limits-to-arbitrage/llm-foundry

Overview

Hedge fund analyst and consultant; CFA/CPA. Long and (mostly) short equity.

I am currently working on systematic, equity market-neutral strategies using fundamental signals while back in school for more mathematics coursework. After getting degrees in finance/accounting, and working as a traditional long/short equity hedge fund analyst, I decided to formally study mathematics and statistics to inch closer to systematic trading/investing. I've professionally traded traditional IPOs, alternative IPOs, SPACs, accounting frauds, distressed equities, bankruptcies, stock promotions, etc., for hedge funds.

Outside of project repos, I also log random finance posts and random general posts. Most recently on:

• Random finance posts: I posted a simple derivation of the duration of a growing perpetuity, as I'd yet to see one readily online.
• Random general posts: I posted a step-by-step derivation of OLS estimates for simple linear regression for those interested (e.g., students in ML courses or certifications).

I am always interested in collaborating on systematic strategies, empirical finance work (I wrote a paper with a former professor of mine on SPACs recently), or any interesting data project!

Please don't hesitate to reach out:

Details

Languages and tools:

Python and Python data science stack (e.g., pandas, NumPy, matplotlib) | Familiar with C++, R, SQL, webscraping with Selenium and Beautiful Soup

Mathematics coursework:

My degrees are in finance/accounting, but I elected to take the following university mathematics coursework:

• Calculus I
• Calculus II
• Multivariable calculus
• Linear algebra and vector geometry
• Differential equations I (ODE)
• Discrete mathematics (proof writing)
• Applied statistics
• Real analysis I
• Abstract algebra I
• Differential equations II (PDE)
• Probability

Working on:

• Working papers / works in progress:
  • Do SPACs Create Value, co-authored with Dr. Mattia Landoni and presented to the Federal Reserve Bank of Boston, examines the drivers of cumulative post-merger abnormal SPAC returns. A model is proposed to quantify the amount by which underperformance is driven by "dilution" versus "value destruction". Uses hand-collected data set from original SPAC merger presentations and presents results in a cohort-based event study. Unlike other SPAC return studies, I merge a data set of daily stock loan rates to estimate a truer measure of short-and-hold returns, leading to a discussion of practical constraints faced by would-be arbitrageurs.