Can machine learning be used to accurately forecast intraday index returns using candlestick data?
This thesis wants to investigate whether machine learning, trained on candlestick data, can be used to forecast intraday returns. Previous research has primarily focused on returns with longer horizons and is therefore leaving a research gap on shorter horizons. This thesis will use a combination of Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) as the deep learning model to
