Portfolio

Technologies Used: Bloomberg Terminal, Excel, Python (NumPy/Pandas)

I created and backtested a VC2-based trading algorithm, which currently manages $25k in assets. The VC2 is a relative valuation strategy that routinely purchases top securities in the S&P 500 based on weighing fundamental ratios. I instrumented a 10-year backtest demonstrating a 21.36% annualized return on investment and 1.31 Sharpe, along with a volatility of 16.33%. I also engineered a Monte Carlo simulation to predict a future return distribution of the strategy versus the S&P500TR, which achieved outperformance of 64.4%. This was the first algorithmic strategy given an allocation in the GTSF Investment Committee's history.
Here is the presentation of the strategy.

Technologies Used: Python (OpenAI, Streamlit)

This project is referenced on my resume as an "LLM Event Planning Web Application". It basically cooks up super cheesy emoji-filled event invite messages using the ChatGPT-3.5 API. There is a simple interface that allows the user to enter their API key and curate some of the invite details. The GitHub is private, but I'll potentially add more juicy details to this here at a later time.