Projects

Explores the use of financial technical indicators to analyze market trends and predict asset price movements.

Implements a statistical arbitrage strategy by identifying and trading pairs of correlated assets.

Focuses on optimizing portfolio allocation using Markowitz's Modern Portfolio Theory. The project balances risk and return by creating efficient frontiers based on asset data.

Applies Markov Chain models to predict stock price movements and analyze market dynamics. The project uses probabilistic techniques to explore financial transitions over time.

Simulates a market-making strategy to provide liquidity in financial markets. This project delves into bid-ask spreads, order book dynamics, and profitability analysis.

Explores the use of deep learning models to analyze financial data. The project leverages neural networks for tasks such as price prediction, sentiment analysis, and algorithmic trading.