Conditional importance-weighted autoencoders modeling equity returns.
Predicting market regimes (crashes) with ML/DL
Deep Reinforcement Learning Application to Algorithmic Trading
Supervised Machine Learning Classification for Short Straddles on the S&P50
Images from historical equity options surface data to predict the VIX index
Financial time series simulation using deep learning and autoencoder-based pair trading strategies.
Uncover the Power of Transfer Learning for Time Series Using Image-Encoded Trading Systems.
How deep learning can assist in factor timing?
Clustering methods to detect and trade market regimes and incorporating news volume and sentiment into trading strategies.
Spatiotemporal transformers and clustering methods for developing stock trading strategies
ML/DL insights and applications to real estate investment portfolios and probability of default prediction.
LLMs applications to sentiment analysis to improve investment strategies.
