This project was done while I was a research intern at the Indian School of Business Hyderabad during December 2019 and January 2020. I also received a Letter of Recommendation for my work.
Highlights:
- Designed and implemented an intuitive approach to storing the history of a stock in the form of a vector using a Ticker Embedding Model, similar to that in a Word Embedding model
- Incorporated a number of technical indicators such as Momentum, Trailing Volatility, Asset Class and average return across each asset class along with these embeddings for time series analysis
- Designed, trained and tested an LSTM classifier (built using PyTorch) on a time series of multiple stock tickers to predict the Expected Return and to study non linearity and inter asset class correlation
- Expanded the base LSTM to incorporate attention, and retrain over the latest data while testing
- Optimized the hyperparameters using libraries: Ray for Grid Search and Hyperopt for Bayesian optimization