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1. Neural-Network-Approach-to-Implied-Volatility-Forecasting Neural-Network-Approach-to-Implied-Volatility-Forecasting Public

   Implied volatility is a key aspect when it comes to derivatives pricing. With the growing influence of machine learning in finance, I have investigated the use of LSTMs to forecast 1-day forward Im…

   Jupyter Notebook 5 4

2. Advanced-Simulation-Methods Advanced-Simulation-Methods Public

   This project focuses on applying advanced simulation methods for derivatives pricing. It includes Monte-Carlo, Variance Reduction Techniques, Distribution Sampling Methods, Euler Schemes, and Milst…

   Jupyter Notebook 1 2

3. Statistical-Arbitrage-Pairs-Trading-Strategy Statistical-Arbitrage-Pairs-Trading-Strategy Public

   On-going project: I will be implementing a combination of pairs trading strategies in attempt to see which type performs best after backtesting. The main ideas involve cointegration, kalman filter,…

   Jupyter Notebook 7 2

4. Portfolio-Optimization Portfolio-Optimization Public

   In Progress: We will investigate the common portfolio optimization methods and explore new ways to improve on this. We will start by building Minimum-Varance Portfolios, Maximum Sharpe Ratio portfo…

   Jupyter Notebook 1

5. Multi-Factor-Portfolios Multi-Factor-Portfolios Public

   University Project: constructing portfolios by blending different types of factor portfolios (low-beta, value, and momentum). We investigate different techniques to weight our portfolio and calcula…

   Jupyter Notebook 2 1

6. Loan-Default-Prediction Loan-Default-Prediction Public

   University Project: building a random forest to predict loan defaults. This involves data processing, standardization, optimization, performance metrics, and model analysis.

   Jupyter Notebook 1