Price Returns Prediction Using RNN With LSTM Units

Suit Khanna, Quant Researcher, Algorithmic Trading, Edelweiss Financial Services

financial market

  • Data Processing and Feature Creation

    • Input features created based on Price returns of Nifty Futures

      • inspired by Taylor expansion
      • derivatives of the returns are used as input features
      • (future: Order Book/Index Options/broad market features)

    • Output: 10 classes

  • Model types and Specification

    • A Simple RNN(MLP)
    • LSTM RNN
    • Stateful LSTM RNN
    • Bi-directional LSTM RNN

  • Strategy Model

    • The output of LSTM RNN can be used as input for a trading strategy model
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