Z-Score Bands + SignalsZ-Score Statistical Market Analyzer
A multi-dimensional market structure indicator based on standardized deviation & regime logic
English Description
Concept
This indicator builds a statistical model of price behaviour by converting every candle’s movement into a Z-score — how many standard deviations each close is away from its moving average.
It visualizes the normal distribution structure of returns and provides adaptive entry signals for both Mean Reversion and Breakout regimes.
Rather than predicting price direction, it measures statistical displacement from equilibrium and dynamically adjusts the decision logic according to the market’s volatility regime.
⚙️ Main Components
Z-Score Bands (±1σ, ±2σ, ±3σ)
– The core structure visualizes volatility boundaries based on rolling mean and standard deviation.
– Price outside ±2σ often indicates statistical extremes.
Dual Signal Systems
Mean Reversion (MRL / MRS): when price (or return z-score) crosses back inside ±2σ bands.
Breakout (BOL / BOS): when price continues to expand beyond ±2σ.
Volatility Regime Classification
The indicator detects whether the market is currently in a low-vol or high-vol regime using percentile statistics of σ.
Low vol → Mean Reversion preferred
High vol → Breakout preferred
🧠 Adaptive Switches
A. Freeze MA/σ - Use previous-bar stats to avoid repainting and lag.
B. Confirm on Close - Only generate signals once the base-timeframe bar closes (eliminates look-ahead bias).
C. Return-based Signal - Use log-return Z-score instead of price deviation — normalizes volatility across assets.
D. Outlier Filter - Exclude bars with abnormal single-bar returns (e.g., >20%). Reduces false spikes.
E. Regime Gating - Automatically switch between Mean Reversion and Breakout logic depending on volatility percentile.
Each module can be toggled individually to test different statistical behaviours or tailor to a specific market condition.
📊 Interpretation
When the histogram of returns approximates a normal distribution, mean-reversion logic is often more effective.
When price persistently drifts beyond ±2σ or ±3σ, the distribution becomes leptokurtic (fat-tailed) — a breakout structure dominates.
Hence, this tool can help you:
Identify whether an asset behaves more “Gaussian” or “fat-tailed”;
Select the correct trading regime (MR or BO);
Quantitatively measure market tension and volatility clusters.
🧩 Recommended Use
Works on any timeframe and any asset.
Best used on liquid instruments (e.g., XAU/USD, indices, major FX pairs).
Combine with volume, sentiment or structural filters to confirm signals.
For strategy automation, pair with the companion script:
🧠 “Z-Score Strategy • Multi-Source Confirm (MRL/MRS/BOL/BOS)”.
⚠️ Disclaimer
This script is designed for educational and research purposes.
Statistical deviation ≠ directional prediction — use with sound risk management.
Past distribution patterns may shift under new volatility regimes.
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中文说明（简体）
概念简介
该指标基于价格的统计分布原理，将每根 K 线的波动转化为标准化的 Z-Score（标准差偏离值），用于刻画市场处于均衡或偏离状态。
它同时支持 均值回归（Mean Reversion） 与 突破延展（Breakout） 两种逻辑，并可根据市场波动结构自动切换策略模式。
⚙️ 主要功能模块
Z-Score 通道（±1σ / ±2σ / ±3σ）
用滚动均值与标准差动态绘制的统计波动带，价格超出 ±2σ 区域通常意味着极端偏离。
双信号系统
MRL / MRS（均值回归多空）：价格重新回到 ±2σ 以内时触发。
BOL / BOS（突破延展多空）：价格持续运行在 ±2σ 之外时触发。
波动率分层
自动识别市场处于高波动还是低波动区间：
低波动期 → 适合均值回归逻辑；
高波动期 → 适合突破趋势逻辑。
🧠 A–E 模块说明
A. 固定统计参数：使用上一根 K 线的均值和标准差，防止重绘。
B. 收盘确认信号：仅在当前时间框架收盘后生成信号，避免前视偏差。
C. 收益率信号模式：采用对数收益率的 Z-Score，更具普适性。
D. 异常波过滤：忽略单根极端波动（如 >20%）的噪声信号。
E. 波动率调节逻辑：根据市场处于高/低波动区间，自动切换 MRL/MRS 或 BOL/BOS。
📊 应用解读
如果收益率分布接近正态分布 → 市场倾向震荡，MRL/MRS 效果较佳；
若价格频繁偏离 ±2σ 或 ±3σ → 市场呈现“肥尾”分布，趋势延展占主导。
因此，该指标的核心目标是：
识别当前市场的统计结构类型；
根据波动特征自动切换交易逻辑；
提供结构化、可量化的市场状态刻画。
💡 使用建议
适用于所有时间框架与金融品种。
建议结合成交量或结构性指标过滤。
若用于策略回测，可搭配同名 “Z-Score Strategy • Multi-Source Confirm” 策略脚本。
⚠️ 免责声明
本指标仅用于研究与教学，不构成任何投资建议。
统计偏离 ≠ 趋势预测，实际市场行为可能在不同波动结构下改变。
Индикатор Pine Script®
