Kedar Khamkar

Quantitative finance with Topological Data Analysis

Started June 18, 2025

Abstract or project description

The student is pursuing an original research project that applies Topological Data Analysis (TDA) to financial market data, with the goal of uncovering structural or temporal patterns in stock price dynamics that traditional methods may overlook. Specifically, the project will focus on selecting a subset of stock tickers and transforming their historical price data into a format suitable for TDA techniques, such as persistent homology. By leveraging open-source Python packages (e.g., scikit-tda) and publicly available market datasets, the student aims to develop both exploratory visualizations and a set of quantitative insights. Ultimately, the project will culminate in a research paper that discusses prior literature, outlines the student’s unique methodology, and evaluates how TDA contributes to understanding market behavior. The student is also motivated by a desire to explore interdisciplinary applications of mathematics in finance, while learning new skills in data science, programming, and research writing.