OPEN-SOURCE SCRIPT

Advanced HMM - 3 States Complete

116
Hidden Markov Model
Aconsistent challenge for quantitative traders is the frequent behaviour modification of financial
markets, often abruptly, due to changing periods of government policy, regulatory environment
and other macroeconomic effects. Such periods are known as market regimes. Detecting such
changes is a common, albeit difficult, process undertaken by quantitative market participants.
These various regimes lead to adjustments of asset returns via shifts in their means, variances,
autocorrelation and covariances. This impacts the effectiveness of time series methods that rely
on stationarity. In particular it can lead to dynamically-varying correlation, excess kurtosis ("fat
tails"), heteroskedasticity (volatility clustering) and skewed returns.
There is a clear need to effectively detect these regimes. This aids optimal deployment of
quantitative trading strategies and tuning the parameters within them. The modeling task then
becomes an attempt to identify when a new regime has occurred adjusting strategy deployment,
risk management and position sizing criteria accordingly.
A principal method for carrying out regime detection is to use a statistical time series tech
nique known as a Hidden Markov Model[5]. These models are well-suited to the task since they
involve inference on "hidden" generative processes via "noisy" indirect observations correlated
to these processes. In this instance the hidden, or latent, process is the underlying regime state,
while the asset returns are the indirect noisy observations that are influenced by these states.


MAIN FEATURES OF THE INDICATOR
The "Advanced HMM - 3 States Complete" indicator is an advanced technical analysis tool that uses Hidden Markov Model (HMM) to identify three main market regimes: BULL, BEAR, and SIDEWAYS.

🎯 KEY FEATURES:
1. HMM-based Trend Detection
3 market states: Bull (0), Bear (1), Sideways (2)

Dynamic probabilities: Calculates probability for each state based on price data

Transition matrix: Models state transitions between regimes

2. Analytical Features
Price volatility: Log returns and standard deviation

Momentum: Rate of Change (ROC)

Volume: Volume ratio vs moving average

Data normalization: Standardizes features to common scale

3. Visual Trading Signals
text
📍 BUY Signals:
- Green upward triangle below bars
- "LONG" label in green

📍 SELL Signals:
- Red downward triangle above bars
- "SHORT" label in red

📍 EXIT Signals:
- Orange X marks when transitioning to sideways
4. Information Display
Probability table (top-right): Shows percentage for each state

State label: Current regime with probability percentages

Chart background color: Reflects dominant market state

5. Automated Alerts
Alerts when new Bull/Bear market detected

Alerts when market transitions to sideways

Configurable TradingView notifications

6. Customizable Parameters
pinescript
length: 100 // Lookback period
smoothing_period: 20 // Probability smoothing
volatility_threshold: 0.5 // Volatility threshold
💡 PRACTICAL APPLICATIONS:
Identify primary trends with quantified probabilities

Entry/exit signals based on state transitions

Risk management during sideways markets

Trend confirmation when combined with other indicators

This indicator is particularly useful for market regime analysis and identifying trend transition points using advanced statistical probability methods.

🔧 TECHNICAL IMPLEMENTATION:
Composite observation: Weighted combination of returns (40%), momentum (30%), and volatility (30%)

Gaussian emission probabilities: Different distributions for each state

Manual HMM updates: Avoids matrix computation limitations in Pine Script

Real-time smoothing: EMA applied to state probabilities

The indicator provides institutional-grade regime detection in a visually intuitive package suitable for both discretionary and systematic traders.

إخلاء المسؤولية

لا يُقصد بالمعلومات والمنشورات أن تكون، أو تشكل، أي نصيحة مالية أو استثمارية أو تجارية أو أنواع أخرى من النصائح أو التوصيات المقدمة أو المعتمدة من TradingView. اقرأ المزيد في شروط الاستخدام.