I am a passionate Quantitative Finance major with a keen interest in applying computational mathematics and finance to solve complex financial problems. My academic background and projects demonstrate a strong foundation in quantitative methods, financial modeling, and programming.
- Financial Modeling
- Risk Management
- Derivatives Pricing
- Statistical Analysis
- Machine Learning in Finance
- Programming Languages: Python, R, MATLAB
- Version Control: Git
This repository contains a collection of projects and code implementations related to various concepts in quantitative finance. Some of the key areas covered include, but not limited to:
-
Options Pricing Models
- Black-Scholes Model
- Monte Carlo Simulations
- Binomial Trees
-
Portfolio Optimization
- Markowitz Portfolio Theory
- Risk-Parity Portfolios
- Factor Models
-
Machine Learning in Finance
- Algorithmic Trading Strategies
- Credit Risk Assessment
- Market Sentiment Analysis
-
Risk Management
- Value at Risk (VaR) Calculations
- Expected Shortfall
- Stress Testing Models
Each project is contained in its own directory with a dedicated README file explaining the concept, methodology, and implementation details.
I am continuously working on expanding this repository with new projects and implementations. Some areas I'm looking to explore in the future include:
- High-Frequency Trading Algorithms
- Blockchain in Finance
- Advanced Deep Learning Models for Financial Forecasting
Feel free to reach out to me for collaborations or questions about my work in quantitative finance.
Harsh Parikh