.
Trailing logic — treat the active band as a dynamic stop. If the side flips or an adverse K·ATR exit prints, reduce or close exposure.
Regime map — on higher timeframes, the combination baseline + band produces a clean up vs down template for allocation decisions.
Tuning guidance
Fast markets — ATR deadband, modest Enter Mult (0.8–1.2), response 0.2–0.35, Supertrend factor 1.7–2.2, small Flip Offset (0.2–0.5 ATR).
Choppy ranges — widen deadband or raise Enter Mult, lower response, and add more Flip Offset so flips require stronger evidence.
Slow trends — longer ATR periods and higher Supertrend factor to keep you on side longer; use a conservative adverse K.
Included alerts
DBHF ST Long — side flips to long.
DBHF ST Short — side flips to short.
Adverse Exit Long / Short — K·ATR stop triggers against the current side.
Strengths
Deadbanded baseline reduces micro whipsaws before Supertrend logic even begins.
Flip hysteresis adds a second layer of confirmation at the boundary.
Optional adverse ATR stop provides a uniform risk cut across assets and regimes.
Clear visuals and minimal parameters to adjust for symbol behavior.
Putting it together
Think of this tool as two decisions layered into one view. The deadband baseline answers “does this move even count,” then the Supertrend wrapped around that baseline answers “if it counts, which side should I be on and where do I flip.” When both parts agree you tend to stay on the correct side of a trend for longer, and when they disagree you get an early warning that conditions are changing.
When the baseline bends and price cannot reclaim the opposite band , momentum is usually continuing. Pullbacks into the baseline that stall before the far band often resolve in trend.
When the baseline flattens and the bands compress , expect indecision. Use the Flip Offset ATR to avoid reacting to the first feint. Wait for a clean band breach with follow through.
When an adverse K·ATR exit prints while the side has not flipped , treat it as a risk event rather than a full regime change. Many users cut size, re-enter only if the side reasserts, and let the next flip confirm a new trend.
Final thoughts
Deadband Hysteresis Supertrend is best read as a regime lens. The baseline defines your tolerance for noise, the bands define your trailing structure, and the flip offset plus adverse ATR stop define how forgiving or strict you want to be at the boundary. On strong trends it helps you hold through shallow shakeouts. In choppy conditions it encourages patience until price does something meaningful. Start with settings that reflect the cadence of your market, observe how often flips occur, then nudge the deadband and flip offset until the tool spends most of its time describing the move you care about rather than the noise in between.
Simplified Market ForecastSimplified Market Forecast Indicator
This indicator pairs nicely with the Contrarian 100 MA and can be located here:
Overview
The "Simplified Market Forecast" (SMF) indicator is a streamlined technical analysis tool designed for traders to identify potential buy and sell opportunities based on a momentum-based oscillator. By analyzing price movements relative to a defined lookback period, SMF generates clear buy and sell signals when the oscillator crosses customizable threshold levels. This indicator is versatile, suitable for various markets (e.g., forex, stocks, cryptocurrencies), and optimized for daily timeframes, though it can be adapted to other timeframes with proper testing. Its intuitive design and visual cues make it accessible for both novice and experienced traders.
How It Works
The SMF indicator calculates a momentum oscillator based on the price’s position within a specified range over a user-defined lookback period. It then smooths this value to reduce noise and plots the result as a line in a separate lower pane. Buy and sell signals are generated when the smoothed oscillator crosses above a user-defined buy level or below a user-defined sell level, respectively. These signals are visualized as triangles either on the main chart or in the lower pane, with a table displaying the current ticker and oscillator value for quick reference.
Key Components
Momentum Oscillator: The indicator measures the price’s position relative to the highest high and lowest low over a specified period, normalized to a 0–100 scale.
Signal Generation: Buy signals occur when the oscillator crosses above the buy level (default: 15), indicating potential oversold conditions. Sell signals occur when the oscillator crosses below the sell level (default: 85), suggesting potential overbought conditions.
Visual Aids: The indicator includes customizable horizontal lines for buy and sell levels, shaded zones for clarity, and a table showing the ticker and current oscillator value.
Mathematical Concepts
Oscillator Calculation: The indicator uses the following formula to compute the raw oscillator value:
c1I = close - lowest(low, medLen)
c2I = highest(high, medLen) - lowest(low, medLen)
fastK_I = (c1I / c2I) * 100
The result is smoothed using a 5-period Simple Moving Average (SMA) to produce the final oscillator value (inter).
Signal Logic:
A buy signal is triggered when the smoothed oscillator crosses above the buy level (ta.crossover(inter, buyLevel)).
A sell signal is triggered when the smoothed oscillator crosses below the sell level (ta.crossunder(inter, sellLevel)).
Entry and Exit Rules
Buy Signal (Blue Triangle): Triggered when the oscillator crosses above the buy level (default: 15), indicating a potential oversold condition and a buying opportunity. The signal appears as a blue triangle either below the price bar (if plotted on the main chart) or at the bottom of the lower pane.
Sell Signal (White Triangle): Triggered when the oscillator crosses below the sell level (default: 85), indicating a potential overbought condition and a selling opportunity. The signal appears as a white triangle either above the price bar (if plotted on the main chart) or at the top of the lower pane.
Exit Rules: Traders can exit positions when an opposite signal occurs (e.g., exit a buy on a sell signal) or based on additional technical analysis tools (e.g., support/resistance, trendlines). Always apply proper risk management.
Recommended Usage
The SMF indicator is optimized for the daily timeframe but can be adapted to other timeframes (e.g., 1H, 4H) with careful testing. It performs best in markets with clear momentum shifts, such as trending or range-bound conditions. Traders should:
Backtest the indicator on their chosen asset and timeframe to validate signal reliability.
Combine with other indicators (e.g., moving averages, support/resistance) or price action for confirmation.
Adjust the lookback period and buy/sell levels to suit market volatility and trading style.
Customization Options
Intermediate Length: Adjust the lookback period for the oscillator calculation (default: 31 bars).
Buy/Sell Levels: Customize the threshold levels for buy (default: 15) and sell (default: 85) signals.
Colors: Modify the colors of the oscillator line, buy/sell signals, and threshold lines.
Signal Display: Toggle whether signals appear on the main chart or in the lower pane.
Visual Aids: The indicator includes dotted horizontal lines at the buy (green) and sell (red) levels, with shaded zones between 0–buy level (green) and sell level–100 (red) for clarity.
Ticker Table: A table in the top-right corner displays the current ticker and oscillator value (in percentage), with customizable colors.
Why Use This Indicator?
The "Simplified Market Forecast" indicator provides a straightforward, momentum-based approach to identifying potential reversals in overbought or oversold markets. Its clear signals, customizable settings, and visual aids make it easy to integrate into various trading strategies. Whether you’re a swing trader or a day trader, SMF offers a reliable tool to enhance decision-making and improve market timing.
Tips for Users
Test the indicator thoroughly on your chosen asset and timeframe to optimize settings.
Use in conjunction with other technical tools for stronger trade confirmation.
Adjust the buy and sell levels based on market conditions (e.g., lower levels for less volatile markets).
Monitor the ticker table for real-time oscillator values to gauge market momentum.
Happy trading with the Simplified Market Forecast indicator!
ConcatenatedAlertsHi all!
This library is useful if you want to concatenate every tick alert for sending on bar close. The 'alert()' function, provided by Tradingview, with the 'freq' parameter set to 'alert.freq_once_per_bar_close' only fires when the realtime bar closes. So if something has happened intrabar, the alert wont be sent.
This library concatenates all alert messages during the bar and sends them on bar close with a header saying how many messages it contains.
It's useful in many cases, but here are a few examples:
When you want alerts for a zone having a breakout (with a candle close) and another one being entered, like this:
When a candle breaks through 2, or more, lines. Like in this example:
There are of course more useful use cases, but above is 2 examples.
The library uses an own enum saying 'alert.freq_all', 'alert.freq_once_per_bar' and 'alert.freq_once_per_bar_close'. The value of this enumeration represents how often an alert will be sent. 'alert.freq_all' and 'alert.freq_once_per_bar' will behave as the once in the 'alert()' function provided by Tradingview. No concatenatination will take place in this case. However, when 'alert.freq_once_per_bar_close' is set, concatenatination will happen with all alert messages during the bar and sent on bar close. Helper functions can be used for both the string value used by the 'alert()' function by Tradingview and this enum type. Example code is provided in the source code, with the usage of input values for both this string and the enumeration.
Hope this is of help!
Concatenate(a_lert, message)
Concatenates all alert messages (called on every tick) to fire all of them with 'Alert()'.
Parameters:
a_lert (Alert) : The 'Alert' object to be used for the alert messages concatination.
message (string) : The string message to be added to the bar alert.
Alert(a_lert)
When the 'Alert.Frequency' is set to fire on the current tick, this function will concatenate all messages on the current bar and fire an alert. Concatenation will occur if 'alert.freq_once_per_bar_close' is set on 'a_lert.Frequency' separated by new lines and a header saying how many messages the bar contains.
Parameters:
a_lert (Alert) : The 'Alert' object to be used for the alert messages concatination and all its 'Messages' will be alerted.
Create(frequency)
Helper function to create an 'Alert' object.
Parameters:
frequency (series Frequency) : The 'Frequency' in the created 'Alert' object.
Returns: The 'Alert' object that can be used for concatination.
CreateFromAlertFreq(alertFreq)
Helper function to convert 'alert.freq_all', 'alert.freq_once_per_bar' or 'lert.freq_once_per_bar_close'.
Parameters:
alertFreq (string) : The 'alert.freq_all', 'alert.freq_once_per_bar' or 'lert.freq_once_per_bar_close' to convert to 'Frequency' enum.
Returns: The 'Alert' object that can be used for concatination.
Alert
Holds all the values for the 'Alert' to be used.
Fields:
Messages (array) : Holds the alert messages within the current bar that will be sent according to 'Frequency'.
Frequency (series Frequency) : The frequency for the final alert. One of 'alert.freq_all', 'alert.freq_once_per_bar' or 'alert.freq_once_per_bar_close'. If 'alert.freq_all' is set the alert messages will be fired on each tick and no concatination will occure. The same when 'alert.freq_once_per_bar' is set, but the alert will only fire once per bar. If 'alert.freq_once_per_bar_close' is set concatenation will occure before sending an alert (with all concatenated messages) on bar close.
SkipAddition (series bool) : Will skip addition of messages. Used internally if 'Frequency' is 'alert.freq_once_per_bar'.
Andean • Dot Watcher (Exact Math + Optional Alerts)Title: Andean • Dot Watcher (1m + 1000T Alerts)
Description:
The Andean • Dot Watcher is a precision trend-detection tool that plots Bull and Bear “dot” signals for both the 1-minute chart and the 1000-tick chart — all in one indicator. It’s designed for traders who want early confirmation from tick data while also monitoring a traditional time-based chart for added confluence.
Key Features:
Dual-Timeframe Signals – Plots and alerts for both 1m and 1000T chart conditions.
Bull Dots – Green markers indicating bullish dominance or trigger events.
Bear Dots – Red markers indicating bearish dominance or trigger events.
Customizable Dot Mode – Choose between continuous dominance, flip-only signals, or crossover conditions.
Real-Time Alerts – Built-in TradingView alerts for:
1m Bull / 1m Bear signals
1000T Bull / 1000T Bear signals
Alert Flexibility – Users can set alerts for either timeframe independently or combine them for confirmation setups.
Usage Tips:
For fastest reaction, combine 1000T dots with 1-minute dots as a confirmation filter.
If your TradingView plan does not include tick charts, you can still use the 1-minute signals without issue.
Works best when combined with your existing trade plan for entries, exits, and risk management.
Requirements:
1-minute chart signals work on any TradingView plan (including Basic).
1000T tick chart signals require a TradingView plan that supports tick charts.
SMZ Scanner 1H (Fib 0.618–0.786) — stableQuickly spot when your watchlist tickers enter high-probability Smart Money Zones. This scanner checks up to 40 symbols on 1-hour candles, using the 0.618–0.786 Fibonacci retracement of the latest impulse leg (based on swing highs/lows).
What it does:
• Scans your custom list of tickers (up to 40 at once).
• Identifies fresh bullish or bearish impulses.
• Marks when price enters the key Fib retracement zone.
• Sends one clean alert per bar with all tickers that just hit.
Perfect for:
Swing traders and intraday traders tracking Smart Money Zone re-entries without flipping through dozens of charts.
Four Trading SessionsIve adapted this from someone else's script to include 4 sessions instead of 3
TradingView Indicator Description: Trading Sessions
Overview:
The "Trading Sessions" indicator, written in Pine Script v5, visually highlights major forex trading sessions (Tokyo, London, New York, and Sydney) on intraday charts. It displays session ranges as colored boxes, with optional open/close lines, average price lines, and labels showing session names, tick ranges, and average prices. Users can customize session times, time zones, colors, and display options.
Key Features:
Customizable Sessions: Supports up to four trading sessions (Tokyo, London, New York, Sydney) with user-defined names, time ranges, and time zones (e.g., "Asia/Tokyo", "America/New_York").
Visual Elements:
Draws semi-transparent boxes to mark session price ranges (high/low).
Optional dashed lines for session open and close prices.
Optional dotted line for the session's average price.
Labels displaying session name, tick range, and/or average price (configurable).
Time Zone Support: Specify time zones using IANA database names (e.g., "Australia/Sydney") or GMT notation, with a recommendation for IANA to handle daylight savings.
Display Options: Toggle session names, open/close lines, tick range, and average price visibility.
Intraday Restriction: Works only on intraday timeframes, with an error for daily/weekly/monthly charts.
Performance Optimized: Limits boxes, lines, and labels to 500 each to ensure smooth performance.
Inputs:
General Settings:
Show session names, open/close lines, tick range, and average price (all enabled by default).
Per Session (Tokyo, London, New York, Sydney):
Enable/disable session display.
Custom session name (e.g., "Tokyo").
Session time range (e.g., "0900-1500" for Tokyo).
Time zone (e.g., "Asia/Tokyo").
Session color (semi-transparent blue, orange, green, purple by default).
How It Works:
The script checks if the current bar falls within a session’s time range (adjusted for the specified time zone).
For each active session, it creates a box spanning the session’s high/low and updates it bar-by-bar.
Optional open/close lines and an average price line are drawn and updated dynamically.
Labels display user-selected metrics (name, range, average price) at the bottom of each session box.
Sessions reset daily, ensuring accurate representation across days.
Use Case:
Ideal for forex traders who want to analyze price action during specific trading sessions. The indicator helps identify session-specific volatility, key price levels, and trends, with clear visual cues and customizable settings.
Limitations:
Only works on intraday timeframes.
Limited to 500 boxes, lines, and labels to prevent performance issues.
Requires accurate time zone settings for proper session alignment.
Example:
Enable the Tokyo and New York sessions, set their respective time zones, and toggle on all display options to see colored boxes, open/close lines, average price lines, and labels with tick ranges and averages for each session.
[Top] LHAMA Consolidation DetectorIntroducing the Low-High Adaptive Moving Average (LHAMA 🦙), a powerful tool designed to help traders visually distinguish between trending and consolidating market phases. Unlike traditional moving averages that can produce false signals in choppy markets, the LHAMA is engineered to flatten out during periods of consolidation and become more responsive when a clear trend emerges.
This indicator's primary function is to act as a "Consolidation Detector." When the LHAMA line goes flat and adopts its "Flat Color," it serves as a clear visual cue that the market is range-bound. Conversely, when the line begins to slope and changes to its Bullish or Bearish color, it signals a potential breakout or the start of a new trend.
How It Works
The LHAMA is a type of adaptive moving average. Its adaptiveness is derived from a unique calculation that measures market "trendiness." It does this by tracking whether new highs or new lows are being made within a specified lookback period.
In a Trending Market: When the price consistently makes new highs or lows, the indicator's responsiveness increases, causing the LHAMA to track the price much more closely and responsively.
In a Consolidating Market: When the price is range-bound and fails to make new highs or lows, the responsiveness decreases significantly. This causes the LHAMA to flatten out and become less sensitive to minor price fluctuations, effectively filtering out market noise.
Key Features
Adaptive Calculation: The core engine of the indicator, which automatically adjusts its smoothing based on trend strength.
Slope-Based Coloring: The line's color dynamically changes based on its slope, providing an at-a-glance view of market conditions: bullish, bearish, or flat.
Multi-Line & Multi-Timeframe (MTF): You can enable up to six fully customizable LHAMA lines. Each line can be configured with its own length, colors, and can even be set to a different timeframe, allowing for comprehensive multi-timeframe analysis on a single chart.
Volatility Clouds: Each LHAMA can display an optional cloud around it. The cloud's width is based on your choice of either the Average True Range (ATR) or Standard Deviation (StdDev), offering a visual representation of volatility.
Volume Weighting: An option to incorporate volume into the adaptive calculation, making the LHAMA even more responsive during high-volume price movements.
How to Use
Identify Consolidation: The primary use case. A flat and consistently colored LHAMA line is a strong indication of a sideways or consolidating market. This can help traders avoid taking trend-following trades in choppy conditions.
Confirm Trends: When the LHAMA begins to slope upwards or downwards and changes to its trend color, it can be used to confirm the direction and strength of a new trend. The steeper the slope, the stronger the momentum, and more solid the directional color.
Dynamic Support & Resistance: Like other moving averages, the LHAMA can act as a dynamic level of support in an uptrend or resistance in a downtrend. The optional cloud can further define these zones.
Multi-MA Ribbon Strategy: By enabling multiple LHAMAs with different lengths (e.g., Fibonacci sequence like 14, 21, 34, 55), you can create a ribbon. The expansion of the ribbon indicates a strong trend, while its contraction signals a weakening trend or consolidation.
Settings Explained
Enable 🦙 Line: A simple checkbox to turn each of the six LHAMA lines on or off.
Length: The lookback period for the LHAMA calculation. Shorter lengths are more responsive, while longer lengths are smoother.
Timeframe: Set a specific timeframe for each LHAMA. Leave blank to use the chart's current timeframe.
Volume Weight: If checked, adds volume weighting to make the LHAMA more responsive to high-volume moves.
Colors (Bullish, Bearish, Flat): Customize the colors for each market state. To only see the line during consolidation, set the Bullish and Bearish colors to 100% transparency. To hide the line during consolidation, set the Flat color to 100% transparency.
Color Sensitivity: This is a crucial setting. Because price scales (tick sizes) vary widely between symbols, this setting allows you to adjust the sensitivity of the slope detection. A lower value requires a steeper slope to trigger a trend color, while a higher value is more sensitive.
Recommended settings are provided in the input tooltip as a starting point:
$5 Tick: 0.25 Sensitivity
$1 Tick: 0.75 Sensitivity
$0.25 Tick: 3 Sensitivity
$0.01 Tick: 50 Sensitivity
$0.005 Tick: 100 Sensitivity
Cloud Settings:
Show Cloud: Toggles the visibility of the volatility cloud around the LHAMA.
Width Based On: Choose between "ATR" or "StdDev" to calculate the cloud's width.
Cloud Length & Width: Set the lookback period and multiplier for the ATR/StdDev calculation to control the size of the cloud.
IU Engulfing Candlestick PatternDISCRIPTION
📈 The IU Engulfing Candlestick Pattern indicator spotlights both bullish and bearish engulfing formations in real‑time. It shades each pattern with a transparent box and drops a concise label so you can catch potential reversals at a glance—no clutter, no noise, just the candles that matter.
USER INPUTS :
1. Pattern Recognition Based on = “Both” | “Wicks” | “Body” ( Default Both )
• Both → only highlights candles that satisfy **both** wick‑and‑body engulfing rules
• Wicks → checks full candle range (high‑to‑low)
• Body → checks only the real bodies (open‑to‑close)
2. Show Labels ( Default true )
If ticked then it will show the text as "Bullish Engulfing" or "Bearish Engulfing".
3. Show The Box ( Default true)
if ticked then it will show the green or red boxes.
INDICATOR LOGIC:
🔹 Bullish Engulfing (green box)
– Current bar closes higher than it opens and fully “wraps” the prior bar per your chosen rule.
🔹 Bearish Engulfing (red box)
– Current bar closes lower than it opens and fully “wraps” the prior bar per your chosen rule.
🔸 When a pattern confirms:
1. The script records the local high/low range.
2. Draws a semi‑transparent box spanning the engulfing pair.
3. Prints a compact up/down label exactly at the reaction point.
4. Fires a once‑per‑bar alert (“Bullish Engulfing” / “Bearish Engulfing”) you can route to webhooks or notifications.
WHY IT IS UNIQUE:
✨ Combines classic body‑only engulfing with an optional wick filter, letting traders demand stricter confirmation when markets are noisy.
✨ Box overlays visually segment the engulfed range—clearer than single‑bar markers.
✨ Lightweight: one input, zero repaint, and capped at 500 boxes to keep charts responsive.
✨ Ready‑to‑use alerts—no extra code needed for automation.
HOW USER CAN BENIFIT FROM IT :
- Spot early reversal zones or continuation thrusts without scanning candle by candle.
- Pair the alerts with trading bots, TradingView strategy testers, or mobile push notifications.
- Adapt the strictness (Body vs. Wicks vs. Both) to suit different assets, timeframes, or volatility regimes.
- Use the colored range boxes as dynamic support/resistance references for entries, targets, and stop‑loss placement.
📌 Tip: Test on multiple instruments and timeframes to find the sweet spot that matches your risk profile. This script is for educational purposes—always combine with sound risk management and confirm signals with broader market context.
Disclaimer :
This Video is not financial advice, it's for educational purposes only highlighting the power of coding( pine script) in TradingView, I am not a SEBI-registered advisor. Trading and investing involve risk, and you should consult with a qualified financial advisor before making any trading decisions. I do not guarantee profits or take responsibility for any losses you may incur.
TradePlanner ProPlan smarter. Trade with precision.
TradePlanner Pro is a professional-grade overlay tool designed to streamline your trading decisions by visually organizing your trade plans directly on the chart. Built for traders who value preparation and clarity, this script enables precise entry planning, risk management, and target visualization—all tailored per symbol.
Core Purpose
TradePlanner Pro helps you map out potential trades using pre-defined symbol-based presets. It dynamically calculates position sizes based on your account size or fixed risk, then visualizes key trade levels (Entry, Take Profits, Stop Loss) with profit/loss metrics in both dollar and percentage terms. It's the perfect companion for traders who prepare their setups in advance and want their plans clearly represented on the chart.
Key Features
🔹 Per-Symbol Presets: Define entries, up to 3 take-profit levels, and stop-losses for each ticker.
🔹 Dynamic Risk Sizing: Choose between percentage-based risk or fixed dollar risk per trade.
🔹 Visual Trade Mapping: Automatically plots Entry, TP1–TP3, and SL lines on your chart.
🔹 Real-Time P&L Labels: Displays profit/loss amounts and percentages, with optional R/R ratios.
🔹 Custom Investment Display: Shows how much capital is allocated per trade.
🔹 Clean, Configurable UI: Adjust label positions, font sizes, opacity, and label visibility to match your style.
Whether you're swing trading or day trading, TradePlanner Pro helps you stay disciplined, organized, and confident in your execution.
How to Use TradePlanner Pro – Step-by-Step Guide
TradePlanner Pro is designed to be easy to set up while giving you full control over how your trades are visualized and calculated. Here’s how to get started:
1. Start with Default Settings
By default, the script assumes:
Account Size: $10,000
Max Money per Trade (%): 1.0%
Max Risk (USD): 0 (disabled; only percentage risk is used)
This means the script will size each trade to risk 1% of your account balance per trade unless you override it with a fixed USD risk amount.
2. Set Up Your Symbol Presets
The "Symbol Presets" input is a flexible text area where you define trade setups for each ticker.
Format (one per line):
SYMBOL:Entry,TP1 ,SL
Example:
AAPL:250,260,270,240
MSFT:100,110,90
TSLA:180,200,170
You can include 1 to 3 take-profit levels.
The script will only activate for the current chart’s symbol, matching what's listed.
3. Customize Risk Parameters
You can use:
Account % Risk – Based on account size and % risk.
Fixed USD Risk – When a dollar amount is entered (>0), it takes priority and calculates share size based on the risk per share.
There's also an option to round share quantities down to whole units, which is useful for stock or crypto trading platforms that only allow whole-number units.
4. Choose What to Display
Toggle on/off these elements as needed:
Show Entry/TP/SL Lines
Show P&L Labels – Profit/loss amounts at each target and SL.
Show Amount Invested – Includes total dollar value in the quantity label.
Show Percentages – Adds % gain/loss to each label.
Show Risk/Reward Ratios – Optionally displayed beside or below TP labels.
You can further adjust:
Font size and label opacity
Label position offset – In percent of price range, so they don’t overlap the actual levels.
5. Read the Visual Outputs
Once the preset matches the current chart symbol:
Lines will appear for Entry, TP1-TP3, and Stop Loss.
Labels will display your:
Trade quantity (and invested amount)
Dollar and % profit at each target
Total loss at stop loss
Optional R/R ratios
Everything updates dynamically and adjusts to your current chart scale and bar availabilit
LTHB & HTLB Zones with AlertsIn price action trading, the Lowest Tick of the Highest Bar (LTHB) and the Highest Tick of the Lowest Bar (HTLB) are important concepts for support/resistance identification, trend exhaustion, and reversal confirmation. Here's what they mean and why they matter:
🔹 Definitions
1. Lowest Tick of the Highest Bar (LTHB):
The lowest price (tick) of the bar (candlestick) with the highest high in a recent price swing.
Significance: It marks the support inside an upward swing. If price breaks below this, it often indicates loss of upward momentum or reversal.
2. Highest Tick of the Lowest Bar (HTLB):
The highest price of the bar with the lowest low in a swing.
Significance: It acts as a resistance inside a downward swing. If price moves above this, it can signal a bullish reversal.
🔸 Why Are They Significant?
Concept LTHB HTLB
Trend Reversal - Break below LTHB → possible bearish reversal Break above HTLB → possible bullish reversal
Swing Confirmation -Holding above LTHB → continuation of uptrend Holding below HTLB → continuation of downtrend
Trap Detection - Stop hunts often occur just below LTHB Stop hunts often occur just above HTLB
Risk Management -Acts as logical stop-loss in long trades Acts as logical stop-loss in short trades
🔸 Uses in Strategy
1. Breakout Traders use these levels as entry triggers.
2. Reversal Traders look for price failing to hold these levels for early reversal signs.
3. Structure-Based Traders use them to confirm higher highs/lower lows.
4. Stop Placement: Tight stops just beyond LTHB/HTLB help manage risk in swing trades.
🔔 How to Set Alerts in TradingView:
Add the script to your chart.
Open the "⚠️ Alerts" tab.
Click "Create Alert".
In the "Condition" dropdown, select one of:
Enter LTHB Zone
Exit LTHB Zone
Enter HTLB Zone
Exit HTLB Zone
Set desired alert frequency (e.g., once per bar or once).
Click Create.
