Research
My research develops neural network–based agents that learn portfolio allocation policies directly from market data, and studies how those agents behave across volatility regimes, market-cap segments, and emerging-market conditions.
Modelling and forecasting of financial time series data.
Quantitative finance methods and risk management applications.
Machine learning and deep learning methods for investment and portfolio management.
Neural network–based portfolio optimization and asset allocation.
No publications match this filter.
Examines how deep reinforcement learning portfolio agents behave under different volatility regimes, offering empirical evidence on regime-aware strategy adaptation and its effect on risk-adjusted returns.
View paper (DOI: 10.1007/s10690-026-09629-8)
Applies deep reinforcement learning agents to dynamic portfolio allocation in Indian equity markets, benchmarking learned strategies against conventional allocation approaches under real market conditions.
View paper (DOI: 10.3905/jfds.2025.1.210)No conference presentations match this filter.
