Research
Publications and working papers from the TRW research team on financial markets, AI, and quantitative methods.
Statistical Models for Pricing Efficiency in Indian Derivatives Markets
This paper examines the pricing efficiency of index and stock options traded on the National Stock Exchange of India using a comprehensive framework of statistical tests. We analyze deviations from theoretical pricing models, investigate the term structure of implied volatility, and evaluate the predictive power of options-derived metrics for underlying asset returns. Our findings reveal systematic pricing patterns that differ significantly from mature derivatives markets.
Machine Learning Approaches to Order Flow Prediction in Indian Equity Markets
We investigate the application of machine learning techniques to predict short-term order flow dynamics in the Indian equity market. Using a novel dataset of level-2 order book snapshots from the NSE, we compare the predictive performance of gradient boosting, LSTM networks, and transformer-based architectures for forecasting order imbalance, trade direction, and short-term price movements. Our results demonstrate that attention-based models achieve superior performance in capturing the complex, non-linear relationships inherent in high-frequency order flow data.