MACD Hidden Markov Model

The MACD Hidden Markov Model strategy is built around MACD Hidden Markov Model.

Testing indicates an average annual return of about 61%. It performs best in the crypto market.

Signals trigger when Markov confirms trend changes on intraday (5m) data. This makes the method suitable for active traders.

Stops rely on ATR multiples and factors like MacdFast, MacdSlow. Adjust these defaults to balance risk and reward.

Details

• Entry Criteria: see implementation for indicator conditions.
• Long/Short: Both directions.
• Exit Criteria: opposite signal or stop logic.
• Stops: Yes, using indicator-based calculations.
• Default Values:
  • MacdFast = 12
  • MacdSlow = 26
  • MacdSignal = 9
  • CandleType = TimeSpan.FromMinutes(5).TimeFrame()
  • HmmHistoryLength = 100
• Filters:
  • Category: Trend following
  • Direction: Both
  • Indicators: Markov
  • Stops: Yes
  • Complexity: Intermediate
  • Timeframe: Intraday (5m)
  • Seasonality: No
  • Neural Networks: Yes
  • Divergence: No
  • Risk Level: Medium