Updated TurtlesThis script has been updated to prevent double orders (short/long) from occurring and modifying backtests results.
This is an update to the script that was written a few years ago to prevent double longs/shorts from occurring and skewin backtesting results. Check out the updated indicator here and let me know what you think.
I also added:
- date range inputs if you want to do some backtesting on a particular set of dates.
- the ability to toggle shorting
Pesquisar nos scripts por "backtesting"
Adding some essential components to a prebuilt RSI strategyThis is more to be used as a blank_slate for any strategy build adding more effective backtesting with a period selector and inputs like TS, TP, SL that can all be used as plots for alerts.
It has the BackTest Component created by Pbergden
It also includes the standard long/short with trailing stop, take profit, stop loss and margin call.
Here is a video using the blank_slate to add in the built-in RSI Strategy.
youtu.be
We hope this brings good results and helps speed things up for everyone.
CM Stochastic POP Method 2-Jake Bernstein_V1Yesterday Jake Bernstein authorized me to post his updated results with the Stochastic Pop Trading System he developed many years ago.
You can take a look at the Original System with Updated Settings at
This indicator is a different set of rules Jake mentioned in the PDF he allowed me to post.
To view the PDF use this link:
dl.dropboxusercontent.com
Today we’re releasing the version described in the PDF that uses the StochK values of 55, 50, and 45. The rules are discussed in the PDF but here is a simple breakdown:
Enter Long when StochK is below 50 and Crosses Above 55
Exit Long on Cross Below 55
Enter Short when StochK is Above 50 and crosses Below 45
Exit Short on Cross Above 45
Two Important Items to understand about this method:
To code the rules Precisely we need a function that will be available when Strategy Capabilities are released on TradingView.
There is one of Jakes Profit Maximizing Strategies that needs to be integrated with this code…which again we need the Strategy based Function that will be coming soon.
To Compare this system to the Stochastic Pop Method 1 System shown yesterday at I used the same Symbol and dates for you to compare…but remember to give this Method 2 System a Fair Look/Evaluation…we need the Soon To Be Released…TradingView Strategy Capabilities.
BackTesting Results Example: EUR-USD Daily Chart Since 01/01/2005
Strategy 1 – Stochastic Pop Method 2 System:
Go Long When Stochasticis below 50 and Crosses Above 55. Go Short When Stochastic is above 50 and Crosses Below 45. Exit Long/Short When Stochastic has a Reverse Cross of Entry Value.
Results:
Total Trades = 151
Profit = 40,758 Pips
Win% = 37.1%
Profit Factor = 1.26
Avg Trade = 270 Pips Profit
***Most Consecutive Wins = 4 ... Most Consecutive Losses = 7
Strategy 2:
Rules - Proprietary Optimization Jake Will Teach. Only Added 1 Additional Exit Rule.
Results:
Total Trades = 151
Profit = 60.305 Pips
Win% = 37.1%
Profit Factor = 1.38
Avg Trade = 399 Pips Profit
***Most Consecutive Wins = 4 ... Most Consecutive Losses = 7
Indicator Includes:
-Ability to Color Candles (CheckBox In Inputs Tab)
Green = Long Trade
Blue = No Trade
Red = Short Trade
Jake Bernstein will be a contributor on TradingView when Backtesting/Strategies are released. Jake is one of the Top Trading System Developers in the world with 45+ years experience and he is going to teach TradingView.com’s community how to create Trading Systems and how to Optimize the correct way.
Link To PDF:
dl.dropboxusercontent.com
Link to Original Version of Indicator with Updated Settings.
CM Stochastic POP Method 1 - Jake Bernstein_V1A good friend ucsgears recently published a Stochastic Pop Indicator designed by Jake Bernstein with a modified version he found.
I spoke to Jake this morning and asked if he had any updates to his Stochastic POP Trading Method. Attached is a PDF Jake published a while back (Please read for basic rules, which also Includes a New Method). I will release the Additional Method Tomorrow.
Jake asked me to share that he has Updated this Method Recently. Now across all symbols he has found the Stochastic Values of 60 and 30 to be the most profitable. NOTE - This can be Significantly Optimized for certain Symbols/Markets.
Jake Bernstein will be a contributor on TradingView when Backtesting/Strategies are released. Jake is one of the Top Trading System Developers in the world with 45+ years experience and he is going to teach how to create Trading Systems and how to Optimize the correct way.
Below are a few Strategy Results....Soon You Will Be Able To Find Results Like This Yourself on TradingView.com
BackTesting Results Example: EUR-USD Daily Chart Since 01/01/2005
Strategy 1:
Go Long When Stochastic Crosses Above 60. Go Short When Stochastic Crosses Below 30. Exit Long/Short When Stochastic has a Reverse Cross of Entry Value.
Results:
Total Trades = 164
Profit = 50, 126 Pips
Win% = 38.4%
Profit Factor = 1.35
Avg Trade = 306 Pips Profit
***Most Consecutive Wins = 3 ... Most Consecutive Losses = 6
Strategy 2:
Rules - Proprietary Optimization Jake Will Teach. Only Added 1 Additional Exit Rule.
Results:
Total Trades = 164
Profit = 62, 876 Pips!!!
Win% = 38.4%
Profit Factor = 1.44
Avg Trade = 383 Pips Profit
***Most Consecutive Wins = 3 ... Most Consecutive Losses = 6
Strategy 3:
Rules - Proprietary Optimization Jake Will Teach. Only added 1 Additional Exit Rule.
Results:
Winning Percent Increases to 72.6%!!! , Same Amount of Trades.
***Most Consecutive Wins = 21 ...Most Consecutive Losses = 4
Indicator Includes:
-Ability to Color Candles (CheckBox In Inputs Tab)
Green = Long Trade
Blue = No Trade
Red = Short Trade
-Color Coded Stochastic Line based on being Above/Below or In Between Entry Lines.
Link To Jakes PDF with Rules
dl.dropboxusercontent.com
DAX 9-10 Breakout Strategy IndicatorOpening Hour Breakout (ORB) indicator for intraday trading.
WHAT IT DOES:
• Identifies the price range of a specific hour (default: 9:00-10:00)
• Detects breakout direction (Long/Short) when price breaks above HIGH or below LOW
• Automatically calculates Take Profit and Stop Loss zones based on range size
• Tracks trade outcome (Win/Lose) when TP or SL is hit
HOW TO USE:
1. Set the session hour according to your chart's timezone
2. Wait for the session range to form (yellow box)
3. Enter on breakout above HIGH (Long) or below LOW (Short)
4. TP and SL levels are automatically calculated
DEFAULT SETTINGS:
• TP Multiplier: 1.41x range (Risk:Reward ≈ 1:2.7)
• SL Multiplier: 0.52x range
FEATURES:
• Works on any timeframe (H1, M15, M30, etc.)
• Visual zones for session range, TP, and SL
• Price labels for all key levels
• Entry arrows and direction letters (L/S)
• Win/Lose markers (W/X) when trade closes
• Fully customizable - show/hide any element
• Info panel with live status and R:R ratio
• Alert conditions for Entry, TP hit, SL hit
BEST USED ON:
• DAX (Germany 40)
• Other indices: US30, US500, NAS100
• Forex majors during London/NY open
NOTE: This is an indicator for visual analysis. Use the Strategy version for backtesting.
My Swift-like Algo ALIMOJANIDSwift Algo Chart is a trend-following trading indicator designed to provide clear bias, precise entries, and visual risk management.
It combines EMA trend direction, pullback-based signals, market structure (HH/HL/LH/LL), and ATR-based Stop Loss & Take Profit levels to help traders make disciplined decisions.
🔑 Key Features
Trend Regime Detection
Identifies LONG, SHORT, or NO TRADE conditions using Fast & Slow EMAs.
Pullback Entry Signals
Signals appear only in the direction of the active trend, with optional RSI confirmation.
ATR-Based Risk Levels
Automatically plots SL, TP1, and TP2, including exact price values on the chart.
Preview Levels
Shows projected SL/TP levels when a trend is active, even before an entry.
Market Structure Visualization
Marks HH / HL / LH / LL, draws structure lines, and highlights BOS and CHOCH.
Clean & Non-Repainting Logic
Uses confirmed pivots and closed candles for stability.
Strategy-Compatible
Can be used for discretionary trading or full strategy backtesting.
🧠 Best Used For
Crypto, Forex, Indices
15m to 4H timeframes
Traders who want structure + trend + risk clarity in one tool
My Swift-like Algo J.ALIMOJANIDSwift Algo Chart — Trend, Structure & ATR Risk
Swift Algo Chart is a trend-following trading indicator designed to provide clear bias, precise entries, and visual risk management.
It combines EMA trend direction, pullback-based signals, market structure (HH/HL/LH/LL), and ATR-based Stop Loss & Take Profit levels to help traders make disciplined decisions.
🔑 Key Features
Trend Regime Detection
Identifies LONG, SHORT, or NO TRADE conditions using Fast & Slow EMAs.
Pullback Entry Signals
Signals appear only in the direction of the active trend, with optional RSI confirmation.
ATR-Based Risk Levels
Automatically plots SL, TP1, and TP2, including exact price values on the chart.
Preview Levels
Shows projected SL/TP levels when a trend is active, even before an entry.
Market Structure Visualization
Marks HH / HL / LH / LL, draws structure lines, and highlights BOS and CHOCH.
Clean & Non-Repainting Logic
Uses confirmed pivots and closed candles for stability.
Strategy-Compatible
Can be used for discretionary trading or full strategy backtesting.
🧠 Best Used For
Crypto, Forex, Indices
15m to 4H timeframes
Traders who want structure + trend + risk clarity in one tool
My Swiftlike Algo Backtest ATR SL/TP HH/HL/LH/LL BOS/CHOCHSwift-Like Algo is a trend-following strategy that trades pullbacks using EMA trend direction, market structure (HH/HL/LH/LL), and ATR-based risk management.
It enters only in the direction of the trend, with automatic Stop-Loss, TP1, and TP2, and supports full strategy backtesting.
Best used on 15m–4H timeframes for crypto, forex, and indices.
⚠️ For educational and testing purposes only.
OBV Apex: Donchian-Bollinger Dual Resonance (DBDR)以下是为您定制的 **OBV Apex: DBDR (Donchian-Bollinger Dual Resonance)** 指标双语简介。
---
## 指标简介 / Indicator Overview
**OBV Apex: Donchian-Bollinger Dual Resonance (DBDR)** 是一款专为捕捉高概率趋势反转和波动率爆发而设计的尖端量价指标。它打破了传统指标单一维度的局限，将基于绝对价格区间的**唐奇安通道逻辑**与基于统计学概率分布的**布林带动能逻辑**深度融合，旨在为交易者提供“跨维度共振”的决策依据。
**OBV Apex: Donchian-Bollinger Dual Resonance (DBDR)** is a cutting-edge volume-price indicator designed to capture high-probability trend reversals and volatility breakouts. It breaks the limitations of single-dimensional indicators by integrating **Donchian Channel logic** (based on absolute price ranges) with **Bollinger Band momentum logic** (based on statistical probability distribution), providing traders with a "cross-dimensional resonance" framework for decision-making.
---
## 核心功能与视觉识别 / Key Features & Visual Identification
### **1. 智能变色主线 / Intelligent Multi-Color Main Line**
指标 OBV 主线根据当前动能状态实时切换颜色。
* **白色 (极端区)**：当 OBV 触碰或刺破唐奇安通道轨道时变为白色，提示动能进入超买或超卖的极端区域。
* **绿色/红色 (趋势区)**：代表 OBV 突破了中轨缓冲区，确认了当前的上涨或下跌趋势。
* **黄色 (噪音区)**：OBV 处于缓冲区内部，提示市场处于震荡或无方向阶段。
The main OBV line switches colors in real-time based on momentum states.
* **White (Extreme)**: Turns white when OBV touches or pierces Donchian boundaries, signaling extreme overbought/oversold momentum.
* **Green/Red (Trend)**: Indicates OBV has broken out of the mid-rail buffer, confirming an uptrend or downtrend.
* **Yellow (Noise)**: OBV stays within the buffer zone, suggesting a sideways or directionless market.
### **2. 波动率挤压背景 / Volatility Squeeze Background**
当唐奇安通道大幅收窄，代表市场进入蓄力阶段。此时离散区域（Dispersion Area）会变为**深紫色**，这是即将发生大级别变盘的重要视觉信号。
When the Donchian Channel narrows significantly, it represents a market accumulation phase. The Dispersion Area turns **Deep Purple**, providing a crucial visual signal for an impending major volatility breakout.
---
## 详细用法说明 / Detailed Usage Instructions
### **1. 逻辑共振星号 (⭐) 的实战意义 / Strategic Meaning of the Resonance Star (⭐)**
这是本指标最具价值的核心信号。
* **基础信号 (R/H)**：当唐奇安系统检测到结构性背离时产生。
* **共振信号 (⭐)**：仅当后台隐藏的布林带算法也同时检测到逻辑背离时，信号后才会附带 ⭐。
* **用法**：普通 R 信号仅代表价格结构的衰竭，而 **R⭐** 则代表空间结构与波动率动能的**双重衰竭**。在实战中，带有星号的信号具有极高的反转成功率，是摸顶抄底的核心参考。
This is the most valuable core signal of the indicator.
* **Basic Signals (R/H)**: Generated when the Donchian system detects structural divergence.
* **Resonance Signal (⭐)**: A star is appended only when the hidden Bollinger Band algorithm also detects logical divergence simultaneously.
* **Usage**: A standard R signal represents structural exhaustion, while **R⭐** signifies **dual exhaustion** of both space structure and volatility momentum. In practice, signals with stars offer significantly higher reversal success rates.
### **2. 顶点爆发策略 (突破交易) / The Apex Explosion Strategy (Breakout)**
* **观察**：寻找背景出现持续**深紫色**填充的区域（挤压期）。
* **入场**：当 OBV 主线由黄转绿（多头突破）或由黄转红（空头突破）并脱离紫色区域时，是爆发性行情的起始点。
* **Observation**: Look for areas with continuous **Deep Purple** background filling (Squeeze phase).
* **Entry**: When the OBV line shifts from yellow to green (Bullish breakout) or red (Bearish breakout) and exits the purple zone, it marks the start of an explosive trend.
### **3. 双重共振反转策略 (反转交易) / Double Resonance Reversal Strategy**
* **确认条件**：OBV 主线变为**白色**进入极端区，随后出现带有 **⭐** 的背离标签。
* **辅助确认**：观察 KDJ 标签。如果共振星号出现后，KDJ 产生顺势的大写 **B (Buy)** 或 **S (Sell)** 标签，则反转的确定性进一步增强。
* **Confirmation**: The OBV line turns **White** (Extreme zone), followed by a divergence label with a **⭐**.
* **Secondary Confirmation**: Monitor KDJ labels. If an uppercase **B (Buy)** or **S (Sell)** appears after the resonance star, the certainty of the reversal is further enhanced.
---
## 下一步建议 / Next Step
您现在可以根据此简介进行实盘复盘。如果您需要我将**警报逻辑 (Alerts)** 进一步细化，例如针对“带星号的背离”设置专门的推送提醒，请随时告诉我。
You can now use this overview for backtesting. If you need me to further refine the **Alert logic**, such as setting specific push notifications for "Divergence with Star," please let me know.
Golder/Silter SetupsGolden/Silver Strategy
Overview
The Tony Rago Golden/Silver Strategy is a high-precision mean-reversion system specifically engineered for the Nasdaq (NQ/MNQ). It leverages the psychological 100-point price blocks to identify institutional exhaustion and reversal points.
Unlike standard "grid" bots, this strategy uses a sophisticated "Arm & Fire" logic: it requires a specific price "touch" to arm the setup, followed by a retracement to a "Golden" entry level to execute.
Key Logic: The 100-Point Grid
The strategy divides price action into 100-point blocks (e.g., 19500 to 19600).
Golden Setup (Long): Triggered when price touches the 50 level (mid-point). The order is placed at the 26 level on the retracement.
Silver Setup (Short): Triggered when price touches the 00 or 100 levels (block boundaries). The order is placed at the 77 or 26 levels on the retracement.
Professional Risk Management
This edition features a Dual-Contract Management system designed for Prop Firm consistency:
Contract 1 (The Scalp): Aims for a quick 24-point target (TP1) to secure realized gains and cover costs.
Contract 2 (The Runner): Stays in the trade for an extended 51-point target (TP2).
Automated Break-Even (BE): The moment TP1 is hit, the Stop Loss for the Runner is automatically moved to the entry price (plus a small offset). This ensures a "risk-free" environment for the remainder of the trade.
Independent Stop Losses: The Scalp and the Runner use different SL distances to account for Nasdaq volatility, preventing a single "noise" wick from wiping out the entire position.
Intelligent Filters
ADX Range Filter: The strategy monitors market trend strength. It only allows trades when the ADX is below a user-defined threshold (default 25), ensuring you only play mean-reversion during ranging or "choppy" markets.
MA Visual Semaphor: The 50 EMA changes color dynamically based on ADX (Lime/Green for Range, Orange/Red for Trend), giving you an instant visual "Go/No-Go" signal.
Time-Session Filtering: Optimized for three custom sessions (NY Open, Mid-Day Reversal, and Late Night). Outside these sessions, the strategy can "Arm" setups in memory but will not "Fire" orders.
How to Use
Timeframe: Optimized for 1-Minute or 2-Minute charts for precision entry.
Asset: Nasdaq 100 (NQ, MNQ) or similar high-volatility indices.
Setup: * Enable Session Filters to avoid news volatility.
Adjust TP/SL in Points (1 Point = 4 Ticks) to suit your specific risk appetite.
Watch for the "Armados" labels—these indicate the system is ready and waiting for the Golden/Silver entry.
Visual Interface
Dynamic Boxes: Real-time visual representation of your TP1, TP2, and SL levels.
Activation Labels: Clear indications of when a Long or Short setup has been "Armed" in memory.
Status Dashboard: A clean top-right table showing current ADX values, Session status, and Risk settings.
Disclaimer
Trading involves significant risk. This strategy is a tool for decision support and backtesting. Past performance does not guarantee future results. Always test on a demo account before risking live capital.
Bear & Bull Builder // visual strategy builderAre you a trend follower?
Trend following systems have been a cornerstone of trading since the first candlestick charts were invented in 18th-century Japan by Munehisa Homma (or Honma), a legendary rice merchant who used them to analyze market sentiment and predict price movements. Since then, legendary traders like Richard Dennis and Dr. David Paul have used technical analysis—the study of turning points and trends of candlestick charts—to develop an edge and strategy for trading equity, commodity, and forex markets.
How to Utilize the Bear & Bull Builder
This script is a way to pick and choose technical methods like SMAs and EMAs to define trend exits and entries. Additionally, you can specify an ATR (Average True Range) calculated stop loss based on your individual strategy and trading plan. Within the settings panel, you can set up this script to display only Long Position values, zones, and levels—or configure it for shorts, or both.
What Makes This Original
Unlike most trend-following indicators that lock you into a single approach, this script lets you combine different indicator types (RSI, WaveTrend, CCI, EMA, SMA) across three separate trend timeframes. The originality comes from the flexibility: you can test whether momentum-based trends (like RSI) work better than moving averages for your timeframe, or experiment with mixing them together. The script also bridges the gap between manual trading and automation by providing visual position values and fill zones that show exactly where signals generate versus where orders execute—critical information most scripts ignore.
Getting Started
For this quick and easy setup example, I built a strategy that is long-only, displays only long positional data and values, and uses a 21 & 55 period exponential moving average for the short and medium-term trend in addition to an 89 period simple moving average for my longer-term outlook. I have set my ATR-based multiplier to 0.75, and have left the fill zone display turned on to help visualize when to set up the built-in alerts for automating my strategy. I have made this the default settings of the script.
Positional Values
GREEN NUMBERS → Entry signal price
YELLOW NUMBERS → Stop loss price
BLUE NUMBERS → Exit signal price
IMPORTANT
I cannot describe how useful it is to use TradingView's built-in Long and Short position tools! The whole reason for this script is that it is as manually friendly as it is automated—especially for backtesting. You can use the long position tool to measure exact profits and losses on individual trades for the strategies you build. This can really help you see clearly if you have built a system with positive expectancy.
Tables
1. Settings Display Table
Displays the trend types that are configurable in the settings panel. Shows if positional values for longs and shorts are currently displayed.
2. Back testing Table
Displays the total amount of long and short entry signals since the first bar of the chart. Additionally, it displays the average amount of bars per trade (time in trade).
Alerts & Automation
There are 4 built-in alerts for automating your strategy to an external server:
1.Long Entries
2.Long Exits
3.Short Entries
4.Short Exits
Since this script uses confirmed bar states for alert generation (to avoid repainting), all alerts and displayed position values (the green, yellow, and blue numbers) will be sent on the closing price. Each alert has a placeholder preset for further customization.
Technical Details
How the trend detection works:
Bullish state triggers when close > all three selected trends
Bearish state triggers when close < all three selected trends
Uses barstate.isconfirmed to prevent repainting
Stop loss calculation:
Long stops: highest_trend - (ATR × multiplier)
Short stops: lowest_trend + (ATR × multiplier)
ATR period is fixed at 20 bars, multiplier is user-adjustable
Entry placement logic:
Long entries execute at the highest value among the three selected trends
Short entries execute at the lowest value among the three selected trends
This ensures entries occur near the support/resistance created by the trend lines
Why calculate all indicators upfront:
The script calculates all five indicator types (EMA, SMA, RSI, CCI, WaveTrend) for all three trend lengths on every bar, then selectively uses the ones you choose in settings. This prevents Pine Script consistency warnings while maintaining flexibility.
Vertical line at 6PMVertical line deliniated every 6pm for the asian session trading and backtesting.
Key Price Levels + Zones"Support and resistance are rarely exact lines; hey are zones where price reacts."
This indicator upgrades standard horizontal levels by visualizing Liquidity Zones around the most critical intraday reference points: Pre-Market, Previous Day, and Previous Week Highs/Lows.
Unlike basic scripts that just draw thin lines, this tool combines the precision of exact price levels with the reality of market volatility. It offers deep customization, allowing you to separate line colors from zone colors, perfect for keeping your charts clean and professional.
Key Features
1. Dual Zone Logic (Dynamic Sizing)
• Price Tier Mode (Default): Zones are sized based on the asset price (e.g., higher-priced stocks get wider zones automatically). This mimics "psychological" levels.
• ATR Volatility Mode: Switches calculation to use the Average True Range (ATR). Zones expand during high volatility and contract during chop, adapting to the market conditions in real-time.
2. Ultimate Customization
• Separate Colors: You can finally set your Line Color (e.g., Bright Green) independently from your Zone Fill (e.g., Faint Grey).
• Individual Toggles: Turn the Line, Zone, or Label on/off individually for every single level.
• Line Styles: Differentiate daily levels (Solid) from weekly levels (Dashed) instantly.
3. The "Smart" Levels
• PM High/Low: Real-time Pre-Market tracking that freezes at the open.
• PD High/Low: Previous Day’s range.
• PW High/Low: Previous Week’s range (Critical for swing points).
---
Settings Guide
• Extension Style:
- Individual: Keeps history of levels for backtesting.
- Most Recent: Keeps the chart minimal by extending only today's levels.
• Zone Thickness Mode: Switch between "Price Tier" and "ATR Volatility".
• ATR Settings: Fully adjustable Length and Multiplier (when in ATR mode).
• Transparency: Global slider to control how subtle or bold the zones appear.
How to Trade This
• The "Trap": If price breaks a Line but fails to close outside the Zone, it is often a liquidity grab (fakeout).
• The Retest: Watch for price to break a level and use the Zone as a cushion for a bounce/retest entry.
SMAcross-mvrOverview
SMAcross-mvrNew is a flexible, non-repainting moving-average strategy designed for clarity, configurability, and reliable backtesting.
It supports multiple entry styles, optional layered exits, and full-capital position sizing, while remaining stable during chart zooming and dragging.
🚀 What’s New in v2
✅ Multiple Entry Modes
You can now choose how trades are entered:
Entry Mode A: Short SMA crosses Long SMA
Entry Mode B: Price crosses Long SMA
This allows both classic MA-crossover trading and trend-continuation pullback entries using the same strategy.
✅ Modular Exit System (Checkbox-Based)
Exit logic is now fully modular using independent checkboxes:
☑ Exit on opposite signal
☑ Exit when price closes beyond Short SMA
You may enable one, both, or neither.
If both are enabled, the strategy exits on whichever condition occurs first.
✅ Terminology Clarity
All labels, inputs, and alerts now use semantic naming:
Short SMA (formerly 13 SMA)
Long SMA (formerly 30 SMA)
This makes the strategy easier to understand and future-proof if SMA lengths are changed.
✅ Full-Capital Position Sizing
Each trade uses 100% of available equity, allowing performance to naturally compound over time during backtests.
✅ Optional Visual Enhancements
Optional cross price labels (can be toggled on/off)
Color-filled zone between Short and Long SMAs for quick trend recognition
Optional 200 SMA (off by default) for higher-timeframe context
✅ Alert-Ready (TV-Safe)
All alerts use static messages compatible with TradingView’s alert system, making the strategy suitable for:
Manual trade notifications
Webhook-based automation
Broker integrations
🔒 Design Principles
No repainting
No line continuations (TradingView-safe formatting)
Stable behavior when zooming or scrolling
Clear separation of entry logic, exit logic, and visuals
⚠️ Notes
This script is intended for educational and research purposes.
Always forward-test and apply proper risk management before live trading.
ML Adaptive SuperTrend Strategy [trade_crush]# ML Adaptive SuperTrend Strategy - User Guide
## Introduction
The **ML Adaptive SuperTrend Strategy** is a sophisticated trading tool that combines traditional trend-following logic with **Machine Learning (K-Means Clustering)** to dynamically adapt to market volatility. Unlike standard SuperTrend indicators that use a fixed ATR, this strategy analyzes historical volatility to categorize the current market into distinct clusters, providing more precise entries and exits.
>
> **Special Thanks:** This strategy is based on the innovative work of **AlgoAlpha**. You can explore their extensive library of high-quality indicators and strategies on TradingView: (www.tradingview.com).
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## Machine Learning Engine (K-Means)
The core of this strategy is its ability to "learn" from recent market behavior.
- **K-Means Clustering**: The script takes the last $N$ bars of ATR data and runs an iterative clustering algorithm to find three "centroids" representing **High**, **Medium**, and **Low** volatility.
- **Adaptive ATR**: Based on the current volatility, the strategy selects the nearest centroid to use as the ATR value for the SuperTrend calculation. This ensures the trailing stop tightens during low volatility and widens during high volatility to avoid "noise".
---
## Key Features
### 1. Non-Repainting Signals
- **Confirm Signals**: When enabled, signals are only triggered after a bar closes. This ensures that the arrows and entries you see on the chart are permanent and reliable for backtesting.
### 2. Intelligent Risk Management
- **Multiple SL/TP Types**: Choose between **Percentage** based stops or **ATR** based stops for both Stop Loss and Take Profit.
- **Trailing Stop Loss (TSL)**:
- Supports both Percentage and ATR modes.
- **Activation Offset**: Only activates the trailing mechanism after the price has moved a certain percentage in your favor, protecting early-stage trades.
### 3. Risk-Based Position Sizing
- **Dynamic Quantity**: If enabled, the strategy automatically calculates the trade size based on your **Risk % Per Trade** and the distance to your **Stop Loss**. This ensures you never lose more than your defined risk on a single trade.
---
## User Input Guide
### SuperTrend & ML Settings
- **ATR Length**: The window used to calculate market volatility.
- **SuperTrend Factor**: The multiplier that determines the distance of the trailing stop from the price.
- **Use ML Adaptive ATR**: Toggle between the ML-enhanced logic and standard ATR.
- **Training Data Length**: How many historical bars the ML engine analyzes to find clusters.
### Risk Management
- **Stop Loss Type**: Set to Percentage, ATR, or None.
- **TS Activation Offset**: The profit buffer required before the trailing stop starts following the price.
- **Use Risk-Based Sizing**: Toggle this to let the script manage your position size automatically.
---
## How to Trade with This Strategy
1. **Monitor the Dashboard**: Check the top-right table to see which volatility cluster the market is currently in.
2. **Observe the Fills**: The adaptive fills (green/red) visualize the "breathing room" the strategy is giving the price.
3. **Execution**: The strategy enters on "ML Bullish" (Triangle Up) and "ML Bearish" (Triangle Down) signals.
4. **Exits**: The script will automatically exit based on your SL, TP, or Trailing Stop settings.
---
## Credits
Original Concept: **AlgoAlpha**
Strategy Conversion & Enhancements: **Antigravity AI**
Triple EMA + RSI + ATRThis comprehensive trading system combines triple EMA alignment, RSI momentum filtering, and dynamic ATR-based risk management. The strategy enters positions only when fast, medium, and slow EMAs align in proper order (bullish or bearish), confirmed by RSI remaining within defined thresholds (not overbought/oversold) and a volume spike above its moving average. Exits are managed intelligently using a multi-tier approach: a fixed stop-loss based on ATR, a first profit target at a predefined risk-reward ratio, and a trailing stop that activates after reaching a second, higher profit tier. Designed for trend-following with built-in momentum and volume confirmation, it features professional order execution with configurable commission and slippage for realistic backtesting. Visual cues including colored backgrounds and signal shapes enhance chart clarity.
LETHINH-Swing pa,smc🟦 📌 Title (English)
Swing High / Swing Low – 3-Candle Fractal (5-Bar Pivot) | Auto Alerts
⸻
🟩 📌 Short Description
A clean and reliable swing high / swing low detector based on the classic 3-candle (5-bar) fractal pivot. Automatically marks SH/SL and triggers alerts when a swing is confirmed. No repainting after confirmation.
⸻
🟧 📌 Full Description (for TradingView Publishing)
🔶 Swing High / Swing Low – 3-Candle Fractal (5-Bar Pivot)
This indicator identifies Swing Highs (SH) and Swing Lows (SL) using the classic 3-candle fractal pattern, also known as the 5-bar pivot.
It marks swing points only after full confirmation, making it highly reliable and suitable for structure-based trading.
⸻
🔶 📍 How It Works
A swing is confirmed when the center candle is higher (or lower) than the two candles on each side:
Swing High (SH)
high > high , high , high
Swing Low (SL)
low < low , low , low
The confirmation occurs after 2 right candles close, so the indicator does not repaint once a swing is identified.
⸻
🔶 📍 Key Features
• Detects clean and accurate swings
• Uses pure price action — no indicators, no lag
• Marks swing high (SH) and swing low (SL) directly on the chart
• Non-repainting after confirmation
• Works on all timeframes and all markets
• Extremely lightweight and fast
• Includes alert conditions for both SH and SL
Perfect for traders using:
• Market Structure (BOS / CHoCH)
• Order Blocks (OB)
• Smart Money Concepts (SMC)
• Liquidity hunts
• Wyckoff
• Support/Resistance
• Price Action entries
⸻
🔶 📍 Why This Indicator Is Useful
Swing points are the foundation of market structure.
Accurately detecting them helps traders:
• Identify trend shifts
• Spot BOS / CHoCH correctly
• Find key zones (OB, liquidity levels, supply/demand)
• Time entries more precisely
• Avoid fake structure breaks
This indicator ensures swings are plotted only when fully confirmed, reducing noise and confusion.
⸻
🔶 📍 Alerts
You can create alerts for both conditions:
• Swing High Confirmed
• Swing Low Confirmed
Recommended settings:
• Once per bar close
• Open-ended alert
With alerts enabled, TradingView will automatically notify you every time a new swing forms.
⸻
🔶 📍 No Repainting
Once a swing is confirmed and plotted, it will not change or disappear.
This makes the indicator reliable for real-time alerts and backtesting.
⸻
🔶 📍 Pine Script (v5)
Paste your indicator code here if you want it visible.
Or leave the code hidden if you are publishing as protected.
⸻
🔶 📍 Final Notes
• This indicator focuses on confirmation, not prediction
• It is designed for clean structure reading
• All markets supported: Forex, Crypto, Stocks, Indexes, Commodities
• Suitable for scalping, intraday, swing, and even higher-timeframe trading
If you find this tool helpful, feel free to give it a like and add it to your favorites ❤️
Your support helps me share more tools with the community!
Static K-means Clustering | InvestorUnknownStatic K-Means Clustering is a machine-learning-driven market regime classifier designed for traders who want a data-driven structure instead of subjective indicators or manually drawn zones.
This script performs offline (static) K-means training on your chosen historical window. Using four engineered features:
RSI (Momentum)
CCI (Price deviation / Mean reversion)
CMF (Money flow / Strength)
MACD Histogram (Trend acceleration)
It groups past market conditions into K distinct clusters (regimes). After training, every new bar is assigned to the nearest cluster via Euclidean distance in 4-dimensional standardized feature space.
This allows you to create models like:
Regime-based long/short filters
Volatility phase detectors
Trend vs. chop separation
Mean-reversion vs. breakout classification
Volume-enhanced money-flow regime shifts
Full machine-learning trading systems based solely on regimes
Note:
This script is not a universal ML strategy out of the box.
The user must engineer the feature set to match their trading style and target market.
K-means is a tool, not a ready made system, this script provides the framework.
Core Idea
K-means clustering takes raw, unlabeled market observations and attempts to discover structure by grouping similar bars together.
// STEP 1 — DATA POINTS ON A COORDINATE PLANE
// We start with raw, unlabeled data scattered in 2D space (x/y).
// At this point, nothing is grouped—these are just observations.
// K-means will try to discover structure by grouping nearby points.
//
// y ↑
// |
// 12 | •
// | •
// 10 | •
// | •
// 8 | • •
// |
// 6 | •
// |
// 4 | •
// |
// 2 |______________________________________________→ x
// 2 4 6 8 10 12 14
//
//
//
// STEP 2 — RANDOMLY PLACE INITIAL CENTROIDS
// The algorithm begins by placing K centroids at random positions.
// These centroids act as the temporary “representatives” of clusters.
// Their starting positions heavily influence the first assignment step.
//
// y ↑
// |
// 12 | •
// | •
// 10 | • C2 ×
// | •
// 8 | • •
// |
// 6 | C1 × •
// |
// 4 | •
// |
// 2 |______________________________________________→ x
// 2 4 6 8 10 12 14
//
//
//
// STEP 3 — ASSIGN POINTS TO NEAREST CENTROID
// Each point is compared to all centroids.
// Using simple Euclidean distance, each point joins the cluster
// of the centroid it is closest to.
// This creates a temporary grouping of the data.
//
// (Coloring concept shown using labels)
//
// - Points closer to C1 → Cluster 1
// - Points closer to C2 → Cluster 2
//
// y ↑
// |
// 12 | 2
// | 1
// 10 | 1 C2 ×
// | 2
// 8 | 1 2
// |
// 6 | C1 × 2
// |
// 4 | 1
// |
// 2 |______________________________________________→ x
// 2 4 6 8 10 12 14
//
// (1 = assigned to Cluster 1, 2 = assigned to Cluster 2)
// At this stage, clusters are formed purely by distance.
Your chosen historical window becomes the static training dataset , and after fitting, the centroids never change again.
This makes the model:
Predictable
Repeatable
Consistent across backtests
Fast for live use (no recalculation of centroids every bar)
Static Training Window
You select a period with:
Training Start
Training End
Only bars inside this range are used to fit the K-means model. This window defines:
the market regime examples
the statistical distributions (means/std) for each feature
how the centroids will be positioned post-trainin
Bars before training = fully transparent
Training bars = gray
Post-training bars = full colored regimes
Feature Engineering (4D Input Vector)
Every bar during training becomes a 4-dimensional point:
This combination balances: momentum, volatility, mean-reversion, trend acceleration giving the algorithm a richer "market fingerprint" per bar.
Standardization
To prevent any feature from dominating due to scale differences (e.g., CMF near zero vs CCI ±200), all features are standardized:
standardize(value, mean, std) =>
(value - mean) / std
Centroid Initialization
Centroids start at diverse coordinates using various curves:
linear
sinusoidal
sign-preserving quadratic
tanh compression
init_centroids() =>
// Spread centroids across using different shapes per feature
for c = 0 to k_clusters - 1
frac = k_clusters == 1 ? 0.0 : c / (k_clusters - 1.0) // 0 → 1
v = frac * 2 - 1 // -1 → +1
array.set(cent_rsi, c, v) // linear
array.set(cent_cci, c, math.sin(v)) // sinusoidal
array.set(cent_cmf, c, v * v * (v < 0 ? -1 : 1)) // quadratic sign-preserving
array.set(cent_mac, c, tanh(v)) // compressed
This makes initial cluster spread “random” even though true randomness is hardly achieved in pinescript.
K-Means Iterative Refinement
The algorithm repeats these steps:
(A) Assignment Step, Each bar is assigned to the nearest centroid via Euclidean distance in 4D:
distance = sqrt(dx² + dy² + dz² + dw²)
(B) Update Step, Centroids update to the mean of points assigned to them. This repeats iterations times (configurable).
LIVE REGIME CLASSIFICATION
After training, each new bar is:
Standardized using the training mean/std
Compared to all centroids
Assigned to the nearest cluster
Bar color updates based on cluster
No re-training occurs. This ensures:
No lookahead bias
Clean historical testing
Stable regimes over time
CLUSTER BEHAVIOR & TRADING LOGIC
Clusters (0, 1, 2, 3…) hold no inherent meaning. The user defines what each cluster does.
Example of custom actions:
Cluster 0 → Cash
Cluster 1 → Long
Cluster 2 → Short
Cluster 3+ → Cash (noise regime)
This flexibility means:
One trader might have cluster 0 as consolidation.
Another might repurpose it as a breakout-loading zone.
A third might ignore 3 clusters entirely.
Example on ETHUSD
Important Note:
Any change of parameters or chart timeframe or ticker can cause the “order” of clusters to change
The script does NOT assume any cluster equals any actionable bias, user decides.
PERFORMANCE METRICS & ROC TABLE
The indicator computes average 1-bar ROC for each cluster in:
Training set
Test (live) set
This helps measure:
Cluster profitability consistency
Regime forward predictability
Whether a regime is noise, trend, or reversion-biased
EQUITY SIMULATION & FEES
Designed for close-to-close realistic backtesting.
Position = cluster of previous bar
Fees applied only on regime switches. Meaning:
Staying long → no fee
Switching long→short → fee applied
Switching any→cash → fee applied
Fee input is percentage, but script already converts internally.
Disclaimers
⚠️ This indicator uses machine-learning but does not predict the future. It classifies similarity to past regimes, nothing more.
⚠️ Backtest results are not indicative of future performance.
⚠️ Clusters have no inherent “bullish” or “bearish” meaning. You must interpret them based on your testing and your own feature engineering.
ParabolicSAR+EMA[TS_Indie]🚀 EMA + Parabolic SAR Reversal Trading Strategy
This trading system effectively combines the use of Exponential Moving Averages (EMA) with the Parabolic SAR to identify both price trends and key reversal points. The EMA Fast is used to signal the primary short-term trend, while the EMA Slow acts as a filter for the long-term trend direction. The Parabolic SAR then helps to confirm the reversal signals.
🛠️ Tools Used
1. EMA Fast – Primary Short-Term Trend
2. EMA Slow – Long-Term Trend Filter
3. Parabolic SAR – Reversal Confirmation
🎯 Entry Rules
📈 Buy Setup
1. Trend Filter: EMA Fast > EMA Slow → Uptrend
2. Pullback: Price pulls back and closes below the EMA Fast line.
3. Reversal: Price reverses/pulls back up and closes above the EMA Fast line.
4. SAR Confirmation: The previous Parabolic SAR dot is above the high, and the dot in the current candle is below the low → Reversal signal confirmed.
5. Entry: Enter Buy immediately.
📉 Sell Setup
1. Trend Filter: EMA Fast < EMA Slow → Downtrend
2. Pullback: Price pulls back and closes above the EMA Fast line.
3. Reversal: Price reverses/pulls back down and closes below the EMA Fast line.
4. SAR Confirmation: The previous Parabolic SAR dot is below the low, and the dot in the current candle is above the high → Reversal signal confirmed.
5. Entry: Enter Sell immediately.
💰 Exit Management (Entry, Stop Loss, Take Profit)
1. Entry: Enter the order at the closing price of the signal candle.
2. Stop Loss (SL): Set the Stop Loss at the Parabolic SAR dot.
3. Take Profit (TP): Calculated from the Entry and Stop Loss points, multiplied by the Risk Reward Ratio.
⚙️ Optional Parameters
➭ Custom Risk/Reward Ratio for Take Profit.
➭ Option to add an ATR buffer to the Stop Loss.
➭ Adjustable EMA Fast period.
➭ Adjustable EMA Slow period.
➭ Adjustable Parabolic SAR parameters.
➭ Option to enable Long-only / Short-only positions.
➭ Customizable Backtest start and end date.
➭ Customizable trading session time.
🔔 Alert Function
Alerts display:
➭ Entry Price
➭ Stop Loss Price
➭ Take Profit Price
💡 This strategy allows for many parameter adjustments, such as the MA type, adding/subtracting from the Stop Loss using ATR, and selecting specific sessions for backtesting. If you find interesting or profitable results after adjusting the parameters, please share your comments with other traders!
⚠️ Disclaimer
This indicator is designed for educational and research purposes only. It does not guarantee profits and should not be considered financial advice. Trading in financial markets involves significant risk , including the potential loss of capital.
Forever ModelForever Model is a comprehensive trading framework that visualizes market structure through Fair Value Gaps (FVGs), Smart Money Technique (SMT) divergences, and order block confirmations. The indicator identifies potential price rotations by tracking internal liquidity zones, correlation breaks between assets, and confirmation signals across multiple timeframes.
Designed for clarity and repeatability, the model presents a structured visual logic that supports manual analysis while maintaining flexibility across different assets and timeframes. All components are non-repainting, ensuring historical accuracy and reliable backtesting.
Description
The model operates through a three-part sequence that forms the visual foundation for identifying potential market rotations:
Fair Value Gaps (FVGs)
FVGs are price imbalances detected on higher timeframes—areas where price moved rapidly between candles, leaving an inefficiency that may be revisited. The indicator identifies both bullish and bearish FVGs, displaying them with color-coded levels that extend until mitigated.
: Chart showing FVG detection with colored lines indicating bullish (green) and bearish (red) gaps
Smart Money Technique (SMT)
SMT detects divergence between the current chart asset and a correlated pair. When one asset makes a higher high while the other forms a lower high (or vice versa), it indicates a potential shift in delivery. The indicator draws visual lines connecting these divergence points and can filter SMTs to only display those occurring within FVG ranges.
: Chart showing SMT divergence lines between two correlated assets with labels indicating the pair name]
Order Block Confirmations (OB)
When price confirms a signal by crossing a pivot level, an Order Block is created. The confirmation line extends from the pivot point, labeled as "OB+" for bullish signals or "OB-" for bearish signals. The latest OB extends to the current bar, while previous OBs remain fixed at their confirmation points.
: Chart showing OB confirmation lines with OB+ and OB- labels at confirmation points]
Key Features
Higher Timeframe (HTF) Detection
FVGs are detected on a higher timeframe than the current chart, with automatic HTF selection based on the current timeframe or manual override options. This ensures that internal liquidity zones are identified from the appropriate structural context.
External Range Liquidity (ERL)
Tracks the latest higher timeframe pivot highs and lows, marking external liquidity levels that may be revisited. ERL levels are displayed as horizontal lines with optional labels, providing context for potential continuation targets.
: Chart showing ERL lines at recent HTF pivot points
Signal Creation and Confirmation System
The model creates pending signals when FVG levels are mitigated. Signals confirm when price closes beyond a pivot level, creating the OB confirmation line. Stop levels are automatically calculated from the maximum (bearish) or minimum (bullish) price between signal creation and confirmation.
SMT Filtering Options
Display all SMTs or only those within FVG ranges
Require SMT for signal confirmation (optional filter)
Automatic or manual SMT pair selection
Support for both correlated and inverse correlated pairs
Directional Bias Filter
Filter FVG detection to show only bullish bias, bearish bias, or both. This allows analysts to align with higher timeframe structure or focus on unidirectional setups.
Confirmation Line Management
Toggle to extend only the latest confirmation line or all confirmation lines
Transparent label backgrounds with colored text (red for bearish, green for bullish)
Automatic cleanup of old confirmation lines (keeps last 50)
Labels positioned at line end (latest) or middle (older lines)
Position Sizing Calculator
Optional position sizing based on account balance, risk percentage or fixed amount, and instrument-specific contract sizes. Supports prop firm calculations and can display position size, entry, and stop levels in the dashboard.
Information Dashboard
A customizable floating table displays:
Current timeframe and HTF
Remaining time in current bar
Current bias direction
Latest confirmed signal details (type, size, entry, stop)
Pending signal status
The dashboard can be repositioned, resized, and styled to match your preferences.
Special Range Creation
When signals confirm, the model can automatically create special range levels from stop prices. These levels persist on the chart as important reference points, even after mitigation, serving as potential reversal zones for future signals.
Label and Visualization Controls
Toggle FVG labels on/off
Toggle confirmation lines on/off
Customizable colors for bullish and bearish FVGs
ERL color customization
SMT line width adjustment
Order Flow Integration (Optional)
The indicator includes optional Open Interest (OI) based special range detection, allowing integration with order flow analysis for enhanced context.
Technical Notes
All components are non-repainting—once formed, they remain on the chart
FVGs cannot be mitigated on their creation bar
Signal-based special ranges persist even after mitigation (important stop levels)
SMT detection supports both HTF and chart timeframe modes
Maximum 50 confirmation lines are maintained for performance
The model is designed to work across all asset classes and timeframes, providing a consistent framework for identifying potential market rotations through the interaction of internal liquidity, correlation breaks, and confirmation signals, this does not constitute as trading advice, past performance is no indication of future performance , this is entirely done for entertainment and educational purposes
Dual Harmonic-based AHR DCA (Default :BTC-ETH)A panel indicator designed for dual-asset BTC/ETH DCA (Dollar Cost Averaging) decisions.
It is inspired by the Chinese community indicator "AHR999" proposed by “Jiushen”.
How to use:
Lower HM-based AHR → cheaper (potential buy zone).
Higher HM-based AHR → more expensive (potential risk zone).
Higher than Risk Threshold → consider to sell, but not suitable for DCA.
When both AHR lines are below the Risk threshold → buy the cheaper one (or split if similar).
If one AHR is above Risk → buy the other asset.
If both are above Risk → simulation shows “STOP (both risk)”.
Not limited to BTC/ETH — you can freely change symbols in the input panel
to build any dual-asset DCA pair you want (e.g., BTC/BNB, ETH/SOL, etc.).
What you’ll see:
Two lines: AHR BTC (HM) and AHR ETH (HM)
Two dashed lines: OppThreshold (green) and RiskThreshold (red)
Colored fill showing which asset is cheaper (BTC or ETH)
Buy markers:
- B = Buy BTC
- E = Buy ETH
- D = Dual (split budget)
Top-right table: prices, AHRs, thresholds, qOpp/qRisk%, simulation, P&L
Labels showing last-bar AHR values
Core idea:
Use an AHR based on Harmonic Moving Average (HM) — a ratio that measures how “cheap or expensive” price is relative to both its short-term mean and long-term trend.
The original AHR999 used SMA and was designed for BTC only.
This indicator extends it with cross-exchange percentile mapping, allowing the empirical “opportunity/risk” zones of the AHR999 (on Bitstamp) to adapt automatically to the current market pair.
The indicator derives two adaptive thresholds:
OppThreshold – opportunity zone
RiskThreshold – risk zone
These thresholds are compared with the current HM-based AHR of BTC and ETH to decide which asset is cheaper, and whether it is good to DCA or not, or considering to sell(When it in risk area).
This version uses
Display base: Binance (default: perpetual) with HM-based AHR
Percentile base: Bitstamp spot SMA-AHR (complete, stable history)
Rolling window: 2920 daily bars (~8 years) for percentile tracking
Concept summary
AHR measures the ratio of price to its long-term regression and short-term mean.
HM replaces SMA to better reflect equal-fiat-cost DCA behavior.
Cross-exchange percentile mapping (Bitstamp → Binance) keeps thresholds consistent with the original AHR999 interpretation.
Recommended settings (1D):
DCA length (harmonic): 200
Log-regression lookback: 1825 (≈5 years)
Rolling window: 2920 (≈8 years)
Reference thresholds: 0.45 / 1.20 (AHR999 empirical priors)
Tie split tolerance (ΔAHR): 0.05
Daily budget: 15 USDT (simulation)
All display options can be toggled: table, markers, labels, etc.
Notes:
When the rolling window is filled (2920 bars by default), thresholds are first calculated and then visually backfilled as left-extended lines.
The “buy markers” and “decision table” are light simulations without fees or funding costs — for rhythm and relative analysis, not backtesting.
Crypto Futures Basis Tracker (Annualized)🧩 What is Basis Arbitrage
Basis arbitrage is a market-neutral trading strategy that exploits the price difference between a cryptocurrency’s spot and its futures markets.
When futures trade above spot (called contango), traders can buy spot and short futures, locking in a potential yield.
When futures trade below spot (backwardation), the reverse applies — short spot and go long futures.
The yield earned (or cost paid) by holding this position until expiry is called the basis. Expressing it as an annualized percentage allows comparison across different contract maturities.
⚙️ How the Indicator Works
This tool calculates the annualized basis for up to 10 cryptocurrency futures against a chosen spot price.
You select one spot symbol (e.g., BITSTAMP:BTCUSD) and up to 10 futures symbols (e.g., DERIBIT:BTCUSD07X2025, DERIBIT:BTCUSD14X2025, etc.).
The script automatically computes the days-to-expiry (DTE) and the annualized basis for each future.
A table displays for each contract: symbol, expiry date, DTE, last price, and annualized basis (%) — making it easy to compare the forward curve across maturities.
⚠️ Risks and Limitations
While basis arbitrage is often considered low-risk, it’s not risk-free:
Funding and financing costs can erode returns, especially when borrowing or using leverage.
Exchange or counterparty risk — if one leg of the trade fails (e.g., exchange default, margin liquidation), the hedge breaks.
Execution and timing risk — the basis can tighten or invert before both legs are opened.
Liquidity differences — thin futures may have large bid-ask spreads or slippage.
Use this indicator for analysis and monitoring, not as an automated trading signal.
Disclaimer: Please remember that past performance may not be indicative of future results. Due to various factors, including changing market conditions, the strategy may no longer perform as well as in historical backtesting. This post and the script don't provide any financial advice.
