LibrarySupertrendLibrary "LibrarySupertrend"
selective_ma(condition, source, length)
Parameters:
condition (bool)
source (float)
length (int)
trendUp(source)
Parameters:
source (float)
smoothrng(source, sampling_period, range_mult)
Parameters:
source (float)
sampling_period (simple int)
range_mult (float)
rngfilt(source, smoothrng)
Parameters:
source (float)
smoothrng (float)
fusion(overallLength, rsiLength, mfiLength, macdLength, cciLength, tsiLength, rviLength, atrLength, adxLength)
Parameters:
overallLength (simple int)
rsiLength (simple int)
mfiLength (simple int)
macdLength (simple int)
cciLength (simple int)
tsiLength (simple int)
rviLength (simple int)
atrLength (simple int)
adxLength (simple int)
zonestrength(amplitude, wavelength)
Parameters:
amplitude (int)
wavelength (simple int)
atr_anysource(source, atr_length)
Parameters:
source (float)
atr_length (simple int)
supertrend_anysource(source, factor, atr_length)
Parameters:
source (float)
factor (float)
atr_length (simple int)
Search in scripts for "supertrend"
AI-Bank-Nifty Tech AnalysisThis code is a TradingView indicator that analyzes the Bank Nifty index of the Indian stock market. It uses various inputs to customize the indicator's appearance and analysis, such as enabling analysis based on the chart's timeframe, detecting bullish and bearish engulfing candles, and setting the table position and style.
The code imports an external script called BankNifty_CSM, which likely contains functions that calculate technical indicators such as the RSI, MACD, VWAP, and more. The code then defines several table cell colors and other styling parameters.
Next, the code defines a table to display the technical analysis of eight bank stocks in the Bank Nifty index. It then defines a function called get_BankComponent_Details that takes a stock symbol as input, requests the stock's OHLCV data, and calculates several technical indicators using the imported CSM_BankNifty functions.
The code also defines two functions called get_EngulfingBullish_Detection and get_EngulfingBearish_Detection to detect bullish and bearish engulfing candles.
Finally, the code calculates the technical analysis for each bank stock using the get_BankComponent_Details function and displays the results in the table. If the engulfing input is enabled, the code also checks for bullish and bearish engulfing candles and displays buy/sell signals accordingly.
The FRAMA stands for "Fractal Adaptive Moving Average," which is a type of moving average that adjusts its smoothing factor based on the fractal dimension of the price data. The fractal dimension reflects self-similarity at different scales. The FRAMA uses this property to adapt to the scale of price movements, capturing short-term and long-term trends while minimizing lag. The FRAMA was developed by John F. Ehlers and is commonly used by traders and analysts in technical analysis to identify trends and generate buy and sell signals. I tried to create this indicator in Pine.
In this context, "RS" stands for "Relative Strength," which is a technical indicator that compares the performance of a particular stock or market sector against a benchmark index.
The "Alligator" is a technical analysis tool that consists of three smoothed moving averages. Introduced by Bill Williams in his book "Trading Chaos," the three lines are called the Jaw, Teeth, and Lips of the Alligator. The Alligator indicator helps traders identify the trend direction and its strength, as well as potential entry and exit points. When the three lines are intertwined or close to each other, it indicates a range-bound market, while a divergence between them indicates a trending market. The position of the price in relation to the Alligator lines can also provide signals, such as a buy signal when the price crosses above the Alligator lines and a sell signal when the price crosses below them.
In addition to these, we have several other commonly used technical indicators, such as MACD, RSI, MFI (Money Flow Index), VWAP, EMA, and Supertrend. I used all the built-in functions for these indicators from TradingView. Thanks to the developer of this TradingView Indicator.
I also created a BankNifty Components Table and checked it on the dashboard.
wbburgin_utilsLibrary "wbburgin_utils"
trendUp(source)
Parameters:
source
smoothrng(source, sampling_period, range_mult)
Parameters:
source
sampling_period
range_mult
rngfilt(source, smoothrng)
Parameters:
source
smoothrng
fusion(overallLength, rsiLength, mfiLength, macdLength, cciLength, tsiLength, rviLength, atrLength, adxLength)
Parameters:
overallLength
rsiLength
mfiLength
macdLength
cciLength
tsiLength
rviLength
atrLength
adxLength
zonestrength(amplitude, wavelength)
Parameters:
amplitude
wavelength
atr_anysource(source, atr_length)
Parameters:
source
atr_length
supertrend_anysource(source, factor, atr_length)
Parameters:
source
factor
atr_length
Open Interest Delta with MAs[Binance Perpetuals]!!!!! This indicator only shows Binance Perpetuals Open Interest Delta !!!!!
!!!!! When Binance Spot pair charts is selected, It still shows the perpetual contract Open Interest, if the pair on the chart is tradeble on perpetual contracts. I assume you know what Open Interest is. !!!!!
ZLEMA , Tillson, VAR MAs codes are coming from @KivancOzbilgic => SuperTrended Moving Averages
KAMA code is coming from @HPOTTER => Kaufman Moving Average Adaptive ( KAMA )
Open Interest with Bollinger Bands and some moving averages!!! This indicator only shows Binance Perpetuals Open Interest !!!
!!!!! When Binance Spot pair charts is selected, It still shows the perpetual contract Open Interest, if the pair on the chart is tradeble on perpetual contracts. I assume you know what Open Interest is. !!!!!
ZLEMA, Tillson, VAR MAs codes are coming from @KivancOzbilgic => SuperTrended Moving Averages
Golden Swing Strategy - Souradeep DeyThis strategy is developed by Mr. Souradeep Dey. Strategy is based on RSI, Stoch, BB & Supertrend.
Coding by Rajkumar
Bollinger Bands Strategy (MA type)The types of moving averages that Mr. Kıvanç Özbilgiç uses in his indicators and especially the "MACD Reloaded" and "SuperTrended Moving Averages" indicators gave me an idea.
Better results can be obtained in different time frames by increasing the range of Moving averages used in Bollinger Bands.
It is a trial and educational work only.
Indicators OverviewThis Indicator help you to see whether the price is above or below vwap, supertrend. Also you can see realtime RSI value.
You can add upto 15 stock of your choice.
HiLo IndicatorNYSE:SPCE
This is an old and simple concept of mine that I am revisiting. It looks similar to the Vortex Indicator but the formulation is different. I was sick and tired of buying late at the top of the peaks, so I wanted to relate the current price to historic highs and lows (you can change how far you want to go back Time Length = tl). The functions are incredible simple:
lo = close -lowest(close,tl)
hi = highest(close,tl) -close
This generates a weaving pattern that shows bullish (lo>hi) and bearish (lo
MTC – Multi-Timeframe Trend ConfirmatorMTC – Multi-Timeframe Trend Confirmator
The Ultimate Multi-Timeframe Trend Analysis Tool
MTC v6 is a comprehensive trend confirmation indicator that analyzes market conditions across multiple timeframes simultaneously. It combines six powerful technical indicators to give you a clear, visual representation of trend strength and direction.
🎯 Key Features
Visual Trend Gauge
Real-time trend strength display for 3 customizable timeframes
Progressive bar visualization (fills from left to right)
Color-coded signals: 🟢 Green (Bullish) | 🔴 Red (Bearish) | 🟡 Yellow (Ranging)
Score range: -10 to +10 for precise trend measurement
Multi-Indicator Analysis
The indicator combines 6 proven technical tools:
EMA 200 – Long-term trend direction
SMA 50/200 – Golden/Death cross signals
RSI 14 – Momentum confirmation
MACD – Trend strength validation
ADX (>25) – Trend intensity measurement (2x weight)
Supertrend – Dynamic support/resistance (2x weight)
⚙️ Customization Options
Flexible Timeframes: Set any timeframes you prefer (default: 15M, 1H, 4H)
Adjustable Gauge Size: Small, Medium, or Large display
Toggle Indicators: Enable/disable any of the 6 technical indicators
Supertrend Settings: Customize factor and ATR period
Built-in Alerts: Get notified when trends confirm
📈 How to Use
Score Interpretation:
Score > +2 = Bullish trend
Score < -2 = Bearish trend
Score between -2 and +2 = Ranging/Neutral
Multi-Timeframe Confirmation:
Look for alignment across timeframes for strongest signals
Higher timeframes confirm the overall trend direction
Lower timeframes help with precise entry timing
Visual Background:
Green background = Confirmed uptrend (Higher + Mid TF aligned)
Red background = Confirmed downtrend (Higher + Mid TF aligned)
💡 Perfect For
Swing traders seeking trend confirmation
Day traders analyzing multiple timeframes
Position traders validating long-term trends
Anyone who wants clear, visual trend analysis
Trade with confidence. Trade with confirmation. Trade with MTC
-Natantia
DAMMU AUTOMATICAL AI ENRTY AND TARGET AND EXITMain Components
Supertrend System –
Detects market trend direction (Buy/Sell zones).
→ Green = Uptrend (Buy)
→ Red = Downtrend (Sell)
SMA Filter –
Uses 50 & 200 moving averages to confirm overall trend.
→ Price above both → Bullish
→ Price below both → Bearish
Buy/Sell Signals –
Generated when Supertrend flips direction and SMA confirms.
→ Triangle up = Buy
→ Triangle down = Sell
Take Profit / Stop Loss Levels –
Automatically calculated after Buy/Sell entry.
→ TP1, TP2, SL shown on chart
ADX (Sideways Zone Filter) –
If ADX < 25 → Market sideways → Avoid trades
Shows “No Trade Zone” area
Smart Money Concepts (SMC) Tools –
🔹 Market structure (HH, HL, LH, LL)
🔹 Order blocks (OB)
🔹 Equal highs/lows
🔹 Fair Value Gaps (FVG)
🔹 Premium & Discount zones
Helps find institutional entry points
Visual Display –
Color-coded background (trend zones)
Labels for buy/sell/structure
Optional FVG and order block boxes
Risk Management –
Input-based position sizing, SL & TP management
(to calculate profit levels and minimize loss)
MTF Intraday v2.0📊 Description
MTF Intraday v2.0 is an informative indicator for analyzing trend strength across multiple timeframes simultaneously. Designed specifically for intraday (session) trading during European and US market hours.
The indicator shows the real market picture without lagging signals - you see the trend strength right now for each timeframe.
🎯 Key Features
1. Multi-Timeframe Analysis (D1, H4, H1, M30, M15)
Analyzes 4 indicators on each TF: SuperTrend, RSI, EMA crossover, EMA200
Shows strength for each timeframe: STRONG / MED / WEAK
Color indication: 🟢 green (LONG strong), 🔴 red (SHORT strong), 🟡 yellow (medium), ⚪ gray (weak)
2. Intraday Trading Hierarchy
D1 - global context (affects quality assessment)
H4 - general (sets the main trend)
H1 - reference point for intraday
M30/M15 - finding entry points during sessions
3. Market Pulse
🔥 HOT - when both H4 and H1 are STRONG (best time to enter!)
✓ GOOD - when H4 or H1 is STRONG
L:45 S:20 - balance of power between LONG and SHORT (statistics instead of "wait")
4. Volume Indicator (24 hours)
Shows volume change over the last 24 hours
SPIKE! - when volume increased by the set % (default 50%)
Considers candle color: 🟢 LONG spike (rise + green candle), 🔴 SHORT spike (rise + red candle)
Works on any timeframe (automatically recalculates)
5. Compact Mode
OFF - shows all details: every indicator for each TF
ON - only strength per timeframe (for clean chart)
⚙️ Settings
Main:
SuperTrend Period (21) / Multiplier (6.3)
RSI Length (14)
EMA Short (50) / Long (100) / 200
Compact Mode - hide detailed indicators
Volume:
Show Volume - show/hide volume indicator
Volume Alerts ON/OFF - enable/disable volume alerts
Volume Spike (%) - spike threshold (30% / 50% / 100%)
🔔 Alerts
The indicator has 5 types of alerts:
Market HOT - H4 and H1 simultaneously became STRONG
VOL LONG - volume spike on bullish candle
VOL SHORT - volume spike on bearish candle
EMA200 UP - price crossed EMA200 upward
EMA200 DN - price crossed EMA200 downward
Set up in TradingView: Create Alert → Select desired alert from the list
📈 How to Use
For finding entry points:
Check H4 - should be at least MED (better STRONG)
Verify H1 - main filter for intraday
Wait for pulse "🔥 HOT" or at least "✓ GOOD"
Look at M30/M15 - seek confirmation
Check 24h VOL - if SPIKE, momentum has started
Quality Assessment:
EXCELLENT ⭐ - all stars aligned (D1 with us, high score)
GOOD - good setup
WARNING ⚠️ - D1 against trend (counter-trend, be careful!)
Color Indication:
🟢 Green cells - bullish signal
🔴 Red cells - bearish signal
🟡 Yellow cells - neutral/waiting
🟠 Orange TF labels - for readability
⚠️ Important
This is an informative indicator, not a trading system
Does not give "entry/exit" signals - shows trend strength in the moment
Use together with Price Action and your trading strategy
RSI on M15 is displayed but not counted (too much noise)
💡 Who is it for
✅ Intraday traders (Europe/US sessions)
✅ Scalpers on crypto and forex
✅ Swing traders for trend confirmation
✅ Those who trade on multiple timeframes simultaneously
my_strategy_2.0Overview:
This is a high-speed scalping strategy optimized for volatile crypto assets (BTC, ETH, etc.) on timeframes 1m–5m. It combines trend-following SuperTrend with confirmations from MACD, RSI, Bollinger Bands, and volume spikes for precise entries. Focus on quick profits (1–3 ATR) with strict risk control: partial take-profits, stop-loss, and trailing breakeven after the first TP.
Key Signals:
Long: SuperTrend flip up + MACD crossover up + RSI >50 + BB Upper breakout + volume spike + volatility filter (ATR >0.5%).
Short: Similar but downward.
Exits and Risks:
TP: 33% at +1 ATR, 33% at +2 ATR, 34% at +3 ATR (customizable).
SL: Initial at -1 ATR, after TP1 — to breakeven with trailing on BB midline (optional).
Filters: Minimum ATR to avoid flat markets; realistic commissions in backtests.
Recommendations:
Test on 2020–2025 data (out-of-sample 2024+). Expected Win Rate ~55%, Profit Factor >1.8, Drawdown <10%. Ideal for 1–2% risk per trade. Not for beginners — use paper trading.
Disclaimer: Past results do not guarantee future performance. Trade at your own risk.
(Pine v6 code, ready for publication. Author: gopog777 with expert fixes.)
Confluence Engine Confluence Engine is a practical, non-repainting decision aid that scores market conditions from −100…+100 by combining six proven modules: Trend, Momentum, Volatility, Volume, Structure, and an HTF confirmation. It’s designed for crypto, forex, indices, and stocks, and it fires entries only on confirmed bar closes.
What’s inside
Trend: EMA 20/50/200 alignment plus a Supertrend/KAMA toggle (you choose the baseline).
Momentum: RSI + MACD with confirmed-pivot divergence detection.
Volatility: ATR% and Bollinger Band width vs its average to favor expansion over chop.
Volume: OBV-style cumulative flow slope + volume surge vs SMA×multiplier.
Market Structure: Confirmed pivots, BOS (break of structure) and CHOCH (change of character).
HTF Filter: Closed higher-timeframe context via request.security(..., barmerge.gaps_on, barmerge.lookahead_off).
Why it does not repaint
Signals are computed and plotted on closed bars only.
Pivots/divergences use confirmed pivot points (no forward look).
HTF series are fetched with lookahead_off and use the last closed HTF bar in realtime.
No future bar references are used for entries or alerts.
How to use (3 steps)
Pick a timeframe pair: use a 4–6× HTF multiplier (5m→30m, 15m→1h, 1h→4h, 4h→1D, 1D→1W).
Trade with the HTF: take longs only when the HTF filter is bullish; shorts only when bearish.
Prefer expansion: act when BB width > its average and ATR% is elevated; skip most signals in compression.
Suggested presets (start here)
Crypto (BTC/ETH): 15m→1h, 1h→4h. stLen=10, stMult=3.0, bbLen=20, surgeMul=1.8–2.2, thresholds +40 / −40 (intraday can try +35 / −35).
Forex majors: 15m→1h, 1h→4h. stLen=10–14, stMult=2.5–3.0, surgeMul=1.5–1.8, thresholds +35 / −35 (swing: +45 / −45).
US equities (liquid): 5m→30m/1h, 15m→1h/2h. stMult=3.0–3.5, surgeMul=1.6–2.0, thresholds +45 / −45 to reduce chop.
Indices (ES/NQ): 5m→30m, 15m→1h. Defaults are fine; start at +40 / −40.
Gold/Oil: 15m→1h, 1h→4h. Thresholds +35 / −35, surgeMul=1.6–1.9.
Inputs (plain English)
Use Supertrend (off = KAMA): choose the trend baseline.
EMA Fast/Mid/Slow: 20/50/200 by default for classic stack.
RSI/MACD + divergence pivots: momentum and exhaustion context.
ATR Length & BB Length: volatility regime detection.
Volume SMA & Surge Multiplier: defines “meaningful” volume spikes.
Pivot left/right & “Confirm BOS/CHOCH on Close”: structure strictness.
Enable HTF & Higher Timeframe: confirms the lower timeframe direction.
Thresholds (+long / −short): when the score crosses these, you get signals.
Signals & alerts (IDs preserved)
Entry shapes plot at bar close when the score crosses thresholds.
Alerts you can enable:
CONFLUENCE LONG — long entry signal
CONFLUENCE SHORT — short entry signal
BULLISH BIAS — score turned positive
BEARISH BIAS — score turned negative
Best practices
Focus on signals with HTF agreement and volatility expansion; require volume participation (surge or rising OBV slope) for higher quality.
Raise thresholds (+45/−45 or +50/−50) to reduce whipsaws in choppy sessions.
Lower thresholds (+35/−35) only if you also require volatility/volume filters.
Performance & scope
Works across crypto/FX/equities/indices; no broker data or special feeds required.
No repainting by design; signals/alerts are computed on closed bars.
As with any tool, results vary by regime; always combine with risk management.
Disclosure
This script is for educational purposes only and is not financial advice. Trading involves risk. Test on historical data and paper trade before using live.
Trend Band Oscillator📌 Trend Band Oscillator
📄 Description
Trend Band Oscillator is a momentum-based trend indicator that calculates the spread between two EMAs and overlays it with a volatility filter using a standard deviation band. It helps traders visualize not only the trend direction but also the strength and stability of the trend.
📌 Features
🔹 EMA Spread Calculation: Measures the difference between a fast and slow EMA to quantify short-term vs mid-term trend dynamics.
🔹 Volatility Band Overlay: Applies an EMA of standard deviation to the spread to filter noise and highlight valid momentum shifts.
🔹 Color-Based Visualization: Positive spread values are shown in lime (bullish), negative values in fuchsia (bearish) for quick directional insight.
🔹 Upper/Lower Bands: Help detect potential overbought/oversold conditions or strong trend continuation.
🔹 Zero Line Reference: A horizontal baseline at zero helps identify trend reversals and neutral zones.
🛠️ How to Use
✅ Spread > 0: Indicates a bullish trend. Consider maintaining or entering long positions.
✅ Spread < 0: Indicates a bearish trend. Consider maintaining or entering short positions.
⚠️ Spread exceeds bands: May signal overextension or strong momentum; consider using with additional confirmation indicators.
🔄 Band convergence: Suggests weakening trend and potential transition to a ranging market.
Recommended timeframes: 1H, 4H, Daily
Suggested complementary indicators: RSI, MACD, OBV, SuperTrend
✅ TradingView House Rules Compliance
This script is open-source and published under Pine Script v5.
It does not repaint, spam alerts, or cause performance issues.
It is designed as an analytical aid only and should not be considered financial advice.
All calculations are transparent, and no external data sources or insecure functions are used.
====================================================================
📌 Trend Band Oscillator
📄 설명 (Description)
Trend Band Oscillator는 두 개의 EMA 간 스프레드(차이)를 기반으로 한 모멘텀 중심의 추세 오실레이터입니다. 여기에 표준편차 기반의 변동성 밴드를 적용하여, 추세의 방향뿐 아니라 강도와 안정성까지 시각적으로 분석할 수 있도록 설계되었습니다.
📌 주요 특징 (Features)
🔹 EMA 기반 스프레드 계산: Fast EMA와 Slow EMA의 차이를 활용해 시장 추세를 정량적으로 표현합니다.
🔹 표준편차 필터링: Spread에 대해 EMA 및 표준편차 기반의 밴드를 적용해 노이즈를 줄이고 유효한 추세를 강조합니다.
🔹 컬러 기반 시각화: 오실레이터 값이 양수일 경우 초록색, 음수일 경우 마젠타 색으로 추세 방향을 직관적으로 파악할 수 있습니다.
🔹 밴드 범위 시각화: 상·하위 밴드를 통해 스프레드의 평균 편차 범위를 보여주며, 추세의 강약과 포화 여부를 진단할 수 있습니다.
🔹 제로 라인 표시: 추세 전환 가능 지점을 시각적으로 확인할 수 있도록 중심선(0선)을 제공합니다.
🛠️ 사용법 (How to Use)
✅ 오실레이터가 0 이상 유지: 상승 추세 구간이며, 롱 포지션 유지 또는 진입 검토
✅ 오실레이터가 0 이하 유지: 하락 추세 구간이며, 숏 포지션 유지 또는 진입 검토
⚠️ 상·하위 밴드를 이탈: 일시적인 과매수/과매도 혹은 강한 추세 발현 가능성 있음 → 다른 보조지표와 함께 필터링 권장
🔄 밴드 수렴: 추세가 약해지고 있음을 나타냄 → 변동성 하락 또는 방향성 상실 가능성 있음
권장 적용 시간대: 1시간봉, 4시간봉, 일봉
보조 적용 지표: RSI, MACD, OBV, SuperTrend 등과 함께 사용 시 신호 필터링에 유리
✅ 트레이딩뷰 하우스룰 준수사항 (TV House Rules Compliance)
이 지표는 **무료 공개용(Open-Source)**이며, Pine Script Version 5로 작성되어 있습니다.
과도한 리페인트, 비정상적 반복 경고(alert spam), 실시간 성능 저하 등의 요소는 포함되어 있지 않습니다.
사용자는 본 지표를 투자 결정의 참고용 보조 도구로 활용해야 하며, 독립적인 매매 판단이 필요합니다.
데이터 소스 및 계산 방식은 완전히 공개되어 있으며, 외부 API나 보안 취약점을 유발하는 구성 요소는 없습니다.
Strategy Builder With IndicatorsThis strategy script is designed for traders who enjoy building systems using multiple indicators.
Please note: This script does not include any built-in indicators. Instead, it works by referencing the plot outputs of the indicators you’ve already added to your chart.
For example, if you add a MACD and an ATR indicator to your chart, you can assign their plot values as inputs in the settings panel of this strategy.
• MACD as a trigger
• ATR as a filter
How Filters Work
Filters check whether certain conditions are met before a trade can be opened. For instance, if you set a filter like ATR > 30, then no trade will be executed unless that condition is true — even if the trigger fires.
All filters are linked, meaning every active filter must be satisfied for a trade to occur.
How Triggers Work
Triggers are what actually fire a trade signal — such as a moving average crossover or RSI breaking above a specific level. Unlike filters, triggers are independent. Only one active trigger needs to be true for the trade to execute.
Thanks to its modular structure, this strategy can be used with any indicator of your choice.
⸻
Risk Management Features
In the settings, you’ll find flexible options for:
• Stop Loss (SL)
• Trailing Stop Loss (TSL)
• Multi Take-Profit (TP)
These features enhance trade safety and let you tailor your risk management.
SL types available:
• Tick-based SL
• Percent-based SL
• ATR-based SL
Once you select your preferred SL type, you can fine-tune its distance using the offset field.
Trailing SL allows your stop to follow price as it moves in your favor — helping to lock in profits.
Multi-TP lets you take profits at two different levels, helping you secure gains while leaving room for extended moves.
Breakeven option is also available to automatically move your SL to entry after reaching a profit threshold.
⸻
How to Build a Solid Strategy
Let’s break down a good setup into three key components:
1. Trend Filter
Avoid trading against the trend — that’s like swimming against the current.
Use a filter like:
• Supertrend
• Momentum indicators
• Candlestick bias, etc.
Example: In this case, I used Supertrend and filtered for trades only if the price is above the uptrend line.
2. Trigger Condition
Once we confirm the trend is on our side, we need a trigger to execute at the right moment. This can be:
• RSI cross
• Candlestick patterns
• Trendline breaks
• Moving average crossovers, etc.
Example: I used RSI crossing above 50 as the entry trigger.
3. Risk Management
Even in the right trend at the right time — anything can happen. That’s why you should always define Stop Loss and Take Profit levels.
⸻
And there you have it! Your strategy is ready to backtest, refine, and deploy with alerts for live trading.
Questions or suggestions? Feel free to reach out
KTUtilsLibrary "KTUtils"
Utility functions for technical analysis indicators, trend detection, and volatility confirmation.
MGz(close, length)
MGz
@description Moving average smoother used for signal processing
Parameters:
close (float) : float Price input (typically close)
length (int) : int Length of smoothing period
Returns: float Smoothed value
atrConf(length)
atrConf
@description Calculates Average True Range (ATR) for volatility confirmation
Parameters:
length (simple int) : int Length for ATR calculation
Returns: float ATR value
f(input)
f
@description Simple Moving Average with fixed length
Parameters:
input (float) : float Input value
Returns: float Smoothed average
bcwSMA(s, l, m)
bcwSMA
@description Custom smoothing function with weight multiplier
Parameters:
s (float) : float Signal value
l (int) : int Length of smoothing
m (int) : int Weighting multiplier
Returns: float Smoothed output
MGxx(close, length)
MGxx
@description Custom Weighted Moving Average (WMA) variant
Parameters:
close (float) : float Price input
length (int) : int Period length
Returns: float MGxx smoothed output
_PerChange(lengthTime)
_PerChange
@description Measures percentage price change over a period and range deviation
Parameters:
lengthTime (int) : int Period for change measurement
Returns: tuple Measured change, high deviation, low deviation
dirmov(len)
dirmov
@description Calculates directional movement components
Parameters:
len (simple int) : int Lookback period
Returns: tuple Plus and Minus DI values
adx(dilen, adxlen)
adx
@description Calculates Average Directional Index (ADX)
Parameters:
dilen (simple int) : int Length for DI calculation
adxlen (simple int) : int Length for ADX smoothing
Returns: float ADX value
trChopAnalysis()
trChopAnalysis
@description Identifies chop and trend phases based on True Range Bollinger Bands
Returns: tuple TR SMA, chop state, trending state
wtiAnalysis(haclose, close, filterValue)
wtiAnalysis
@description Wave Trend Indicator (WTI) with signal crossover logic
Parameters:
haclose (float) : float Heikin-Ashi close
close (float) : float Standard close
filterValue (simple int) : int Smoothing length
Returns: tuple WTI lines and direction states
basicTrend(hahigh, halow, close, open, filterValue)
basicTrend
@description Determines trend direction based on HA high/low and close
Parameters:
hahigh (float) : float Heikin-Ashi high
halow (float) : float Heikin-Ashi low
close (float) : float Standard close
open (float) : float Standard open
filterValue (simple int) : int Smoothing period
Returns: tuple Uptrend, downtrend flags
metrics(close, filterValue)
metrics
@description Common market metrics
Parameters:
close (float) : float Price input
filterValue (int) : int RSI smoothing length
Returns: tuple VWMA, SMA10, RSI, smoothed RSI
piff(close, trend_change)
piff
@description Price-Informed Forward Forecasting (PIFF) model for trend strength
Parameters:
close (float) : float Price input
trend_change (float) : float Change in trend
Returns: tuple Percent change, flags for trend direction
getMACD()
getMACD
@description Returns MACD, signal line, and histogram
Returns: tuple MACD line, Signal line, Histogram
getStoch()
getStoch
@description Returns K and D lines of Stochastic Oscillator
Returns: tuple K and D lines
getKDJ()
getKDJ
@description KDJ momentum oscillator
Returns: tuple K, D, J, Average
getBBRatio()
getBBRatio
@description Bollinger Band Ratio (BBR) and signal flags
Returns: tuple Basis, Upper, Lower, BBR, BBR Up, BBR Down
getSupertrend()
getSupertrend
@description Supertrend values and direction flags
Returns: tuple Supertrend, Direction, Up, Down
Exponential Trend [AlgoAlpha]OVERVIEW
This script plots an adaptive exponential trend system that initiates from a dynamic anchor and accelerates based on time and direction. Unlike standard moving averages or trailing stops, the trend line here doesn't follow price directly—it expands exponentially from a pivot determined by a modified Supertrend logic. The result is a non-linear trend curve that starts at a specific price level and accelerates outward, allowing traders to visually assess trend strength, persistence, and early-stage reversal points through both base and volatility-adjusted extensions.
CONCEPTS
This indicator builds on the idea that trend-following tools often need dynamic, non-static expansion to reflect real market behavior. It uses a simplified Supertrend mechanism to define directional context and anchor levels, then applies an exponential growth function to simulate trend acceleration over time. The exponential growth is unidirectional and resets only when the direction flips, preserving trend memory. This method helps avoid whipsaws and adds time-weighted confirmation to trends. A volatility buffer—derived from ATR and modifiable by a width multiplier—adds a second layer to indicate zones of risk around the main trend path.
FEATURES
Exponential Trend Logic : Once a directional anchor is set, the base trend line accelerates using an exponential formula tied to elapsed bars, making the trend stronger the longer it persists.
Volatility-Adjusted Extension : A secondary band is plotted above or below the base trend line, widened by ATR to visualize volatility zones, act as soft stop regions or as a better entry point (Dynamic Support/Resistance).
Color-Coded Visualization : Clear green/red base and extension lines with shaded fills indicate trend direction and confidence levels.
Signal Markers & Alerts : Triangle markers indicate confirmed trend reversals. Built-in alerts notify users of bullish or bearish direction changes in real-time.
USAGE
Use this script to identify strong trends early, visually measure their momentum over time, and determine safe areas for entries or exits. Start by adjusting the *Exponential Rate* to control how quickly the trend expands—the higher the rate, the more aggressive the curve. The *Initial Distance* sets how far the anchor band is placed from price initially, helping filter out noise. Increase the *Width Multiplier* to widen the volatility zone for more conservative entries or exits. When the price crosses above or below the base line, a new trend is assumed and the exponential projection restarts from the new anchor. The base trend and its extension both shift over time, but only reset on a confirmed reversal. This makes the tool especially useful for momentum continuation setups or trailing stop logic in trending markets.
Strategy Stats [presentTrading]Hello! it's another weekend. This tool is a strategy performance analysis tool. Looking at the TradingView community, it seems few creators focus on this aspect. I've intentionally created a shared version. Welcome to share your idea or question on this.
█ Introduction and How it is Different
Strategy Stats is a comprehensive performance analytics framework designed specifically for trading strategies. Unlike standard strategy backtesting tools that simply show cumulative profits, this analytics suite provides real-time, multi-timeframe statistical analysis of your trading performance.
Multi-timeframe analysis: Automatically tracks performance metrics across the most recent time periods (last 7 days, 30 days, 90 days, 1 year, and 4 years)
Advanced statistical measures: Goes beyond basic metrics to include Information Coefficient (IC) and Sortino Ratio
Real-time feedback: Updates performance statistics with each new trade
Visual analytics: Color-coded performance table provides instant visual feedback on strategy health
Integrated risk management: Implements sophisticated take profit mechanisms with 3-step ATR and percentage-based exits
BTCUSD Performance
The table in the upper right corner is a comprehensive performance dashboard showing trading strategy statistics.
Note: While this presentation uses Vegas SuperTrend as the underlying strategy, this is merely an example. The Stats framework can be applied to any trading strategy. The Vegas SuperTrend implementation is included solely to demonstrate how the analytics module integrates with a trading strategy.
⚠️ Timeframe Limitations
Important: TradingView's backtesting engine has a maximum storage limit of 10,000 bars. When using this strategy stats framework on smaller timeframes such as 1-hour or 2-hour charts, you may encounter errors if your backtesting period is too long.
Recommended Timeframe Usage:
Ideal for: 4H, 6H, 8H, Daily charts and above
May cause errors on: 1H, 2H charts spanning multiple years
Not recommended for: Timeframes below 1H with long history
█ Strategy, How it Works: Detailed Explanation
The Strategy Stats framework consists of three primary components: statistical data collection, performance analysis, and visualization.
🔶 Statistical Data Collection
The system maintains several critical data arrays:
equityHistory: Tracks equity curve over time
tradeHistory: Records profit/loss of each trade
predictionSignals: Stores trade direction signals (1 for long, -1 for short)
actualReturns: Records corresponding actual returns from each trade
For each closed trade, the system captures:
float tradePnL = strategy.closedtrades.profit(tradeIndex)
float tradeReturn = strategy.closedtrades.profit_percent(tradeIndex)
int tradeType = entryPrice < exitPrice ? 1 : -1 // Direction
🔶 Performance Metrics Calculation
The framework calculates several key performance metrics:
Information Coefficient (IC):
The correlation between prediction signals and actual returns, measuring forecast skill.
IC = Correlation(predictionSignals, actualReturns)
Where Correlation is the Pearson correlation coefficient:
Correlation(X,Y) = (nΣXY - ΣXY) / √
Sortino Ratio:
Measures risk-adjusted return focusing only on downside risk:
Sortino = (Avg_Return - Risk_Free_Rate) / Downside_Deviation
Where Downside Deviation is:
Downside_Deviation = √
R_i represents individual returns, T is the target return (typically the risk-free rate), and n is the number of observations.
Maximum Drawdown:
Tracks the largest percentage drop from peak to trough:
DD = (Peak_Equity - Trough_Equity) / Peak_Equity * 100
🔶 Time Period Calculation
The system automatically determines the appropriate number of bars to analyze for each timeframe based on the current chart timeframe:
bars_7d = math.max(1, math.round(7 * barsPerDay))
bars_30d = math.max(1, math.round(30 * barsPerDay))
bars_90d = math.max(1, math.round(90 * barsPerDay))
bars_365d = math.max(1, math.round(365 * barsPerDay))
bars_4y = math.max(1, math.round(365 * 4 * barsPerDay))
Where barsPerDay is calculated based on the chart timeframe:
barsPerDay = timeframe.isintraday ?
24 * 60 / math.max(1, (timeframe.in_seconds() / 60)) :
timeframe.isdaily ? 1 :
timeframe.isweekly ? 1/7 :
timeframe.ismonthly ? 1/30 : 0.01
🔶 Visual Representation
The system presents performance data in a color-coded table with intuitive visual indicators:
Green: Excellent performance
Lime: Good performance
Gray: Neutral performance
Orange: Mediocre performance
Red: Poor performance
█ Trade Direction
The Strategy Stats framework supports three trading directions:
Long Only: Only takes long positions when entry conditions are met
Short Only: Only takes short positions when entry conditions are met
Both: Takes both long and short positions depending on market conditions
█ Usage
To effectively use the Strategy Stats framework:
Apply to existing strategies: Add the performance tracking code to any strategy to gain advanced analytics
Monitor multiple timeframes: Use the multi-timeframe analysis to identify performance trends
Evaluate strategy health: Review IC and Sortino ratios to assess predictive power and risk-adjusted returns
Optimize parameters: Use performance data to refine strategy parameters
Compare strategies: Apply the framework to multiple strategies to identify the most effective approach
For best results, allow the strategy to generate sufficient trade history for meaningful statistical analysis (at least 20-30 trades).
█ Default Settings
The default settings have been carefully calibrated for cryptocurrency markets:
Performance Tracking:
Time periods: 7D, 30D, 90D, 1Y, 4Y
Statistical measures: Return, Win%, MaxDD, IC, Sortino Ratio
IC color thresholds: >0.3 (green), >0.1 (lime), <-0.1 (orange), <-0.3 (red)
Sortino color thresholds: >1.0 (green), >0.5 (lime), <0 (red)
Multi-Step Take Profit:
ATR multipliers: 2.618, 5.0, 10.0
Percentage levels: 3%, 8%, 17%
Short multiplier: 1.5x (makes short take profits more aggressive)
Stop loss: 20%
AI Trend Momentum SniperThe AI Trend Momentum Sniper is a powerful technical analysis tool designed for day trading. This strategy combines multiple momentum and trend indicators to identify high-probability entry and exit points. The indicator utilizes a combination of Supertrend, MACD, RSI, ATR (Average True Range), and On-Balance Volume (OBV) to generate real-time signals for buy and sell opportunities.
Key Features:
Supertrend for detecting market direction (bullish or bearish).
MACD for momentum confirmation, highlighting changes in market momentum.
RSI to filter out overbought/oversold conditions and ensure high-quality trades.
ATR as a volatility filter to adjust for changing market conditions.
OBV (On-Balance Volume) to confirm volume strength and trend validity.
Dynamic Stop-Loss & Take-Profit based on ATR to manage risk and lock profits.
This indicator is tailored for intraday traders looking for quick market moves, especially in volatile and high liquidity assets like Bitcoin (BTC) and Ethereum (ETH). It helps traders capture short-term trends with efficient risk management tools.
How to Apply:
Set Your Chart: Apply the AI Trend Momentum Sniper to a 5-minute (M5) or 15-minute (M15) chart for optimal performance.
Buy Signal: When the indicator generates a green arrow below the bar, it indicates a buy signal based on positive trend and momentum alignment.
Sell Signal: A red arrow above the bar signals a sell condition when the trend and momentum shift bearish.
Stop-Loss and Take-Profit: The indicator automatically calculates dynamic stop-loss and take-profit levels based on the ATR value for each trade, ensuring proper risk management.
Alerts: Set up custom alerts for buy or sell signals, and get notified instantly when opportunities arise.
Best Markets for Use:
BTC/USDT, ETH/USDT – High liquidity and volatility.
Major altcoins with sufficient volume.
Avoid using it on low-liquidity assets where price action may become erratic.
Timeframes:
This indicator is best suited for lower timeframes (5-minute to 15-minute charts) to capture quick price movements in trending markets.
Machine Learning Moving Average [LuxAlgo]The Machine Learning Moving Average (MLMA) is a responsive moving average making use of the weighting function obtained Gaussian Process Regression method. Characteristic such as responsiveness and smoothness can be adjusted by the user from the settings.
The moving average also includes bands, used to highlight possible reversals.
🔶 USAGE
The Machine Learning Moving Average smooths out noisy variations from the price, directly estimating the underlying trend in the price.
A higher "Window" setting will return a longer-term moving average while increasing the "Forecast" setting will affect the responsiveness and smoothness of the moving average, with higher positive values returning a more responsive moving average and negative values returning a smoother but less responsive moving average.
Do note that an excessively high "Forecast" setting will result in overshoots, with the moving average having a poor fit with the price.
The moving average color is determined according to the estimated trend direction based on the bands described below, shifting to blue (default) in an uptrend and fushia (default) in downtrends.
The upper and lower extremities represent the range within which price movements likely fluctuate.
Signals are generated when the price crosses above or below the band extremities, with turning points being highlighted by colored circles on the chart.
🔶 SETTINGS
Window: Calculation period of the moving average. Higher values yield a smoother average, emphasizing long-term trends and filtering out short-term fluctuations.
Forecast: Sets the projection horizon for Gaussian Process Regression. Higher values create a more responsive moving average but will result in more overshoots, potentially worsening the fit with the price. Negative values will result in a smoother moving average.
Sigma: Controls the standard deviation of the Gaussian kernel, influencing weight distribution. Higher Sigma values return a longer-term moving average.
Multiplicative Factor: Adjusts the upper and lower extremity bounds, with higher values widening the bands and lowering the amount of returned turning points.
🔶 RELATED SCRIPTS
Machine-Learning-Gaussian-Process-Regression
SuperTrend-AI-Clustering
AadTrend [InvestorUnknown]The AadTrend indicator is an experimental trading tool that combines a user-selected moving average with the Average Absolute Deviation (AAD) from this moving average. This combination works similarly to the Supertrend indicator but offers additional flexibility and insights. In addition to generating Long and Short signals, the AadTrend indicator identifies RISK-ON and RISK-OFF states for each trade direction, highlighting areas where taking on more risk may be considered.
Core Concepts and Features
Moving Average (User-Selected Type)
The indicator allows users to select from various types of moving averages to suit different trading styles and market conditions:
Simple Moving Average (SMA)
Exponential Moving Average (EMA)
Hull Moving Average (HMA)
Double Exponential Moving Average (DEMA)
Triple Exponential Moving Average (TEMA)
Relative Moving Average (RMA)
Fractal Adaptive Moving Average (FRAMA)
Average Absolute Deviation (AAD)
The Average Absolute Deviation measures the average distance between each data point and the mean, providing a robust estimation of volatility.
aad(series float src, simple int length, simple string avg_type) =>
avg = // Moving average as selected by the user
abs_deviations = math.abs(src - avg)
ta.sma(abs_deviations, length)
This provides a volatility measure that adapts to recent market conditions.
Combining Moving Average and AAD
The indicator creates upper and lower bands around the moving average using the AAD, similar to how the Supertrend indicator uses Average True Range (ATR) for its bands.
AadTrend(series float src, simple int length, simple float aad_mult, simple string avg_type) =>
// Calculate AAD (volatility measure)
aad_value = aad(src, length, avg_type)
// Calculate the AAD-based moving average by scaling the price data with AAD
avg = switch avg_type
"SMA" => ta.sma(src, length)
"EMA" => ta.ema(src, length)
"HMA" => ta.hma(src, length)
"DEMA" => ta.dema(src, length)
"TEMA" => ta.tema(src, length)
"RMA" => ta.rma(src, length)
"FRAMA" => ta.frama(src, length)
avg_p = avg + (aad_value * aad_mult)
avg_m = avg - (aad_value * aad_mult)
var direction = 0
if ta.crossover(src, avg_p)
direction := 1
else if ta.crossunder(src, avg_m)
direction := -1
A chart displaying the moving average with upper and lower AAD bands enveloping the price action.
Signals and Trade States
1. Long and Short Signals
Long Signal: Generated when the price crosses above the upper AAD band,
Short Signal: Generated when the price crosses below the lower AAD band.
2. RISK-ON and RISK-OFF States
These states provide additional insight into the strength of the current trend and potential opportunities for taking on more risk.
RISK-ON Long: When the price moves significantly above the upper AAD band after a Long signal.
RISK-OFF Long: When the price moves back below the upper AAD band, suggesting caution.
RISK-ON Short: When the price moves significantly below the lower AAD band after a Short signal.
RISK-OFF Short: When the price moves back above the lower AAD band.
Highlighted areas on the chart representing RISK-ON and RISK-OFF zones for both Long and Short positions.
A chart showing the filled areas corresponding to trend directions and RISK-ON zones
Backtesting and Performance Metrics
While the AadTrend indicator focuses on generating signals and highlighting risk areas, it can be integrated with backtesting frameworks to evaluate performance over historical data.
Integration with Backtest Library:
import InvestorUnknown/BacktestLibrary/1 as backtestlib
Customization and Calibration
1. Importance of Calibration
Default Settings Are Experimental: The default parameters are not optimized for any specific market condition or asset.
User Calibration: Traders should adjust the length, aad_mult, and avg_type parameters to align the indicator with their trading strategy and the characteristics of the asset being analyzed.
2. Factors to Consider
Market Volatility: Higher volatility may require adjustments to the aad_mult to avoid false signals.
Trading Style: Short-term traders might prefer faster-moving averages like EMA or HMA, while long-term traders might opt for SMA or FRAMA.
Alerts and Notifications
The AadTrend indicator includes built-in alert conditions to notify traders of significant market events:
Long and Short Alerts:
alertcondition(long_alert, "LONG (AadTrend)", "AadTrend flipped ⬆LONG⬆")
alertcondition(short_alert, "SHORT (AadTrend)", "AadTrend flipped ⬇Short⬇")
RISK-ON and RISK-OFF Alerts:
alertcondition(risk_on_long, "RISK-ON LONG (AadTrend)", "RISK-ON LONG (AadTrend)")
alertcondition(risk_off_long, "RISK-OFF LONG (AadTrend)", "RISK-OFF LONG (AadTrend)")
alertcondition(risk_on_short, "RISK-ON SHORT (AadTrend)", "RISK-ON SHORT (AadTrend)")
alertcondition(risk_off_short, "RISK-OFF SHORT (AadTrend)", "RISK-OFF SHORT (AadTrend)")
Important Notes and Disclaimer
Experimental Nature: The AadTrend indicator is experimental and should be used with caution.
No Guaranteed Performance: Past performance is not indicative of future results. Backtesting results may not reflect real trading conditions.
User Responsibility: Traders and investors should thoroughly test and calibrate the indicator settings before applying it to live trading.
Risk Management: Always use proper risk management techniques, including stop-loss orders and position sizing.
