Predict profitability of trades based on indicator buy / sell signals

Trade profitability analysis for trades based on various indicators signals:

  • MACD
  • Simple Moving Average
  • Exponential Moving Average

    • Trading assumptions:

    1. Trade is profitable if, profit >0
    2. Buy / sell happen the following day of the signal
    3. Buy / sell are taken 10% from the open price towards close price

    Machine learning assumptions:

    • Binary classification: 1 – profit, 0 – loss
    • A separate model for each company / ticker
    • Model is trained vs optimal precision

    Machine learning models used:

    1. Linear Support Vector Classifier
    2. Decision Tree Classifier
    3. Random Forest Classifier
    4. Gradient Boosting Classifier
    5. XGBoost Classifier
    6. Keras classifier

    Trade analysis intermediate results:

    30-40% of trades based on indicator signals are profitable

    In general trades on SMA signals are more often profitable than the ones based on EMA signals

    Trade profitability predictions intermediate results (based on test data)/

    The precision of the predictions is oscilating around 70%, which is pretty good, considering that the analysts estimate other signals accuracy as 30 to 50% (double top, shoulder & arms, etc). This means, there is ~70% chance that predicted trade will be profitable (Reminder: profitable -> profit > 0)

    However, the recall is only around 15%, which means that very the model pick-up very few of the actually profitable trades.

    #Detailed analysis tbc

    GitHub

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