Important High/Low (Manual DateTime Picker + Strong BOS) v2.5📐 Important High / Low（结构趋势指标）使用指南
定位一句话
这是一个 “结构派趋势确认 + 关键防守位识别” 的指标
👉 不预测行情
👉 不频繁给信号
👉 只在你定义的趋势里，标出 必须尊重的高点 / 低点
一、这个指标解决什么问题？
在一段趋势中，你真正关心的只有三件事：
趋势是否还成立
哪里是“不能被破”的关键结构位
止损应该放在哪里才是“逻辑止损”而不是情绪止损
本指标通过 结构拐点（Pivot）+ 结构突破（BOS）确认 来回答这三件事。
二、核心设计理念（非常重要）
1️⃣ 重要低点 > 次要低点
不是每个低点都重要
只有“低点 → 后续出现强势突破并创新高”
才会被确认成 重要低点
2️⃣ 上涨趋势里，只允许重要低点
不会在上涨趋势里画“重要高点”
下跌趋势同理
3️⃣ 所有重要点，都是事后确认
这是优点，不是缺点
它保证：
被画出来的点，一定“已经被市场认可”
三、输入参数详解（逐个解释）
🟦 A. 趋势控制（最重要）
Trend mode
选项 含义
Auto(EMA144) 自动趋势（推荐）
Manual(Time Window) 手动定义趋势区间
Auto(EMA144)（默认、最常用）
价格在 EMA144 上方 → 视为上涨趋势
价格在 EMA144 下方 → 视为下跌趋势
📌 行为约束：
上涨趋势：只画重要低点
下跌趋势：只画重要高点
适合 90% 日内 / 波段交易
Manual(Time Window)
当你已经主观判断趋势方向时使用。
配套参数：
Manual trend direction
Up：只允许重要低点
Down：只允许重要高点
Use manual time window?
打开后，才会启用时间段控制
Manual trend START / END (date & time)
用 TradingView 日期时间选择器 直接选
不需要手填时间戳
📌 常见用途：
回测一整段趋势
训练“趋势内只做一个方向”
事件行情 / 主升浪
🟦 B. 结构拐点识别
Pivot strength (L/R)
决定一个高点 / 低点
需要左右各多少根K线确认
周期 推荐值
1–5 分钟 2–3
15–30 分钟 3–5
1 小时 5–7
4 小时+ 7–10
📌 数值越大：
结构越“干净”
但确认越慢
🟦 C. 结构突破（BOS）规则
BOS uses Wick (High/Low)
true（推荐）：
影线突破就算结构突破
false：
必须收盘价突破（更保守）
Must keep making NEW high/low
是否要求“持续创新高 / 新低”
选项 效果
true（强烈推荐） 过滤横盘、假突破
false 信号更多，但更杂
📌 打开后：
每一次 BOS
必须比上一次突破更高 / 更低
才会确认新的重要点
这是“稳”的关键来源之一。
🟦 D. 强势K线过滤（可选）
Use strong candle filter on BOS bar?
决定 BOS 那根K线是否必须是强势K线
Body / Range >=
K线实体占整根K线的比例
推荐：
0.5：宽松
0.6：平衡（推荐）
0.7：非常严格
Range >= ATR *
BOS K线的波动幅度
推荐：
日内：0.8 ~ 1.0
波段：1.0 ~ 1.2
📌 强势过滤适合：
山寨币
假突破多的品种
你想 少而准
🟦 E. 画线与止损体验
Line offset (ATR multiplier)
决定重要高/低点横线
离影线多远
市场 推荐
BTC / ETH 0.1 ~ 0.15
山寨 / 高波动 0.2 ~ 0.3
Short line length (bars)
横线长度
只影响视觉，不影响逻辑
推荐：5 ~ 8
四、不同周期的推荐模板
🔹 日内模板（15m / 30m）
Trend mode: Auto(EMA144)
Pivot strength: 3
Use wick BOS: true
Must make new high/low: true
Strong candle filter: true
Body/Range: 0.6
ATR multiple: 1.0
Line offset: 0.15
特点：
结构清晰
假突破明显减少
适合顺趋势波段
🔹 波段模板（1h / 4h）
Trend mode: Auto(EMA144)
Pivot strength: 5–7
Use wick BOS: true
Must make new high/low: true
Strong candle filter: false 或 true
Line offset: 0.2
特点：
重要点很少
但每一个都极具意义
非常适合“结构止损”
五、如何用它做交易（一句话版）
只在趋势方向上进场，
止损永远放在最近的“重要结构点”之外，
一旦被破，承认你的趋势假设是错的。
六、什么时候你“应该退出”，而不是“继续找理由”
多单：重要低点被有效跌破
空单：重要高点被有效突破
📌 这不是指标失效
📌 而是 你的趋势已经结束
📐 Important High / Low
User Guide (English Version)
One-line description
A market structure–based trend confirmation and key defense level indicator
Not predictive
No frequent signals
Only marks critical highs/lows inside a defined trend
1. What problem does this indicator solve?
In a trend, traders only care about:
Is the trend still valid?
Which level must NOT be broken?
Where should a logical stop-loss be placed?
This indicator answers these questions using
Pivot structure + Break of Structure (BOS).
2. Core Concepts
1️⃣ Important Low > Minor Low
Not every low is important
A low becomes important only if price later breaks structure and makes a new high
2️⃣ In an uptrend, only Important Lows exist
No important highs in uptrends
Vice versa for downtrends
3️⃣ All important points are confirmed after the fact
This is a feature, not a flaw
Ensures all marked levels are validated by price action
3. Input Parameters Explained
🟦 A. Trend Control (Most Important)
Trend mode
Option Meaning
Auto(EMA144) Automatic trend (recommended)
Manual(Time Window) Manually defined trend
Auto(EMA144)
Price above EMA144 → Uptrend
Price below EMA144 → Downtrend
Rules:
Uptrend → only Important Lows
Downtrend → only Important Highs
Manual(Time Window)
Used when you already know the trend direction.
Related inputs:
Manual trend direction
Up → only Important Lows
Down → only Important Highs
Use manual time window?
Enables the time window
Manual trend START / END (date & time)
Select via TradingView date-time picker
No timestamp typing required
🟦 B. Pivot Structure
Pivot strength (L/R)
Defines how many bars on each side confirm a swing point.
Timeframe Suggested
1–5m 2–3
15–30m 3–5
1h 5–7
4h+ 7–10
🟦 C. Break of Structure (BOS)
BOS uses Wick (High/Low)
true → wick break counts (recommended)
false → close break only
Must keep making NEW high/low
Requires continuous higher highs / lower lows.
true (strongly recommended)
Filters chop and fake breaks
Fewer but higher-quality structure points
false
More signals, more noise
🟦 D. Strong Candle Filter (Optional)
Use strong candle filter on BOS bar?
Defines whether the BOS candle must be strong.
Body / Range >=
Body dominance, recommended 0.6
Range >= ATR *
Expansion requirement
Intraday: 0.8–1.0
Swing: 1.0–1.2
🟦 E. Drawing & Stop-Loss Behavior
Line offset (ATR multiplier)
Distance between structure line and candle wick.
Market Suggested
BTC / ETH 0.1–0.15
Altcoins 0.2–0.3
4. Recommended Presets
🔹 Intraday (15m / 30m)
Trend mode: Auto(EMA144)
Pivot strength: 3
Use wick BOS: true
Must make new high/low: true
Strong candle filter: true
Body/Range: 0.6
ATR multiple: 1.0
Line offset: 0.15
🔹 Swing (1h / 4h)
Trend mode: Auto(EMA144)
Pivot strength: 5–7
Use wick BOS: true
Must make new high/low: true
Strong candle filter: optional
Line offset: 0.2
5. Trading Principle (One Sentence)
Trade with the trend,
place stops beyond the most recent important structure level,
and exit immediately when that structure is broken.
Indicateurs et stratégies
PA SystemPA System
短简介 Short Description（放在最上面）
中文：
PA System 是一套以 AL Brooks 价格行为为核心的策略（Strategy），将 结构（HH/HL/LH/LL）→ 回调（H1/L1）→ 二次入场（H2/L2 微平台突破） 串成完整可回测流程，并可选叠加 BoS/CHoCH 结构突破过滤 与 Liquidity Sweep（扫流动性）确认。内置风险管理：定风险仓位、部分止盈、保本、移动止损、时间止损、冷却期。
English:
PA System is an AL Brooks–inspired Price Action strategy that chains Market Structure (HH/HL/LH/LL) → Pullback (H1/L1) → Second Entry (H2/L2 via Micro Range Breakout) into a complete backtestable workflow, with optional BoS/CHoCH structure-break filtering and Liquidity Sweep confirmation. Built-in risk management includes risk-based sizing, partial exits, breakeven, trailing stops, time stop, and cooldown.
⸻
1) 核心理念 Core Idea
中文：
这不是“指标堆叠”，而是一条清晰的价格行为决策链：
结构确认 → 回调出现 → 小平台突破（二次入场）→ 风控出场。
策略把 Brooks 常见的“二次入场”思路程序化，同时用可选的结构突破与扫流动性模块提升信号质量、减少震荡误入。
English:
This is not an “indicator soup.” It’s a clear price-action decision chain:
Confirmed structure → Pullback → Micro-range breakout (second entry) → Risk-managed exits.
The system programmatically implements the Brooks-style “second entry” concept, and optionally adds structure-break and liquidity-sweep context to reduce chop and improve trade quality.
⸻
2) 主要模块 Main Modules
A. 结构识别 Market Structure (HH/HL/LH/LL)
中文：
使用 pivot 摆动点确认结构，标记 HH/HL/LH/LL，并可显示最近一组摆动水平线，方便对照结构位置。
English:
Uses confirmed pivot swings to label HH/HL/LH/LL and optionally plots the most recent swing levels for clean structure context.
B. 状态机 Market Regime (State Machine + “Always In”)
中文：
基于趋势K强度、EMA关系与波动范围，识别市场环境（Breakout/Channel/Range）以及 Always-In 方向，用于过滤不合适的交易环境。
English:
A lightweight regime engine detects Breakout/Channel/Range and an “Always In” directional bias using momentum and EMA/range context to avoid low-quality conditions.
C. 二次入场 Second Entry Engine (H1→H2 / L1→L2)
中文：
• H1/L1：回调到结构附近并出现反转迹象
• H2/L2：在 H1/L1 后等待最小 bars，然后触发 Micro Range Breakout（小平台突破）并要求信号K收盘强度达标
这一段是策略的“主发动机”。
English:
• H1/L1: Pullback into structure with reversal intent
• H2/L2: After a minimum wait, triggers on Micro Range Breakout plus a configurable close-strength filter
This is the main “entry engine.”
D. 可选过滤器 Optional Filters (Quality Boost)
BoS/CHoCH（结构突破过滤）
中文： 可识别 BoS / CHoCH，并可要求“入场前最近 N bars 必须有同向 break”。
English: Detects BoS/CHoCH and can require a recent same-direction break within N bars.
Liquidity Sweeps（扫流动性确认）
中文： 画出 pivot 高/低的流动性水平线，检测“刺破后收回”的 sweep，并可要求入场前出现同向 sweep。
English: Tracks pivot-based liquidity levels, confirms sweeps (pierce-and-reclaim), and can require a recent sweep before entry.
E. FVG 可视化 FVG Visualization
中文： 提供 FVG 区域盒子与管理模式（仅保留未回补 / 仅保留最近N），主要用于区域理解与复盘，不作为强制入场条件（可自行扩展）。
English: Displays FVG boxes with retention modes (unfilled-only or last-N). Primarily for context/analysis; not required for entries (you can extend it as a filter/target).
⸻
3) 风险管理 Risk Management (Built-In)
中文：
• 定风险仓位：按账户权益百分比计算仓位
• SL/TP：基于结构 + ATR 缓冲，且限制最大止损 ATR 倍
• 部分止盈：到达指定 R 后减仓
• 保本：到达指定 R 后推到 BE
• 移动止损：到达指定 R 后开始跟随
• 时间止损：持仓太久不动则退出
• 冷却期：出场后等待 N bars 再允许新单
English:
• Risk-based sizing: position size from equity risk %
• SL/TP: structure + ATR buffer with max ATR risk cap
• Partial exits at an R threshold
• Breakeven at an R threshold
• Trailing stop activation at an R threshold
• Time stop to reduce chop damage
• Cooldown after exit to avoid rapid re-entries
⸻
4) 推荐使用方式 Recommended Usage
中文：
• 推荐从 5m / 15m / 1H 开始测试
• 想更稳：开启 EMA Filter + Break Filter + Sweep Filter，并提高 Close Strength
• 想更多信号：关闭 Break/Sweep 过滤或降低 Swing Length / Close Strength
• 回测时务必设置合理的手续费与滑点，尤其是期货/指数
English:
• Start testing on 5m / 15m / 1H
• For higher quality: enable EMA Filter + Break Filter + Sweep Filter and increase Close Strength
• For more signals: disable Break/Sweep filters or reduce Swing Length / Close Strength
• Use realistic commissions/slippage in backtests (especially for futures/indices)
⸻
5) 重要说明 Notes
中文：
结构 pivot 需要右侧确认 bars，因此结构点存在天然滞后（确认后不会再变）。策略逻辑尽量避免不必要的对象堆叠，并对数组/对象做了稳定管理，适合长期运行与复盘。
English:
Pivot-based structure requires right-side confirmation (inherent lag; once confirmed it won’t change). The script is designed for stability and resource-safe object management, suitable for long sessions and review.
⸻
免责声明 Disclaimer（建议原样保留）
中文：
本脚本仅用于教育与研究目的，不构成任何投资建议。策略回测结果受市场条件、手续费、滑点、交易时段、数据质量等影响显著。使用者需自行验证并承担全部风险。过往表现不代表未来结果。
English:
This script is for educational and research purposes only and does not constitute financial advice. Backtest results are highly sensitive to market conditions, fees, slippage, session settings, and data quality. Use at your own risk. Past performance is not indicative of future results.
Smart Money Zones (FVG + OB) + MTF Trend Panel## Overview
Professional-grade institutional trading zones indicator that identifies **Fair Value Gaps (FVG)** and **Order Blocks (OB)** - key price inefficiencies where smart money operates. Includes a comprehensive **Multi-Timeframe Trend Panel** for complete market context at a glance.
## Core Features
### 🎯 Fair Value Gaps (FVG)
Fair Value Gaps occur when price moves so aggressively that it leaves an "imbalance" or "gap" in the market structure. These zones often act as magnets where price returns to find liquidity.
**Detection Logic:**
- **Bullish FVG**: When current candle's low is above the high of the candle 2 bars ago
- **Bearish FVG**: When current candle's high is below the low of the candle 2 bars ago
- Requires strong impulse candle (configurable body percentage threshold)
- Color-coded zones: Green for bullish, Red for bearish
### 📦 Order Blocks (OB)
Order Blocks represent the last opposite candle before a significant price move - the zone where institutional orders were placed before the breakout.
**Detection Logic:**
- Identifies the last bearish candle before a strong bullish breakout (Bullish OB)
- Identifies the last bullish candle before a strong bearish breakout (Bearish OB)
- Validates breakout strength using ATR multiplier (1.2x default)
- Color-coded zones: Blue for bullish, Orange for bearish
### 📊 Multi-Timeframe Trend Panel
Real-time trend analysis across **7 timeframes** displayed in an elegant dashboard:
- **1 Minute** - Ultra short-term scalping
- **5 Minutes** - Short-term momentum
- **15 Minutes** - Intraday swings
- **30 Minutes** - Session trends
- **1 Hour** - Multi-session trends
- **4 Hours** - Daily structure
- **Daily** - Long-term direction
**Visual Indicators:**
- 🟢 Green circle = Bullish trend
- 🔴 Red circle = Bearish trend
- Clean, professional table design with customizable position and size
## Intelligence Features
### 🧠 Zone Strength Rating
Every zone is automatically classified by strength based on size relative to ATR:
- **VERY STRONG** - 2.0x ATR or more (major institutional zones)
- **STRONG** - 1.5x to 2.0x ATR (significant zones)
- **MEDIUM** - 1.0x to 1.5x ATR (moderate zones)
- **WEAK** - Below 1.0x ATR (minor zones)
Strength rating helps you prioritize which zones to trade from!
### 📉 Smart Mitigation Tracking
Zones automatically track how much they've been "filled" or mitigated:
- Calculates penetration percentage as price enters the zone
- Zones turn **gray** when 50%+ mitigated or fully filled
- Option to **auto-delete** mitigated zones to keep chart clean
- Live zones extend dynamically with price action
### 🎨 Trend Filter (Optional)
When enabled, only shows zones aligned with the current trend:
- Uses customizable MA period (default 50)
- Bullish zones only appear in uptrend
- Bearish zones only appear in downtrend
- Reduces noise and false signals significantly
## Customization Options
### Display Settings
- Toggle FVGs and OBs independently
- Adjust max zones per type (5-200)
- Choose to remove or gray out mitigated zones
- Color customization for all zone types
### Detection Parameters
- **Min Impulse Body %**: Controls how strong the impulse candle must be (0.3-1.0)
- **Order Block Lookback**: How many bars to look back for OB validation (5-50)
- **ATR Length**: Period for ATR calculation (5-50)
### Trend Filter
- Enable/disable trend filtering
- Adjustable MA period for trend determination
### MTF Panel
- Show/hide the trend panel
- 4 position options: Top Right, Top Left, Bottom Right, Bottom Left
- 3 size options: Small, Normal, Large
- Customizable MA period for trend calculation across all timeframes
## Trading Applications
### 1. **Liquidity Grab Entries**
Wait for price to sweep a zone (50%+ mitigation) then enter on reversal. Smart money often "hunts" these zones before the real move begins.
### 2. **Confluence Trading**
Look for zones that align with:
- Multiple timeframe trends showing same direction
- Multiple FVGs/OBs stacking in same area
- Key support/resistance levels
### 3. **Breakout Confirmation**
Use Order Blocks to confirm the strength of breakouts. Strong OBs indicate institutional participation.
### 4. **Retracement Entries**
Enter when price returns to a fresh, unmitigated zone in the direction of the higher timeframe trend.
### 5. **Range Trading**
Identify FVG zones at range extremes - price often reverses at these inefficiencies.
## How It Works
**Fair Value Gaps** form when the middle candle creates such aggressive movement that it leaves a price gap between the high/low of surrounding candles. Institutional traders know these gaps get filled.
**Order Blocks** mark the origin of major moves. The last opposite-colored candle before a breakout is where large orders were placed. Price often returns to these zones for "retests" before continuing.
**Mitigation** happens when price returns to fill these zones. The indicator tracks this automatically, showing you which zones are still "fresh" and which have been used up.
## Best Practices
✅ **Use higher timeframe trends** - Always check the MTF panel before taking trades
✅ **Trade fresh zones** - Unmitigated zones (not gray) have the highest probability
✅ **Combine with price action** - Look for rejection wicks and engulfing candles at zones
✅ **Respect zone strength** - VERY STRONG and STRONG zones are most reliable
✅ **Use trend filter** - Especially on lower timeframes to reduce false signals
❌ **Don't overtrade** - Not every zone will react, wait for confirmation
❌ **Don't ignore context** - Check the MTF panel for conflicting trends
❌ **Don't chase** - Wait for price to come to the zone, don't enter mid-zone
## Technical Details
- **Non-repainting**: All zones are drawn on confirmed candles only
- **Performance optimized**: Uses efficient array management with per-type caps
- **Real-time updates**: Zones extend and track mitigation as price moves
- **Universal compatibility**: Works on all markets and timeframes
## Recommended Settings by Style
**Scalping (1m-5m charts):**
- Max zones: 10-15
- Use trend filter: ON
- MTF Panel: Focus on 1m-15m trends
- Remove mitigated: ON (keep chart clean)
**Day Trading (5m-1H charts):**
- Max zones: 15-20
- Use trend filter: ON
- MTF Panel: Focus on 15m-4H trends
- Remove mitigated: OFF (track zone history)
**Swing Trading (1H-D charts):**
- Max zones: 20+
- Use trend filter: Optional
- MTF Panel: Focus on 1H-1D trends
- Remove mitigated: OFF (important zones persist)
---
## Perfect For
- Smart Money Concept (SMC) traders
- ICT methodology followers
- Institutional order flow traders
- Price action traders seeking key zones
- Multi-timeframe analysis enthusiasts
**Compatible with all markets:** Forex, Crypto, Stocks, Indices, Commodities, Futures
*Trade where the institutions trade. Follow the smart money.*
ICT FVG MNQ (Fixed Stop + Multi-TP Toggles)use- 18 min timeframe.
ICT FVG - use on MNQ 18 min time frame.
it has muti TP levels.-
Prop firm compatible.
Enjoy trading
Auto Price-to-Bar ScaleIt adjusts the chart’s scaling according to Mitotic scaling rules, as defined in the book Geometrical Analysis by Anand Kene (available on Amazon). This method of scaling allows the application of various angles and Gann boxes, resulting in more precise target levels.
Hookes Kinetics | IkkeOmarHooke's Kinetics: A Physics-Based Volatility System
This indicator applies the principles of Hooke's Law to financial time series data to model market volatility as a system of potential and kinetic energy.
Theoretical Foundation: Hooke's Law In physics, Hooke's Law states that the force (F) needed to extend or compress a spring by some distance (x) scales linearly with respect to that distance: F = -kx, where k is the spring constant.
Potential Energy (PE): PE = 0.5 * k * x^2 Kinetic Energy (KE): Energy possessed due to motion.
In this system, we treat Price Action as a spring. Compression (Potential Energy): When price consolidates, volatility compresses. The "spring" is being wound up. Energy is accumulated, not released. Release (Kinetic Energy): When price breaks out of compression, potential energy transforms into kinetic energy. The spring snaps back, driving price motion.
Indicator Mechanics The Hooke's Kinetics oscillator visualizes this energy transfer cycle to identify trend origins and exhaustion points.
Accumulating Energy (Potential): The Blue Area represents the buildup of Potential Energy. This occurs during periods of low volatility (consolidation). The algorithm detects when price variance drops below a threshold (representing spring compression) and aggregates this "stored force" over time. As long as the price remains compressed, the Blue potential energy grows.
Energy Conversion (Kinetic Release): The Red Histogram represents Kinetic Energy. When volatility expands significantly (a breakout), the system triggers a release event. The accumulated Blue potential energy is discharged and converted into the Red kinetic spike. This marks the moment the "spring" is released.
Trend Direction & Decay: Once the Kinetic Energy (Red spike) appears, the "explosive" phase is active. As the Red histogram decays (lowers back to zero), the market enters a coasting phase. The trend direction is established by the price movement during the initial Kinetic release. Traders observe the price vector as the Red energy dissipates to confirm the prevailing trend.
Reversion Signals (Bonus): Extreme peaks in Kinetic Energy (exceptionally high Red spikes) indicate a maximum extension of the spring. Just as a physical spring oscillates, extreme kinetic release often precedes a mean reversion. If price action opposes the direction of the Kinetic decay, it signals a likely reversal.
Visual Reference Referencing the chart above: Blue Ramp: Note the linear buildup of the blue area during sideways price action. This is the "loading" phase. Red Spike: Note the immediate drop in Blue and spike in Red coinciding with the green highlight circles on the chart. These are the breakout points. Green Circles: These highlight the specific candles where Potential converted to Kinetic, marking the optimal entry or decision points.
Code Description
The system defines market state using a composite variable "k" (Stiffness), which combines Price Volatility (NATR) and Relative Volume (RVOL).
k_price = range_natr != 0 ? 1.0 - ((natr - lowest_natr) / range_natr) : 0 k = (k_price * price_weight) + (k_vol * vol_weight) Here, we normalize volatility relative to a historical lookback. High values of "k" indicate high compression—this is the "winding" of the spring.
if is_compressed potential_energy := potential_energy + k kinetic_energy := kinetic_energy * DECAY_RATE When the market is tighter than the user-defined "stiff_thresh", the system accumulates Potential Energy. Note that Kinetic Energy actively decays during this phase, simulating friction or inertia slowing down price movement.
else drain_factor = (1.0 - k) transfer = potential_energy * drain_factor potential_energy := potential_energy - transfer kinetic_energy := (kinetic_energy * DECAY_RATE) + (transfer * ENERGY_MULT) This acts as the conservation of energy. We do not reset Potential to zero instantly; we drain it. The "drain_factor" ensures that a violent expansion (low k) drains potential energy faster than a mild move. This transferred energy is scaled up and added to the Kinetic state.
Note - AMPLITUDE MATTERS!
Observe the amplitude of the Kinetic Energy - higher peaks are more significant. Lower values are usually artifacts, but they can indicate mean reversion on a smaller scale while price remains within a range.
SM Triple Zone: Daily / PM / ORB with AlertsTitle: SM Triple Zone: Daily / PM / ORB with Alerts
Description: This indicator is designed for intraday traders who focus on high-probability session levels. It visualizes three critical zones without cluttering your chart with historical data:
Daily Zone: Highlights the Previous Day High (PDH), Low (PDL), and Midpoint, anchored to the 9:30 AM NY Open.
Pre-Market Zone: Identifies the High and Low of the 04:00–09:30 AM pre-market session.
ORB Zone: Sets a 5-minute Opening Range Breakout zone (customizable) to capture early morning volatility.
Key Features:
Y-Axis Price Labels: All major levels are pinned to the price scale for quick reference.
Fully Customizable: Independent settings for line thickness, style (Solid/Dashed), and colors for every zone.
Master Alerts: Includes "Master Bullish" and "Master Bearish" alerts to notify you of breakouts from any of the three zones with a single alert setup.
Jimbob Channel/Breakout (Current TF)I have used this indicator to show a breakout of price.
The way to use it is: if there is a channel printing on the time frame you are looking at,
then it means that a directional change is coming in the future.
It is a way to see that something is coming.
It doesn’t tell you which way the price is moving while the channel is printing; it only tells you that something is coming.
I have a directional movement programmed in by an arrow printing after price has moved out of the channel, but this usually means you have missed the move. So it’s better to use these channels as an indication that price will be breaking out soon.
I hope this indicator helps people get prepared for a move that is about to happen.
Use this as an indication that something is coming rather than something that has happened.
One way of looking at this indicator is to check that the current time frame has a channel, then look at the time frames above it and see if there is a channel on them. If there isn’t, then think of it as a freeway for cars: if there is no channel in the time frames above the one you are looking at, then the move out of the current time frame shouldn’t have much headway. But if there is a channel on the higher time frames, then expect the price to go sideways until the channel on the higher time frame has broken out.
Good luck with investing using this indicator.
Cheers
Jimbob :)
Rachev Regime AnalyzerRachev Regime Analyzer ~ GForge
What It Does
Measures the ratio of extreme gains to extreme losses to identify whether markets favor bulls or bears. When your best moves are bigger than your worst moves, conditions are bullish. When the opposite is true, conditions are bearish.
Simple Interpretation:
Ratio > 1.2 → Bullish regime (tail gains exceed tail losses)
Ratio < 0.8 → Bearish regime (tail losses exceed tail gains)
Between → Neutral/transitional
Key Features
Two Modes:
Single Asset: Analyze current chart
Multi-Asset: Aggregate regime across 5 assets with custom weights (great for gauging overall crypto/market conditions)
Customizable:
Lookback period (20-200 bars)
Tail percentile (what counts as "extreme")
Bullish/bearish thresholds
6 color schemes
Optional MA smoothing
Visual Signals:
Buy/sell markers at threshold crosses
Background regime coloring
Info table with current values and confidence score
Configurable alerts
How to Use
Choose lookback period based on your timeframe (40-60 bars is a good start)
Watch for threshold crosses - these mark regime changes
Check confidence score - higher = more reliable
Use multi-asset mode to see if entire market is shifting (not just one coin)
Best combined with: Trend indicators, support/resistance, volume analysis
Parameters
Lookback: More bars = smoother, less responsive
Alpha (0.10): Defines extreme events - lower = more extreme
Thresholds: Adjust based on asset volatility
Return Type: Log returns recommended for most assets
What Makes It Useful
Unlike simple volatility measures, this shows asymmetry - whether extreme moves favor upside or downside. A ratio of 1.5 means your extreme gains are 50% larger than extreme losses - that's actionable information about risk-reward dynamics.
Multi-asset aggregation is particularly powerful for crypto traders wanting to gauge if BTC, ETH, SOL, etc. are all showing similar regime characteristics.
Disclaimer
Educational tool only. Not financial advice. Use proper risk management. No indicator works in isolation - always consider broader market context.
Developed by GForge
Comments and feedback welcome! 👍
Confluence Execution Engine (2of3)The Confluence Execution Engine is a high-performance logic gate designed to filter out market noise and identify high-probability "Golden" entries. It moves beyond simple indicator signals by acting as a mathematical validator for price action. This engine is designed for the Systematic Trader. It removes the "guesswork" of whether a move is real or an exhaustion pump by requiring a mathematical confluence of volume, multi-timeframe momentum, and volatility-adjusted space.
Why This Tool is Unique:
Multi-Dimensional Scoring, Momentum-Adjusted Stretch, Institutional Fingerprint (RVOL + Spike)
Unlike a standard MACD or RSI, this engine uses a weighted scoring matrix. It pulls a "Bundle" of data (WaveTrend, RSI, ROC) from four different timeframes simultaneously. It doesn't give a signal unless the mathematical weight of all four timeframes crosses your "Hurdle" (Base Threshold).
Standard "overbought" indicators are often wrong during strong trends. This engine uses Dynamic Z-Score logic. The Logic: If the price moves away from the mean, it checks the Rate of Change (ROC). The Result: If momentum is massive, the "Stretch" limit expands. It understands that a "stretched" price is actually a sign of strength in a breakout, not a reason to exit. It only warns of a TRAP RISK when the price is far from the mean but momentum is starting to stall.
The engine is gated by Relative Volume. If the market is "sleepy," the engine stays in "PATIENCE" mode. It specifically hunts for Volume Spikes (default 2.5x average). A signal is only upgraded to "HIGH CONVICTION" when an institutional volume spike occurs, confirming that "Big Money" is participating.
How to Operate the Engine
Define Your Hurdle: Set your Confluence Hurdle. A higher number (e.g., 14+) requires more agreement across timeframes, leading to fewer but higher-quality trades.
Monitor the Z/Dynamic Ratio: In the HUD, watch the Z: X.XX / Y.YY. When X approaches Y, you are reaching the edge of the momentum-adjusted move.
The Entry Trigger: Wait for a "LOOK FOR..." advice to turn into a "HIGH CONVICTION" signal (marked by a triangle shape). This confirms that the MTF scoring, Volume, and HTF Trend are all aligned.
Execute the Lines: Use the red and green "Ghost Lines" to set your orders. These are ATR-based, meaning they widen during high volatility to give your trade room to breathe.
For holistic trading system, pair with Volatility Shield Pro and Session Levels
Jimbob rangethis is a range indication for round numbers should give you levels to trade off when price is in new all time highs where there is no price action to level off.
Breakdown Hold (1m) - Manual Level//@version=6
// =============================================================================
// EN — Script Overview
// Name: Breakdown Hold (1m) - Manual Level
// Purpose:
// Detect a simple pattern: price breaks below a manually set level, then
// stabilizes ("holds") within ~1 minute (default) without further dumping.
// When confirmed, it prints "HOLD OK" and triggers an alert.
//
// How it works:
// 1) You input a fixed price Level.
// 2) On the FIRST break below Level (LOW sweep by default), the script "arms".
// 3) For the next N bars on the 1-minute stream (default N=1):
// - If price drops too deep (beyond Max Further Drop), it fails.
// 4) When the window ends:
// - If it did NOT drop too deep AND it bounced from the window low by at
// least Min Bounce (and optional reclaim above Level), it confirms HOLD.
//
// Recommended usage:
// - Works best on a 1-minute chart.
// - If you are on another timeframe, keep "Force 1m Evaluation" enabled
// so the logic still evaluates on 1-minute data.
//
// Alert:
// - Condition title: breakdown_hold_confirm
//
// =============================================================================
// 中文 — 脚本说明
// 名称：Breakdown Hold (1m) - Manual Level
// 用途：
// 识别一个非常简单的“跌破手动固定价位后，约 1 分钟内踩住不再继续下跌”的形态。
// 确认后在图上打出 “HOLD OK”，并触发提醒。
//
// 原理：
// 1) 手动输入固定价位 Level。
// 2) 当价格第一次跌破 Level（默认按 LOW 刺破）后进入监测（armed）。
// 3) 在接下来 N 根 1分钟K（默认 N=1）内：
// - 若继续下探太深（超过允许最大继续下跌幅度），判定失败，不触发。
// 4) 窗口结束时：
// - 若未下探过深，且从窗口最低点出现至少 Min Bounce 的反弹
// （可选要求收盘站回 Level 上方），则判定“踩住确认”。
//
// 推荐用法：
// - 最推荐 1分钟图使用。
// - 如果你在其他周期图上用，请保持 “Force 1m Evaluation” 开启，
// 让判断仍然基于 1分钟数据进行。
//
// 提醒条件：
// - breakdown_hold_confirm
// =============================================================================
MA Crossover with R SquaredThis indicator enhances the classic Moving Average (MA) crossover strategy with statistical filtering and prediction capabilities.
Let me explain what it does:
Instead of just showing when a fast MA crosses above/below a slow MA, this indicator adds R² (R-squared) filtering to identify higher-quality crossovers and predicts future crossovers.
What is R²?
R² (Coefficient of Determination) is a statistical measure that shows how well one variable explains the movement of another variable. In simpler terms:
R² = 1.0: Perfect relationship - 100% of the movement in one MA is explained by the other MA
R² = 0.8: Strong relationship - 80%
R² = 0.5: Moderate relationship - 50%
R² = 0.0: No relationship - 0%
Imagine two cars driving on a highway:
High R² (0.9): Both cars are in the same lane, moving together consistently
Low R² (0.3): One car is weaving between lanes while the other stays straight - poor coordination.
Traditional MA crossovers often generate false signals during:
Choppy markets (price bouncing around)
Sideways/ranging markets
Low volatility periods
News events causing temporary spikes
The R² Solution:
R² acts as a "quality filter" that answers: "How meaningful this crossover is?"
What this means:
Before R² filtering: Every crossover generates a signal
After R² filtering: Only crossovers with R² > threshold generate signals
Result: Fewer but higher-quality signals.
MARKET REGIME DETECTION
High R² (> 0.7): Strong trending market - MA crossovers are reliable
Medium R² (0.4-0.7): Moderate trending - use with caution
Low R² (< 0.4): Choppy/range-bound market - avoid MA crossover signals
Increasing R²: MAs are converging/moving together more closely
Decreasing R²: MAs are diverging/losing coordination
Sudden R² drop: Potential market regime change.
Why Square the Correlation?
Correlation: Measures direction AND strength (-1 to +1)
R²: Measures strength ONLY (0 to 1)
In trading: We care about relationship strength, not direction
Direction is already indicated by crossover type (bullish/bearish)
Real-World Interpretation:
If R² = 0.64, it means:
64% of the variation in the fast MA is explained by the slow MA
36% is "noise" or unexplained movement
The MAs are moderately coordinated.
R² Trend Confirmation:
Entry: When crossover occurs AND R² is above threshold
Confirmation: R² continues rising after entry
Exit: R² drops below threshold (relationship weakening)
Multi-Timeframe R² Analysis
Check R² on higher timeframe for trend context
Use current timeframe for entry signals
Example: Daily R² > 0.7 gives bullish bias, use 1-hour for entries.
R² LIMITATIONS & CAUTIONS
1. Lagging Nature
R² is calculated from past data
By the time R² is high, the trend may already be established
2. Not a Standalone Indicator
R² should confirm other signals, not generate them alone
Always combine with price action, volume, support/resistance
3. Curve Fitting Risk
Don't over-optimize R² thresholds on historical data
What worked in the past may not work in the future
Use R² as a filter, not a predictor
4. Market-Specific Behavior
R² thresholds that work in trending stocks may fail in Forex
Cryptocurrencies may require different R² settings than commodities
Always test on your specific market/instrument
Before Taking Any Signal:
✅ Does the crossover have a colored circle? (R² > threshold)
✅ What's the R² number shown? (Higher = better)
✅ Is R² rising or falling? (Rising = strengthening relationship)
✅ Check history table - what happened with similar R² values?
✅ Consider prediction - does it align with current signal?
Simple R² Rules of Thumb:
R² > 0.8: Excellent signal quality
R² 0.6-0.8: Good signal quality
R² 0.4-0.6: Moderate - use additional confirmation
R² < 0.4: Poor - avoid or use extreme caution
Think of R² as:
A quality control inspector for MA crossovers
A relationship therapist for your moving averages
A statistical bouncer that only lets strong signals through
Higher win rate + Better risk/reward = More profitable trading
This script transforms the basic "when lines cross" approach into a sophisticated, statistically-validated trading system. R² is the secret sauce that separates random crossovers (Golden/Death) from meaningful trend changes.
DISCLAIMER: This information is provided for educational purposes only and should not be considered financial, investment, or trading advice. Please do boost if you like it. Happy Trading.
Advanced Power Index (GGE)# Advanced Power Index (GGE)
## Overview
The Advanced Power Index is a momentum oscillator that provides faster and more responsive signals compared to traditional RSI indicators. It uses direct summation calculations instead of exponential smoothing, making it particularly effective for short to medium-term trading.
## Key Features
- **Faster Response**: Reacts more quickly to price changes than standard RSI
- **Clearer Signals**: Provides sharper, more defined momentum shifts
- **Customizable Levels**: Overbought (68) and Oversold (32) zones
- **Visual Alerts**: Color-coded plot and background highlighting for critical zones
- **Adaptive**: Works well in both trending and ranging markets
## How It Works
The indicator calculates the ratio between positive and negative price changes over a specified period, converting this into a 0-100 scale oscillator. Unlike traditional RSI which uses Wilder's smoothing method, this approach delivers more immediate signals for momentum changes.
## Trading Applications
### 1. Overbought/Oversold Strategy
- **Oversold (< 32)**: Potential buying opportunity when indicator rises back above 32
- **Overbought (> 68)**: Potential selling opportunity when indicator falls back below 68
### 2. Midline Crossovers
- **Above 50**: Bullish momentum, consider long positions
- **Below 50**: Bearish momentum, consider short positions
### 3. Divergence Trading
- **Bullish Divergence**: Price makes lower lows while indicator makes higher lows
- **Bearish Divergence**: Price makes higher highs while indicator makes lower highs
### 4. Trend Following
- In uptrends: Use pullbacks to the 50 level as entry points
- In downtrends: Use rallies to the 50 level as exit/short points
## Color Coding
- **Green**: Strong bullish momentum (> 68)
- **Red**: Strong bearish momentum (< 32)
- **Yellow**: Neutral zone (32-68)
## Settings
- **Period**: Default 14, adjustable based on your trading timeframe
- **Price Type**: Close, Open, High, Low, or custom source
- **Highlight Zones**: Toggle background highlighting for critical levels
## Best Timeframes
- Most effective on 5-minute to 4-hour charts
- Ideal for day trading and scalping strategies
- Can be combined with trend indicators for confirmation
## Tips for Use
- Don't use in isolation - combine with volume, support/resistance levels
- Works best in liquid, actively traded markets
- Consider using alongside moving averages or MACD
- Always implement proper risk management and stop-losses
## Advantages Over Standard RSI
✓ Faster signal generation
✓ Less lag in volatile markets
✓ Better suited for short-term trading
✓ Clearer momentum shifts
✓ More responsive to sudden price changes
---
**Note**: No indicator is perfect. Always use proper risk management and combine multiple forms of analysis before making trading decisions.
**Disclaimer**: This indicator is for educational and informational purposes only. Past performance does not guarantee future results. Trading involves substantial risk of loss.
Session Volume Analyzer [JOAT]
Session Volume Analyzer — Global Trading Session and Volume Intelligence System
This indicator addresses the analytical challenge of understanding market participation patterns across global trading sessions. It combines precise session detection with comprehensive volume analysis to provide insights into when and how different market participants are active. The tool recognizes that different trading sessions exhibit distinct characteristics in terms of participation, volatility, and volume patterns.
Why This Combination Provides Unique Analytical Value
Traditional session indicators typically only show time boundaries, while volume indicators show raw volume data without session context. This creates analytical gaps:
1. **Session Context Missing**: Volume spikes without session context provide incomplete information
2. **Participation Patterns Hidden**: Different sessions have different participant types (retail, institutional, algorithmic)
3. **Comparative Analysis Lacking**: No easy way to compare volume patterns across sessions
4. **Timing Intelligence Absent**: Understanding WHEN volume occurs is as important as HOW MUCH volume occurs
This indicator's originality lies in creating an integrated session-volume analysis system that:
**Provides Session-Aware Volume Analysis**: Volume data is contextualized within specific trading sessions
**Enables Cross-Session Comparison**: Compare volume patterns between Asian, London, and New York sessions
**Delivers Participation Intelligence**: Understand which sessions are showing above-normal participation
**Offers Real-Time Session Tracking**: Know exactly which session is active and how current volume compares
Technical Innovation and Originality
While session detection and volume analysis exist separately, the innovation lies in:
1. **Integrated Session-Volume Architecture**: Simultaneous tracking of session boundaries and volume statistics creates comprehensive market participation analysis
2. **Multi-Session Volume Comparison System**: Real-time calculation and comparison of volume statistics across different global sessions
3. **Adaptive Volume Threshold Detection**: Automatic identification of above-average volume periods within session context
4. **Comprehensive Visual Integration**: Session backgrounds, volume highlights, and statistical dashboards provide complete market participation picture
How Session Detection and Volume Analysis Work Together
The integration creates a sophisticated market participation analysis system:
**Session Detection Logic**: Uses Pine Script's time functions to identify active sessions
// Session detection based on exchange time
bool inAsian = not na(time(timeframe.period, asianSession))
bool inLondon = not na(time(timeframe.period, londonSession))
bool inNY = not na(time(timeframe.period, nySession))
// Session transition detection
bool asianStart = inAsian and not inAsian
bool londonStart = inLondon and not inLondon
bool nyStart = inNY and not inNY
**Volume Analysis Integration**: Volume statistics are calculated within session context
// Session-specific volume accumulation
if asianStart
asianVol := 0.0
asianBars := 0
if inAsian
asianVol += volume
asianBars += 1
// Real-time session volume analysis
float asianAvgVol = asianBars > 0 ? asianVol / asianBars : 0
**Relative Volume Assessment**: Current volume compared to session-specific averages
float volMA = ta.sma(volume, volLength)
float volRatio = volMA > 0 ? volume / volMA : 1
// Volume classification within session context
bool isHighVol = volRatio >= 1.5 and volRatio < 2.5
bool isVeryHighVol = volRatio >= 2.5
This creates a system where volume analysis is always contextualized within the appropriate trading session, providing more meaningful insights than raw volume data alone.
Comprehensive Session Analysis Framework
**Default Session Definitions** (customizable based on broker timezone):
- **Asian Session**: 1800-0300 (exchange time) - Represents Asian market participation including Tokyo, Hong Kong, Singapore
- **London Session**: 0300-1200 (exchange time) - Represents European market participation
- **New York Session**: 0800-1700 (exchange time) - Represents North American market participation
**Session Overlap Analysis**: The system recognizes and highlights overlap periods:
- **London/New York Overlap**: 0800-1200 - Typically the highest volume period
- **Asian/London Overlap**: 0300-0300 (brief) - Transition period
- **New York/Asian Overlap**: 1700-1800 (brief) - End of NY, start of Asian
**Volume Intelligence Features**:
1. **Session-Specific Volume Accumulation**: Tracks total volume within each session
2. **Cross-Session Volume Comparison**: Compare current session volume to other sessions
3. **Relative Volume Detection**: Identify when current volume exceeds historical averages
4. **Participation Pattern Analysis**: Understand which sessions show consistent high/low participation
Advanced Volume Analysis Methods
**Relative Volume Calculation**:
float volMA = ta.sma(volume, volLength) // Volume moving average
float volRatio = volMA > 0 ? volume / volMA : 1 // Current vs average ratio
// Multi-tier volume classification
bool isNormalVol = volRatio < 1.5
bool isHighVol = volRatio >= 1.5 and volRatio < 2.5
bool isVeryHighVol = volRatio >= 2.5
bool isExtremeVol = volRatio >= 4.0
**Session Volume Tracking**:
// Cumulative session volume with bar counting
if londonStart
londonVol := 0.0
londonBars := 0
if inLondon
londonVol += volume
londonBars += 1
// Average volume per bar calculation
float londonAvgVol = londonBars > 0 ? londonVol / londonBars : 0
**Cross-Session Volume Comparison**:
The system maintains running totals for each session, enabling real-time comparison of participation levels across different global markets.
What the Display Shows
Session Backgrounds — Colored backgrounds indicating which session is active
- Pink: Asian session
- Blue: London session
- Green: New York session
Session Open Lines — Horizontal lines at each session's opening price
Session Markers — Labels (AS, LN, NY) when sessions begin
Volume Highlights — Bar coloring when volume exceeds thresholds
- Orange: High volume (1.5x+ average)
- Red: Very high volume (2.5x+ average)
Dashboard — Current session, cumulative volume, and averages
Color Scheme
Asian — #E91E63 (pink)
London — #2196F3 (blue)
New York — #4CAF50 (green)
High Volume — #FF9800 (orange)
Very High Volume — #F44336 (red)
Inputs
Session Times:
Asian Session window (default: 1800-0300)
London Session window (default: 0300-1200)
New York Session window (default: 0800-1700)
Volume Settings:
Volume MA Length (default: 20)
High Volume threshold (default: 1.5x)
Very High Volume threshold (default: 2.5x)
Visual Settings:
Session colors (customizable)
Show/hide backgrounds, lines, markers
Background transparency
How to Read the Display
Background color shows which session is currently active
Session open lines show where each session started
Orange/red bars indicate above-average volume
Dashboard shows cumulative volume for each session today
Alerts
Session opened (Asian, London, New York)
High volume bar detected
Very high volume bar detected
Important Limitations and Realistic Expectations
Session times are approximate and depend on your broker's server timezone—manual adjustment may be required for accuracy
Volume data quality varies significantly by broker, instrument, and market type
Cryptocurrency and some forex markets trade continuously, making traditional session boundaries less meaningful
High volume indicates participation level only—it does not predict price direction or market outcomes
Session participation patterns can change over time due to market structure evolution, holidays, and economic conditions
This tool displays historical and current market participation data—it cannot predict future volume or price movements
Volume spikes can occur for numerous reasons unrelated to directional price movement (news, algorithmic trading, etc.)
Different instruments exhibit different session sensitivity and volume patterns
Market holidays and special events can significantly alter normal session patterns
Appropriate Use Cases
This indicator is designed for:
- Market participation pattern analysis
- Session-based trading schedule planning
- Volume context and comparison across sessions
- Educational study of global market structure
- Supplementary analysis for session-based strategies
This indicator is NOT designed for:
- Standalone trading signal generation
- Volume-based price direction prediction
- Automated trading system triggers
- Guaranteed session pattern repetition
- Replacement of fundamental or sentiment analysis
Understanding Session Analysis Limitations
Session analysis provides valuable context but has inherent limitations:
- Session patterns can change due to economic conditions, holidays, and market structure evolution
- Volume patterns may not repeat consistently across different market conditions
- Global events can override normal session characteristics
- Different asset classes respond differently to session boundaries
- Technology and algorithmic trading continue to blur traditional session distinctions
— Made with passion by officialjackofalltrades
Minervini Trend Template upgrade - TP Minervini Trend Template (SMA/EMA + RS vs Major Indices)
Credits: Original script by © yogy.frestarahmawan (MPL 2.0).
Modified & updated by: © TradersPod (added MA selection + RS comparison vs major index futures).
This indicator is a simple checklist tool based on Mark Minervini’s “Trend Template” concept. It helps you quickly see if a stock is behaving like a leading stock in an uptrend by evaluating key trend and strength conditions.
What it does:
>The script checks 8 conditions and shows the results in a table panel on your chart:
>Price is above MA150 and MA200
>MA150 is above MA200 (a classic “healthy uptrend” structure)
>MA200 is rising vs ~1 month ago (uses 22 bars back)
>MA50 is above MA150 and MA200
>Price is above MA50
>Price is at least 25% above the 52-week low (stronger stocks tend to be far from lows)
>Price is within 25% of the 52-week high (leaders often stay near highs)
>RS is > Major Indices (TradersPod upgrade)
At the bottom, it also totals how many conditions are met: (X of 8).
TradersPod upgrades included
1) SMA/EMA selection
You can choose whether the trend template uses:
SMA (Simple Moving Average)
or
EMA (Exponential Moving Average)
This lets you match your preferred moving-average style without changing the logic.
2) RS must beat the major indices (futures)
Instead of the old “RS > 70” rule, this updated version requires the stock’s RS Rating to be greater than the strongest (highest RS) among:
-Nasdaq Futures (NQ)
-S&P 500 Futures (ES)
-Dow Jones Futures (YM)
The table shows the RS Rating for each index futures symbol and then confirms whether the stock is stronger than the best-performing major index.
In other words:
If the stock can’t outperform the major indices, it’s probably not a true “leader.”
Inputs / settings
MA Type: SMA or EMA
High/Low Lookback Length: default 260 bars (approx. 52 weeks on daily charts)
Show 52-week High/Low: toggle on/off
Major Indices Symbols: you can change the futures tickers if your broker/data feed uses different symbols
Panel Position: choose where the table appears
Notes (important)
The RS calculation uses the chart’s timeframe (ex: Daily, Weekly). On Weekly charts, the lookbacks become weeks (not days).
This tool is a trend/strength filter, not a full trading strategy. Always add your own risk management, entries, and exits.
ETH Dynamic Risk Strategy# ETH Dynamic Risk Strategy - Publication Description
## Overview
The ETH Dynamic Risk Strategy is a systematic approach to accumulating Ethereum during bear markets and distributing during bull markets. It combines multiple risk indicators into a single composite metric (0-1 scale) that identifies optimal buying and selling zones based on market conditions.
## Key Features
• **Multi-Component Risk Metric**: Combines 4 weighted indicators to assess market conditions
• **Tiered Buy/Sell System**: 3 levels of buy signals (L1, L2, L3) and 3 levels of sell signals based on risk thresholds
• **Configurable Filters**: Optional buy filters to reduce signal frequency by 30-50%
• **Visual Risk Zones**: Color-coded risk metric plot with clear threshold lines
• **Comprehensive Dashboard**: Real-time statistics including position size, P/L, and component scores
## How It Works
### Risk Components (Configurable Weights)
1. **Log Return from ATH** (Default: 35%)
- Tracks drawdown from all-time high over lookback period
- Deep drawdowns (-70% to -90%) = low risk / buying opportunity
- Near ATH (0% to -20%) = high risk / selling opportunity
2. **ETH/BTC Ratio** (Default: 25%)
- Measures ETH strength relative to Bitcoin
- Below historical average = ETH undervalued = low risk
- Above historical average = ETH overvalued = high risk
3. **Volatility Regime** (Default: 20%)
- Compares current volatility to long-term average
- Compressed volatility at lows = opportunity
- Expanded volatility at highs = danger
4. **Trend Strength** (Default: 20%)
- Uses multiple EMA alignment and slope analysis
- Strong downtrends = low risk scores
- Strong uptrends = high risk scores
### Trading Logic
**Buy Signals:**
- L1: Risk ≤ 0.30 → Buy $100 (default)
- L2: Risk ≤ 0.20 → Buy $250 total
- L3: Risk ≤ 0.10 → Buy $450 total
**Sell Signals (Sequential):**
- L1: Risk ≥ 0.75 → Sell 25% of position
- L2: Risk ≥ 0.85 → Sell 35% of remaining
- L3: Risk ≥ 0.95 → Sell 40% of remaining
**Buy Filters (Optional):**
- Minimum days between buys (prevents clustering)
- Minimum risk drop required (ensures falling risk)
- Toggle on/off to compare performance
## Settings Guide
### Risk Components
Toggle individual components on/off and adjust their weights. Total weight is automatically normalized. Experiment with different combinations to match your market view.
### Advanced Settings
- ATH Lookback: How far back to look for all-time highs (500-2000 recommended)
- Volatility Period: Window for volatility calculations (40-100 recommended)
- ETH/BTC MA Period: Moving average for ratio comparison (100-300 recommended)
- Trend Period: Base period for trend calculations (50-150 recommended)
### Trading Thresholds
Customize buy/sell trigger points and position sizes. Lower buy thresholds = more aggressive accumulation. Higher sell thresholds = holding longer into bull markets.
### Buy Filters
- Enable/disable filtering system
- Min Days Between Buys: Spacing between purchases (1-3 recommended)
- Min Risk Drop: How much risk must fall (-0.001 to -0.01 range)
## Best Practices
• **Timeframe**: Works best on daily (1D) and 3-day (3D) charts
• **Initial Capital**: Set based on your DCA budget (default $10,000)
• **Backtest First**: Test different parameter combinations on historical data
• **Position Sizing**: Adjust buy amounts to match your risk tolerance
• **Monitor Filters**: Check "Filtered Buys" stat to ensure filter isn't too strict
## Use Cases
- Long-term ETH accumulation strategy
- Systematic DCA with market-adaptive buying
- Risk-based portfolio rebalancing
- Educational tool for understanding crypto market cycles
## Disclaimer
This strategy is for educational purposes only. Past performance does not guarantee future results. Cryptocurrency trading involves substantial risk. The strategy uses historical price action and technical indicators which may not predict future movements. Always do your own research and never invest more than you can afford to lose.
## Credits
Strategy concept and development by nakphanan with assistance from Claude AI (Anthropic). Built using Pine Script v5....Mostly from Claude AI!!!
## Version History
v7.0 - Initial release with 4-component risk metric, tiered trading system, and optional buy filters
SCOTTGO - Float, Change %, Vol & RVol DataFloat, Vol & Short Data Dashboard
Overview
The Float, Vol & Short Data Dashboard is a professional-grade monitoring tool designed for equity traders who need to track supply, demand, and momentum in real-time. By aggregating float size, relative volume, and short-selling activity into a clean, customizable table, this script helps you identify high-conviction trade setups without cluttering your price chart.
Key Metrics Included
Float: (Shares) – Instantly see the available supply of shares to gauge potential volatility.
Change %: (From close) – Tracks the percentage gain/loss since the previous day's closing price.
Change %: (From open) – Monitors intraday strength by calculating the move from the 9:30 AM EST market open.
Volume: – Displays current daily volume with automated formatting (K, M, B).
RVOL: (Daily) – Relative Volume compared to a 10-day SMA; essential for spotting "volume-fueled" breakouts.
Short %: (Approx.) – Calculates the daily Short Volume Ratio (Short Volume / Total Volume), providing a real-time proxy for short-seller sentiment.
Professional Customization
This script was built with a focus on UI/UX:
Three-Row Header System: Features high-contrast main titles with muted-grey sub-titles for maximum readability.
Smart Color Logic: Price changes automatically toggle between green and red, while RVol highlights in orange when activity exceeds 1.5x average.
Adjustable Layout: Change the table position, text size, and background opacity.
Column Spacing: Includes a custom slider to adjust the horizontal gap between data columns, ensuring the dashboard fits any screen resolution.
How To Use
Add the script to your chart and use the Settings menu to toggle metrics or adjust the Column Spacing to your preference. Ideal for day traders and swing traders monitoring US Equities where float and short volume data are most impactful.
MACD Backtesting IndicatorThis Pine Script v5 indicator replicates TradingView's standard MACD with full backtesting capabilities. Traders can adjust all parameters (12,26,9 defaults) through inputs and see real-time performance metrics in the table. Buy/sell signals appear as labeled arrows, matching classic MACD crossover strategy while providing visual backtest results for strategy evaluation.
RS Rating (1-99)RS Rating
This indicator implements a Relative Strength (RS) rating for TradingView and is designed specifically to be used with the Pine Screener.
Concept
Relative Strength is calculated using weighted price performance over multiple time windows (approximately 3, 6, 9, and 12 months).
More recent performance is weighted more heavily, following well-established relative strength methodologies.
The resulting raw RS score is then compressed into a 1–99 scale, creating an intuitive and stable ranking metric.
Because TradingView scripts cannot rank a stock against the entire market universe, this indicator uses a behavioral proxy: the current RS score is mapped against its own historical distribution.
This produces RS values that behave similarly to widely used RS ratings, but it is not a true cross-sectional percentile rank.
IPO handling
RS Rating is not displayed until sufficient price history exists (default: ~9 months / 189 bars).
This avoids distorted RS values for newly listed stocks. IPOs are better evaluated using separate momentum, volume, or structure-based tools until they mature.
Interpretation (rule of thumb)
- RS ≥ 80 → strong relative performance
- RS ≥ 90 → leader
- RS ≥ 95 → very selective / top-tier
- RS Rating is best used as a ranking and confirmation tool, not as an entry signal.
Using RS Rating with TradingView Pine Screener
This indicator is designed to work directly with the TradingView Pine Screener (beta).
Setup
- Add the indicator to a chart
- Open Pine Screener
- Select this script as a filter source
- Use the plotted RS Rating (1–99) value for sorting or filtering
The screener reads the single plotted RS value and treats it as a sortable numeric column.
Typical screening workflows
Leader scan
Filter: RS Rating ≥ 90
Sort: Descending by RS Rating
Identifies stocks with sustained relative outperformance.
Broad strength scan
Filter: RS Rating ≥ 80
Useful for identifying emerging leaders or strong secondary names.
Top-of-universe view
No filter
Sort: Descending by RS Rating
Shows the strongest names within the selected universe.
Important notes on Pine Screener (beta)
The Pine Screener currently displays a limited number of results (approximately 100).
Symbols may be pre-sampled before filtering.
For larger universes, consider:
- splitting symbols to be scanned into multiple watchlists
Best practices
Use RS Rating to rank and prioritize candidates, not to time entries.
Combine RS with:
- price structure,
- volume behavior,
- overall market regime.
RS is most effective when used as part of a multi-factor screening process.
CryptoFlux Dynamo [JOAT]CryptoFlux Dynamo: Velocity Scalping Strategy
WHAT THIS STRATEGY IS
CryptoFlux Dynamo is an open-source Pine Script v6 strategy designed for momentum-based scalping on cryptocurrency perpetual futures. It combines multiple technical analysis methods into a unified system that adapts its behavior based on current market volatility conditions.
This script is published open-source so you can read, understand, and modify the complete logic. The description below explains everything the strategy does so that traders who cannot read Pine Script can fully understand how it works before using it.
HOW THIS STRATEGY IS ORIGINAL AND WHY THE INDICATORS ARE COMBINED
This strategy uses well-known indicators (MACD, EMA, RSI, MFI, Bollinger Bands, Keltner Channels, ATR). The originality is not in the individual indicators themselves, but in the specific way they are integrated into a regime-adaptive system. Here is the detailed justification for why these components are combined and how they work together:
The Problem Being Solved:
Standard indicator-based strategies use fixed thresholds. For example, a typical MACD strategy might enter when the histogram crosses above zero. However, in cryptocurrency markets, volatility changes dramatically throughout the day and week. A MACD crossover during a low-volatility consolidation period has very different implications than the same crossover during a high-volatility trending period. Using the same entry thresholds and stop distances in both conditions leads to either:
Too many false signals during consolidation (if thresholds are loose)
Missing valid opportunities during expansion (if thresholds are tight)
Stops that are too tight during volatility spikes (causing premature exits)
Stops that are too wide during compression (giving back profits)
The Solution Approach:
This strategy first classifies the current volatility regime using normalized ATR (ATR as a percentage of price), then dynamically adjusts ALL other parameters based on that classification. This creates a context-aware system rather than a static threshold comparison.
How Each Component Contributes to the System:
ATR-Based Regime Classification (The Foundation)
The strategy calculates ATR over 21 periods, smooths it with a 13-period EMA to reduce noise from wicks, then divides by price to get a normalized percentage. This ATR% is classified into three regimes:
- Compression (ATR% < 0.8%): Market is consolidating, breakouts are more likely but false signals are common
- Expansion (ATR% 0.8% - 1.6%): Normal trending conditions
- Velocity (ATR% > 1.6%): High volatility, larger moves but also larger adverse excursions
This regime classification then controls stop distances, profit targets, trailing stop offsets, and signal strength requirements. The regime acts as a "meta-parameter" that tunes the entire system.
EMA Ribbon (8/21/34) - Trend Structure Detection
The three EMAs establish trend direction and structure. When EMA 8 > EMA 21 > EMA 34, the trend structure is bullish. The slope of the middle EMA (21) is calculated over 8 bars and converted to degrees using arctangent. This slope measurement quantifies trend strength, not just direction.
Why these specific periods? The 8/21/34 sequence follows Fibonacci-like spacing and provides good separation on 5-minute cryptocurrency charts. The fast EMA (8) responds to immediate price action, the mid EMA (21) represents the short-term trend, and the slow EMA (34) acts as a trend filter.
The EMA ribbon works with the regime classification: during compression regimes, the strategy requires stronger ribbon alignment before entry because false breakouts are more common.
MACD (8/21/5) - Momentum Measurement
The MACD uses faster parameters (8/21/5) than the standard (12/26/9) because cryptocurrency markets move faster than traditional markets. The histogram is smoothed with a 5-period EMA to reduce noise.
The key innovation is the adaptive histogram baseline. Instead of using a fixed threshold, the strategy calculates a rolling baseline from the smoothed absolute histogram value, then multiplies by a sensitivity factor (1.15). This means the threshold for "significant momentum" automatically adjusts based on recent momentum levels.
The MACD works with the regime classification: during velocity regimes, the histogram baseline is effectively higher because recent momentum has been stronger, preventing entries on relatively weak momentum.
RSI (21 period) and MFI (21 period) - Independent Momentum Confirmation
RSI measures momentum using price changes only. MFI (Money Flow Index) measures momentum using price AND volume. By requiring both to confirm, the strategy filters out price moves that lack volume support.
The 21-period length is longer than typical (14) to reduce noise on 5-minute charts. The trigger threshold (55 for longs, 45 for shorts) is slightly offset from 50 to require momentum in the trade direction, not just neutral readings.
These indicators work together: a signal requires RSI > 55 AND MFI > 55 for longs. This dual confirmation reduces false signals from price manipulation or low-volume moves.
Bollinger Bands (1.5 mult) and Keltner Channels (1.8 mult) - Squeeze Detection
When Bollinger Bands contract inside Keltner Channels, volatility is compressing and a breakout is likely. This is the "squeeze" condition. When the bands expand back outside the channels, the squeeze "releases."
The strategy uses a 1.5 multiplier for Bollinger Bands (tighter than standard 2.0) and 1.8 for Keltner Channels. These values were chosen to identify meaningful squeezes on 5-minute cryptocurrency charts without triggering too frequently.
The squeeze detection works with the regime classification: squeeze releases during compression regimes receive additional signal strength points because breakouts from consolidation are more significant.
Volume Impulse Detection - Institutional Participation Filter
The strategy calculates a volume baseline (34-period SMA) and standard deviation. A "volume impulse" is detected when current volume exceeds the baseline by 1.15x OR when the volume z-score exceeds 0.5.
This filter ensures entries occur when there is meaningful market participation, not during low-volume periods where price moves are less reliable.
Volume impulse is required for all entries and adds points to the composite signal strength score.
Cycle Oscillator - Trend Alignment Filter
The strategy calculates a 55-period EMA as a cycle basis, then measures price deviation from this basis as a percentage. When price is more than 0.15% above the cycle basis, the cycle is bullish. When more than 0.15% below, the cycle is bearish.
This filter prevents counter-trend entries. Long signals require bullish cycle alignment; short signals require bearish cycle alignment.
BTC Dominance Filter (Optional) - Market Regime Filter
The strategy can optionally use BTC.D (Bitcoin Dominance) as a market regime filter. When BTC dominance is rising (slope > 0.12), the market is in "risk-off" mode and long entries on altcoins are filtered. When dominance is falling (slope < -0.12), short entries are filtered.
This filter is optional because the BTC.D data feed may lag during low-liquidity periods.
How The Components Work Together (The Mashup Justification):
The strategy uses a composite scoring system where each signal pathway contributes points:
Trend Break pathway (30 points): Requires EMA ribbon alignment + positive slope + price breaks above recent structure high
Momentum Surge pathway (30 points): Requires MACD histogram > adaptive baseline + MACD line > signal + RSI > 55 + MFI > 55 + volume impulse
Squeeze Release pathway (25 points): Requires BB inside KC (squeeze) then release + momentum bias + histogram confirmation
Micro Pullback pathway (15 points): Requires shallow retracement to fast EMA within established trend + histogram confirmation + volume impulse
Additional modifiers:
+5 points if volume impulse is present, -5 if absent
+5 points in velocity regime, -2 in compression regime
+5 points if cycle is aligned, -5 if counter-trend
A trade only executes when the composite score reaches the minimum threshold (default 55) AND all filters agree (session, cycle bias, BTC dominance if enabled).
This scoring system is the core innovation: instead of requiring ALL conditions to be true (which would generate very few signals) or ANY condition to be true (which would generate too many false signals), the strategy requires ENOUGH conditions to be true, with different conditions contributing different weights based on their reliability.
HOW THE STRATEGY CALCULATES ENTRIES AND EXITS
Entry Logic:
1. Calculate current volatility regime from ATR%
2. Calculate all indicator values (MACD, EMA, RSI, MFI, squeeze, volume)
3. Evaluate each signal pathway and sum points
4. Check all filters (session, cycle, dominance, kill switch)
5. If composite score >= 55 AND all filters pass, generate entry signal
6. Calculate position size based on risk per trade and regime-adjusted stop distance
7. Execute entry with regime name as comment
Position Sizing Formula:
RiskCapital = Equity * (0.65 / 100)
StopDistance = ATR * StopMultiplier(regime)
RawQuantity = RiskCapital / StopDistance
MaxQuantity = Equity * (12 / 100) / Price
Quantity = min(RawQuantity, MaxQuantity)
Quantity = round(Quantity / 0.001) * 0.001
This ensures each trade risks approximately 0.65% of equity regardless of volatility, while capping total exposure at 12% of equity.
Stop Loss Calculation:
Stop distance is ATR multiplied by a regime-specific multiplier:
Compression regime: 1.05x ATR (tighter stops because moves are smaller)
Expansion regime: 1.55x ATR (standard stops)
Velocity regime: 2.1x ATR (wider stops to avoid premature exits during volatility)
Take Profit Calculation:
Target distance is ATR multiplied by regime-specific multiplier and base risk/reward:
Compression regime: 1.6x ATR * 1.8 base R:R * 0.9 regime bonus = approximately 2.6x ATR
Expansion regime: 2.05x ATR * 1.8 base R:R * 1.0 regime bonus = approximately 3.7x ATR
Velocity regime: 2.8x ATR * 1.8 base R:R * 1.15 regime bonus = approximately 5.8x ATR
Trailing Stop Logic:
When adaptive trailing is enabled, the strategy calculates a trailing offset based on ATR and regime:
Compression regime: 1.1x base offset (looser trailing to avoid noise)
Expansion regime: 1.0x base offset (standard)
Velocity regime: 0.8x base offset (tighter trailing to lock in profits during fast moves)
The trailing stop only activates when it would be tighter than the initial stop.
Momentum Fail-Safe Exits:
The strategy closes positions early if momentum reverses:
Long positions close if MACD histogram turns negative OR EMA ribbon structure breaks (fast EMA crosses below mid EMA)
Short positions close if MACD histogram turns positive OR EMA ribbon structure breaks
This prevents holding through momentum reversals even if stop loss hasn't been hit.
Kill Switch:
If maximum drawdown exceeds 6.5%, the strategy disables new entries until manually reset. This prevents continued trading during adverse conditions.
HOW TO USE THIS STRATEGY
Step 1: Apply to Chart
Use a 5-minute chart of a high-liquidity cryptocurrency perpetual (BTC/USDT, ETH/USDT recommended)
Ensure at least 200 bars of history are loaded for indicator stabilization
Use standard candlestick charts only (not Heikin Ashi, Renko, or other non-standard types)
Step 2: Understand the Visual Elements
EMA Ribbon: Three lines (8/21/34 periods) showing trend structure. Bullish when stacked upward, bearish when stacked downward.
Background Color: Shows current volatility regime
- Indigo/dark blue = Compression (low volatility)
- Purple = Expansion (normal volatility)
- Magenta/pink = Velocity (high volatility)
Bar Colors: Reflect signal strength divergence. Brighter colors indicate stronger directional bias.
Triangle Markers: Entry signals. Up triangles below bars = long entry. Down triangles above bars = short entry.
Dashboard (top-right): Real-time display of regime, ATR%, signal strengths, position status, stops, targets, and risk metrics.
Step 3: Interpret the Dashboard
Regime: Current volatility classification (Compression/Expansion/Velocity)
ATR%: Normalized volatility as percentage of price
Long/Short Strength: Current composite signal scores (0-100)
Cycle Osc: Price deviation from 55-period EMA as percentage
Dominance: BTC.D slope and filter status
Position: Current position direction or "Flat"
Stop/Target: Current stop loss and take profit levels
Kill Switch: Status of drawdown protection
Volume Z: Current volume z-score
Impulse: Whether volume impulse condition is met
Step 4: Adjust Parameters for Your Needs
For more conservative trading: Increase "Minimum Composite Signal Strength" to 65 or higher
For more aggressive trading: Decrease to 50 (but expect more false signals)
For higher timeframes (15m+): Increase "Structure Break Window" to 12-15, increase "RSI Momentum Trigger" to 58
For lower liquidity pairs: Increase "Volume Impulse Multiplier" to 1.3, increase slippage in strategy properties
To disable short selling: Uncheck "Enable Short Structure"
To disable BTC dominance filter: Uncheck "BTC Dominance Confirmation"
STRATEGY PROPERTIES (BACKTEST SETTINGS)
These are the exact settings used in the strategy's Properties dialog box. You must use these same settings when evaluating the backtest results shown in the publication:
Initial Capital: $100,000
Justification: This amount is higher than typical retail accounts. I chose this value to demonstrate percentage-based returns that scale proportionally. The strategy uses percentage-based position sizing (0.65% risk per trade), so a $10,000 account would see the same percentage returns with 10x smaller position sizes. The absolute dollar amounts in the backtest should be interpreted as percentages of capital.
Commission: 0.04% (commission_value = 0.04)
Justification: This reflects typical perpetual futures exchange fees. Major exchanges charge between 0.02% (maker) and 0.075% (taker). The 0.04% value is a reasonable middle estimate. If your exchange charges different fees, adjust this value accordingly. Higher fees will reduce net profitability.
Slippage: 1 tick
Justification: This is conservative for liquid pairs like BTC/USDT on major exchanges during normal conditions. For less liquid altcoins or during high volatility, actual slippage may be higher. If you trade less liquid pairs, increase this value to 2-3 ticks for more realistic results.
Pyramiding: 1
Justification: No position stacking. The strategy holds only one position at a time. This simplifies risk management and prevents overexposure.
calc_on_every_tick: true
Justification: The strategy evaluates on every price update, not just bar close. This is necessary for scalping timeframes where waiting for bar close would miss opportunities. Note that this setting means backtest results may differ slightly from bar-close-only evaluation.
calc_on_order_fills: true
Justification: The strategy recalculates immediately after order fills for faster response to position changes.
RISK PER TRADE JUSTIFICATION
The default risk per trade is 0.65% of equity. This is well within the TradingView guideline that "risking more than 5-10% on a trade is not typically considered viable."
With the 12% maximum exposure cap, even if the strategy takes multiple consecutive losses, the total risk remains manageable. The kill switch at 6.5% drawdown provides additional protection by halting new entries during adverse conditions.
The position sizing formula ensures that stop distance (which varies by regime) is accounted for, so actual risk per trade remains approximately 0.65% regardless of volatility conditions.
SAMPLE SIZE CONSIDERATIONS
For statistically meaningful backtest results, you should select a dataset that generates at least 100 trades. On 5-minute BTC/USDT charts, this typically requires:
2-3 months of data during normal market conditions
1-2 months during high-volatility periods
3-4 months during low-volatility consolidation periods
The strategy's selectivity (requiring 55+ composite score plus all filters) means it generates fewer signals than less filtered approaches. If your backtest shows fewer than 100 trades, extend the date range or reduce the minimum signal strength threshold.
Fewer than 100 trades produces statistically unreliable results. Win rate, profit factor, and other metrics can vary significantly with small sample sizes.
STRATEGY DESIGN COMPROMISES AND LIMITATIONS
Every strategy involves trade-offs. Here are the compromises made in this design and the limitations you should understand:
Selectivity vs. Opportunity Trade-off
The 55-point minimum threshold filters many potential trades. This reduces false signals but also misses valid setups that don't meet all criteria. Lowering the threshold increases trade frequency but decreases win rate. There is no "correct" threshold; it depends on your preference for fewer higher-quality signals vs. more signals with lower individual quality.
Regime Classification Lag
The ATR-based regime detection uses historical data (21 periods + 13-period smoothing). It cannot predict sudden volatility spikes. During flash crashes or black swan events, the strategy may be classified in the wrong regime for several bars before the classification updates. This is an inherent limitation of any lagging indicator.
Indicator Parameter Sensitivity
The default parameters (MACD 8/21/5, EMA 8/21/34, RSI 21, etc.) are tuned for BTC/ETH perpetuals on 5-minute charts during 2024 market conditions. Different assets, timeframes, or market regimes may require different parameters. There is no guarantee that parameters optimized on historical data will perform similarly in the future.
BTC Dominance Filter Limitations
The CRYPTOCAP:BTC.D data feed may lag during low-liquidity periods or weekends. The dominance slope calculation uses a 5-bar SMA, adding additional delay. If you notice the filter behaving unexpectedly, consider disabling it.
Backtest vs. Live Execution Differences
TradingView backtesting does not replicate actual broker execution. Key differences:
Backtests assume perfect fills at calculated prices; real execution involves order book depth, latency, and partial fills
The calc_on_every_tick setting improves backtest realism but still cannot capture sub-bar price action or order book dynamics
Commission and slippage settings are estimates; actual costs vary by exchange, time of day, and market conditions
Funding rates on perpetual futures are not modeled in backtests and can significantly impact profitability over time
Exchange-specific limitations (position limits, liquidation mechanics, order types) are not modeled
Market Condition Dependencies
This strategy is designed for trending and breakout conditions. During extended sideways consolidation with no clear direction, the strategy may generate few signals or experience whipsaws. No strategy performs well in all market conditions.
Cryptocurrency-Specific Risks
Cryptocurrency markets operate 24/7 without session boundaries. This means:
No natural "overnight" risk reduction
Volatility can spike at any time
Liquidity varies significantly by time of day
Exchange outages or issues can occur at any time
WHAT THIS STRATEGY DOES NOT DO
To be straightforward about limitations:
This strategy does not guarantee profits. Past backtest performance does not indicate future results.
This strategy does not predict the future. It reacts to current conditions based on historical patterns.
This strategy does not account for funding rates, which can significantly impact perpetual futures profitability.
This strategy does not model exchange-specific execution issues (partial fills, requotes, outages).
This strategy does not adapt to fundamental news events or black swan scenarios.
This strategy is not optimized for all market conditions. It may underperform during extended consolidation.
IMPORTANT RISK WARNINGS
Past performance does not guarantee future results. The backtest results shown reflect specific historical market conditions and parameter settings. Markets change constantly, and strategies that performed well historically may underperform or lose money in the future. A single backtest run does not constitute proof of future profitability.
Trading involves substantial risk of loss. Cryptocurrency derivatives are highly volatile instruments. You can lose your entire investment. Only trade with capital you can afford to lose completely.
This is not financial advice. This strategy is provided for educational and informational purposes only. It does not constitute investment advice, trading recommendations, or any form of financial guidance. The author is not a licensed financial advisor.
You are responsible for your own decisions. Before using this strategy with real capital:
Thoroughly understand the code and logic by reading the open-source implementation
Forward test with paper trading or very small positions for an extended period
Verify that commission, slippage, and execution assumptions match your actual trading environment
Understand that live results will differ from backtest results
Consider consulting with a qualified financial advisor
No guarantees or warranties. This strategy is provided "as is" without any guarantees of profitability, accuracy, or suitability for any purpose. The author is not responsible for any losses incurred from using this strategy.
OPEN-SOURCE CODE STRUCTURE
The strategy code is organized into these sections for readability:
Configuration Architecture: Input parameters organized into logical groups (Core Controls, Optimization Constants, Regime Intelligence, Signal Pathways, Risk Architecture, Visualization)
Helper Functions: calcQty() for position sizing, clamp01() and normalize() for value normalization, calcMFI() for Money Flow Index calculation
Core Indicator Engine: EMA ribbon, ATR and regime classification, MACD with adaptive baseline, RSI, MFI, volume analytics, cycle oscillator, BTC dominance filter, squeeze detection
Signal Pathway Logic: Trend break, momentum surge, squeeze release, micro pullback pathways with composite scoring
Entry/Exit Orchestration: Signal filtering, position sizing, entry execution, stop/target calculation, trailing stop logic, momentum fail-safe exits
Visualization Layer: EMA plots, regime background, bar coloring, signal labels, dashboard table
You can read and modify any part of the code. Understanding the logic before deployment is strongly recommended.
- Made with passion by officialjackofalltrades
