PINE LIBRARY
CyberMarketLib
# CyberMarketLib v2
CyberMarketLib provides market structure analysis combining swing point detection, Break of Structure (BoS) / Change of Character (CHoCH) identification, session classification, and volatility regime tracking.
## What it does
Delivers four core capabilities: swing point tracking (configurable left/right bar lookback), market structure events (BoS/CHoCH for trend continuation vs reversal), session classification (Asia/London/NY via UTC bucketing), and volatility regimes (LOW/NORMAL/HIGH/EXTREME via ATR percentiles). Build context-aware indicators that adapt to market conditions.
Outputs FractalData structs, StructureEvent/Session/VolRegime enums. All pivots use confirmed swing points (requires right_len bars validation), preventing repainting.
## How it works
Swing detection: `high[left_len] < high[0] > high[right_len]`. Stores pivots in SwingHistory circular buffers with automatic capacity management.
BoS/CHoCH follows Smart Money Concepts:
- BOS_UP/DOWN: Price breaks recent swing (trend continuation)
- CHOCH_UP/DOWN: Pivot break after opposite swing (reversal)
Sessions via UTC hours: ASIA (00-08), LONDON (08-13), NY_OVERLAP (13-17), NY_AFTERNOON (17-21), OFF_HOURS (21-24).
Volatility regimes via ATR percentiles (100-bar window): LOW (<25th), NORMAL (25-75th), HIGH (75-90th), EXTREME (>90th).
## Why this is original
Only TradingView library combining BoS/CHoCH, sessions, and volatility regimes. Existing SMC indicators lack reusable libraries.
Unique features:
- Confirmed pivots only (no repainting)
- CHoCH sequence analysis (pivot pattern detection)
- UTC-based sessions (exchange-agnostic, DST-safe)
- Percentile volatility (asset-adaptive)
- Circular buffer (O(1) operations, memory-efficient)
Designed for composability: sessions → conditional logic, regimes → stop multipliers, BoS/CHoCH → entry/exit signals.
## How to use it
```pine
//version=6
indicator("CyberMarketLib Demo", overlay=true)
import cybermediaboy/CyberMarketLib/2 as ML
// Swing points + BoS/CHoCH detection
var swing_hist = ML.f_swing_history_new(max_n=20)
var fractal = ML.f_detect_pivot(left_len=5, right_len=5)
if not na(fractal)
swing_hist.push(fractal)
var event = ML.f_detect_structure_event(swing_hist, close)
// event: BOS_UP, BOS_DOWN, CHOCH_UP, CHOCH_DOWN, NONE
// Session + volatility regime
session = ML.f_current_session() // ASIA, LONDON, NY_OVERLAP, etc.
vol_regime = ML.f_volatility_regime(14, 100) // LOW, NORMAL, HIGH, EXTREME
// Adaptive stops
atr = ta.atr(14)
stop_mult = vol_regime == ML.VolRegime.EXTREME ? 3.0 : 1.5
plot(close - atr * stop_mult, "Stop", color.red)
```
## Key functions
- `f_detect_pivot()` - Confirmed swing points (no repainting)
- `f_detect_structure_event()` - BoS/CHoCH detection
- `f_current_session()` - UTC-based session classification
- `f_volatility_regime()` - ATR percentile regimes
- `f_htf_for()` - Higher timeframe string generation
- SwingHistory UDT - Circular buffer for pivot storage
## Limitations
- Swing detection: `right_len` bars confirmation delay (lag vs repainting indicators)
- BoS/CHoCH: Assumes trending markets (false signals in choppy ranges)
- Sessions: UTC-only (no exchange-native or DST-aware sessions)
- Volatility: ATR-based only (may lag on sudden spikes)
- SwingHistory: Fixed capacity at initialization
- CHoCH: Requires manual state tracking to avoid duplicate signals
CyberMarketLib provides market structure analysis combining swing point detection, Break of Structure (BoS) / Change of Character (CHoCH) identification, session classification, and volatility regime tracking.
## What it does
Delivers four core capabilities: swing point tracking (configurable left/right bar lookback), market structure events (BoS/CHoCH for trend continuation vs reversal), session classification (Asia/London/NY via UTC bucketing), and volatility regimes (LOW/NORMAL/HIGH/EXTREME via ATR percentiles). Build context-aware indicators that adapt to market conditions.
Outputs FractalData structs, StructureEvent/Session/VolRegime enums. All pivots use confirmed swing points (requires right_len bars validation), preventing repainting.
## How it works
Swing detection: `high[left_len] < high[0] > high[right_len]`. Stores pivots in SwingHistory circular buffers with automatic capacity management.
BoS/CHoCH follows Smart Money Concepts:
- BOS_UP/DOWN: Price breaks recent swing (trend continuation)
- CHOCH_UP/DOWN: Pivot break after opposite swing (reversal)
Sessions via UTC hours: ASIA (00-08), LONDON (08-13), NY_OVERLAP (13-17), NY_AFTERNOON (17-21), OFF_HOURS (21-24).
Volatility regimes via ATR percentiles (100-bar window): LOW (<25th), NORMAL (25-75th), HIGH (75-90th), EXTREME (>90th).
## Why this is original
Only TradingView library combining BoS/CHoCH, sessions, and volatility regimes. Existing SMC indicators lack reusable libraries.
Unique features:
- Confirmed pivots only (no repainting)
- CHoCH sequence analysis (pivot pattern detection)
- UTC-based sessions (exchange-agnostic, DST-safe)
- Percentile volatility (asset-adaptive)
- Circular buffer (O(1) operations, memory-efficient)
Designed for composability: sessions → conditional logic, regimes → stop multipliers, BoS/CHoCH → entry/exit signals.
## How to use it
```pine
//version=6
indicator("CyberMarketLib Demo", overlay=true)
import cybermediaboy/CyberMarketLib/2 as ML
// Swing points + BoS/CHoCH detection
var swing_hist = ML.f_swing_history_new(max_n=20)
var fractal = ML.f_detect_pivot(left_len=5, right_len=5)
if not na(fractal)
swing_hist.push(fractal)
var event = ML.f_detect_structure_event(swing_hist, close)
// event: BOS_UP, BOS_DOWN, CHOCH_UP, CHOCH_DOWN, NONE
// Session + volatility regime
session = ML.f_current_session() // ASIA, LONDON, NY_OVERLAP, etc.
vol_regime = ML.f_volatility_regime(14, 100) // LOW, NORMAL, HIGH, EXTREME
// Adaptive stops
atr = ta.atr(14)
stop_mult = vol_regime == ML.VolRegime.EXTREME ? 3.0 : 1.5
plot(close - atr * stop_mult, "Stop", color.red)
```
## Key functions
- `f_detect_pivot()` - Confirmed swing points (no repainting)
- `f_detect_structure_event()` - BoS/CHoCH detection
- `f_current_session()` - UTC-based session classification
- `f_volatility_regime()` - ATR percentile regimes
- `f_htf_for()` - Higher timeframe string generation
- SwingHistory UDT - Circular buffer for pivot storage
## Limitations
- Swing detection: `right_len` bars confirmation delay (lag vs repainting indicators)
- BoS/CHoCH: Assumes trending markets (false signals in choppy ranges)
- Sessions: UTC-only (no exchange-native or DST-aware sessions)
- Volatility: ATR-based only (may lag on sudden spikes)
- SwingHistory: Fixed capacity at initialization
- CHoCH: Requires manual state tracking to avoid duplicate signals
مكتبة باين
كمثال للقيم التي تتبناها TradingView، نشر المؤلف شيفرة باين كمكتبة مفتوحة المصدر بحيث يمكن لمبرمجي باين الآخرين من مجتمعنا استخدامه بحرية. تحياتنا للمؤلف! يمكنك استخدام هذه المكتبة بشكل خاص أو في منشورات أخرى مفتوحة المصدر، ولكن إعادة استخدام هذا الرمز في المنشورات تخضع لقواعد الموقع.
إخلاء المسؤولية
لا يُقصد بالمعلومات والمنشورات أن تكون، أو تشكل، أي نصيحة مالية أو استثمارية أو تجارية أو أنواع أخرى من النصائح أو التوصيات المقدمة أو المعتمدة من TradingView. اقرأ المزيد في شروط الاستخدام.
مكتبة باين
كمثال للقيم التي تتبناها TradingView، نشر المؤلف شيفرة باين كمكتبة مفتوحة المصدر بحيث يمكن لمبرمجي باين الآخرين من مجتمعنا استخدامه بحرية. تحياتنا للمؤلف! يمكنك استخدام هذه المكتبة بشكل خاص أو في منشورات أخرى مفتوحة المصدر، ولكن إعادة استخدام هذا الرمز في المنشورات تخضع لقواعد الموقع.
إخلاء المسؤولية
لا يُقصد بالمعلومات والمنشورات أن تكون، أو تشكل، أي نصيحة مالية أو استثمارية أو تجارية أو أنواع أخرى من النصائح أو التوصيات المقدمة أو المعتمدة من TradingView. اقرأ المزيد في شروط الاستخدام.