Elliott Wave Supply-Demand Strategyelliot wave strategy in chart time frame: The updated Pine Script enhances the Elliott Wave Supply-Demand Strategy by adding lines connecting wave points (1-2-3-4-5 or A-B-C) for visual clarity. It detects impulse (5-point) and ABC (3-point) patterns using pivot highs/lows, storing swings in arrays. Lines are drawn between consecutive wave labels (e.g., 1→2, A→B) using a user-defined color and style (solid, dashed, dotted), with a new show_wave_lines input. A debug label displays swing count, wave detection status, and label count to troubleshoot issues. The visibility window for labels and lines is extended to 1000 bars to ensure recent patterns are shown. Supply/demand zones and Fibonacci extensions remain unchanged, supporting rejection-based trades. If lines don’t appear, check the debug label for low swing counts or adjust pivot_left/pivot_right. The script is optimized for liquid markets (e.g., EUR/USD) and customizable timeframes. Alerts and trading logic are preserved.
在腳本中搜尋"the script"
Larry Williams Bonus Track PatternThis strategy trades the day immediately following an Inside Day, under specific directional and timing conditions. It is designed for daily-based setups but executed on intraday charts to ensure orders are placed exactly at the open of the following day, rather than at the daily bar close.
Entry Conditions
Only trades on Monday, Thursday, or Friday.
The previous day must be an Inside Day (its high is lower than the prior high and its low is higher than the prior low).
The bar before the Inside Day must be bullish (close > open).
On the following day (t):
The daily open must be below both the Inside Day’s high and the highest high of the two days before that.
A buy stop is placed at the highest high of the three previous days (Inside Day and the two days before it).
If the new day’s open is already above that level (gap up), the strategy enters long immediately at the open.
Exit Rules
Stop Loss: Fixed, defined in points or percentage (user input).
FPO (First Profitable Open): the position is closed at the first daily open after the entry day where the open price is above the average entry price (the first profitable open).
Notes
The script must be applied on an intraday timeframe (e.g., 15-minute or 1-hour) so that the strategy can:
Detect the Inside Day pattern using daily data (request.security).
Execute orders in real time at the next day’s open.
Running it directly on the daily timeframe will delay executions by one bar due to Pine Script’s evaluation model.
Adaptive Chikou Strategy - Level 1This strategy is based on the Ichimoku cloud system and the power of delaying the signal. I changed how the averages are calculated to better detect the range areas.
The strategy uses this concept to determine the market regime, whether the price is below or above its delayed signal, and acts accordingly:
Bull (green) – when the price is above the average of the highs, delayed, the strategy favors long entries.
Bear (red) – when the price is below the average of the lows delayed, the strategy favors short entries.
Range (brown) – when the percent rank is in between those 2 conditions, we detect range, and no trades are initiated.
The transition between these regimes depends mainly on 4 key parameters.
The first parameter controls the lookback period for the highest and lowest functions.
The second controls how much we delay the signal of these 2 functions.
The third adjusts how much range is detected in bull conditions; it changes the transition from bull to range conditions. The bigger it is, the less bull and the more range.
The fourth parameter is similar to the third, but for bear conditions. The bigger it is, the less bear and the more range conditions are detected.
The user can configure the strategy to run long-only, short-only, or both directions, depending on the market or preference. In addition to the core regime logic, the strategy includes several risk and trade management controls that are featured in all my strategies.
Four oscillators are also integrated into the logic to detect short-term overbought and oversold conditions. These help the strategy avoid entering or exiting a trade when the price has already extended too far in one direction, improving timing and potentially reducing false entries and exits. When overbought or oversold are detected, a red or green dot appears on the chart.
The script is designed to be flexible across different assets and timeframes. However, to achieve consistent results, it is important to optimize parameters carefully. A recommended workflow is as follows:
Disable the walk-forward option during the optimization phase.
Optimize the first main parameter while keeping others fixed.
Once a satisfactory value is found, move to the second parameter.
Continue the process for subsequent parameters.
Optionally, repeat the full sequence once more to refine the results.
Finally, activate walk-forward analysis and check the out-of-sample results.
This strategy is published as invite-only with hidden source code. Access may be granted upon request for research or evaluation purposes. It is part of a broader collection of technical analysis strategies I have developed, which focus on regime detection and adaptive trading systems.
There are five levels of strategy complexity and performance in my collection. This script represents a Level 1 strategy, designed as a solid foundation and introduction to the framework. More advanced levels progressively add greater complexity, adaptability, and robustness.
When multiple strategies are combined under this same framework, the results become more robust and stable. In particular, combining my suite of technical analysis strategies with my macro strategies and alternative data strategies, such as onchain for cryptocurrencies. It creates a multi-layered system that adapts across regimes, timeframes, and market conditions.
Percent Rank Strategy - Level 1This strategy is based on the Percent Rank math, a statistical measure that evaluates how the current price compares to its historical prices over a specified lookback period.
In simple terms, Percent Rank tells you the percentile position of the current price within a recent window, for example, a value of 80% means the price is higher than 80% of the previous prices in that period, while 20% means it’s lower than 80% of them.
The strategy uses this concept to determine the market regime, whether price is high, low, or neutral relative to its recent range, and acts accordingly:
Bull (green) – when the price percent rank is usually above 50% the price is normally high, and the strategy favors long entries.
Bear (red) – when the price percent rank is usually below 50% the price is normally low, and the strategy favors short entries.
Range (brown) – when the percent rank is in between those 2 conditions, we detect range, and no trades are initiated.
The transition between these regimes depends mainly on 3 key parameters.
The first parameter controls the maximum lookback period for the percent rank array and so the maximum cycle length.
The second controls how much range is detected in bull conditions; it changes the transition from bull to range conditions. The bigger it is, the less bull and the more range.
The third parameter is similar to the second, but for bear conditions. The smaller it is, the less bear and the more range conditions are detected.
The user can configure the strategy to run long-only, short-only, or both directions, depending on the market or preference. In addition to the core regime logic, the strategy includes several risk and trade management controls that are featured in all my strategies.
Four oscillators are also integrated into the logic to detect short-term overbought and oversold conditions. These help the strategy avoid entering or exiting a trade when the price has already extended too far in one direction, improving timing and potentially reducing false entries and exits. When overbought or oversold are detected, a red or green dot appears on the chart.
The script is designed to be flexible across different assets and timeframes. However, to achieve consistent results, it is important to optimize parameters carefully. A recommended workflow is as follows:
Disable the walk-forward option during the optimization phase.
Optimize the first main parameter while keeping others fixed.
Once a satisfactory value is found, move to the second parameter.
Continue the process for subsequent parameters.
Optionally, repeat the full sequence once more to refine the results.
Finally, activate walk-forward analysis and check the out-of-sample results.
This strategy is published as invite-only with hidden source code. Access may be granted upon request for research or evaluation purposes. It is part of a broader collection of technical analysis strategies I have developed, which focus on regime detection and adaptive trading systems.
There are five levels of strategy complexity and performance in my collection. This script represents a Level 1 strategy, designed as a solid foundation and introduction to the framework. More advanced levels progressively add greater complexity, adaptability, and robustness.
When multiple strategies are combined under this same framework, the results become more robust and stable. In particular, combining my suite of technical analysis strategies with my macro strategies and alternative data strategies, such as onchain for cryptocurrencies. It creates a multi-layered system that adapts across regimes, timeframes, and market conditions.
Kootch Moon Phase Strategy🌙 Moon Phases Equity Strategy
This strategy explores the relationship between lunar cycles and equity price action.
It is based on a simple idea: markets may respond differently around New Moons and Full Moons.
🛠 How it works
• New Moon → Long Entry
The strategy enters a long position at the first bar after a New Moon event.
• Full Moon → Exit
The strategy closes the long position at the first bar after the following Full Moon.
• Optional Filters
• 200-day Moving Average (on by default): only take longs in bullish regimes.
• ATR-based Stops & Targets: risk management can be added with configurable multiples of ATR.
• Minimum Gap: ensures a cooldown period between trades to avoid clustering.
• Position Sizing: by default, trades risk a configurable % of equity (set to 35%).
📊 Notes
• This script is designed for equities (stocks, ETFs).
• It is a long-only system by default. If you enable “Always Flip,” the script will alternate long/short each lunar phase, but that is more experimental.
• Results can vary widely depending on the underlying asset. Trending stocks (e.g., AMZN, AAPL, SPY) tend to perform better with the long-only mode.
• Risk/Reward tracking in R-multiples is included for more consistent performance evaluation.
⚠️ Disclaimer
This strategy is for educational and research purposes only. It does not guarantee profitability and should not be used as financial advice. Past performance does not indicate future results. Always backtest on your preferred instruments and use sound risk management.
RSI Momentum ScalperOverview
The "RSI Momentum Scalper" is a Pine Script v5 strategy crafted for trading highly volatile markets, with a special focus on newly listed cryptocurrencies. This strategy harnesses the Relative Strength Index (RSI) alongside volume analysis and momentum thresholds to pinpoint short-term trading opportunities. It supports both long and short trades, managed with customizable take profit, stop loss, and trailing stop levels, which are visually plotted on the chart for easy tracking.
Why I Created This Strategy
I developed the "RSI Momentum Scalper" because I was seeking a reliable trading strategy tailored to newly listed, highly volatile cryptocurrencies. These assets often experience rapid price fluctuations, rendering traditional strategies less effective. I aimed to create a tool that could exploit momentum and volume spikes while managing risk through adaptable exit parameters. This strategy is designed to address that need, offering a flexible approach for traders in dynamic crypto markets.
How It Works
The strategy utilizes RSI to identify momentum shifts, combined with volume confirmation, to trigger long or short entries. Trades are controlled with take profit, stop loss, and trailing stop levels, which adjust dynamically as the price moves in your favor. The trailing stop helps lock in profits, while the plotted exit levels provide clear visual cues for trade management.
Customizable Settings
The script is highly customizable, allowing you to adjust it to various market conditions and trading styles. Here’s a brief overview of the key settings:
Trade Mode: Select "Both," "Long Only," or "Short Only" to determine the trade direction.
(Default: Both)
RSI Length: Sets the lookback period for the RSI calculation (2 to 30).
(Default: 8)
A shorter length increases RSI sensitivity, suitable for volatile assets.
RSI Overbought: Defines the upper RSI threshold (60 to 99) for short entries.
(Default: 90)
Higher values signal stronger overbought conditions.
RSI Oversold: Defines the lower RSI threshold (1 to 40) for long entries.
(Default: 10)
Lower values indicate stronger oversold conditions.
RSI Momentum Threshold: Sets the minimum RSI momentum change (1 to 15) to trigger entries.
(Default: 14)
Adjusts the sensitivity to price momentum.
Volume Multiplier: Multiplies the volume moving average to filter high-volume bars (1.0 to 3.0).
(Default: 1)
Higher values require stronger volume confirmation.
Volume MA Length: Sets the lookback period for the volume moving average (5 to 50).
(Default: 13)
Influences the volume trend sensitivity.
Take Profit %: Sets the profit target as a percentage of the entry price (0.1 to 10.0).
(Default: 4.15)
Determines when to close a winning trade.
Stop Loss %: Sets the loss limit as a percentage of the entry price (0.1 to 6.0).
(Default: 1.85)
Protects against significant losses.
Trailing Stop %: Sets the trailing stop distance as a percentage (0.1 to 4.0).
(Default: 2.55)
Locks in profits as the price moves favorably.
Visual Features
Exit Levels: Take profit (green), fixed stop loss (red), and trailing stop (orange) levels are plotted when in a position.
Performance Table: Displays win rate, total trades, and net profit in the top-right corner.
How to Use
Add the strategy to your chart in TradingView.
Adjust the input settings based on the cryptocurrency and timeframe you’re trading.
Monitor the plotted exit levels for trade management.
Use the performance table to assess the strategy’s performance over time.
Notes
Test the strategy on a demo account or with historical data before live trading.
The strategy is optimized for short-term scalping; adjust settings for longer timeframes if needed.
Composite PR Signal (Trend↔Revert + ADX gate)Core Components
1. Dynamic Inputs
Max/PR windows (maxLen, prWin) – define historical lookbacks for oscillators and percentile ranks.
Smoothing (smooth) – applies an EMA filter to stabilize composite scores.
Threshold (th) – governs entry sensitivity.
Holding period (hBars) – maximum bars allowed in a trade.
Execution options – allow shorting, fast approximations for PR and CCI.
2. Custom Utility Functions
The script implements optimized versions of common TA operations:
Rolling sums, delays, and moving averages (EMA, RMA, SMA).
Lazy rolling extrema (efficient highest/lowest lookups).
Stateful arrays for tracking oscillator values across bars.
Fast approximations for percentile ranks and indicators.
3. Indicators Used
The system calculates a broad set of oscillators, including:
Trend/Momentum: ROC, TRIX, TSI, MACD histogram, OBV ROC, AO, CMF, BOP, UO, ADX.
Reversion/Oscillators: RSI, Stochastic K/D, MFI, Williams %R, CCI, CMO.
Each is converted into a percentile rank (PR) to normalize values between 0–100.
4. Composite Scoring
Two composite signals are built:
Trend Score – averages normalized outputs of momentum indicators.
Reversion Score – averages normalized outputs of oscillators prone to mean reversion.
ADX Gate – when ADX PR is high, the strategy favors trend score; when low, it favors reversion score.
Final score is smoothed and compared against entry thresholds.
5. Trade Logic
Entry:
Long: When composite score crosses above +th.
Short: When composite score crosses below -th (if enabled).
Exit:
Opposite crossover signal.
Or trade duration exceeds hBars.
6. Risk/Execution Parameters
Initial capital: 100,000
Commission: 0.01% per trade
Fixed order size: 100 units
No pyramiding
Intended Use
This script is designed for:
Swing trading across multiple assets (equities, forex, crypto).
Adapting to market regimes — capturing breakouts during strong trends, but fading moves when markets are choppy.
CoinGpt NQ策略# CoinGpt NQ 策略（MACD·多因子·可金字塔）
## 概述
**CoinGpt NQ策略**是一套面向 **纳指期货 NQ（建议：`CME_MINI:NQ1!`）30 分钟** 的可运行交易策略。
核心以 **MACD 趋势动量** 为骨架，叠加 **EMA 趋势过滤**、**可选金字塔加仓**、**三种出场模式（固定 TP/SL、追踪、追踪+TP）** 与 **风控上限**，提供三套一键预设（Balanced / Trend / Scalper），满足不同市场状态与风险偏好。
> 适配：期货/连续合约；仅做多（本脚本版本）。
> 时间框架：**30m**（可在“仅在 30m 生效”开关控制）。
---
## 进场逻辑
* **信号触发**：`MACD 上穿 Signal`（并要求直方图连续上升 2 根）。
* **趋势过滤**：价格位于 `EMA(p_emaLen)` 上方，且 `MACD>0 & Signal>0`（可关闭）。
* **时间框架限制**：默认仅在 30m 有效（可关闭）。
## 出场逻辑
* **固定 TP/SL**：按百分比计算限价止盈与止损。
* **追踪止盈**：默认以 **ATR 偏移** 跟踪；
* **追踪 + TP**：在拖尾的同时设置上沿 TP。
* **反向保护**：`MACD 下穿 Signal` 时市价平仓。
> 出场模式在输入项 **「出场模式」** 选择：
> `Auto(by preset) / Fixed TP/SL / Trailing / Trailing + TP`
---
## 金字塔加仓（可选）
* 仅在已有多单且不利回撤达到阈值时触发；
* 最多 `p_maxAdds` 层；每层在 **上次加仓价** 基础上按 `p_addStep%` 回撤触发；
* 目的：**拉低均价、提高持仓性价比**；采用小步长、有限层数控制回撤风险。
---
## 风险管理
* **当日最大亏损**：`strategy.risk.max_intraday_loss(p_maxDailyDD, %权益)`
* **单笔头寸上限**：`strategy.risk.max_position_size(p_posCapPct)`
* **订单量**（策略属性）：默认 **90% 权益**。
* 实盘更建议：Balanced≈**40%**、Trend≈**35%**、Scalper≈**30%**（在“策略属性 → 订单大小”中调整）。
---
## 三套预设（参数一键生效）
| 预设 | MACD(fast/slow/signal) | 趋势EMA | 金字塔 | 加仓步长 | 固定TP/SL(%) | 追踪(ATR倍数) | 单笔上限 | 当日亏损 |
| ---------------- | ---------------------- | ----- | --- | ----- | ----------------- | --------- | ---- | ---- |
| **Balanced（默认）** | 8 / 21 / 5 | 233 | 2 层 | 0.12% | TP 0.22 / SL 0.15 | 1.2× | 50% | 1.5% |
| **Trend** | 10 / 24 / 7 | 200 | 3 层 | 0.10% | TP 0.25 / SL 0.18 | 1.6× | 45% | 1.2% |
| **Scalper** | 6 / 19 / 4 | 100 | 关闭 | —— | TP 0.18 / SL 0.12 | 1.3× | 35% | 1.0% |
> 说明：
>
> * Balanced：均衡型，适合多数时期；
> * Trend：顺势拉伸，持仓更久、盈亏比更高；
> * Scalper：快进快出、高胜率、不过度叠仓。
---
## 使用建议
1. **品种/周期**：`CME_MINI:NQ1!`（或当季主力合约），**30m**。
2. **手续费**：本策略默认 **1 USD/合约**（在“策略属性”可按实盘成本调整）。
3. **成交精度**：建议在“策略属性 → 高级设置”勾选 **Bar Magnifier**，提升限价/拖尾成交模拟精度。
4. **仓位**：策略默认 90% 仅为展示；回测与实盘更建议 **30%\~40% 权益**。
5. **风险**：金字塔仅做轻量、有限层数；若市场极端震荡，适当降低单笔上限与当日亏损阈值。
---
## 输入项（TradingView 右侧面板）
* **参数预设**：`Balanced / Trend / Scalper`
* **仅在 30m 周期生效**：开/关
* **出场模式**：`Auto(by preset) / Fixed TP/SL / Trailing / Trailing + TP`
> 其余细节参数由预设自动注入，无需手动繁杂调整，**开箱即用**。
---
## 注意事项
* 本脚本为研究与教育用途，不构成投资建议。期货与杠杆交易风险高，请在可承受范围内使用。
* 预设适配历史统计特征，未来表现不保证；建议结合自身风控与账户规模，先小仓/纸面验证。
* 仅做多版本；若需要双向（多空）或加入 RTH（美股盘中）/HTF（更高周期确认）等扩展，请在评论区留言。
---
**作者注**：
* 本策略在 Pine v6 编写，避免了常见的 v6 语法踩坑（如 `strategy.risk.max_position_size()` 仅 1 参、`plot` 标题需常量、追踪需成对参数 `trail_price + trail_offset` 等）。
* 欢迎在评论区反馈你的回测截图（区间、手续费、订单量），我会根据数据给出更贴合你的参数档。
# CoinGpt NQ Strategy (MACD · Multi-Factor · Optional Pyramiding)
## Overview
**CoinGpt NQ Strategy** is a ready-to-trade system for **Nasdaq-100 futures (NQ; recommended: `CME_MINI:NQ1!`) on the 30-minute timeframe**.
It uses **MACD momentum** as the backbone, adds an **EMA trend filter**, optional **pyramiding**, and **three exit modes** (Fixed TP/SL, Trailing, Trailing+TP) with built-in risk caps. Three one-click presets—**Balanced / Trend / Scalper**—cover different regimes and risk appetites.
> Instruments: futures / continuous contract
> Direction: **Long-only** (this script version)
> Timeframe: **30m** (toggleable)
---
## Entry
* **Trigger:** `MACD` line crossing **above** `Signal`.
* **Trend filter (optional):** price above `EMA(p_emaLen)` and `MACD > 0 & Signal > 0`.
* **Timeframe guard:** by default, signals are valid on **30m** only.
## Exit
* **Fixed TP/SL:** percentage-based limit and stop.
* **Trailing:** ATR-based trailing offset (or percent).
* **Trailing + TP:** trailing stop **and** a take-profit cap.
* **Protective flip:** when `MACD` crosses **below** `Signal`, close the long.
> Choose exit mode in **Inputs → “Exit Mode”**:
> `Auto(by preset) / Fixed TP/SL / Trailing / Trailing + TP`.
---
## Pyramiding (optional)
* Adds only **against adverse pullbacks** from the last add price.
* Up to `p_maxAdds` layers; each layer triggers at `p_addStep%` pullback from the **previous add**.
* Goal: **improve average price** with **small steps & limited layers** to keep drawdowns controlled.
---
## Risk Management
* **Daily loss cap:** `strategy.risk.max_intraday_loss(p_maxDailyDD, % of equity)`.
* **Per-trade size cap:** `strategy.risk.max_position_size(p_posCapPct)`.
* **Order size (strategy properties):** default **90% of equity** (for display).
* Practical suggestion: Balanced ≈ **40%**, Trend ≈ **35%**, Scalper ≈ **30%** (set in Strategy Properties → Order size).
---
## Presets (one-click)
| Preset | MACD (fast/slow/signal) | Trend EMA | Pyramiding | Add Step | Fixed TP/SL (%) | Trailing (ATR) | Pos Cap | Daily DD |
| ---------------------- | ----------------------- | --------- | ---------- | -------- | ------------------------- | -------------- | ------- | -------- |
| **Balanced (default)** | 8 / 21 / 5 | 233 | 2 layers | 0.12% | TP **0.22** / SL **0.15** | **1.2×** | **50%** | **1.5%** |
| **Trend** | 10 / 24 / 7 | 200 | 3 layers | 0.10% | TP **0.25** / SL **0.18** | **1.6×** | **45%** | **1.2%** |
| **Scalper** | 6 / 19 / 4 | 100 | Off | — | TP **0.18** / SL **0.12** | **1.3×** | **35%** | **1.0%** |
> **Balanced:** all-weather, stable.
> **Trend:** holds longer and targets higher R multiples.
> **Scalper:** quick in/out, higher hit-rate, no stacking.
---
## Usage Tips
1. **Symbol/TF:** `CME_MINI:NQ1!`, **30m**.
2. **Fees:** default **\$1 per contract** (adjust to your broker in Strategy Properties).
3. **Execution realism:** enable **Bar Magnifier** (Strategy Properties → Advanced) for more accurate limit/trailing fills.
4. **Sizing:** the script defaults to 90% only to showcase behavior—use **30–40%** in realistic tests.
5. **Pyramiding:** keep layers small & capped. In choppy regimes, reduce `p_posCapPct` and `p_maxDailyDD`.
---
## Inputs (right-panel)
* **Param Preset:** `Balanced / Trend / Scalper`
* **30m-only:** on/off
* **Exit Mode:** `Auto(by preset) / Fixed TP/SL / Trailing / Trailing + TP`
> All other parameters are pre-wired by the chosen preset for **plug-and-play** operation.
---
## Notes & Disclaimer
* Educational use only—**not** financial advice. Futures and leverage carry substantial risk.
* Presets reflect historical characteristics; **future performance is not guaranteed**. Start small or paper trade first.
* This version is **long-only**; if you need a two-sided (long & short) variant or extras (RTH/HTF filters), leave a comment.
---
**Author Notes**
* Written in **Pine v6** with common pitfalls avoided (e.g., `strategy.risk.max_position_size()` takes **one** arg, `plot` titles are **const strings**, trailing requires `trail_price + trail_offset`).
* Share your backtest screenshots (period, fees, order size) and I can suggest **tighter, data-driven knobs** for your setup.
Delta Drift Allocator - StrategySummary
Bar-close, drift-based allocation alerts that keep exposure centered around a user-set base with full compounding by default. One alert per bar close. Non-repainting. Invite-Only.
Description
Delta Drift Allocator monitors how far current exposure drifts from a reference profile. When drift exceeds your threshold, it issues a single bar-close instruction (BUY/SELL with quantity) to nudge exposure back toward center. The emphasis is path discipline—rules that react to swings without predicting direction—plus a simple one-alert workflow.
A start-sync input lets you align the script with your actual initial fill so subsequent sizes match your account. Profit handling supports Reinvest (compound) or Skim to base (bookkeep excess).
How to use (overview)
Add to chart (recommended timeframe: 4h).
Set Inputs: drift threshold, min notional, start method (Auto or Manual sync at your bar-close time + filled units).
Create one alert: This strategy → Any alert() function call, Once per bar close. Leave Message empty.
Execute externally: place BUY/SELL for exactly the shown qty (manual or your own webhook executor outside TradingView).
Note: A detailled manual is provided after purchase.
Why traders choose it
Bar-close discipline (no intra-bar churn, non-repainting)
Drift-responsive adjustments that can harvest parts of oscillations
Full compounding by default; optional “skim to base” bookkeeping
Start-sync to match real fills; minimal panel plots you can hide
Access (Invite-Only)
To request access, send me a PM on TradingView. You’ll receive detailled information about the process.
Note: Requests for older strategies are no longer processed—please refer to this release only.
Compliance
Signals only; the script does not place orders or read balances. Backtests are approximations and are not indicative of future results. Markets involve risk, including possible loss. Extended one-way advances can lag all-in exposure; starting right after strong rallies may show initial drawdowns.
Maiko Range Scalper (Sideways BB + RSI) – v4 cleanPurpose
It’s a range scalping strategy for crypto. It tries to take small, repeatable trades inside a sideways market: buy near the bottom of the range, sell near the middle/top (and the reverse for shorts).
Core idea (two timeframes)
Define the trading range on a higher timeframe (HTF)
You choose the HTF (e.g., 15m or 1h).
The script finds the highest high and lowest low over a lookback window (e.g., last 96 HTF candles) → these become HTF Resistance and HTF Support.
It also calculates the midline (average of support/resistance).
Trade signals on your lower timeframe (LTF)
You run the strategy on a fast chart (e.g., 1m or 5m).
Entries are only allowed inside the HTF range.
Entry logic (mean reversion)
Indicators on the LTF:
Bollinger Bands (length & std dev configurable).
RSI (length & thresholds configurable).
Optional VWAP proximity filter (price must be within X% of VWAP).
Long setup:
Price touches/under-cuts the lower Bollinger band AND RSI ≤ threshold (default 30) AND price is inside the HTF range (and passes VWAP filter if enabled).
Short setup:
Price touches/exceeds the upper Bollinger band AND RSI ≥ threshold (default 70) AND price is inside the HTF range (and passes VWAP filter if enabled).
Exits and risk
Stop-loss: placed just outside the HTF range with a configurable buffer %:
Long SL = HTF Support × (1 − buffer).
Short SL = HTF Resistance × (1 + buffer).
Take-profit (selectable):
Mid band (the Bollinger basis) → conservative, faster exits.
Opposite band / HTF boundary → more aggressive, higher RR but more give-backs.
Position sizing
A simple cap: maximum position size = percent of account equity (e.g., 20%).
The script calculates quantity from that cap and current price.
Plots you’ll see on the chart
HTF Resistance (red) and HTF Support (green) via plot().
HTF Midline (gray dashed) drawn with a line.new() object (because plot() cannot do dashed).
Bollinger basis/upper/lower on the LTF.
Optional VWAP line (only shown if you enable the filter).
Signal markers (green triangle up for Long setups, red triangle down for Short setups).
Alerts
Two alertconditions:
“Long Setup” – when a long entry condition appears.
“Short Setup” – when a short entry condition appears.
Create alerts from these to get notified in real time.
How to use it (quick start)
Add to a 1m or 5m chart of a liquid coin (BTC, ETH, SOL).
Set HTF timeframe (start with 1h) and lookback (e.g., 96 = ~4 days on 1h).
Keep default Bollinger/RSI first; tune later.
Choose TP mode:
“Mid band” for quick scalps.
“Opposite band/Range” if the range is very clean and you want bigger targets.
Set SL buffer (0.15–0.30% is common; adjust for volatility).
Set Max position % to control size (e.g., 20%).
(Optional) Enable VWAP filter to skip stretched moves.
When it works best
Clearly sideways markets with visible support/resistance on the HTF.
High-liquidity pairs where spreads/fees are small relative to your scalp target.
Limitations & safety notes
True breakouts will invalidate mean-reversion logic—your SL outside the range is there to cut losses fast.
Fees can eat into small scalps—prefer limit orders, rebates, and liquid pairs.
Backtest results vary by exchange data; always forward-test on small size.
If you want, I can:
Add an ATR-based stop/target option.
Provide a study-only version (signals/alerts, no trading engine).
Pre-set risk to your €5,000 plan (e.g., ~0.5% max loss/trade) with calculated qty.
EMA inFusion Pro - Multiple SourcesEMA Fusion Pro: Dynamic Trend & Momentum Strategy with Three Exit Modes
EMA Fusion Pro is a highly customizable, multi-exit trend-following strategy designed for traders who value both precision and flexibility. By leveraging exponential moving averages (EMA), average directional index (ADX), and volume analysis, this strategy aims to capture trending market moves while offering three distinct exit modes for optimal risk management across varying market conditions.
Strategy Overview
This strategy systematically identifies potential entry points using a moving average crossover with highly configurable data sources (including price, volume, rate of change, or their Heikin Ashi versions) and filters signal quality with ADX trend strength and volume spikes. Each trade is managed with one of three advanced exit methodologies—reverse signal, ATR-based stop/take profit, or fixed percentage—giving you the control to adapt your risk profile to different market regimes.
Key Features
Customizable EMA Source: Calculate the core trend-filtering EMA from price (default), volume, rate of change, or their Heikin Ashi counterparts for unique market perspectives.
Trend Filter with ADX: Confirm entries only when the trend is strong, as measured by the user-adjustable ADX threshold.
Volume Spike Confirmation: Optional filter to only take trades with above-average volume activity, reducing false signals.
Three Exit Modes:
Reverse Signal: Exit trades when a new, opposite entry signal occurs.
ATR-Based Stop/Take Profit: Dynamic risk management using multiples of the average true range (ATR) for both take profit and stop loss.
Percent-Based Stop/Take Profit: Fixed-percentage risk management with user-defined thresholds.
Visual Annotations: Signal markers, EMA line color-coded by source, trend background coloring, and optional ATR/percent-based TP/SL levels.
Info Panel: Real-time display of all core indicators, current trading mode, exit parameters, and position status for quick oversight.
How It Works
Entry Logic: A crossover signal (above/below the EMA) triggers a new entry, but only if both ADX trend strength and (optionally) volume spike conditions are met.
Exit Logic: Three selectable modes allow you to exit trades on reverse signals, at a dynamic ATR-based profit or loss, or at a fixed percentage gain/loss.
Flexible Data Analysis: The EMA source can be chosen from six options—standard price, volume, rate of change, or their Heikin Ashi variants—allowing experimentation with different market dimensions.
Risk Management: All exits are precisely controlled, either by the next opposing signal, by volatility-adjusted levels, or by fixed risk/reward ratios.
Backtest & Optimization: The strategy is fully backtestable within TradingView’s Strategy Tester, with adjustable parameters for optimization.
Customization & Usage
Indicator Source: Select your preferred data type for EMA calculation, opening the door to creative strategy variations (e.g., volume momentum, pure price trend, rate of change divergence).
Filter Toggles: Enable/disable ADX and volume filters as desired—useful for different market environments.
Exit Mode Selection: Switch between reverse, ATR, or percent-based exits with a single parameter—ideal for adapting to ranging vs. trending markets.
Visual Clarity: The EMA line color reflects its underlying source, and the info panel summarizes all critical values for easy monitoring.
Who Should Use This Strategy?
Trend Followers seeking to ride strong moves with multiple exit options.
Experienced Traders who want to experiment with different data types (volume, momentum, Heikin Ashi) for trend analysis.
Algorithmic Traders looking for a robust, flexible base to build upon with their own ideas.
Getting Started
Apply the script to your chart and review default settings.
Customize parameters—EMA length, ADX threshold, volume settings, exit type—as desired.
Backtest on multiple instruments and timeframes to evaluate performance.
Optimize filters, exit rules, and risk parameters for your preferred trading style.
Monitor with the real-time info panel and trade alerts.
Disclaimer
This script is for educational and entertainment purposes only. It is not financial advice. Past performance is not indicative of future results. Always conduct thorough testing and consider your risk tolerance before trading real capital.
— Happy Trading —
Feel free to adapt, share, and contribute to this open-source strategy!
Ifvgs with Targets
This strategy identifies inversion fair value gaps on the 1-5 minute timeframe that occur with a 5 or 15 minute unfilled fair value gap existing in the direction of the trade.
The script marks out the 5 and 15 minute unfilled gap targets with red and green lines.
The script also calculates how many contracts to enter based on the risk and dollar per point value that you set in the settings.
Trades are triggered upon a candle closure that inverses the fair value gap. When a trade is triggered, a bold red line is drawn at the suggested stop loss (low of the body of the gap), and a bold green line is drawn at the price level that is a 1R distance from the entry.
This strategy will only run on the 1-5 minute timeframes, and is designed specifically for Nasdaq futures (NQ or MNQ).
The suggested way to use this indicator is by adding alerts to be notified when an IFVG occurs.
Add alerts by going to the three dots next to the indicator, selecting "Add alert", and then setting the condition to "alert() function calls only". This will alert you on potential trades before the trade actually triggers on the candle closure, so you have time to look at the setup before the entry.
Do not follow this indicator blindly, always do your own analysis and use this as a tool.
The Barking Rat LiteMomentum & FVG Reversion Strategy
The Barking Rat Lite is a disciplined, short-term mean-reversion strategy that combines RSI momentum filtering, EMA bands, and Fair Value Gap (FVG) detection to identify short-term reversal points. Designed for practical use on volatile markets, it focuses on precise entries and ATR-based take profit management to balance opportunity and risk.
Core Concept
This strategy seeks potential reversals when short-term price action shows exhaustion outside an EMA band, confirmed by momentum and FVG signals:
EMA Bands:
Parameters used: A 20-period EMA (fast) and 100-period EMA (slow).
Why chosen:
- The 20 EMA is sensitive to short-term moves and reflects immediate momentum.
- The 100 EMA provides a slower, structural anchor.
When price trades outside both bands, it often signals overextension relative to both short-term and medium-term trends.
Application in strategy:
- Long entries are only considered when price dips below both EMAs, identifying potential undervaluation.
- Short entries are only considered when price rises above both EMAs, identifying potential overvaluation.
This dual-band filter avoids counter-trend signals that would occur if only a single EMA was used, making entries more selective..
Fair Value Gap Detection (FVG):
Parameters used: The script checks for dislocations using a 12-bar lookback (i.e. comparing current highs/lows with values 12 candles back).
Why chosen:
- A 12-bar displacement highlights significant inefficiencies in price structure while filtering out micro-gaps that appear every few bars in high-volatility markets.
- By aligning FVG signals with candle direction (bullish = close > open, bearish = close < open), the strategy avoids random gaps and instead targets ones that suggest exhaustion.
Application in strategy:
- Bullish FVGs form when earlier lows sit above current highs, hinting at downward over-extension.
- Bearish FVGs form when earlier highs sit below current lows, hinting at upward over-extension.
This gives the strategy a structural filter beyond simple oscillators, ensuring signals have price-dislocation context.
RSI Momentum Filter:
Parameters used: 14-period RSI with thresholds of 80 (overbought) and 20 (oversold).
Why chosen:
- RSI(14) is a widely recognized momentum measure that balances responsiveness with stability.
- The thresholds are intentionally extreme (80/20 vs. the more common 70/30), so the strategy only engages at genuine exhaustion points rather than frequent minor corrections.
Application in strategy:
- Longs trigger when RSI < 20, suggesting oversold exhaustion.
- Shorts trigger when RSI > 80, suggesting overbought exhaustion.
This ensures entries are not just technically valid but also backed by momentum extremes, raising conviction.
ATR-Based Take Profit:
Parameters used: 14-period ATR, with a default multiplier of 4.
Why chosen:
- ATR(14) reflects the prevailing volatility environment without reacting too much to outliers.
- A multiplier of 4 is a pragmatic compromise: wide enough to let trades breathe in volatile conditions, but tight enough to enforce disciplined exits before mean reversion fades.
Application in strategy:
- At entry, a fixed target is set = Entry Price ± (ATR × 4).
- This target scales automatically with volatility: narrower in calm periods, wider in explosive markets.
By avoiding discretionary exits, the system maintains rule-based discipline.
Visual Signals on Chart
Blue “▲” below candle: Potential long entry
Orange/Yellow “▼” above candle: Potential short entry
Green “✔️”: Trade closed at ATR take profit
Blue (20 EMA) & Orange (100 EMA) lines: Dynamic channel reference
⚙️Strategy report properties
Position size: 25% equity per trade
Initial capital: 10,000.00 USDT
Pyramiding: 10 entries per direction
Slippage: 2 ticks
Commission: 0.055% per side
Backtest timeframe: 1-minute
Backtest instrument: HYPEUSDT
Backtesting range: Jul 28, 2025 — Aug 17, 2025
Note on Sample Size:
You’ll notice the report displays fewer than the ideal 100 trades in the strategy report above. This is intentional. The goal of the script is to isolate high-quality, short-term reversal opportunities while filtering out low-conviction setups. This means that the Barking Rat Lite strategy is very selective, filtering out over 90% of market noise. The brief timeframe shown in the strategy report here illustrates its filtering logic over a short window — not its full capabilities. As a result, even on lower timeframes like the 1-minute chart, signals are deliberately sparse — each one must pass all criteria before triggering.
For a larger dataset:
Once the strategy is applied to your chart, users are encouraged to expand the lookback range or apply the strategy to other volatile pairs to view a full sample.
💡Why 25% Equity Per Trade?
While it's always best to size positions based on personal risk tolerance, we defaulted to 25% equity per trade in the backtesting data — and here’s why:
Backtests using this sizing show manageable drawdowns even under volatile periods.
The strategy generates a sizeable number of trades, reducing reliance on a single outcome.
Combined with conservative filters, the 25% setting offers a balance between aggression and control.
Users are strongly encouraged to customize this to suit their risk profile.
What makes Barking Rat Lite valuable
Combines multiple layers of confirmation: EMA bands + FVG + RSI
Adaptive to volatility: ATR-based exits scale with market conditions
Clear, actionable visuals: Easy to monitor and manage trades
The Barking Rat ReversionsMean Reversion with Multi-Layered Precision
The Barking Rat Reversions is a short-term mean reversion strategy tailored for high-volatility markets. It combines several well-established technical tools in a configuration to identify overextended price movements likely to revert toward equilibrium. The goal is to isolate high-quality, short-term reversal opportunities while filtering out low-conviction setups.
At its core, our strategy triggers off Fair Value Gaps (FVGs) that occur a considerable distance away from a dynamically defined equilibrium band. It then validates these gaps by checking proximity to recent support and resistance drawn from swing extremes.
Additional confirmation comes from momentum filters and wick-rejection patterns, ensuring each entry aligns with both price structure and stretched momentum. Exits use volatility-adjusted profit targets. Keeping the approach disciplined and adaptive.
🧠Core Logic: Selectivity & Structure
This strategy is intentionally very selective. We have designed it to filter out roughly 95% of all market noise, highlighting only setups that pass multiple validation layers outlined below.
Fair Value Gaps (FVGs) as the Primary Trigger
FVGs identify imbalance zones where price historically retraces. These inefficient zones often become magnets for reversion as the market seeks to rebalance.
Dynamic Equilibrium Band + S/R
Defines a fair value zone with a long-term moving average and combines it with shorter-term swing pivots to establish support/resistance. Only FVGs that occur outside the band and near recent pivots are considered, ensuring reversals are sufficiently distanced and not taken too close to the mean.
Proximity to Support/Resistance
Setup validity depends on location. The strategy filters for FVGs near well-defined structural levels — areas where price has previously turned (i.e., recent swing highs or lows). This increases the likelihood that reversals are occurring at legitimate zones of confluence.
Wick-Rejection Confirmation
Confirms potential exhaustion through characteristic candle wick patterns beyond the equilibrium region. This acts as another filter to improve signal accuracy.
Sequential Filtered Signals
Custom logic ensures that a new signal in any direction must improve upon the previous one, preventing repetitive or suboptimal entries.
Multi-Step Confirmation
All validation layers must coincide on the same bar before a signal triggers, dramatically reducing false positives.
📈Chart Visuals: Designed for Clarity
To ensure transparency and easy interpretation, the script overlays intuitive visuals:
Green “▲” below a candle: Indicates a potential long entry
Red “▼” above a candle: Indicates a potential short entry
Green “✔️”: Marks exit from a trade when ATR target is met
Background shading (green/red): Indicates trade direction while active
Support/Resistance lines: Auto-plotted from recent swing levels
🔔Alerts: Stay Notified Without Watching
The strategy supports real-time alerts on candle close, ensuring that signals are only triggered once fully confirmed.
You must manually set up alerts within your TradingView account. Once configured, you’ll be able to set up one alert per instrument. This one alert covers all relevant signals and exits — ideal for hands-free monitoring.
⚙️Strategy report properties
Position size: 25% equity per trade
Initial capital: 10,000.00 USDT
Pyramiding: 10 entries per direction
Slippage: 2 ticks
Commission: 0.055% per side
Backtest timeframe: 1-minute
Backtest instrument: HYPEUSDT
Backtesting range: Jul 21, 2025 — Aug 7, 2025
Note on Sample Size:
You’ll notice the report displays fewer than the ideal 100 trades in the strategy report above. This is intentional. The goal of the script is to isolate high-quality, short-term reversal opportunities while filtering out low-conviction setups. This means that the Barking Rat Reversions strategy is ultra-selective, filtering out over 95% of market noise by enforcing multiple validation layers. The brief timeframe shown in the strategy report here illustrates its filtering logic over a short window — not its full capabilities. As a result, even on lower timeframes like the 1-minute chart, signals are deliberately sparse — each one must pass all criteria before triggering.
We conducted a broader backtest covering the period from December 5, 2024 to July 31, 2025, during which the strategy identified 968 high-probability setups on the same instrument and timeframe as the strategy report.
For a larger dataset:
Once the strategy is applied to your chart, users are encouraged to expand the lookback range or apply the strategy to other volatile pairs to view a full sample.
💡Why 25% Equity Per Trade?
While it's always best to size positions based on personal risk tolerance, we defaulted to 25% equity per trade in the backtesting data — and here’s why:
Backtests using this sizing show manageable drawdowns even under volatile periods
The strategy generates a sizeable number of trades, reducing reliance on a single outcome
Combined with conservative filters, the 25% setting offers a balance between aggression and control
Users are strongly encouraged to customize this to suit their risk profile.
🔍What Makes This Strategy Unique?
Multi-factor confirmation using FVGs, EMA deviation, RSI, wick rejection, and S/R
Clean, Intuitive Chart Experience
Real-time alerts triggered only on confirmation
Variables monitor prior reversal points, guaranteeing each new signal offers an improved entry
Tracks active positions and resets filters upon exit.
Strategy Designer
**Strategy Designer**
This script is a highly modular, multi-indicator strategy framework that allows users to enable or disable a wide range of signals for precision trading control. Key components include:
* **AlphaTrend**: A dynamic trailing filter built using ATR volatility combined with directional input from RSI or MFI. It helps define bullish or bearish regimes more responsively than fixed moving averages.
* **Inverse Fisher Transformed Indicators**: The script normalizes and transforms traditional oscillators (CCI, RSI, Stochastic, MFI) using the inverse Fisher transform. This boosts signal clarity by compressing values between -1 and +1, making crossovers and trend thresholds more defined.
* **Composite Indicators**: RSI + MFI and CCI + Stoch are averaged to produce smoother, noise-reduced momentum signals. These are ideal for filtering or confirming entries across multiple timeframes or asset types.
* **Volatility & Trend Filters**:
* **ATR Trend Filter**: Confirms trades only when short-term ATR exceeds its smoothed average, indicating rising volatility or breakout conditions.
* **ADX Filter**: Includes two types of filters—ADX vs its MA and ADX vs threshold—to ensure trade entries only happen during clear trend strength.
* **Moving Averages**: Multiple MA types (SMA, EMA, HMA, WMA, DEMA, TEMA, T3, VWMA) are available for crossover and trend conditions. The structure supports general trend, long-trend, and short-trend configurations independently.
* **Volume Filter**: An optional condition to confirm that volume exceeds a moving average, helping avoid trades in low-liquidity periods.
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**Exit Logic & Risk Management**
This strategy offers powerful and flexible exit controls to suit various risk profiles:
* **Fixed TP/SL**: You can activate classic percentage-based take profit and stop loss levels.
* **ATR-Based Floating Stop**: Dynamically calculates trailing stops based on recent volatility using a smoothed ATR, offering better adaptability in trending environments.
* **Signal-Based Exits**: Includes the ability to exit trades when the original entry conditions reverse (e.g. AlphaTrend flips, Fisher crosses back, MA cross reverses, etc.).
* **Modular Exit Triggers**: Each indicator (CCI, RSI, MFI, Stoch, AlphaTrend, Composite Indicators) can independently trigger an exit based on reversal signals or loss of trend strength.
* **Multi-Layered Protection**: Combine multiple exits (e.g. ATR + AlphaTrend + RSI reversal) to minimize drawdowns and prevent false breakouts.
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This tool is designed for advanced traders and strategy developers who want granular control over both entries and exits. Every module is toggleable, allowing for endless backtest scenarios and tailored setups to match different market conditions or asset classes. Whether you're trend-following or counter-trading reversals, this strategy adapts.
0-5 Box Strategy Tester v4🟩 0-5 Box Strategy Tester v4 — Explained Simply
This script is a modular hourly breakout strategy designed to help traders test and trade breakouts (or pullbacks) from the first 5-minute range of any selected hour. It supports both long and short positions and is optimized for scalping or intraday strategies.
🔑 Core Strategy Logic
Box Formation: At the start of every hour, the script tracks the high and low of the first 5 minutes (e.g., from 9:00 to 9:04).
Trade Trigger: Once price breaks out above or below this 5-minute box (either instantly or after a pullback), it can trigger a long or short entry depending on your settings.
Entry Type: Supports two main styles:
Breakout entry: Buy/sell as soon as price breaks the box.
Pullback re-entry: Wait for price to break the box, pull back, then re-enter on a limit order.
🧪 Smart Entry Filters (Optional but Powerful)
You can refine your trades using several filters:
✅ Previous Hour Direction – Only trade in the direction of the last hour’s candle (bullish/bearish).
🔄 Reversal Filter – Only trade against the previous hour’s direction.
💧 Liquidity Sweep – Require the previous hour’s high or low to be swept first (liquidity-based entry).
🔁 Q2 Confirmation (15–30 min logic) – Confirm price action in the second quarter of the hour (like retests or wick-based logic).
🕒 Max Entry Time – Prevent late trades within the hour (e.g., no entries after minute 45).
📦 Max Range % – Avoid trading during overly volatile hours by filtering out wide boxes.
🕘 Flexible Hour Selection
You can choose to:
Trade all hours
Or select specific hours manually (like 4AM, 9AM, etc.)
📉 Risk & Position Sizing Options
Supports stop-loss and take-profit by:
Points
Percentage
Risk:Reward Ratio
Choose fixed contract size or auto-size based on dollar risk.
📊 Built-In Analytics
The strategy tracks and displays:
Win rate
PnL (total, by hour, by day)
Average drawdown
Risk metrics (Expectancy, Profit Factor, Payoff Ratio)
Hour-by-hour stats (how each hour performs historically)
Day-of-week performance
Visual tables on chart for easy analysis
🧠 Use Cases
This strategy is ideal for:
Futures traders (like NQ/ES/GC) who trade specific sessions (e.g., NY open, London)
Scalpers looking for tight breakouts or pullbacks
Systematic traders backtesting precision setups
Traders using confluence like session breaks, liquidity sweeps, and inside-hour confirmations
MA wiht Logistic [Jsk]This script is published for educational purposes only and does not constitute financial advice. Past performance does not guarantee future results. Trade at your own risk; the author accepts no liability for any financial loss incurred.
Concept
• Direction is defined by the relationship between price and two moving averages (Fast & Slow).
Long: Close > Fast MA > Slow MA
Short: Close < Fast MA < Slow MA
• Three independent exit modes are available:
1) None – positions are closed only when an opposite signal appears.
2) Percentage – fixed take-profit / stop-loss expressed in % of entry price (default +20 % / –5 %).
3) Logistic – a dynamic take-profit / stop-loss based on a logistic transformation of unrealised P&L.
Key Inputs
• MA Type: EMA, SMA or WMA
• Fast / Slow MA length
• Exit Mode: None | Percentage | Logistic
• Percentage TP / SL values (active when Exit Mode = Percentage)
• Logistic settings: slope k, midpoint, TP / SL probability thresholds (active when Exit Mode = Logistic)
Recommended Use
The script works on any market or timeframe, but MA-based trend filters usually perform better in assets with smooth, directional moves. Always verify results in the Strategy Tester and account for commissions and slippage.
Combo 2/20 EMA & Bandpass Filter by TamarokDescription:
This strategy combines a 2/20 exponential moving average (EMA) crossover with a custom bandpass filter to generate buy and sell signals.
Use the Fast EMA and Slow EMA inputs to adjust trend sensitivity, and the Bandpass Filter Length, Delta, and Zones to fine-tune momentum turns.
Signals occur when both EMA and BPF agree in direction, with optional reversal and time filters.
How to use:
1. Add the script to your chart in TradingView.
2. Adjust the EMA and BP Filter parameters to match your asset’s volatility.
3. Enable ‘Reverse Signals’ to trade counter-trend, or use the time filter to limit sessions.
4. Set alerts on Long Alert and Short Alert for automated notifications.
Inspiration:
Based on HPotter’s original combo strategy (Stocks & Commodities Mar 2010).
Updated to Pine Script v6 with streamlined code and alerts.
WARNING:
For purpose educate only
ALMA Optimized Strategy - Volatility Filter + UT BotThe strategy you provided is an ALMA Optimized Strategy implemented in Pine Script™ version 5 for TradingView. Here is a brief English summary of what it is and how it works:
It is a trend-following strategy combining multiple technical indicators to optimize trade entries and exits.
The core moving average used is the ALMA (Arnaud Legoux Moving Average), known for smoother and less lagging price smoothing compared to traditional EMAs or SMAs.
The strategy also uses other indicators:
Fast EMA (Exponential Moving Average)
EMA 50
ATR (Average True Range) for volatility measurement and dynamic stop loss and take profit levels
RSI (Relative Strength Index) for momentum with overbought/oversold levels
ADX (Average Directional Index) for confirming trend strength
Bollinger Bands as a volatility filter
Buy signals trigger when volatility is sufficient (ATR filter), price is above EMA 50 and ALMA, RSI indicates bullish momentum, ADX confirms trend strength, price is below the upper Bollinger Band, and there is a cooldown period to prevent repeated buys within a short time.
Sell signals are generated when price crosses below the fast EMA.
The strategy manages position entries and exits dynamically, applying ATR-based stop loss and take profit levels, and optionally a time-based exit.
Additionally, the script integrates the UT Bot, an ATR-based trailing stop and signal system, enhancing trade exit precision.
Buy and sell signals are visually marked on the chart with colored triangles for easy identification.
In essence, this strategy blends advanced smoothing (ALMA) with volatility filters and trend/momentum indicators to generate reliable buy and sell signals, while managing risk dynamically through ATR-based stops and profit targets. It aims to adapt to changing market conditions by filtering noise and confirming trends before entering trades.
Breakouts With DXY Filter Strategy [LuciTech]This advanced breakout strategy combines pivot-based breakout detection with an innovative DXY (US Dollar Index) inverse correlation filter to enhance trade selection quality. The strategy identifies breakouts from recent pivot highs and lows while using DXY movements as a confirmation filter, based on the principle that USD strength/weakness often inversely correlates with other asset movements.
Key Features
Core Breakout Logic
- Pivot-Based Detection: Identifies breakouts above recent pivot highs (bullish) and below recent pivot lows (bearish)
- Customizable Lookback: Adjustable pivot length for different market conditions
- Visual Breakout Lines: Optional display of breakout levels with customizable colors
DXY Inverse Correlation Filter
- Smart USD Filter: Uses DXY movements to confirm breakout signals
- Inverse Logic: Long signals require DXY bearishness, short signals require DXY bullishness
- Threshold Control: Minimum DXY movement percentage required for signal confirmation
- Real-time DXY Data: Pulls live DXY data for accurate correlation analysis
Moving Average Filter
- Multiple MA Types: Support for SMA, EMA, WMA, VWMA, and HMA
- Trend Confirmation: Only takes trades in the direction of the selected moving average
- Customizable Parameters: Adjustable length and source for the moving average
Advanced Risk Management
- Multiple Stop Loss Types:
- ATR-based stops with customizable multiplier
- Candle-based stops using previous candle levels
- Fixed point-based stops
- Risk-Reward Optimization: Configurable risk-reward ratios (1:1 to 1:10)
- Breakeven Function: Automatic stop loss adjustment to breakeven after specified R-multiple
- Position Sizing: Percentage-based risk management with automatic position calculation
Time-Based Trading
- Session Filter: Trade only during specified time windows
- London Time Zone: Uses Europe/London timezone for consistency
- Visual Session Highlighting: Optional background fill for active trading hours
Alert System
- Webhook Integration: JSON-formatted alerts for automated trading
- Telegram Support: Pre-formatted messages for Telegram bot integration
- Multiple Formats: Standard, Telegram, and Concise Telegram alert options
- Real-time Notifications: Instant alerts on breakout signals
How It Works
1. Breakout Detection: The script continuously monitors for closes above recent pivot highs or below recent pivot lows
2. DXY Confirmation: When a breakout occurs, the script checks if DXY is moving in the opposite direction with sufficient momentum
3. MA Filter: If enabled, ensures the breakout aligns with the overall trend direction
4. Time Filter: Validates that the signal occurs within the specified trading hours
5. Risk Calculation: Automatically calculates position size based on the defined risk percentage and stop loss distance
6. Trade Execution: Places trades with predetermined stop loss and take profit levels
Unique Advantages
- Multi-Timeframe Approach: Combines asset-specific breakouts with broader USD market sentiment
- False Breakout Reduction: DXY filter helps eliminate breakouts that lack fundamental backing
- Comprehensive Risk Management: Multiple stop loss methods and automatic position sizing
- High Customization: Extensive parameters for different trading styles and market conditions
- Professional Alert System: Ready for automated trading integration
CVD Divergence + Volume HMA RSI MACD StrategyHow the script works:
The script calculates the HMA for trend direction. The HMA (shown in orange) is used as a filter: long trades are taken only if price is above the HMA, and short trades when below.
The CVD is computed by cumulatively adding volume on up bars and subtracting volume on down bars.
Pivot routines (with the input "Pivot Length") detect swing lows/highs for both price and CVD. A bullish divergence is flagged when the price makes a lower low while the CVD makes a higher low. Similarly, a bearish divergence is flagged when the price makes a higher high while the CVD makes a lower high.
Trading is triggered when the divergence condition also agrees with the HMA filter.
Feel free to further adjust the parameters or add risk‐management/exit rules as needed for your trading style.
Pullback Pro Dow Strategy v7 (ADX Filter)
### **Strategy Description (For TradingView)**
#### **Title:** Pullback Pro: Dow Theory & ADX Strategy
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#### **1. Summary**
This strategy is designed to identify and trade pullbacks within an established trend, based on the core principles of Dow Theory. It uses market structure (pivot highs and lows) to determine the trend direction and an Exponential Moving Average (EMA) to pinpoint pullback entry opportunities.
To enhance trade quality and avoid ranging markets, an ADX (Average Directional Index) filter is integrated to ensure that entries are only taken when the trend has sufficient momentum.
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#### **2. Core Logic: How It Works**
The strategy's logic is broken down into three main steps:
**Step 1: Trend Determination (Dow Theory)**
* The primary trend is identified by analyzing recent pivot points.
* An **Uptrend** is confirmed when the script detects a pattern of higher highs and higher lows (HH/HL).
* A **Downtrend** is confirmed by a pattern of lower highs and lower lows (LH/LL).
* If neither pattern is present, the strategy considers the market to be in a range and will not seek trades.
**Step 2: Entry Signal (Pullback to EMA)**
* Once a clear trend is established, the strategy waits for a price correction.
* **Long Entry:** In a confirmed uptrend, a long position is initiated when the price pulls back and crosses *under* the specified EMA.
* **Short Entry:** In a confirmed downtrend, a short position is initiated when the price rallies and crosses *over* the EMA.
**Step 3: Confirmation & Risk Management**
* **ADX Filter:** To ensure the trend is strong enough to trade, an entry signal is only validated if the ADX value is above a user-defined threshold (e.g., 25). This helps filter out weak signals during choppy or consolidating markets.
* **Stop Loss:** The initial Stop Loss is automatically and logically placed at the last market structure point:
* For long trades, it's placed at the `lastPivotLow`.
* For short trades, it's placed at the `lastPivotHigh`.
* **Take Profit:** Two Take Profit levels are calculated based on user-defined Risk-to-Reward (R:R) ratios. The strategy allows for partial profit-taking at the first target (TP1), moving the remainder of the position to the second target (TP2).
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#### **3. Input Settings Explained**
**① Dow Theory Settings**
* **Pivot Lookback Period:** Determines the sensitivity for detecting pivot highs and lows. A smaller number makes it more sensitive to recent price swings; a larger number focuses on more significant, longer-term pivots.
**② Entry Logic (Pullback)**
* **Pullback EMA Length:** Sets the period for the Exponential Moving Average used to identify pullback entries.
**③ Risk & Exit Management**
* **Take Profit 1 R:R:** Sets the Risk-to-Reward ratio for the first take-profit target.
* **Take Profit 1 (%):** The percentage of the position to be closed when TP1 is hit.
* **Take Profit 2 R:R:** Sets the Risk-to-Reward ratio for the final take-profit target.
**④ Filters**
* **Use ADX Trend Filter:** A master switch to enable or disable the ADX filter.
* **ADX Length:** The lookback period for the ADX calculation.
* **ADX Threshold:** The minimum ADX value required to confirm a trade signal. Trades will only be placed if the ADX is above this level.
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#### **4. Best Practices & Recommendations**
* This is a trend-following system. It is designed to perform best in markets that exhibit clear, sustained trending behavior.
* It may underperform in choppy, sideways, or strongly ranging markets. The ADX filter is designed to help mitigate this, but no filter is perfect.
* **Crucially, you must backtest this strategy thoroughly** on your preferred financial instrument and timeframe before considering any live application.
* Experiment with the `Pivot Lookback Period`, `Pullback EMA Length`, and `ADX Threshold` to optimize performance for a specific market's characteristics.
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#### **DISCLAIMER**
This script is provided for educational and informational purposes only. It does not constitute financial advice. All trading involves a high level of risk, and past performance is not indicative of future results. You are solely responsible for your own trading decisions. The author assumes no liability for any financial losses you may incur from using this strategy. Always conduct your own research and due diligence.
VoVix DEVMA🌌 VoVix DEVMA: A Deep Dive into Second-Order Volatility Dynamics
Welcome to VoVix+, a sophisticated trading framework that transcends traditional price analysis. This is not merely another indicator; it is a complete system designed to dissect and interpret the very fabric of market volatility. VoVix+ operates on the principle that the most powerful signals are not found in price alone, but in the behavior of volatility itself. It analyzes the rate of change, the momentum, and the structure of market volatility to identify periods of expansion and contraction, providing a unique edge in anticipating major market moves.
This document will serve as your comprehensive guide, breaking down every mathematical component, every user input, and every visual element to empower you with a profound understanding of how to harness its capabilities.
🔬 THEORETICAL FOUNDATION: THE MATHEMATICS OF MARKET DYNAMICS
VoVix+ is built upon a multi-layered mathematical engine designed to measure what we call "second-order volatility." While standard indicators analyze price, and first-order volatility indicators (like ATR) analyze the range of price, VoVix+ analyzes the dynamics of the volatility itself. This provides insight into the market's underlying state of stability or chaos.
1. The VoVix Score: Measuring Volatility Thrust
The core of the system begins with the VoVix Score. This is a normalized measure of volatility acceleration or deceleration.
Mathematical Formula:
VoVix Score = (ATR(fast) - ATR(slow)) / (StDev(ATR(fast)) + ε)
Where:
ATR(fast) is the Average True Range over a short period, representing current, immediate volatility.
ATR(slow) is the Average True Range over a longer period, representing the baseline or established volatility.
StDev(ATR(fast)) is the Standard Deviation of the fast ATR, which measures the "noisiness" or consistency of recent volatility.
ε (epsilon) is a very small number to prevent division by zero.
Market Implementation:
Positive Score (Expansion): When the fast ATR is significantly higher than the slow ATR, it indicates a rapid increase in volatility. The market is "stretching" or expanding.
Negative Score (Contraction): When the fast ATR falls below the slow ATR, it indicates a decrease in volatility. The market is "coiling" or contracting.
Normalization: By dividing by the standard deviation, we normalize the score. This turns it into a standardized measure, allowing us to compare volatility thrust across different market conditions and timeframes. A score of 2.0 in a quiet market means the same, relatively, as a score of 2.0 in a volatile market.
2. Deviation Analysis (DEV): Gauging Volatility's Own Volatility
The script then takes the analysis a step further. It calculates the standard deviation of the VoVix Score itself.
Mathematical Formula:
DEV = StDev(VoVix Score, lookback_period)
Market Implementation:
This DEV value represents the magnitude of chaos or stability in the market's volatility dynamics. A high DEV value means the volatility thrust is erratic and unpredictable. A low DEV value suggests the change in volatility is smooth and directional.
3. The DEVMA Crossover: Identifying Regime Shifts
This is the primary signal generator. We take two moving averages of the DEV value.
Mathematical Formula:
fastDEVMA = SMA(DEV, fast_period)
slowDEVMA = SMA(DEV, slow_period)
The Core Signal:
The strategy triggers on the crossover and crossunder of these two DEVMA lines. This is a profound concept: we are not looking at a moving average of price or even of volatility, but a moving average of the standard deviation of the normalized rate of change of volatility.
Bullish Crossover (fastDEVMA > slowDEVMA): This signals that the short-term measure of volatility's chaos is increasing relative to the long-term measure. This often precedes a significant market expansion and is interpreted as a bullish volatility regime.
Bearish Crossunder (fastDEVMA < slowDEVMA): This signals that the short-term measure of volatility's chaos is decreasing. The market is settling down or contracting, often leading to trending moves or range consolidation.
⚙️ INPUTS MENU: CONFIGURING YOUR ANALYSIS ENGINE
Every input has been meticulously designed to give you full control over the strategy's behavior. Understanding these settings is key to adapting VoVix+ to your specific instrument, timeframe, and trading style.
🌀 VoVix DEVMA Configuration
🧬 Deviation Lookback: This sets the lookback period for calculating the DEV value. It defines the window for measuring the stability of the VoVix Score. A shorter value makes the system highly reactive to recent changes in volatility's character, ideal for scalping. A longer value provides a smoother, more stable reading, better for identifying major, long-term regime shifts.
⚡ Fast VoVix Length: This is the lookback period for the fastDEVMA. It represents the short-term trend of volatility's chaos. A smaller number will result in a faster, more sensitive signal line that reacts quickly to market shifts.
🐌 Slow VoVix Length: This is the lookback period for the slowDEVMA. It represents the long-term, baseline trend of volatility's chaos. A larger number creates a more stable, slower-moving anchor against which the fast line is compared.
How to Optimize: The relationship between the Fast and Slow lengths is crucial. A wider gap (e.g., 20 and 60) will result in fewer, but potentially more significant, signals. A narrower gap (e.g., 25 and 40) will generate more frequent signals, suitable for more active trading styles.
🧠 Adaptive Intelligence
🧠 Enable Adaptive Features: When enabled, this activates the strategy's performance tracking module. The script will analyze the outcome of its last 50 trades to calculate a dynamic win rate.
⏰ Adaptive Time-Based Exit: If Enable Adaptive Features is on, this allows the strategy to adjust its Maximum Bars in Trade setting based on performance. It learns from the average duration of winning trades. If winning trades tend to be short, it may shorten the time exit to lock in profits. If winners tend to run, it will extend the time exit, allowing trades more room to develop. This helps prevent the strategy from cutting winning trades short or holding losing trades for too long.
⚡ Intelligent Execution
📊 Trade Quantity: A straightforward input that defines the number of contracts or shares for each trade. This is a fixed value for consistent position sizing.
🛡️ Smart Stop Loss: Enables the dynamic stop-loss mechanism.
🎯 Stop Loss ATR Multiplier: Determines the distance of the stop loss from the entry price, calculated as a multiple of the current 14-period ATR. A higher multiplier gives the trade more room to breathe but increases risk per trade. A lower multiplier creates a tighter stop, reducing risk but increasing the chance of being stopped out by normal market noise.
💰 Take Profit ATR Multiplier: Sets the take profit target, also as a multiple of the ATR. A common practice is to set this higher than the Stop Loss multiplier (e.g., a 2:1 or 3:1 reward-to-risk ratio).
🏃 Use Trailing Stop: This is a powerful feature for trend-following. When enabled, instead of a fixed stop loss, the stop will trail behind the price as the trade moves into profit, helping to lock in gains while letting winners run.
🎯 Trail Points & 📏 Trail Offset ATR Multipliers: These control the trailing stop's behavior. Trail Points defines how much profit is needed before the trail activates. Trail Offset defines how far the stop will trail behind the current price. Both are based on ATR, making them fully adaptive to market volatility.
⏰ Maximum Bars in Trade: This is a time-based stop. It forces an exit if a trade has been open for a specified number of bars, preventing positions from being held indefinitely in stagnant markets.
⏰ Session Management
These inputs allow you to confine the strategy's trading activity to specific market hours, which is crucial for day trading instruments that have defined high-volume sessions (e.g., stock market open).
🎨 Visual Effects & Dashboard
These toggles give you complete control over the on-chart visuals and the dashboard. You can disable any element to declutter your chart or focus only on the information that matters most to you.
📊 THE DASHBOARD: YOUR AT-A-GLANCE COMMAND CENTER
The dashboard centralizes all critical information into one compact, easy-to-read panel. It provides a real-time summary of the market state and strategy performance.
🎯 VOVIX ANALYSIS
Fast & Slow: Displays the current numerical values of the fastDEVMA and slowDEVMA. The color indicates their direction: green for rising, red for falling. This lets you see the underlying momentum of each line.
Regime: This is your most important environmental cue. It tells you the market's current state based on the DEVMA relationship. 🚀 EXPANSION (Green) signifies a bullish volatility regime where explosive moves are more likely. ⚛️ CONTRACTION (Purple) signifies a bearish volatility regime, where the market may be consolidating or entering a smoother trend.
Quality: Measures the strength of the last signal based on the magnitude of the DEVMA difference. An ELITE or STRONG signal indicates a high-conviction setup where the crossover had significant force.
PERFORMANCE
Win Rate & Trades: Displays the historical win rate of the strategy from the backtest, along with the total number of closed trades. This provides immediate feedback on the strategy's historical effectiveness on the current chart.
EXECUTION
Trade Qty: Shows your configured position size per trade.
Session: Indicates whether trading is currently OPEN (allowed) or CLOSED based on your session management settings.
POSITION
Position & PnL: Displays your current position (LONG, SHORT, or FLAT) and the real-time Profit or Loss of the open trade.
🧠 ADAPTIVE STATUS
Stop/Profit Mult: In this simplified version, these are placeholders. The primary adaptive feature currently modifies the time-based exit, which is reflected in how long trades are held on the chart.
🎨 THE VISUAL UNIVERSE: DECIPHERING MARKET GEOMETRY
The visuals are not mere decorations; they are geometric representations of the underlying mathematical concepts, designed to give you an intuitive feel for the market's state.
The Core Lines:
FastDEVMA (Green/Maroon Line): The primary signal line. Green when rising, indicating an increase in short-term volatility chaos. Maroon when falling.
SlowDEVMA (Aqua/Orange Line): The baseline. Aqua when rising, indicating a long-term increase in volatility chaos. Orange when falling.
🌊 Morphism Flow (Flowing Lines with Circles):
What it represents: This visualizes the momentum and strength of the fastDEVMA. The width and intensity of the "beam" are proportional to the signal strength.
Interpretation: A thick, steep, and vibrant flow indicates powerful, committed momentum in the current volatility regime. The floating '●' particles represent kinetic energy; more particles suggest stronger underlying force.
📐 Homotopy Paths (Layered Transparent Boxes):
What it represents: These layered boxes are centered between the two DEVMA lines. Their height is determined by the DEV value.
Interpretation: This visualizes the overall "volatility of volatility." Wider boxes indicate a chaotic, unpredictable market. Narrower boxes suggest a more stable, predictable environment.
🧠 Consciousness Field (The Grid):
What it represents: This grid provides a historical lookback at the DEV range.
Interpretation: It maps the recent "consciousness" or character of the market's volatility. A consistently wide grid suggests a prolonged period of chaos, while a narrowing grid can signal a transition to a more stable state.
📏 Functorial Levels (Projected Horizontal Lines):
What it represents: These lines extend from the current fastDEVMA and slowDEVMA values into the future.
Interpretation: Think of these as dynamic support and resistance levels for the volatility structure itself. A crossover becomes more significant if it breaks cleanly through a prior established level.
🌊 Flow Boxes (Spaced Out Boxes):
What it represents: These are compact visual footprints of the current regime, colored green for Expansion and red for Contraction.
Interpretation: They provide a quick, at-a-glance confirmation of the dominant volatility flow, reinforcing the background color.
Background Color:
This provides an immediate, unmistakable indication of the current volatility regime. Light Green for Expansion and Light Aqua/Blue for Contraction, allowing you to assess the market environment in a split second.
📊 BACKTESTING PERFORMANCE REVIEW & ANALYSIS
The following is a factual, transparent review of a backtest conducted using the strategy's default settings on a specific instrument and timeframe. This information is presented for educational purposes to demonstrate how the strategy's mechanics performed over a historical period. It is crucial to understand that these results are historical, apply only to the specific conditions of this test, and are not a guarantee or promise of future performance. Market conditions are dynamic and constantly change.
Test Parameters & Conditions
To ensure the backtest reflects a degree of real-world conditions, the following parameters were used. The goal is to provide a transparent baseline, not an over-optimized or unrealistic scenario.
Instrument: CME E-mini Nasdaq 100 Futures (NQ1!)
Timeframe: 5-Minute Chart
Backtesting Range: March 24, 2024, to July 09, 2024
Initial Capital: $100,000
Commission: $0.62 per contract (A realistic cost for futures trading).
Slippage: 3 ticks per trade (A conservative setting to account for potential price discrepancies between order placement and execution).
Trade Size: 1 contract per trade.
Performance Overview (Historical Data)
The test period generated 465 total trades , providing a statistically significant sample size for analysis, which is well above the recommended minimum of 100 trades for a strategy evaluation.
Profit Factor: The historical Profit Factor was 2.663 . This metric represents the gross profit divided by the gross loss. In this test, it indicates that for every dollar lost, $2.663 was gained.
Percent Profitable: Across all 465 trades, the strategy had a historical win rate of 84.09% . While a high figure, this is a historical artifact of this specific data set and settings, and should not be the sole basis for future expectations.
Risk & Trade Characteristics
Beyond the headline numbers, the following metrics provide deeper insight into the strategy's historical behavior.
Sortino Ratio (Downside Risk): The Sortino Ratio was 6.828 . Unlike the Sharpe Ratio, this metric only measures the volatility of negative returns. A higher value, such as this one, suggests that during this test period, the strategy was highly efficient at managing downside volatility and large losing trades relative to the profits it generated.
Average Trade Duration: A critical characteristic to understand is the strategy's holding period. With an average of only 2 bars per trade , this configuration operates as a very short-term, or scalping-style, system. Winning trades averaged 2 bars, while losing trades averaged 4 bars. This indicates the strategy's logic is designed to capture quick, high-probability moves and exit rapidly, either at a profit target or a stop loss.
Conclusion and Final Disclaimer
This backtest demonstrates one specific application of the VoVix+ framework. It highlights the strategy's behavior as a short-term system that, in this historical test on NQ1!, exhibited a high win rate and effective management of downside risk. Users are strongly encouraged to conduct their own backtests on different instruments, timeframes, and date ranges to understand how the strategy adapts to varying market structures. Past performance is not indicative of future results, and all trading involves significant risk.
🔧 THE DEVELOPMENT PHILOSOPHY: FROM VOLATILITY TO CLARITY
The journey to create VoVix+ began with a simple question: "What drives major market moves?" The answer is often not a change in price direction, but a fundamental shift in market volatility. Standard indicators are reactive to price. We wanted to create a system that was predictive of market state. VoVix+ was designed to go one level deeper—to analyze the behavior, character, and momentum of volatility itself.
The challenge was twofold. First, to create a robust mathematical model to quantify these abstract concepts. This led to the multi-layered analysis of ATR differentials and standard deviations. Second, to make this complex data intuitive and actionable. This drove the creation of the "Visual Universe," where abstract mathematical values are translated into geometric shapes, flows, and fields. The adaptive system was intentionally kept simple and transparent, focusing on a single, impactful parameter (time-based exits) to provide performance feedback without becoming an inscrutable "black box." The result is a tool that is both profoundly deep in its analysis and remarkably clear in its presentation.
⚠️ RISK DISCLAIMER AND BEST PRACTICES
VoVix+ is an advanced analytical tool, not a guarantee of future profits. All financial markets carry inherent risk. The backtesting results shown by the strategy are historical and do not guarantee future performance. This strategy incorporates realistic commission and slippage settings by default, but market conditions can vary. Always practice sound risk management, use position sizes appropriate for your account equity, and never risk more than you can afford to lose. It is recommended to use this strategy as part of a comprehensive trading plan. This was developed specifically for Futures
"The prevailing wisdom is that markets are always right. I take the opposite view. I assume that markets are always wrong. Even if my assumption is occasionally wrong, I use it as a working hypothesis."
— George Soros
— Dskyz, Trade with insight. Trade with anticipation.
