AI Snake Game with Reinforcement Learning
- Developed an AI agent to play the classic Snake game using Deep Q Learning implemented from scratch in Python with Pygame and PyTorch.
- Built and trained a neural network to predict the AI’s actions, achieving consistent gameplay improvement through reinforcement learning.
Nov - 2024
Portfolio Optimization with Graph Convolutional Networks (GCN) on Nifty 50 Stocks
- Developed GCN Model: Created a GCN to capture dependencies among Nifty 50 stocks using daily returns, volatility, and RSI.
- Constructed Stock Graph and Applied Spectral Clustering for Diversification: Built a stock graph with correlations as edges, enhancing diversification.
- Validated through Backtesting: Demonstrated effective risk-adjusted returns, showcasing GCN’s potential in financial optimization.
Nov 2024
Monte Carlo Simulation and Risk Management for Nifty 50 Portfolio Optimization
- Applied Monte Carlo simulation to optimize a portfolio of Nifty 50 stocks, selecting top stocks based on Sharpe ratios.
- Evaluated portfolio risk using Value at Risk (VaR) and Conditional Value at Risk (CVaR).
- Identified optimal portfolio allocations to maximize returns while managing risk exposure.
May – June 2024
Interest Rate Modeling and Derivative Pricing using the Hull-White Model
- Calibrated the Hull-White model parameters (mean-reversion rate and volatility) using historical interest rate data to simulate short-term interest rate paths.
- Implemented Monte Carlo simulations to forecast future interest rate scenarios and used these to price interest rate derivatives (Caps and Floors).
- Conducted scenario analysis by adjusting economic variables (volatility, mean reversion) to assess the impact on derivative pricing and market risks.
May 2024
Derivative Instruments and Their Features
- Investigated trading mechanisms and valuation models of futures and options, and developed sophisticated option trading strategies.
- Conducted three detailed case studies, providing an in-depth exploration of the Black-Scholes and Heston models.
Finlatics | Jun–Aug 2024
Optimizing Supertrend Parameters for Enhanced Profit
Framed an algorithm to optimize indicator parameters for maximizing profit gain using Bayesian Optimization techniques.
Advisor: Dr. Neelesh Upadhye, IIT Madras | Jan–May 2024
Optimizing Supertrend Parameters for Enhanced Sharpe Ratio
Developed algorithmic optimization framework using Grid Search Optimization techniques to improve Sharpe ratio performance.
Advisor: Dr. Neelesh Upadhye, IIT Madras | Jun–Dec 2023
Linear Algebra for Machine Learning and Data Science
Collaborative project exploring linear algebra’s practical applications in data science and autonomous systems, emphasizing the link between mathematical principles and technological advancements.
Advisor: Dr. Suguna, GACBE | Jun–Dec 2021
