[Current Project] Trade volume forecasting with deep learning

Modeling changes in intraday trading volume is a key component in algorithmic trading strategies. Deep learning can be a useful tool for discovering new edges for investors, but for several reasons the use of recurrent neural network models in financial data have produced mixed results. In this on-going project, I explore the application of deep learning models on time series data by first attempting to replicate on a different data set the methods and results detailed in Libman, et al 2019, which combined Long Short Term Memory (LSTM) networks with support vector regression (SVR) and autoregression (AR).