Ch. 20Strategy #692

Strategy #692

Kalman Filter Trend Trade

Entry Logic

  • A Kalman filter is used to estimate the underlying trend of a time series.
  • A long entry is triggered when the filtered price crosses above a certain threshold.
  • A short entry is triggered when the filtered price crosses below a certain threshold.
  • Confirmation is provided by the velocity of the filtered price.
  • The timeframe is determined by the parameters of the Kalman filter.
  • The location context is provided by the filtered price relative to the raw price.
  • The market condition is a trending market.

Exit Logic

  • The exit is triggered when the filtered price shows signs of reversing.
  • A trailing stop can be used based on the filtered price.
  • The trade is exited if the filtered price moves against the position.
  • An opposite signal from the Kalman filter can be used as an exit signal.

Stop Loss Structure

  • The stop loss is placed at a level that invalidates the trend signal.

Risk Management Framework

  • Risk management rules are applied to the trades generated by the Kalman filter.

Position Sizing Model

  • Position sizing can be adjusted based on the strength of the trend signal.

Trade Filtering

  • The Kalman filter itself acts as a filter for noise.

Context Framework

  • The Kalman filter provides the context for the trend.

Trade Management Rules

  • The trade is managed based on the evolution of the filtered price.

Time Rules

  • The strategy can be applied at any time.

Setup Classification

  • The strength of the setup is determined by the strength of the trend signal.

Market Selection Criteria

  • The strategy is best suited for trending markets.

Statistical Edge Metrics

  • The edge is determined by backtesting the strategy.

Failure Conditions

  • The strategy can fail in choppy or range-bound markets.

Psychological Rules

  • The main challenge is to trust the filter and not to get shaken out by noise.

Advanced Components

  • The parameters of the Kalman filter need to be tuned for each market.
  • The Kalman filter can be extended to a multivariate setting.

Location

  • The strategy is most effective in markets that exhibit clear trends.