This repository showcases my journey through the prestigious Executive Program in Algorithmic Trading (EPAT), a globally recognized certification program offered by QuantInsti. EPAT focuses on empowering professionals with the knowledge and skills required to excel in the field of algorithmic and quantitative trading.
EPAT is a comprehensive program designed for individuals aiming to specialize in financial markets, data analysis, and quantitative strategies. The program combines cutting-edge tools, theoretical foundations, and practical applications across various domains of trading and quantitative finance. It covers:
- Programming and Data Analysis: Python, R, Excel, and other essential tools for financial data modeling.
- Mathematical and Statistical Techniques: Probability, regression, time-series analysis, and machine learning for strategy building.
- Algorithmic Trading Strategies: Momentum, mean-reversion, statistical arbitrage, and options trading.
- Risk Management and Execution: Techniques for portfolio optimization, risk control, and market impact minimization.
- Market Microstructure: Understanding trading systems, order types, and high-frequency trading dynamics.
This repository contains projects I have completed during the program, guided by the EPAT curriculum. It is a demonstration of the practical application of the knowledge gained, covering topics such as:
- Quantitative finance concepts
- Algorithmic strategy development
- Backtesting and optimization techniques
- Risk assessment and portfolio management
The repository is a work-in-progress as I continue to refine and add new projects while progressing through the EPAT program. Each project reflects the use of real-world tools, industry-best practices, and advanced financial modeling techniques.