Feature Extraction in hedging

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In financial derivatives hedging, feature extraction is locating and extracting useful data or features from raw data that may be utilized to make forecasts or choices. These characteristics may include historical price data, volatility, interest rates, and other market indicators in the context of financial derivatives.

For hedging, you may utilize machine learning models such as Feedforward Neural Networks (FNN) and Long Short Term Memory (LSTM), which collect and analyze data to forecast effective hedging strategies.