lib_vsop87_mercuryLibrary "lib_vsop87_mercury"
Heliocentric and geocentric position calculations for Mercury
using VSOP87 theory. Provides longitude, latitude, radius, speed,
and declination functions.
@author BlueprintResearch (Javonnii)
@license MIT License - Free to use with attribution
@theory VSOP87A (Heliocentric rectangular coordinates)
@accuracy Truncated series (~10-15 terms per series) - arcsecond precision
@time_scale Julian millennia from J2000.0 (use core.get_julian_millennia)
@reference Meeus, Jean. "Astronomical Algorithms" (2nd Ed., 1998)
Bretagnon & Francou. "VSOP87 Solutions" (1988)
@showcase Includes commented showcase code with 250-bar future projection.
Uncomment to display Mercury data with polyline projections.
@open_source This library is part of an open-source alternative to
proprietary astronomical libraries. Study, modify, and
share freely. We believe knowledge of the cosmos belongs
to everyone.
════════════════════════════════════════════════════════════════
© 2025 BlueprintResearch / Javonnii
Licensed under MIT License
════════════════════════════════════════════════════════════════
@version=6
import BlueprintResearch/lib_vsop_core/1 as core
get_helio_lon(t)
Computes Mercury's heliocentric ecliptic longitude using VSOP87 theory.
Parameters:
t (float) : (float) Julian millennia from J2000.0 (use core.get_julian_millennia(time)).
Returns: (float) Heliocentric ecliptic longitude in degrees, normalized to range [0, 360).
get_helio_lat(t)
Computes Mercury's heliocentric ecliptic latitude using VSOP87 theory.
Parameters:
t (float) : (float) Julian millennia from J2000.0 (use core.get_julian_millennia(time)).
Returns: (float) Heliocentric ecliptic latitude in radians, range approximately . Note: Returns radians, not degrees.
get_helio_radius(t)
Computes Mercury's heliocentric radius (distance from Sun) using VSOP87 theory.
Parameters:
t (float) : (float) Julian millennia from J2000.0 (use core.get_julian_millennia(time)).
Returns: (float) Heliocentric radius in astronomical units (AU). Typical range is 0.31-0.47 AU.
get_geo_speed(t)
Computes Mercury's geocentric longitude speed (rate of change over time).
Parameters:
t (float) : (float) Julian millennia from J2000.0 (use core.get_julian_millennia(time)).
Returns: (float) Geocentric longitude speed in degrees per day. Negative values indicate retrograde motion (apparent backward movement).
get_geo_lon(t)
Computes Mercury's geocentric ecliptic longitude (as seen from Earth).
Parameters:
t (float) : (float) Julian millennia from J2000.0 (use core.get_julian_millennia(time)).
Returns: (float) Geocentric ecliptic longitude in degrees, normalized to range [0, 360).
get_geo_ecl_lat(t)
Computes Mercury's geocentric ecliptic latitude (as seen from Earth).
Parameters:
t (float) : (float) Julian millennia from J2000.0 (use core.get_julian_millennia(time)).
Returns: (float) Geocentric ecliptic latitude in degrees, range approximately .
get_geo_decl(t)
Computes Mercury's geocentric equatorial declination (as seen from Earth).
Parameters:
t (float) : (float) Julian millennia from J2000.0 (use core.get_julian_millennia(time)).
Returns: (float) Geocentric equatorial declination in degrees, range where positive is north.
Cari skrip untuk "algo"
lib_vsop87_venusLibrary "lib_vsop87_venus"
Heliocentric and geocentric position calculations for Venus
using VSOP87 theory. Provides longitude, latitude, radius, speed,
and declination functions.
@author BlueprintResearch (Javonnii)
@license MIT License - Free to use with attribution
@theory VSOP87A (Heliocentric rectangular coordinates)
@accuracy Truncated series (~10-15 terms per series) - arcsecond precision
@time_scale Julian millennia from J2000.0 (use core.get_julian_millennia)
@reference Meeus, Jean. "Astronomical Algorithms" (2nd Ed., 1998)
Bretagnon & Francou. "VSOP87 Solutions" (1988)
@showcase Includes commented showcase code with 250-bar future projection.
Uncomment to display Venus data with polyline projections.
@open_source This library is part of an open-source alternative to
proprietary astronomical libraries. Study, modify, and
share freely. We believe knowledge of the cosmos belongs
to everyone.
════════════════════════════════════════════════════════════════
© 2025 BlueprintResearch / Javonnii
Licensed under MIT License
════════════════════════════════════════════════════════════════
@version=6
import BlueprintResearch/lib_vsop_core/1 as core
get_helio_lon(t)
Computes Venus's heliocentric ecliptic longitude using VSOP87 theory.
Parameters:
t (float) : (float) Julian millennia from J2000.0 (use core.get_julian_millennia(time)).
Returns: (float) Heliocentric ecliptic longitude in degrees, normalized to range [0, 360).
get_helio_lat(t)
Computes Venus's heliocentric ecliptic latitude using VSOP87 theory.
Parameters:
t (float) : (float) Julian millennia from J2000.0 (use core.get_julian_millennia(time)).
Returns: (float) Heliocentric ecliptic latitude in radians, range approximately . Note: Returns radians, not degrees.
get_helio_radius(t)
Computes Venus's heliocentric radius (distance from Sun) using VSOP87 theory.
Parameters:
t (float) : (float) Julian millennia from J2000.0 (use core.get_julian_millennia(time)).
Returns: (float) Heliocentric radius in astronomical units (AU). Typical range is 0.72-0.73 AU.
get_geo_speed(t)
Computes Venus's geocentric longitude speed (rate of change over time).
Parameters:
t (float) : (float) Julian millennia from J2000.0 (use core.get_julian_millennia(time)).
Returns: (float) Geocentric longitude speed in degrees per day. Negative values indicate retrograde motion (apparent backward movement).
get_geo_lon(t)
Computes Venus's geocentric ecliptic longitude (as seen from Earth).
Parameters:
t (float) : (float) Julian millennia from J2000.0 (use core.get_julian_millennia(time)).
Returns: (float) Geocentric ecliptic longitude in degrees, normalized to range [0, 360).
get_geo_ecl_lat(t)
Computes Venus's geocentric ecliptic latitude (as seen from Earth).
Parameters:
t (float) : (float) Julian millennia from J2000.0 (use core.get_julian_millennia(time)).
Returns: (float) Geocentric ecliptic latitude in degrees, range approximately .
get_geo_decl(t)
Computes Venus's geocentric equatorial declination (as seen from Earth).
Parameters:
t (float) : (float) Julian millennia from J2000.0 (use core.get_julian_millennia(time)).
Returns: (float) Geocentric equatorial declination in degrees, range where positive is north.
lib_vsop87_uranusLibrary "lib_vsop87_uranus"
Heliocentric and geocentric position calculations for Uranus
using VSOP87 theory. Provides longitude, latitude, radius, speed,
and declination functions.
@author BlueprintResearch (Javonnii)
@license MIT License - Free to use with attribution
@theory VSOP87A (Heliocentric rectangular coordinates)
@accuracy Truncated series (~10-15 terms per series) - arcsecond precision
@time_scale Julian millennia from J2000.0 (use core.get_julian_millennia)
@reference Meeus, Jean. "Astronomical Algorithms" (2nd Ed., 1998)
Bretagnon & Francou. "VSOP87 Solutions" (1988)
@showcase Includes commented showcase code with 250-bar future projection.
Uncomment to display Uranus data with polyline projections.
@open_source This library is part of an open-source alternative to
proprietary astronomical libraries. Study, modify, and
share freely. We believe knowledge of the cosmos belongs
to everyone.
════════════════════════════════════════════════════════════════
© 2025 BlueprintResearch / Javonnii
Licensed under MIT License
════════════════════════════════════════════════════════════════
@version=6
import BlueprintResearch/lib_vsop_core/1 as core
get_helio_lon(t)
Computes Uranus's heliocentric ecliptic longitude using VSOP87 theory.
Parameters:
t (float) : (float) Julian millennia from J2000.0 (use core.get_julian_millennia(time)).
Returns: (float) Heliocentric ecliptic longitude in degrees, normalized to range [0, 360).
get_helio_lat(t)
Computes Uranus's heliocentric ecliptic latitude using VSOP87 theory.
Parameters:
t (float) : (float) Julian millennia from J2000.0 (use core.get_julian_millennia(time)).
Returns: (float) Heliocentric ecliptic latitude in radians, range approximately . Note: Returns radians, not degrees.
get_helio_radius(t)
Computes Uranus's heliocentric radius (distance from Sun) using VSOP87 theory.
Parameters:
t (float) : (float) Julian millennia from J2000.0 (use core.get_julian_millennia(time)).
Returns: (float) Heliocentric radius in astronomical units (AU). Typical range is 18.28-20.09 AU.
get_geo_speed(t)
Computes Uranus's geocentric longitude speed (rate of change over time).
Parameters:
t (float) : (float) Julian millennia from J2000.0 (use core.get_julian_millennia(time)).
Returns: (float) Geocentric longitude speed in degrees per day. Negative values indicate retrograde motion (apparent backward movement).
get_geo_lon(t)
Computes Uranus's geocentric ecliptic longitude (as seen from Earth).
Parameters:
t (float) : (float) Julian millennia from J2000.0 (use core.get_julian_millennia(time)).
Returns: (float) Geocentric ecliptic longitude in degrees, normalized to range [0, 360).
get_geo_ecl_lat(t)
Computes Uranus's geocentric ecliptic latitude (as seen from Earth).
Parameters:
t (float) : (float) Julian millennia from J2000.0 (use core.get_julian_millennia(time)).
Returns: (float) Geocentric ecliptic latitude in degrees, range approximately .
get_geo_decl(t)
Computes Uranus's geocentric equatorial declination (as seen from Earth).
Parameters:
t (float) : (float) Julian millennia from J2000.0 (use core.get_julian_millennia(time)).
Returns: (float) Geocentric equatorial declination in degrees, range where positive is north.
lib_vsop87_neptuneLibrary "lib_vsop87_neptune"
Heliocentric and geocentric position calculations for Neptune
using VSOP87 theory. Provides longitude, latitude, radius, speed,
and declination functions.
@author BlueprintResearch (Javonnii)
@license MIT License - Free to use with attribution
@theory VSOP87A (Heliocentric rectangular coordinates)
@accuracy Truncated series (~10-15 terms per series) - arcsecond precision
@time_scale Julian millennia from J2000.0 (use core.get_julian_millennia)
@reference Meeus, Jean. "Astronomical Algorithms" (2nd Ed., 1998)
Bretagnon & Francou. "VSOP87 Solutions" (1988)
@showcase Includes commented showcase code with 250-bar future projection.
Uncomment to display Neptune data with polyline projections.
@open_source This library is part of an open-source alternative to
proprietary astronomical libraries. Study, modify, and
share freely. We believe knowledge of the cosmos belongs
to everyone.
════════════════════════════════════════════════════════════════
© 2025 BlueprintResearch / Javonnii
Licensed under MIT License
════════════════════════════════════════════════════════════════
@version=6
import BlueprintResearch/lib_vsop_core/1 as core
get_helio_lon(t)
Computes Neptune's heliocentric ecliptic longitude using VSOP87 theory.
Parameters:
t (float) : (float) Julian millennia from J2000.0 (use core.get_julian_millennia(time)).
Returns: (float) Heliocentric ecliptic longitude in degrees, normalized to range [0, 360).
get_helio_lat(t)
Computes Neptune's heliocentric ecliptic latitude using VSOP87 theory.
Parameters:
t (float) : (float) Julian millennia from J2000.0 (use core.get_julian_millennia(time)).
Returns: (float) Heliocentric ecliptic latitude in radians, range approximately . Note: Returns radians, not degrees.
get_helio_radius(t)
Computes Neptune's heliocentric radius (distance from Sun) using VSOP87 theory.
Parameters:
t (float) : (float) Julian millennia from J2000.0 (use core.get_julian_millennia(time)).
Returns: (float) Heliocentric radius in astronomical units (AU). Typical range is 29.81-30.33 AU.
get_geo_speed(t)
Computes Neptune's geocentric longitude speed (rate of change over time).
Parameters:
t (float) : (float) Julian millennia from J2000.0 (use core.get_julian_millennia(time)).
Returns: (float) Geocentric longitude speed in degrees per day. Negative values indicate retrograde motion (apparent backward movement).
get_geo_lon(t)
Computes Neptune's geocentric ecliptic longitude (as seen from Earth).
Parameters:
t (float) : (float) Julian millennia from J2000.0 (use core.get_julian_millennia(time)).
Returns: (float) Geocentric ecliptic longitude in degrees, normalized to range [0, 360).
get_geo_ecl_lat(t)
Computes Neptune's geocentric ecliptic latitude (as seen from Earth).
Parameters:
t (float) : (float) Julian millennia from J2000.0 (use core.get_julian_millennia(time)).
Returns: (float) Geocentric ecliptic latitude in degrees, range approximately .
get_geo_decl(t)
Computes Neptune's geocentric equatorial declination (as seen from Earth).
Parameters:
t (float) : (float) Julian millennia from J2000.0 (use core.get_julian_millennia(time)).
Returns: (float) Geocentric equatorial declination in degrees, range where positive is north.
lib_meeus_plutoLibrary "lib_meeus_pluto"
Heliocentric and geocentric position calculations for Pluto using
Meeus truncated analytical series. Valid ±1 century from J2000.
@author BlueprintResearch (Javonnii)
@license MIT License - Free to use with attribution
@theory Meeus truncated series (not full planetary theory)
@accuracy Arcminute precision within ±1 century of J2000
@time_scale Julian centuries from J2000.0 (use core.get_julian_centuries)
@reference Meeus, Jean. "Astronomical Algorithms" (2nd Ed., 1998), Chapter 37
@showcase Includes commented showcase code with 250-bar future projection.
Uncomment to display Pluto data with polyline projections.
@open_source This library is part of an open-source alternative to
proprietary astronomical libraries. Study, modify, and
share freely. We believe knowledge of the cosmos belongs
to everyone.
════════════════════════════════════════════════════════════════
© 2025 BlueprintResearch / Javonnii
Licensed under MIT License
════════════════════════════════════════════════════════════════
@version=6
import BlueprintResearch/lib_vsop_core/1 as core
get_helio_lon(t)
Computes Pluto's heliocentric ecliptic longitude using Meeus truncated analytical series.
Parameters:
t (float) : (float) Julian centuries from J2000.0 (use core.get_julian_centuries(time)).
Returns: (float) Heliocentric ecliptic longitude in degrees, normalized to range [0, 360). Accurate within ±1 century from J2000.
get_helio_lat(t)
Computes Pluto's heliocentric ecliptic latitude using Meeus truncated analytical series.
Parameters:
t (float) : (float) Julian centuries from J2000.0 (use core.get_julian_centuries(time)).
Returns: (float) Heliocentric ecliptic latitude in degrees, range approximately . Accurate within ±1 century from J2000.
get_helio_radius(t)
Computes Pluto's heliocentric radius (distance from Sun) using Meeus truncated analytical series.
Parameters:
t (float) : (float) Julian centuries from J2000.0 (use core.get_julian_centuries(time)).
Returns: (float) Heliocentric radius in astronomical units (AU). Typical range is 29.6-49.3 AU. Accurate within ±1 century from J2000.
get_geo_lon(t)
Computes Pluto's geocentric ecliptic longitude (as seen from Earth).
Parameters:
t (float) : (float) Julian centuries from J2000.0 (use core.get_julian_centuries(time)).
Returns: (float) Geocentric ecliptic longitude in degrees, normalized to range [0, 360).
get_geo_ecl_lat(t)
Computes Pluto's geocentric ecliptic latitude (as seen from Earth).
Parameters:
t (float) : (float) Julian centuries from J2000.0 (use core.get_julian_centuries(time)).
Returns: (float) Geocentric ecliptic latitude in degrees, range approximately .
get_geo_decl(t)
Computes Pluto's geocentric equatorial declination (as seen from Earth).
Parameters:
t (float) : (float) Julian centuries from J2000.0 (use core.get_julian_centuries(time)).
Returns: (float) Geocentric equatorial declination in degrees, range where positive is north.
get_geo_speed(t)
Computes Pluto's geocentric longitude speed (rate of change over time).
Parameters:
t (float) : (float) Julian centuries from J2000.0 (use core.get_julian_centuries(time)).
Returns: (float) Geocentric longitude speed in degrees per day. Negative values indicate retrograde motion (apparent backward movement).
lib_vsop_coreLibrary "lib_vsop_core"
Foundation library providing core types, evaluators, and utilities
for VSOP87 planetary theory calculations. Required by all planetary
libraries. Includes Earth heliocentric model and Sun geocentric functions.
@author BlueprintResearch (Javonnii)
@license MIT License - Free to use with attribution
@theory VSOP87 (Variations Séculaires des Orbites Planétaires)
@accuracy Truncated series - suitable for financial astrology and education
@time_scale Julian millennia from J2000.0 for VSOP87 planets
Julian centuries from J2000.0 for Moon and Pluto
@reference Meeus, Jean. "Astronomical Algorithms" (2nd Ed., 1998)
Bretagnon & Francou. "VSOP87 Solutions" (1988)
@showcase Includes commented showcase code with 250-bar future projection.
Uncomment to display Sun/Earth data with polyline projections.
@open_source This library is part of an open-source alternative to
proprietary astronomical libraries. Study, modify, and
share freely. We believe knowledge of the cosmos belongs
to everyone.
════════════════════════════════════════════════════════════════
© 2025 BlueprintResearch / Javonnii
Licensed under MIT License
════════════════════════════════════════════════════════════════
@version=6
get_julian_millennia(time_)
Parameters:
time_ (float)
get_julian_centuries(time_)
Parameters:
time_ (float)
eval_vsop87(terms, t)
Parameters:
terms (array)
t (float)
eval_vsop87_derivative(terms, t)
Parameters:
terms (array)
t (float)
mod360(x)
Parameters:
x (float)
custom_atan2(y, x)
Parameters:
y (float)
x (float)
get_earth_helio_radius(t)
Parameters:
t (float)
get_earth_helio_coords(t)
Parameters:
t (float)
get_obliquity(t)
Parameters:
t (float)
get_earth_helio_lon(t)
Parameters:
t (float)
get_sun_geo_lon(t)
Parameters:
t (float)
get_sun_geo_speed(t)
Parameters:
t (float)
get_sun_decl(t)
Parameters:
t (float)
get_bar_gap_ms()
Get bar interval in milliseconds for current timeframe
Returns: (int) Time interval between bars in milliseconds
get_future_time(current_time, bars_ahead)
Calculate future timestamp for projection plotting
Parameters:
current_time (int) : (int) Current bar time in milliseconds (use built-in 'time')
bars_ahead (int) : (int) Number of bars to project into future
Returns: (int) Future timestamp suitable for xloc.bar_time and chart.point.from_time
is_projection_bar()
Check if current bar is suitable for drawing future projections
Returns: (bool) True on last bar when projections should be drawn
vsop_term
Fields:
amp (series float)
phase (series float)
freq (series float)
PA SystemPA System - Price Action Trading System
价格行为交易系统
📊 概述 / Overview
PA System is a comprehensive price action trading indicator that combines Smart Money Concepts (SMC), market structure analysis, and multi-timeframe confirmation to identify high-probability trade setups. Designed for both manual traders and algorithmic trading systems.
PA System 是一个综合性价格行为交易指标，结合了Smart Money概念(SMC)、市场结构分析和多时间框架确认，用于识别高概率交易机会。适用于手动交易者和算法交易系统。
✨ 核心特性 / Key Features
🎯 Four-Phase Signal System / 四阶段信号系统
H1 (First Pullback) - Initial bullish retracement in uptrend
H2 (Confirmed Entry) - Breakout confirmation for long entries
L1 (First Bounce) - Initial bearish bounce in downtrend
L2 (Confirmed Entry) - Breakdown confirmation for short entries
中文说明：
H1（首次回调） - 上升趋势中的初次回撤信号
H2（确认入场） - 突破确认的做多入场点
L1（首次反弹） - 下降趋势中的初次反弹信号
L2（确认入场） - 跌破确认的做空入场点
📐 Market Structure Detection / 市场结构识别
HH (Higher High) - Uptrend confirmation / 上升趋势确认
HL (Higher Low) - Bullish pullback / 多头回调
LH (Lower High) - Bearish bounce / 空头反弹
LL (Lower Low) - Downtrend confirmation / 下降趋势确认
💎 Smart Money Concepts (SMC) / 智能资金概念
BoS (Break of Structure) - Trend continuation signal / 趋势延续信号
CHoCH (Change of Character) - Potential trend reversal / 潜在趋势反转
📈 Dynamic Trendlines / 动态趋势线
Auto-drawn support and resistance trendlines / 自动绘制支撑阻力趋势线
Real-time extension to current bar / 实时延伸至当前K线
Slope-filtered for accuracy / 斜率过滤确保准确性
🎚️ Multi-Timeframe Analysis / 多时间框架分析
Higher timeframe trend filter (default 4H) / 大周期趋势过滤（默认4小时）
Prevents counter-trend trades / 防止逆势交易
Configurable timeframe / 可配置时间周期
📊 Volume Confirmation / 成交量确认
Filters signals based on volume strength / 基于成交量强度过滤信号
20-period volume MA comparison / 与20期成交量均线对比
High-volume bars highlighted / 高成交量K线高亮显示
🎯 Risk Management Tools / 风险管理工具
Automatic SL/TP calculation and display / 自动计算并显示止损止盈
Visual stop loss and take profit lines / 可视化止损止盈线条
Risk percentage and R:R ratio display / 显示风险百分比和盈亏比
Dynamic stop loss sizing (0.3% - 1.5%) / 动态止损范围（0.3% - 1.5%）
📱 Real-Time Alerts / 实时警报
Instant notifications on H2/L2 signals / H2/L2信号即时通知
Webhook support for automation / 支持Webhook自动化
Mobile, email, and popup alerts / 手机、邮件和弹窗警报
📊 Professional Dashboard / 专业仪表盘
Real-time market state (CHANNEL/RANGE/BREAKOUT) / 实时市场状态
Local and MTF trend indicators / 本地及大周期趋势指标
Order flow status (HIGH VOL / LOW VOL) / 订单流状态
Last signal tracker / 最新信号追踪
🔧 参数设置 / Parameter Settings
Structure Settings / 结构设置
Parameter Default Range Description
Swing Length / 摆动长度 5 2-20 Pivot detection sensitivity / 枢轴点检测灵敏度
Trend Confirm Bars / 趋势确认根数 3 2-10 Consecutive bars for breakout / 突破所需连续K线数
Channel ATR Mult / 通道ATR倍数 2.0 1.0-5.0 Range detection threshold / 区间检测阈值
Signal Settings / 信号设置
Parameter Default Description
Enable H2 Longs / 启用H2做多 ✅ Toggle long signals / 开关做多信号
Enable L2 Shorts / 启用L2做空 ✅ Toggle short signals / 开关做空信号
Micro Range Length / 微平台长度 3 Breakout detection bars / 突破检测K线数
Close Strength / 收盘强度 0.6 Minimum close position in bar / K线内最小收盘位置
Filter Settings / 过滤设置
Parameter Default Description
Use MTF Filter / 大周期过滤 ✅ Enable higher timeframe filter / 启用大周期过滤
MTF Timeframe / 大周期时间框架 240 (4H) Higher timeframe period / 大周期时间
Use Volume Filter / 成交量过滤 ✅ Require high volume confirmation / 需要高成交量确认
Volume MA Length / 成交量均线周期 20 Volume comparison period / 成交量对比周期
Fast EMA / 快速EMA 20 Short-term trend / 短期趋势
Slow EMA / 慢速EMA 50 Long-term trend / 长期趋势
Risk Management / 风险管理
Parameter Default Description
Risk % / 风险百分比 1.0% Risk per trade / 每笔交易风险
R:R Ratio / 盈亏比 2.0 Reward to risk ratio / 盈亏比率
Max SL ATR / 最大止损ATR 3.0 Maximum stop loss in ATR / 最大止损ATR倍数
Min SL % / 最小止损百分比 0.3% Minimum stop loss percentage / 最小止损百分比
Max SL % / 最大止损百分比 1.5% Maximum stop loss percentage / 最大止损百分比
📖 使用方法 / How to Use
1. 基础设置 / Basic Setup
For Day Trading (5-15 min charts) / 日内交易（5-15分钟图）
text
Swing Length: 5
MTF Timeframe: 240 (4H)
Risk %: 1.0%
R:R: 2.0
For Swing Trading (1-4H charts) / 波段交易（1-4小时图）
text
Swing Length: 8
MTF Timeframe: D (Daily)
Risk %: 0.5%
R:R: 3.0
For Scalping (1-5 min charts) / 剥头皮（1-5分钟图）
text
Swing Length: 3
MTF Timeframe: 60 (1H)
Risk %: 0.5%
R:R: 1.5
Use Volume Filter: ✅
2. 信号识别 / Signal Identification
Long Entry / 做多入场
✅ Dashboard shows "Local Trend: BULL" / 仪表盘显示"本地趋势：多头"
✅ MTF Trend shows "BULLISH" / 大周期趋势显示"看涨"
✅ Green circle (H1) appears below bar / 绿色圆点(H1)出现在K线下方
⏳ Wait for H2 signal (green triangle ▲) / 等待H2信号（绿色三角▲）
📊 Check volume bar is cyan (HIGH VOL) / 检查成交量柱为青色（高成交量）
🎯 Enter at close of H2 bar / 在H2 K线收盘价入场
🛡️ Set SL at red dashed line / 止损设在红色虚线位置
🎁 Set TP at green dashed line / 止盈设在绿色虚线位置
Short Entry / 做空入场
✅ Dashboard shows "Local Trend: BEAR" / 仪表盘显示"本地趋势：空头"
✅ MTF Trend shows "BEARISH" / 大周期趋势显示"看跌"
✅ Red circle (L1) appears above bar / 红色圆点(L1)出现在K线上方
⏳ Wait for L2 signal (red triangle ▼) / 等待L2信号（红色倒三角▼）
📊 Check volume bar is cyan (HIGH VOL) / 检查成交量柱为青色（高成交量）
🎯 Enter at close of L2 bar / 在L2 K线收盘价入场
🛡️ Set SL at red dashed line / 止损设在红色虚线位置
🎁 Set TP at green dashed line / 止盈设在绿色虚线位置
3. 警报设置 / Alert Setup
Step-by-Step / 分步操作
Click the "⏰" alert icon on chart / 点击图表上的"⏰"警报图标
Select "PA System - Indicator Version" / 选择"PA System (V1.1) - Indicator Version"
Condition: "Any alert() function call" / 条件：选择"Any alert() function call"
Choose notification method: / 选择通知方式：
📱 Mobile Push / 手机推送
📧 Email / 邮件
🔗 Webhook URL (for automation) / Webhook网址（用于自动化）
Set frequency: "Once Per Bar Close" / 频率：选择"Once Per Bar Close"
Click "Create" / 点击"创建"
Webhook Example for IBKR API / IBKR API的Webhook示例
json
{
"signal": "{{strategy.order.action}}",
"ticker": "{{ticker}}",
"entry": {{close}},
"stop_loss": {{plot_0}},
"take_profit": {{plot_1}},
"timestamp": "{{timenow}}"
}
4. 交易管理 / Trade Management
Position Sizing / 仓位计算
text
Account: $10,000
Risk per Trade: 1% = $100
Entry Price: $690.45
Stop Loss: $687.38
Risk per Share: $690.45 - $687.38 = $3.07
Position Size: $100 / $3.07 = 32 shares
Partial Profit Taking / 部分止盈
Close 50% position at 1:1 R:R / 在1:1盈亏比时平仓50%
Move SL to breakeven / 移动止损至保本位
Let remaining 50% run to 2R target / 让剩余50%跑向2R目标
🎨 视觉元素说明 / Visual Elements Guide
Chart Markers / 图表标记
Symbol Color Meaning
⚫ Small Circle / 小圆点 🟢 Green / 绿色 H1 - First bullish pullback / 首次多头回调
▲ Triangle / 三角形 🟢 Green / 绿色 H2 - Confirmed long entry / 确认做多入场
⚫ Small Circle / 小圆点 🔴 Red / 红色 L1 - First bearish bounce / 首次空头反弹
▼ Inverted Triangle / 倒三角 🔴 Red / 红色 L2 - Confirmed short entry / 确认做空入场
Structure Labels / 结构标签
Label Position Meaning
HH Above high / 高点上方 Higher High - Bullish / 更高的高点-看涨
HL Below low / 低点下方 Higher Low - Bullish / 更高的低点-看涨
LH Above high / 高点上方 Lower High - Bearish / 更低的高点-看跌
LL Below low / 低点下方 Lower Low - Bearish / 更低的低点-看跌
BoS/CHoCH Lines / 破位线条
Type Color Width Meaning
BoS 🔵 Teal / 青色 2px Break of Structure - Trend continues / 结构突破-趋势延续
CHoCH 🔴 Red / 红色 2px Change of Character - Trend reversal / 性质改变-趋势反转
Trendlines / 趋势线
Type Color Style Meaning
Bullish / 看涨 🔵 Teal / 青色 Solid / 实线 Uptrend support / 上升趋势支撑
Bearish / 看跌 🔴 Red / 红色 Solid / 实线 Downtrend resistance / 下降趋势阻力
Risk Lines / 风险线条
Type Color Style Meaning
Stop Loss / 止损 🔴 Red / 红色 Dashed / 虚线 Suggested stop loss level / 建议止损位
Take Profit / 止盈 🟢 Green / 绿色 Dashed / 虚线 Suggested take profit level / 建议止盈位
Dashboard Colors / 仪表盘颜色
Status Color Meaning
BULL / 多头 🟢 Green / 绿色 Bullish trend / 看涨趋势
BEAR / 空头 🔴 Red / 红色 Bearish trend / 看跌趋势
NEUTRAL / 中性 ⚪ Gray / 灰色 No clear trend / 无明确趋势
BREAKOUT / 突破 🟡 Lime / 黄绿 Strong momentum / 强劲动能
HIGH VOL / 高成交量 🔵 Cyan / 青色 High volume confirmation / 高成交量确认
💡 交易策略建议 / Trading Strategy Tips
✅ High Probability Setups / 高概率设置
Trend Alignment / 趋势一致
Local Trend = BULL + MTF Trend = BULLISH / 本地多头 + 大周期看涨
Or: Local Trend = BEAR + MTF Trend = BEARISH / 或：本地空头 + 大周期看跌
Volume Confirmation / 成交量确认
H2/L2 signal appears with cyan volume bar / H2/L2信号伴随青色成交量柱
Volume > 20-period MA / 成交量 > 20期均线
Trendline Support / 趋势线支撑
H2 appears near bullish trendline / H2出现在看涨趋势线附近
L2 appears near bearish trendline / L2出现在看跌趋势线附近
BoS Confirmation / BoS确认
Recent BoS in same direction / 最近同方向的BoS
No CHoCH against the trade / 无逆向的CHoCH
❌ Avoid These Setups / 避免这些情况
Conflicting Trends / 趋势冲突
Local BULL but MTF BEARISH / 本地多头但大周期看跌
Market State = RANGE / 市场状态 = 区间
Low Volume / 低成交量
Order Flow shows "LOW VOL" / 订单流显示"低成交量"
Volume bar is red (below MA) / 成交量柱为红色（低于均线）
Against Trendline / 逆趋势线
Shorting at bullish trendline support / 在看涨趋势线支撑处做空
Buying at bearish trendline resistance / 在看跌趋势线阻力处做多
Recent CHoCH / 近期CHoCH
CHoCH appeared within 10 bars / 10根K线内出现CHoCH
Potential trend reversal zone / 潜在趋势反转区域
🔄 优化建议 / Optimization Tips
For Different Markets / 针对不同市场
Stocks / 股票
text
Swing Length: 5-8
MTF: 240 (4H) or D (Daily)
Risk %: 0.5-1.0%
Best on: SPY, QQQ, AAPL, TSLA
Forex / 外汇
text
Swing Length: 5
MTF: 240 (4H)
Risk %: 1.0-2.0%
Best on: EUR/USD, GBP/USD, USD/JPY
Use Volume Filter: OFF (Forex volume is unreliable)
Crypto / 加密货币
text
Swing Length: 3-5
MTF: 240 (4H)
Risk %: 0.5-1.0% (high volatility)
Max SL %: 2.0-3.0%
Best on: BTC, ETH, SOL
Futures / 期货
text
Swing Length: 5
MTF: 240 (4H)
Risk %: 1.0-1.5%
Best on: ES, NQ, RTY, CL
🤖 自动化集成 / Automation Integration
Python + IBKR API Example / Python + IBKR API示例
python
import requests
from ib_insync import *
def handle_tradingview_alert(alert_data):
"""
Receives webhook from TradingView alert
接收来自TradingView警报的webhook
"""
signal = alert_data # "H2 LONG" or "L2 SHORT"
ticker = alert_data # "SPY"
entry = alert_data # 690.45
stop_loss = alert_data # 687.38
take_profit = alert_data # 696.59
# Connect to IBKR
ib = IB()
ib.connect('127.0.0.1', 7497, clientId=1)
# Create contract
contract = Stock(ticker, 'SMART', 'USD')
# Calculate position size (1% risk)
account_value = ib.accountValues() .value
risk_amount = float(account_value) * 0.01
risk_per_share = abs(entry - stop_loss)
quantity = int(risk_amount / risk_per_share)
# Place order
if "LONG" in signal:
order = MarketOrder('BUY', quantity)
else:
order = MarketOrder('SELL', quantity)
trade = ib.placeOrder(contract, order)
# Set stop loss and take profit
ib.placeOrder(contract, StopOrder('SELL', quantity, stop_loss))
ib.placeOrder(contract, LimitOrder('SELL', quantity, take_profit))
ib.disconnect()
TradersPost Integration / TradersPost集成
Create TradersPost account / 创建TradersPost账户
Connect IBKR broker / 连接IBKR券商
Get Webhook URL / 获取Webhook网址
Add to TradingView alert / 添加到TradingView警报
Test with paper trading / 用模拟账户测试
📊 性能指标 / Performance Metrics
Expected Performance (Backtested) / 预期表现（回测）
Metric Value Notes
Win Rate / 胜率 60-75% With all filters enabled / 启用所有过滤器
Avg R:R / 平均盈亏比 1.8-2.2 Using 2R target / 使用2R目标
Max Drawdown / 最大回撤 8-12% 1% risk per trade / 每笔1%风险
Profit Factor / 盈利因子 1.8-2.5 Trend-following bias / 趋势跟随偏向
Best Markets / 最佳市场 Trending Avoid ranging markets / 避免区间市场
⚠️ Disclaimer: Past performance does not guarantee future results. Always test in paper trading first.
⚠️ 免责声明：历史表现不保证未来结果。请先在模拟账户测试。
🛠️ 故障排除 / Troubleshooting
Problem: No signals appearing / 问题：没有信号出现
Solution / 解决方案:
Disable MTF Filter temporarily / 暂时关闭大周期过滤
Disable Volume Filter / 关闭成交量过滤
Reduce Swing Length to 3 / 将摆动长度降至3
Check if market is ranging (no clear trend) / 检查市场是否处于区间（无明确趋势）
Problem: Too many signals / 问题：信号太多
Solution / 解决方案:
Enable MTF Filter / 启用大周期过滤
Enable Volume Filter / 启用成交量过滤
Increase Swing Length to 8 / 将摆动长度增至8
Enable Break Filter / 启用破位过滤
Problem: Alerts not working / 问题：警报不工作
Solution / 解决方案:
Check "Enable Alerts" is ON / 检查"启用警报"已开启
Verify alert condition is "Any alert() function call" / 确认警报条件为"Any alert() function call"
Check notification settings in TradingView / 检查TradingView通知设置
Test alert with "Test" button / 用"测试"按钮测试警报
Problem: SL/TP lines not showing / 问题：止损止盈线不显示
Solution / 解决方案:
Enable "Show SL/TP Labels" in settings / 在设置中启用"显示止损止盈标签"
Check if signal is recent (lines expire after 10 bars) / 检查信号是否近期（线条在10根K线后消失）
Zoom in to see lines more clearly / 放大图表以更清楚地看到线条
📚 常见问题 FAQ
Q1: Can I use this on any timeframe? / 可以在任何时间框架使用吗？
A: Yes, but works best on 5min-4H charts. Recommended: 15min (day trading), 1H (swing trading).
可以，但在5分钟-4小时图表效果最佳。推荐：15分钟（日内交易），1小时（波段交易）。
Q2: Do I need to enable all filters? / 需要启用所有过滤器吗？
A: No. Start with all enabled, then disable based on your risk tolerance. MTF filter is highly recommended.
不需要。从全部启用开始，然后根据风险承受能力禁用。强烈推荐MTF过滤器。
Q3: Can I automate this with IBKR? / 可以与IBKR自动化吗？
A: Yes! Use TradingView alerts + Webhook + Python script + IBKR API. See automation example above.
可以！使用TradingView警报 + Webhook + Python脚本 + IBKR API。参见上方自动化示例。
Q4: What's the difference between Strategy and Indicator version? / 策略版和指标版有什么区别？
A: Strategy = backtesting only. Indicator = real-time alerts + automation. Use both: backtest with strategy, trade with indicator.
策略版=仅回测。指标版=实时警报+自动化。两者结合使用：用策略版回测，用指标版交易。
Q5: Why does H2 appear but no trade? / 为什么出现H2但没有交易？
A: This is an indicator, not a strategy. You need to manually place orders or use automation via alerts.
这是指标，不是策略。你需要手动下单或通过警报使用自动化。
⚖️ 免责声明 / Disclaimer
IMPORTANT / 重要提示:
This indicator is for educational purposes only. Trading involves substantial risk of loss. Past performance does not guarantee future results. Always:
本指标仅供教育目的。交易涉及重大亏损风险。历史表现不保证未来结果。请务必：
✅ Test in paper trading first / 先在模拟账户测试
✅ Use proper risk management (1-2% max per trade) / 使用适当风险管理（每笔最多1-2%）
✅ Never risk more than you can afford to lose / 永远不要冒超出承受能力的风险
✅ Understand the strategy before using / 使用前理解策略原理
Not financial advice. Trade at your own risk.
非投资建议。交易风险自负。
Hero Zero+ Gamma (False Breakout Filter)Hero Zero – EMA + VWAP + Gamma (Strong Candle)
Purpose:
This script is designed to capture high-momentum intraday moves (Gamma Blasts / Hero Zero trades) by combining:
Trend strength (EMA stack)
Institutional reference (VWAP)
Momentum candle quality (Full Body / Marubozu)
Participation confirmation (Volume burst – OI proxy)
It avoids weak breakouts and focuses only on decisive price expansion candles.
1️⃣ EMA STRUCTURE – TREND FILTER
emaFast = ta.ema(close, 9)
emaMid = ta.ema(close, 20)
emaSlow = ta.ema(close, 50)
📈 Why EMAs?
EMAs react faster to price → ideal for intraday momentum
The script uses EMA stacking, not just crossovers
Bullish EMA Stack
emaFast > emaMid > emaSlow
✔ Indicates strong uptrend
✔ Buyers are in control across short, medium & intraday timeframes
Bearish EMA Stack
emaFast < emaMid < emaSlow
✔ Indicates strong downtrend
✔ Sellers dominate
🔒 No EMA stack = no trade
This removes sideways and choppy markets.
2️⃣ VWAP – INSTITUTIONAL BIAS
vwapVal = ta.vwap(hlc3)
Why VWAP?
Used by institutions, algos, prop desks
Acts as a fair value line
Conditions
Bullish trade: close > VWAP
Bearish trade: close < VWAP
📌 This ensures:
You trade with smart money
You avoid mean-reversion traps
3️⃣ VOLUME BURST – GAMMA / OI PROXY
avgVol = ta.sma(volume, 20)
volBurst = volume > avgVol * 1.5
What this represents
Sudden increase in participation
Acts as a proxy for OI build-up / Gamma activity
✔ No volume = no follow-through
✔ Volume burst confirms real interest, not fake moves
4️⃣ STRONG CANDLE LOGIC – CORE EDGE 🔥
Candle Anatomy
bodySize = abs(close - open)
upperWick = high - max(close, open)
lowerWick = min(close, open) - low
A) FULL BODY CANDLE
Meaning:
Price moves strongly in one direction with minimal rejection.
Bullish Full Body
bodySize > upperWick
✔ Buyers pushed price up and held it
Bearish Full Body
bodySize > lowerWick
✔ Sellers dominated without pullback
B) MARUBOZU CANDLE (Institutional Candle)
upperWick <= mintick*2
lowerWick <= mintick*2
✔ Almost no wicks
✔ Pure aggression
✔ Typically seen during:
Option Gamma expansion
Index hero moves
Breakout candles
C) STRONG CANDLE (Final Filter)
Strong Candle = Full Body OR Marubozu
📌 This is powerful because:
Full Body → strong but normal momentum
Marubozu → explosive institutional move
Weak candles are fully filtered out.
5️⃣ HERO ZERO (GAMMA BLAST) CONDITIONS
Bullish Gamma Blast
EMA Stack + Price above VWAP +
Strong Bull Candle + Volume Burst
Bearish Gamma Blast
EMA Stack + Price below VWAP +
Strong Bear Candle + Volume Burst
💥 When all align → probability spike
💥 Designed for fast 1–3 candle expansion
6️⃣ SIGNAL VISUALS
Green “GAMMA BUY” → below candle
Red “GAMMA SELL” → above candle
EMAs + VWAP plotted for context
Signals are rare but high-quality.
7️⃣ ALERT SYSTEM
alertcondition(bullGamma)
alertcondition(bearGamma)
✔ Use for:
Bank Nifty / Nifty
Option buying
Scalping during power hours
8️⃣ BEST USAGE (IMPORTANT)
✅ Recommended Timeframes
3-min → Best balance
5-min → Safer
1-min → Aggressive scalping only
✅ Best Time Window (IST)
9:20 – 11:00 AM
2:30 – 3:15 PM (Hero Zero zone)
9️⃣ WHAT THIS SCRIPT AVOIDS ❌
Sideways chop
Low volume traps
Wicky fake breakouts
EMA crossover noise
🧠 TRADER MINDSET
This is not a signal-spamming indicator.
It is a confirmation engine for:
Index options
Momentum scalps
Gamma expansion trades
BE-Synergistic RSI Fusion Strategy█ Overview of the Script:
The Synergistic RSI Fusion Strategy is a sophisticated technical analysis tool designed to detect market turning points (reversals) and high-momentum breakouts. Unlike standard indicators that simply tell you to "Buy" or "Sell" based on a crossed line or overbought/oversold levels, this script builds a structural trade setup using zones. It waits for price action to confirm the signal before acting.
█ Why "Synergistic RSI Fusion"?:
The core engine of the indicator makes it all:
Fusion : Standard RSI only looks at the closing price relative to the previous closing price. This script calculates a comprehensive RSI that incorporates the candle's Highs and Lows.
Why is this more powerful? Imagine a "Hammer" candle where price drops significantly during the session but recovers to close near the open. A standard RSI sees almost no change because the Close is near the Open. However, Fusion RSI captures the full volatility of that dip and recovery, recognizing the massive "effort" and hidden battle between buyers and sellers that standard RSI completely misses.
Synergy : It combines this advanced momentum reading with ATR (Average True Range) to define volatility-based entry and exit zones. It blends momentum (RSI) with market structure (Price Action Zones).
█ How it Stands Unique:
The Core engine: Capturing the true efforts of the movement in price.
Multi-Peak Divergence: Instead of simple A-to-B divergence, this script uses a state machine to track local peaks by filtering out weak signals and waits for a significant disagreement between price and momentum.
The Zone System: It doesn't plot signals blindly. When divergence is found, it draws two "waiting rooms" (Green and Red zones). The trade is only taken if the candle closes inside one of these zones.
█ Divergence Trades: The Two-Way Setup:
A unique feature of this script is that when a Divergence signal appears, it generates two potential entry zones: a Bullish zone and a Bearish zone.
The Rational Behind the Two-Way Approach:
New traders often assume a Divergence means "Reversal." However, experienced traders know that Divergence simply means "Tension is building."
Scenario A (The Reversal): The RSI is screaming that momentum is dying, but price is pushing higher. If price respects the divergence, it will drop into the reversal zone. This is the standard divergence trade.
Scenario B (The Failure/Trap): sometimes, momentum is so strong that it blows through the divergence. If price ignores the RSI warning and breaks into the continuation zone, it signals that the trend is incredibly powerful.
Why Trade Both Ways?
By placing zones on both sides, the script essentially says: " I know a big move is coming because of the tension (Divergence), but I will let the market prove direction first. " This prevents you from " catching a falling knife " by trying to pick the exact top or bottom.
The Counter-Trading Logic (The Trap):
The script includes advanced logic for failed trades. If you enter a trade and the Stop Loss is hit immediately (a "fake-out"), the script adjusts the opposing zone by considering the liquidity of that particular candle.
Why? If the market traps Long traders and hits their stops, that selling pressure often fuels a massive move downwards. This logic allows the script to flip bias instantly and join the real move.
█ Continuation Trends: Why Price Runs After TP:
You may notice that often, after the Take Profit (TP) is hit, the price continues to run in that direction for a long time.
The "Breakout" Effect:
The Take Profit levels in this script are calculated using ATR (Average True Range). This is a conservative target based on recent average volatility.
Structural Breaks: The entry zones are usually positioned at key structural pivots. When price has enough energy to enter the zone and hit 100% of the ATR target, it effectively confirms a Break of Structure.
Momentum Release: The Divergence phase acts like a coiled spring. When that spring finally snaps (the trade entry), the release of energy is often far greater than just one ATR unit.
Psychology: When the TP is hit, it confirms the analysis was correct. This draws in other traders and algorithms who missed the initial entry, adding fuel to the fire and extending the trend.
█ Major Support & Resistance Zone:
The untested zones are typically the safe haven to place your SLs, which definitely act as Support & Resistance once the price approaches these zones.
enigmaMarkets move, but price remembers.
Long before indicators flash signals or momentum shifts, price reacts to levels that were already there — quiet, patient, and unmoving.
This tool reveals those levels.
Fixed price intervals — the kind institutions respect, algorithms acknowledge, and charts quietly obey — are drawn automatically above and below current price. No predictions. No signals. Just structure.
The levels don’t chase price.
They wait for it.
On their own, they are simple.
Paired with time, context, and comparison, they become something else entirely.
When price reaches a level in alignment with a larger cycle, reactions tend to be cleaner and more decisive.
When related markets arrive at similar prices but disagree in direction, the divergence often tells a deeper story.
And when those moments occur within broader macro conditions, the response is rarely random.
Use these levels to observe reactions, pauses, rejections, and expansions.
Use them to frame risk across sessions, instruments, and regimes.
Use them to see how short-term movement fits inside a much larger narrative.
Nothing here tells you when to trade.
It only reveals where price matters — and when the market is paying attention.
If you know, you know.
Smart Gap Concepts [MarkitTick]💡 This indicator automates the identification and classification of price gaps, commonly known as Fair Value Gaps (FVG) or Imbalances, by integrating market structure and volume analysis. Unlike standard gap detectors that simply highlight empty space on a chart, this script applies algorithmic filters to categorize gaps into three distinct phases of market movement: Breakaway, Runaway, and Exhaustion. This helps traders understand the potential context of a move rather than just seeing a support or resistance zone.
● Originality and Utility
The primary innovation of this tool is its dynamic classification system. It moves beyond visual detection by checking the "why" behind the gap. By referencing Swing Highs and Swing Lows (Market Structure) alongside Volume efficiency, it determines if a gap represents a breakout, a trend continuation, or a climatic end to a move. Additionally, the script features an automated mitigation tracking system that removes gaps from the chart once price has re-tested the midpoint, ensuring the visual workspace remains clean and relevant to current price action.
● Methodology
The script operates on a multi-stage logic engine:
• Gap Detection
It first identifies the core imbalance where the Low of the current bar does not overlap with the High of the bar two periods prior (for bullish gaps), ensuring the intervening candle represents a strong displacement.
• Structural Analysis (Breakaway Gaps)
The script monitors Pivot Highs and Lows. If a gap occurs simultaneously with a close beyond a key structural Pivot, it is classified as a "Breakaway Gap." This signals the potential start of a new trend.
• Volume and Time Analysis (Exhaustion Gaps)
To identify potential reversals, the script looks for "Trend Maturity." If a gap forms after a long duration since the last pivot and is accompanied by a volume spike (defined by the Volume Spike Multiplier), it is labeled as an "Exhaustion Gap."
• Continuation (Runaway Gaps)
If a gap is valid but meets neither the Breakaway nor Exhaustion criteria, it is considered a "Runaway Gap," typically found in the middle of an established trend.
• Dynamic Cleanup
The script tracks the midpoint of every active gap. If price creates a lower low (for bullish gaps) or higher high (for bearish gaps) beyond this midpoint, the gap is considered mitigated and is removed from the screen.
📖 How to Use
Traders can utilize the color-coded classifications to gauge market intent:
Breakaway (Default Blue): Watch these zones for potential trend initiations. These are often high-probability areas for a retest entry after a structure break.
Runaway (Default Orange): These indicate strong momentum. They can be used to trail stop-losses or add to winning positions, as price should ideally not close below these gaps in a healthy trend.
Exhaustion (Default Red): Be cautious when these appear. They suggest the current move is overextended and a reversal or complex pullback may be imminent.
• Exhaustion Gap : A Practical Case Study
• Breakaway Gap: A Practical Case Study
• Runaway Gap : A Practical Case Study
⚙️ Inputs and Settings
Min Gap Size (Points): Filters out insignificant gaps smaller than this threshold.
Structure Lookback: Defines the sensitivity of the Pivot detection (Swing High/Low).
Volume Avg Length & Multiplier: Determines what qualifies as a "Volume Spike" for exhaustion logic.
Trend Maturity: The minimum number of bars required to consider a trend "old" enough for an exhaustion signal.
Visual Settings: Custom colors for each gap type and box extension length.
● Disclaimer
All provided scripts and indicators are strictly for educational exploration and must not be interpreted as financial advice or a recommendation to execute trades. I expressly disclaim all liability for any financial losses or damages that may result, directly or indirectly, from the reliance on or application of these tools. Market participation carries inherent risk where past performance never guarantees future returns, leaving all investment decisions and due diligence solely at your own discretion.
Bens Platypus Dual VWAP_Rolling 7D vs Weekly AnchoredBen’s Platypus Dual VWAP: Rolling 7D vs Weekly Anchored (optional σ bands)
Weekly-anchored VWAP resets on Monday (exchange time). That makes sense for assets tied to a traditional weekly “market open,” but BTC trades 24/7 and often doesn’t respect Monday as a real regime boundary—so the Monday reset can create a mechanical jump that looks like signal but is just arithmetic. If you drive entries/exits off that reset, some algos will get spooked into early entries, fake “stretch” readings, or sudden mean shifts that aren’t actually market behaviour.
This indicator fixes that by plotting:
• Rolling 7D VWAP (thick aqua): a continuous trailing VWAP that does not reset on Mondays, giving you a stable mean for reversion logic.
• Weekly Anchored VWAP (thin purple): kept for context, so you can see the reset effect rather than accidentally trade it.
Result: you can visually compare the two means and quantify when “weekly structure” is useful versus when it’s just a calendar artifact on a 24/7 market.
Rango Pre-Apertura (8am-9am)Overview
This indicator is specifically designed for the index trading community, with a focus on US30 (Dow Jones). It centers on the concepts of "Capital Injection" and "Opening Traps," automatically identifying the most critical liquidity levels prior to the New York Open (09:30 AM EST).
Indicator Logic
The script operates on the premise that the range formed between 08:00 AM and 09:00 AM EST acts as a key accumulation or manipulation zone before the official session. By marking these levels, traders can visualize where institutional algorithms are likely to seek liquidity before the day’s primary expansive move begins.
Key Features
08:00 - 09:00 AM Range: Automatically calculates and projects the exact High and Low of this pre-market window.
Previous Day Levels (PDH/PDL): Identifies the Previous Day High and Low as primary zones for External Liquidity (BSL/SSL).
Visual Clarity: Lines are projected only until 01:00 PM EST to keep the chart clean for post-session analysis.
Professional Styling: Uses non-continuous plots to avoid visual noise and diagonal line "bleeding" between trading days.
How to Trade with this Script
Mapping: Identify whether the price opens above or below the 8:00 AM range.
The Trap: Look for liquidity sweeps (Stop Runs) of the marked lines exactly at 09:30 AM.
Confirmation: Combine this indicator with price action to detect "Force Invalidations" (Engulfing patterns) at H1 or H4 Points of Interest (POI).
Universal Moving Average🙏🏻 UMA (Universal Moving Average) represents the most natural and prolly ‘the’ final general universal entity for calculating rolling typical value for any type of time-series. Simply via different weighting schemes applied together, it encodes:
Location of each datapoint in corresponding fields (price, time, volume)
Informational relevance of each datapoint via using windowing functions that are fundamental in nature and go beyond DSP inventions & approximations
Innovation in state space (in our case = volatility)
The real beauty of this development: being simply a weighting scheme that can be applied to anything: be it weighted median , weighted quantile regression, or weighted KDE , or a simple weighted mean (like in this script). As long as a method accepts weights, you can harness the power of this entity. It means that final algorithmic complexity will match your initial tool.
As a moving ‘average’ it beats ALMA, KAMA, MAMA, VIDYA and all others because it is a simple and general entity, and all it does is encoding ‘all’ available information. I think that post might anger a lot of people, because lotta things will be realized as legacy and many paywalls gonna be ignored, specially for the followers of DSP cult, the ones who yet don’t understand that aggregated tick data is not a signal omg, it’s a completely different type of time series where your methods simply don’t fit even closely. I am also sorry to inform y’all, that spectral analysis is much closer to state-space methods in spirit than to DSP. But in fact DSP is cool and I love it, well for actual signals xD
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Weights explained & how to use them: as I already said, the whole thing is based on combining different set of weights, and you can turn them on/off in script settings. Btw I've set em up defaults so you can use the thing on price data out of the box right away.
Price, Time, Volume weights: encode location of every datapoint in Price & TIme & Volume field
Howtouse: u have to disable one weight that corresponds to the field you apply UMA to. E.g if you apply UMA to prices, you turn off price weighting And turn on time and volume weighting. Or if you apply UMA to volume delta, you turn off volume weighting And turn on price and time weighting.
Higher prices are more important, this asymmetry is confirmed and even proved by the fact that prices can’t be negative (don’t even mention that incorrect rollover on CL contract in 2k20...).
Signal weights: encode actuality/importance/relevance of datapoints.
Howtouse: in DSP terms, it provides smoothing, but also compensates for the lag it introduces. This smoothness is useful if you use slope reversals for signal generation aka watching peaks and valleys in a moving average shape. It's also better to perturb smoothed outputs with this , this way you inject high freq content back, But in controlled way!
Signal = information.
The fundamental universal entity behind so-called “smoothing” in DSP has nothing to do with signals and goes eons beyond DSP. This is simply about measuring the relevance of data in time.
First, new datapoints need some time to be “embedded” into the timeline, you can think of it as time proof, kinda stuff needs time to be proved, accepted; while earliest datapoints lose relevance in time.
Second, along with the first notion, at the same time there’s the counter notion that simply weights new data more, acting as a counterweight from the down-weighting of the latest datapoints introduced by the first notion.
The first part can be represented as PDF of beta(2, 2) window (a set of weights in our case). It’s actually well known as the Welch window, that lives in between so called statistical and DSP worlds, emerges in multiple contexts. Mainstream DSP users tho mostly don’t use this one, they use primitive legacy windowing function, you can find all kinds on this wiki page.
Now the second part, where DSP adepts usually stop, is to introduce the second compensating windowing function. Instead they try to reduce window size, or introduce other kinds of volatility weights, do some tricks, but it ain’t provides obviously. The natural step here is to simply use the integral of the initial window; if the initial window is beta(2, 2) then what we simply need is CDF of beta(2, 2), in fact the vertically inverted shape of it aka survival function . That’s it bros. Simply as that.
When both of these are applied you have smth magical, your output becomes smooth and yet not lagging. No arbitrary windowing functions, tricks with data modification etc
Why beta(2, 2)? It naturally arises in many contexts, it’s based on one of the most fundamental functions in the universe: x^2. It has finite support. I can talk more bout it on request, but I am absolutely sure this is it.
^^ impulse response of the resulting weighs together (green) compared with uniform weights aka boxcar (red). Made with this script .
Weighing by state: encodes state-space innovation of each datapoint, basically magnitude of changes, strength of these changes, aka volatility.
Howtouse: this makes your moving average volatility aware in proper math ways. The influence of datapoints will be stronger when changes are stronger. This is weighting by innovations, or weighting by volatility by using squared returns.
Why squared returns? They encode state‑space innovations properly because the innovation of any continuous‑time semimartingale is about its quadratic variation, and quadratic variation is built from squared increments, not absolute increments.
Adaptive length is not the right way to introduce adaptivity by volatility xD. When you weight datapoints by squared returns you’re already dynamically varying ‘effective’ data size, you don’t need anything else.
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It’s all good, progress happens, that’s how the Universe works, that's how Universal Moving Average works. Time to evolve. I might update other scripts with this complete weighting scheme, either by my own desire or your request.
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∞
cd_VW_Cx IMPROVED - Quant VWAP System: Regime, Magnets & Z-ScoQuant VWAP System: Regime, Magnets & Z-Score Matrix
This indicator is a comprehensive Quantitative Trading System designed to move beyond simple support and resistance. Instead of static lines, it uses Statistical Probability (Z-Score) and Standard Deviation to define the current market regime, identify institutional value zones, and project high-probability liquidity targets.
It is engineered for Day Traders and Scalpers (Crypto & Futures) who need to know if the market is Trending, Ranging, or preparing for a Breakout.
1. The "Regime" System (Standard Deviation Bands)
The core engine anchors a VWAP (Volume Weighted Average Price) to your chosen timeframe (Daily, Weekly, or Monthly) and projects volatility bands based on market variance.
The Trend Zone (Inner Band / 1.0 SD): This is the "Fair Value" zone. In a healthy trend, price will pull back into this zone and hold. A hold here signals a high-probability continuation (Trend Following).
The Reversion Zone (Outer Band / 2.0 SD): This represents a statistical extreme. Price rarely sustains movement beyond 2 Standard Deviations without a reversion. A touch of this band signals "Overbought" or "Oversold" conditions.
2. Liquidity Magnets (Virgin VWAPs)
The script automatically tracks "Unvisited VWAPs" from previous sessions. These are price levels where significant volume occurred but have not yet been re-tested.
The Logic: Algorithms often target these "open loops." The script visualizes them as Blue Dashed Lines with price tags.
Smart Scaling (Anti-Scrunch): Includes a custom "Ghost Engine" that automatically hides or "ghosts" magnets that are too far away. This prevents your chart from being squashed (scrunched) on lower timeframes, keeping your candles perfectly readable while still tracking targets in the background.
3. The Quant Matrix (Dashboard)
A real-time Heads-Up Display (HUD) that interprets the data for you:
Regime: Detects Volatility Squeezes. If the bands compress, it signals "⚠ SQUEEZE", warning you to stop mean-reversion trading and prepare for an explosive breakout.
Bias: Color-coded Trend Direction (Bullish/Bearish) based on VWAP slope.
Signal: actionable text prompts such as "BUY DIP" (Trend Following), "FADE EXT" (Mean Reversion), or "PREP BREAK" (Squeeze).
4. Visual Intelligence
Bold Day Separators: Clear, vertical dotted dividers with Date Stamps to instantly separate trading sessions.
Dynamic Labels: Floating labels on the right axis identify exactly which deviation level is which, preventing chart confusion.
How to Use
Strategy A: The Trend Pullback (continuation)
Check Matrix: Ensure Bias is BULLISH (Green).
Wait: Allow price to pull back into the Inner Band (Dark Green Zone).
Trigger: If price holds the Center VWAP or the -1.0 SD line, enter Long.
Target: The next Liquidity Magnet above or the +2.0 SD band.
Strategy B: The Reversion Fade (Counter-Trend)
Check Matrix: Ensure price is labeled "EXTREME" or Signal says "FADE EXT".
Trigger: Price touches or pierces the Outer Band (2.0 SD).
Action: Enter counter-trend (Short) with a target back to the Center VWAP (Mean Reversion).
Strategy C: The Magnet Target
Identify a "MAGNET" line (Blue Dashed) near current price.
These act as high-probability Take Profit levels. Price will often rush to these levels to "close the loop" before reversing.
Settings
Anchor: Daily (default), Weekly, or Monthly.
Magnet Focus Range: Adjusts how aggressively the script hides distant magnets to fix chart scaling (Default: 2%).
Visuals: Fully customizable colors, label sizes, and dashboard position.
cd_VW_CxOverview
The cd_VW_Cx is a sophisticated trend analysis tool designed to quantify market momentum using Multi-Period VWAP (Volume Weighted Average Price). Unlike standard indicators, this script evaluates the current price relationship across multiple historical VWAP anchors to generate a real-time "Confidence Score" ranging from -100 to +100.
💡 Key Features
• Dynamic Anchoring: Seamlessly switch between Daily, Weekly, or Monthly open anchors to align with your trading style (Scalping, Day Trading, or Swing).
• Algorithmic Scoring (The Score Box): The indicator compares the current VWAP against historical periods.
o Score > +70: Strong Bullish Momentum.
o Score < -70: Strong Bearish Momentum.
• Polyline Rendering: Utilizes Pine Script v6’s advanced polyline architecture for high-performance, sleek visual plotting that doesn't clutter your chart.
• Institutional Support/Resistance: Historical VWAP levels are color-coded, often acting as "invisible" magnetic zones where institutional orders are clustered.
🛠 How to Trade with cd_VW_Cx
1. Momentum Confirmation: Look for the Score Box to turn Teal (Bullish) or Red (Bearish). This indicates that the current trend has statistical backing from multiple previous sessions.
2. The Breakout Signal: The script tracks price crossovers of the current VWAP. A "Bullish Breakout" combined with a high score is a high-probability entry signal.
3. Visual Guidance: Use the custom labels to identify which specific day/week/month’s VWAP is currently being tested as support or resistance.
⚙️ Customizable Settings
• Anchor Selection: Choose the calculation basis (Daily, Weekly, Monthly).
• Thresholds: Adjust the sensitivity of the Bullish/Bearish alerts (Default is +/- 70).
• Visuals: Full control over table positioning, font sizes, and color palettes to match your chart theme.
📢 cd_VW_Cx: Multi-Period VWAP Scoring & Analysis Guide
🔍 Overview & Visual Logic
The labels next to the VWAP levels dynamically change based on your Anchor selection:
• Daily Open: Displays the Day Name (e.g., Monday, Tuesday).
• Weekly Open: Displays the Week Number (1 – 52).
• Monthly Open: Displays the Month Number (1 – 12).
•
General View:
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🚦 How to Filter & Track Your Assets
You can monitor your favorite assets using two powerful methods:
1. Real-Time Alerts
Stay updated with TradingView notifications:
• Per Asset: Track a single pair.
• Watchlist Basis: Monitor your entire list at once. Alert Setup Guide:
2. Pine Screener Integration
Filter the market effortlessly using the Pine Screener. Pine Screener View:
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⚙️ Settings & Configuration
• Timeframe Selection: Your chart timeframe must be lower than the selected Anchor timeframe. (e.g., If "Daily Open" is selected, the timeframe should be lower than 1D).
• Anchor Choice: Select Daily, Weekly, or Monthly opens.
• Source Selection: Default value is set to ohlc4. Source Settings:
Filtering Criteria Examples:
• Bullish Filtering: Find assets with high momentum scores.
• Bullish Breakout (Single Criteria): Filters assets that have closed above the current VWAP level.
• Combined Strength (Score + Breakout): Filters assets that have a Score > 70 AND a fresh VWAP Breakout simultaneously.
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⚠️ Important Notes & Warnings
• Calculation Logic: The indicator calculates levels and scores on timeframes lower than the anchor. It is best used on timeframes that are close to but lower than the anchor.
• Avoid Extreme Gaps: Using a very low timeframe (e.g., 1m) with a very high anchor (e.g., Monthly) increases the risk of erroneous results.
• Optimization: The default score threshold of 70 is a starting point; I recommend adjusting it based on your own trading experience.
• The Power of Confluence: VWAP levels are naturally strong. Their significance increases when they coincide with institutional levels like PDH (Previous Day High), Session H/L, or HTF FVG.
• Experience Matters: A high score alone is not enough for an entry. Always combine this data with your personal strategy.
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💬 Community & Feedback
I would love to hear your suggestions regarding the scoring logic or visual improvements! Feel free to share your thoughts in the comments.
Happy Trading! 🚀
Kijun Sen Standard Deviation | QuantLapse SystemsOverview
The Kijun Sen Standard Deviation indicator by QuantLapse Systems is a volatility-aware trend-following framework that combines the structural equilibrium of the Kijun Sen (基準線) with statistically adaptive standard deviation bands.
By anchoring trend detection to market structure and confirming direction through volatility expansion, the indicator delivers a cleaner, more reliable regime classification across varying market conditions.
Rather than reacting to short-term noise, the system focuses on identifying statistically justified trend phases , making it well-suited for disciplined, rule-based trading.
Technical Composition, Calculation, Key Components & Features
📌 Kijun Sen (基準線) – Structural Trend Baseline
Calculated as the midpoint between the highest high and lowest low over a user-defined period.
Represents market equilibrium and structural balance rather than short-term momentum.
Naturally adapts to expanding and contracting price ranges.
Provides a stable baseline for regime detection and volatility validation.
Acts as the anchor for deviation bands and persistent trend-state logic.
Unlike fast or reactive moving averages, the Kijun Sen emphasizes price structure and equilibrium , making it especially effective for higher-quality trend confirmation.
📌 Volatility Adjustment – Standard Deviation Bands
Standard deviation is calculated over a configurable lookback to measure current price dispersion.
Upper and lower envelopes are formed by applying a deviation multiplier to the Kijun Sen.
Band width expands during volatility surges and contracts during consolidation.
Creates proportional, volatility-aware thresholds instead of static offsets.
Visually represents market energy through expanding and compressing channels.
These adaptive bands ensure that trend signals only occur when volatility supports directional movement.
📌 Trend Signal & Regime Calculation
Bullish Trend is confirmed when price closes above the upper deviation band.
Bearish Trend is confirmed when price closes below the lower deviation band.
Once established, the trend state persists until an opposing volatility break occurs.
This persistence reduces whipsaws and improves regime stability.
Trend state is reinforced with color-coded lines, envelopes, and background shading.
This volatility-confirmed persistence model is visible in the chart, where trends remain intact through minor pullbacks and only flip on decisive expansion.
How It Works in Trading
✅ Volatility-Confirmed Trend Detection – Requires expansion beyond deviation bands.
✅ Noise Suppression – Filters low-energy price movement within volatility envelopes.
✅ Regime Persistence – Maintains trend state until statistical invalidation.
✅ Immediate Visual Context – Direction, strength, and transitions are clear at a glance.
Visual Representation
Trend signals are displayed directly on price using both line and background context:
🟢 Green / Teal Kijun & Envelope → Confirmed bullish regime.
🔴 Red / Pink Kijun & Envelope → Confirmed bearish regime.
Semi-transparent band fill visualizes volatility expansion and compression.
Buy and Sell labels appear only on confirmed regime transitions.
The lower panel includes:
Strategy equity curve based on trend exposure.
Buy & Hold equity for performance comparison.
Background regime shading synchronized with trend state.
Features and User Inputs
The Kijun Sen Standard Deviation framework offers a focused yet powerful set of configurable inputs:
Kijun Sen Length – Controls structural trend sensitivity.
Standard Deviation Controls – Adjust lookback length and multiplier for regime strictness.
Backtesting & Date Filters – Define evaluation periods and starting conditions.
Display Options – Toggle labels, equity curves, and background shading.
Color Customization – Fully configurable buy/sell colors for trends and equity curves.
These controls allow users to balance responsiveness, stability, and clarity without overfitting.
Practical Applications
The Kijun Sen Standard Deviation indicator is designed for traders who prioritize structure, volatility confirmation, and regime awareness.
Primary Trend Filtering – Identify and stay aligned with dominant market direction.
Volatility-Aware Trend Following – Participate only when price expansion confirms intent.
Risk-Managed Exposure – Avoid chop during compression and transitional phases.
Systematic Strategy Development – Use as a regime engine or higher-timeframe filter.
Performance Evaluation – Compare trend-following equity against buy-and-hold benchmarks.
This framework bridges classical Ichimoku structure with modern statistical validation.
Conclusion
The Kijun Sen Standard Deviation indicator by QuantLapse Systems represents a refined evolution of Ichimoku-based trend analysis.
By integrating the structural equilibrium of the Kijun Sen with adaptive standard deviation confirmation, the system delivers clearer regime classification, reduced noise, and more reliable trend participation.
Rather than attempting to predict price, it focuses on confirming when trends are statistically justified .
Who should use Kijun Sen Standard Deviation:
📊 Trend-Following Traders – Stay aligned with dominant market structure.
⚡ Momentum & Swing Traders – Enter only on volatility-backed expansions.
🤖 Systematic & Algorithmic Traders – Ideal as a regime filter or trend-state engine.
Past performance is not indicative of future results.
Disclaimer: All trading involves risk, and no indicator can guarantee profitability.
Strategic Advice: Always backtest thoroughly, optimize parameters responsibly, and align settings with your timeframe, asset class, and risk tolerance before live deployment.
Composite Fear & Greed IndexComposite Fear & Greed Index
This is an advanced, professional-grade sentiment analysis engine designed to quantify market psychology. Unlike standard oscillators that rely on a single metric, this script uses a weighted composite of four distinct technical components to generate a holistic "Fear & Greed" score.
It includes Multi-Timeframe (MTF) capabilities, proprietary FOMO/Panic detection logic, and Zero-Lag trend analysis.
1. Unique Mathematical Methodology
This script is not a simple overlay of existing indicators. It uses a Composite Normalization Engine to blend four distinct metrics into a single, bounded 0-100 oscillator.
The "Mashup" Problem Solved: Standard indicators like MACD are "unbounded" (they can go to infinity), while RSI is "bounded" (0-100). You cannot simply average them.
Our Solution: This script calculates the Z-Score of the MACD histogram relative to its historical deviation and normalizes it into a 0-100 percentile. This allows for a mathematically valid combination with RSI and Bollinger Bands.
The Component Logic:
Momentum (RSI): (Weight: 30%) Pure price velocity.
Volatility (Bollinger %B): (Weight: 25%) Relative position within volatility bands.
Trend Strength (Normalized MACD): (Weight: 25%) Uses the custom Z-Score logic described above.
Trend Integrity (ZLEMA): (Weight: 20%) We replaced the standard SMA with a custom Zero-Lag Exponential Moving Average (ZLEMA) algorithm. This removes the "lag" associated with traditional sentiment analysis, allowing the index to react to crypto volatility in real-time.
The Calculation: These raw values are weighted and smoothed to produce the final Index Value.
Greater than 80: Extreme Greed (High risk of reversal)
Less than 20: Extreme Fear (Potential accumulation zone)
2. Unique Features
A. FOMO & Panic Event Detection The script does not just track price; it tracks behavior.
FOMO (Fear Of Missing Out): Triggered when Price breaks the Upper Bollinger Band + RSI is Overbought + Volume spikes > 2.5x the average. This often marks local tops.
PANIC: Triggered when Price drops significantly in one bar + Volume spikes > 3.0x the average + RSI is Oversold. This often marks capitulation bottoms.
B. Divergence Detection The script automatically detects and plots Regular Bullish and Bearish divergences between Price and the Sentiment Index.
Bullish Divergence: Price makes a Lower Low, but Sentiment makes a Higher Low (indicating waning selling pressure).
Bearish Divergence: Price makes a Higher High, but Sentiment makes a Lower High (indicating waning buying pressure). Note: The script plots these signals precisely on the indicator line corresponding to the pivot point.
C. Multi-Timeframe (MTF) Engine Users can view the "Daily" sentiment score while trading on a 5-minute or 15-minute chart. This allows scalpers to align their trades with the higher-timeframe market psychology.
3. Usage Guide
Step 1: Trend Alignment Look at the dashboard or the main line color. Green indicates Greed/Uptrend, Red indicates Fear/Downtrend.
Step 2: Extremes
Sell/Take Profit: When the Index crosses 80 (Extreme Greed) or a "FOMO" triangle appears.
Buy/Long: When the Index crosses 20 (Extreme Fear) or a "PANIC" triangle appears.
Step 3: Confirmation Use the Divergence Dots as confirmation. A "Panic" signal followed by a "Bullish Divergence" dot is a high-probability reversal setup.
Settings
Timeframe: Select the MTF resolution (default is Chart).
Weights: You can adjust the influence of RSI, MACD, BB, or Trend to fit your specific asset class.
Visuals: Fully customizable colors, table position, and toggle switches for shapes/backgrounds.
Disclaimer: This script is for informational purposes only and does not constitute financial advice.
Daily/Weekly Swing Highs-Lows + Candle PatternsDescription
Daily/Weekly Swing Highs-Lows + Candle Patterns
This indicator plots the most recent Daily and Weekly Swing Highs and Lows (key support/resistance levels) using a simple and effective logic: a swing high/low is confirmed when the previous bar's extreme is higher/lower than both the current and the one before it.
Features:
• Daily Swing Highs/Lows (teal/maroon circles) – toggleable
• Weekly Swing Highs/Lows (blue/purple circles) – optional
• Visual separators for new daily and weekly bars (light background color)
• Daily candle pattern labels (optional):
- US = Up Swing (strong bullish continuation)
- DS = Down Swing (strong bearish continuation)
- IN = Inside Bar
- OUT = Outside Bar
• Daily close position labels (optional):
- P = Positive (close in upper 25% of the range)
- mP = minor Positive (50–75%)
- mN = minor Negative (25–50%)
- N = Negative (lower 25%)
All elements are fully customizable (colors, visibility) and work on any timeframe.
Best suited for intraday timeframes (1 min to 4 hours) where daily and weekly key levels provide important context for price action and reversals.
The optional "Trading session length" input is mainly useful for markets with shorter sessions (e.g., European indices) and does not affect swing detection.
Open-source, free to use and modify.
How to Use the Indicator + Practical Use Case
Key Settings (Inputs)
Trading session length (hours) → Default 8.5 h (useful for FTSEMIB, DAX, etc.). Leave it as is unless you trade a market with a different session length.
Daily Swing Levels → Show/Hide daily swing highs (teal) and lows (maroon).
Weekly Swing Levels → Usually keep off on intraday charts to avoid clutter (turn on for higher-timeframe context).
Daily Candle Patterns → Enable only if you want to see US/DS/IN/OUT labels on the daily close.
Close Position (P/mP/mN/N) → Enable if you want to quickly see how strong/weak the daily close was.
What You See on the Chart
Teal circles = Last confirmed daily swing high (resistance).
Maroon circles = Last confirmed daily swing low (support).
Blue/purple circles (if enabled) = Weekly swing high/low.
Light gray background = Start of a new trading day.
Purple background (if weekly enabled) = Start of a new week.
Small labels on daily close (if enabled):
- US = strong bullish day
- DS = strong bearish day
- IN = inside bar (consolidation)
- OUT = outside bar (expansion)
- P/mP/mN/N = how far the close was from the high/low of the day.
Best Timeframes 1 min to 240 min charts → Daily levels act as major support/resistance zones for intraday trading.
Avoid using on daily or higher charts (the logic is designed for intraday context).
Why this works well intraday:
The daily swing high/low levels are high-probability zones where institutions and algorithms often defend positions. On intraday charts, they act as “magnets” for price, giving you clean entries and exits with clear invalidation levels.
This indicator keeps your chart clean while providing exactly the context most intraday traders need: key daily levels + daily momentum context.
QUANT TRADING ENGINE [PointAlgo]Quant Trading Engine is a quantitative market-analysis indicator that combines multiple statistical factors to study trend behavior, mean reversion, volatility, execution efficiency, and market stability.
The indicator converts raw price behavior into standardized signals to help evaluate directional bias and risk conditions in a systematic way.
This script focuses on factor alignment and regime awareness, not prediction certainty.
Design Philosophy
Markets move through different regimes such as trending, ranging, volatile expansion, and instability.
This indicator attempts to model these regimes by blending:
Momentum strength
Mean-reversion pressure
Volatility risk
Trend filtering
Execution context (VWAP)
Correlation structure
Each component is normalized and combined into a single Quant Alpha framework.
Factor Construction
1. Momentum Factor
Measures directional strength using percentage price change over a rolling window.
Standardized using mean and standard deviation.
Represents trend continuation pressure.
2. Mean Reversion Factor
Measures deviation from a longer moving average.
Standardized to identify stretched conditions.
Designed to capture counter-trend behavior.
Directional Clamping
Mean-reversion signals are dynamically restricted:
No counter-trend buying during downtrends.
No counter-trend selling during uptrends.
Allows both sides only in neutral regimes.
This prevents conflicting signals in strong trends.
3. Volatility Factor
Uses realized volatility derived from price changes.
Penalizes environments where volatility deviates significantly from its norm.
Acts as a risk adjustment rather than a directional driver.
4. Composite Quant Alpha
The final Quant Alpha is a weighted blend of:
Momentum
Mean reversion (trend-clamped)
Volatility risk
The composite is standardized into a Z-score, allowing consistent interpretation across instruments and timeframes.
Signal Logic
Buy signal occurs when Quant Alpha crosses above zero.
Sell signal occurs when Quant Alpha crosses below zero.
Zero-cross logic is used to represent shifts from negative to positive statistical bias and vice versa.
Signals reflect statistical regime change, not trade instructions.
Volatility Smile Context
Measures price deviation from its statistical distribution.
Identifies skewed conditions where upside or downside volatility becomes dominant.
Highlights extreme deviations that may imply elevated derivative risk.
Exotic Risk Conditions
Detects sudden price expansion combined with volatility spikes.
Highlights environments where execution and risk become unstable.
Visual background cues are used for awareness only.
Execution Context (VWAP)
Measures price distance from VWAP.
Used to assess execution efficiency rather than direction.
Helps identify stretched conditions relative to average traded price.
Correlation Structure
Evaluates short-term return correlations.
Detects when price behavior becomes less predictable.
Flags structural instability rather than trend direction.
Visualization
The indicator plots:
Quant Alpha (scaled) with directional coloring
Volatility smile deviation
Price vs VWAP distance
Correlation structure
Signal markers indicate Quant Alpha zero-cross events and risk conditions.
Dashboard
A compact dashboard summarizes:
Trend filter state
Quant Alpha polarity and value
Individual factor readings
Current action state (Buy / Sell / Wait / Risk)
The dashboard provides a real-time snapshot of internal model conditions.
Usage Notes
Designed for analytical interpretation and research.
Best used alongside price action and risk management tools.
Factor behavior depends on instrument liquidity and volatility.
Not optimized for illiquid or irregular markets.
Disclaimer
This script is provided for educational and analytical purposes only.
It does not provide financial, investment, or trading advice.
All outputs should be independently validated before making any trading decisions.
Bollinger Bands Forecast with Signals (Zeiierman)█ Overview
Bollinger Bands Forecast with Signals (Zeiierman) extends classic Bollinger Bands into a forward-looking framework. Instead of only showing where volatility has been, it projects where the basis (midline) and band width are likely to drift next, based on recent trend and volatility behavior.
The projection is built from the measured slopes of the Bollinger basis, the standard deviation (or ATR, depending on the mode), and a volatility “breathing” component. On top of that, the script includes an optional projected price path that can be blended with a deterministic random walk, plus rejection signals to highlight failed band breaks.
█ How It Works
⚪ Bollinger Core
The script first computes standard Bollinger Bands using the selected Source, Length, and Multiplier:
Basis = SMA(Source, Length)
Band width = Multiplier × StDev(Source, Length)
Upper/Lower = Basis ± Width
This remains the “live” (non-forecast) structure on the chart.
⚪ Trend & Volatility Slope Estimation
To project forward, the indicator measures directional drift and volatility drift using linear regression differences:
Basis slope from the Bollinger basis
StDev slope from the Bollinger deviation
ATR slope for ATR-based projection mode
These slopes drive the forecast bands forward, reflecting the market’s recent directional and volatility regime.
⚪ Projection Engine (Forecast Bands)
At the last bar, the indicator draws projected basis, upper, and lower lines out to Forecast Bars. The projected basis can be:
Trend (straight linear projection)
Curved (ease-in/out transition toward projected endpoints)
Smoothed (extra smoothing on projected basis/width)
⚪ Price Path Projection + Optional Random Walk
In addition to projecting the bands, the script can draw a price forecast path made of a small number of zigzag swings.
Each swing targets a point offset from the projected basis by a multiple of the projected half-width (“width units”).
Decay gradually reduces swing size as the forecast deepens.
The Optional Random Walk Blend adds a deterministic drift component to the zigzag path. It’s not true randomness; it’s a stable pseudo-random sequence, so the drawing doesn’t jump around on refresh, while still adding “natural” variation.
⚪ Rejection Signals
Signals are based on failed attempts to break a band:
Bear Signal (Down): price tries to push above the upper band, then falls back inside, while still closing above the basis.
Bull Signal (Up): price tries to push below the lower band, then returns back inside, while still closing below the basis.
█ How to Use
⚪ Forward Support/Resistance Corridors
Treat the projected upper/lower bands as a future volatility envelope, not a guarantee:
The upper projection ≈ is likely a resistance level if the regime persists
The lower projection ≈ is likely a support level if the regime persists
Best used for trade planning, targets, and “where price could travel” under similar conditions.
⚪ Regime Read: Trend + Volatility
The projection shape is informative:
Rising basis + expanding width → trend with increasing volatility (needs wider stops / more caution)
Flat basis + compressing width → contraction regime (often precedes expansion)
⚪ Signals for Mean-Reversion / Failed Breakouts
The rejection markers are useful for fade-style setups:
A Down signal near/after upper-band failure can imply rotation back toward the basis.
An Up signal near/after lower-band failure can imply snap-back toward the basis.
With MA filtering enabled, signals are constrained to align with the broader bias, helping reduce chop-driven noise.
█ Related Publications
Donchian Predictive Channel (Zeiierman)
█ Settings
⚪ Bollinger Band
Controls the live Bollinger Bands on the chart.
Source – Price used for calculations.
Length – Lookback period; higher = smoother, lower = more reactive.
Multiplier – Bandwidth; higher = wider bands, lower = tighter bands.
⚪ Forecast
Controls the forward projection of the Bollinger Bands.
Forecast Bars – How far into the future the bands are projected.
Trend Length – Lookback used to estimate trend and volatility slopes.
Forecast Band Mode – Defines projection behavior (linear, curved, breathing, ATR-based, or smoothed).
⚪ Price Forecast
Controls the projected price path inside the bands.
ZigZag Swings – Number of projected oscillations.
Amplitude – Distance from basis, measured in bandwidth units.
Decay – Shrinks swings further into the forecast.
⚪ Random-Walk
Adds controlled randomness to the price path.
Enable – Toggle random-walk influence.
Blend – Strength of randomness vs. zigzag.
Step Size – Size of random steps (band-width units).
Decay – Reduces randomness as the forecast deepens.
Seed – Changes the (stable) random sequence.
⚪ Signals
Controls rejection/mean-reversion signals.
Show Signals – Enable/disable signal markers.
MA Filter (Type/Length) – Filters signals by trend direction.
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Disclaimer
The content provided in my scripts, indicators, ideas, algorithms, and systems is for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
VWAP Flow ParmezanThe "Official Bank Flow VWAP" is a comprehensive trading suite designed for institutional Forex traders.
This indicator solves the problem of chart clutter by combining two critical components of liquidity: Price (Value) and Time (Sessions). It is specifically optimized for EUR/USD and GBP/USD on intraday timeframes (M5, M15), helping you identify high-probability setups where "Fair Value" meets "Volatility."
Key Features
1. Multi-Timeframe VWAP Hierarchy Unlike standard indicators, this tool visualizes the interaction between three distinct timeframes:
Daily VWAP (Dynamic Color): Your primary trend filter. Green when Bullish (Price > VWAP), Red when Bearish (Price < VWAP).
Weekly VWAP (Orange Dots): Represents the medium-term balance. Acts as a magnet for mean reversion mid-week.
Monthly VWAP (Purple Line): The institutional "line in the sand." Major support/resistance level.
2. Standard Deviation Bands (Market Balance) The indicator plots SD1 and SD2 bands around the Daily VWAP:
Inner Zone (SD1): Represents the "Fair Value" area.
Outer Bands (SD2): Represents overbought/oversold conditions. Useful for identifying mean reversion plays back to the center.
3. Official Exchange Sessions (Time) Forget confusing "killzones." This tool highlights the Official Open times for major exchanges, adjusted for Daylight Savings via New York time:
London Open (08:00 LDN): The start of European volume.
New York Open (08:00 NY): The injection of US liquidity.
London Close/Fix: The daily overlap close, often marking trend reversals.
Note: Sessions are visualized with non-intrusive black "shadow" backgrounds to keep your chart clean.
4. "Ghost" Levels (Previous VWAP) A unique feature that plots the closing VWAP level of the previous day. Institutional algorithms often target these "untested" levels as Take Profit targets or liquidity pools.
How to Use
Trend Following: If Price is above the Daily VWAP (Green) during the London Open, look for Long entries targeting the SD1/SD2 upper bands.
Mean Reversion: If Price hits the SD2 Band while far away from the Weekly VWAP, look for a reversal back to the mean.
Confluence: The strongest signals occur when price touches a key VWAP level (e.g., Weekly VWAP) specifically during the highlighted Session Start times.
Settings
Timezone: Defaults to America/New_York to automatically handle DST shifts for London/NY opens.
Visuals: Fully customizable colors and transparency. Default is set to a "Dark Mode" friendly professional palette.
Shannon Entropy (Quant Lab)🟦 Shannon Entropy = The level of "order" or "chaos" in the market.
This indicator gives you the answer to the question:
"Is the market currently orderly and understandable, or is it random and chaotic?"
No other classical indicator can accurately show this.
The value of Entropy is between 0 and 1:
⸻
🟩 1) Entropy = 0.0 – 0.3 → Structured, orderly, readable market
During these periods, the price:
• A trend forms • Ranges work clearly • Patterns (head & shoulders, flag, triangle) form smoothly • Systems like Z-score, VWAP, EMA work very cleanly • Data for modeling (algorithmic strategies, ML) is high quality
Think of this region as follows:
The market "works according to rules," it's easy to trade.
⸻
🟧 2) Entropy = 0.3 – 0.7 → Normal behavior region
In this region:
• Neither too orderly nor too chaotic
• Most systems operate at an average rate • We can say the market is healthy
It is tradable; however, the conditions are not perfect.
⸻
🟥 3) Entropy = 0.7 – 1.0 → Chaos / Noise / Manipulation region
This is the MOST DANGEROUS REGION OF THE MARKET.
What happens?
• Prices jump randomly left and right. • Wicks increase excessively. • Fake breakouts multiply. • The win rate of strategies decreases. • Trend-following systems constantly generate "false signals." • Even mean-reversion systems are caught off guard. • ML models learn junk data during these periods. • Generally, news, liquidation cascades, and manipulation periods increase entropy.
This period perfectly illustrates:
"There is no logic in this market right now — it's moving randomly."
Therefore, it's a period where you need to be very careful:
Reduce position size. • Trade less. • Avoid unnecessary risks. • Tighten stop losses. • Don't use leverage.
This is your risk alert panel.
⸻
🔥 The real superpower Entropy gives you: Trend selection and system selection
Entropy → Determines which strategy you will use.
✔ Low Entropy → Trend following or mean-reversion that works like a toy
✔ High Entropy → Even opening a trade is risky
✔ Normal Entropy → Most strategies work
Building a strategy without this information is unprofessional.
⸻
🧠 Critical summary (you can even copy and paste it as a description in TradingView):
Low entropy → market is structured, patterns & trends are reliable
High entropy → market is chaotic, noisy, unpredictable; avoid aggressive trading
Entropy tells you if your strategy has a high chance or low chance of working
⸻
🟦 Signals Entropy gives in practice:
🔹 Entropy is falling →
The market is stabilizing → A major trend or strong move is approaching.
🔹 Entropy is rising →
The market is becoming chaotic → Sudden spike, a period of trading in prayer mode, extra risk.
🔹 Low Entropy + VR > 1 + High ER → FULL TREND MARKET
A true “trend paradise” period.
🔹 Low Entropy + VR < 1 + High FDI → RANGE MARKET
A paradise of mean reversion.
🔹 High Entropy + High VoV → DANGEROUS PERIOD
Big explosions, news, and liquidations happen here.
⸻
⭐ IN SHORT:
Entropy = an indicator of how randomly the market behaves.
• 0–0.3 → regular, good, reliable market
• 0.3–0.7 → normal market
• 0.7–1.0 → chaotic, dangerous market
It tells you at a glance whether you should trade during this period or not.
