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Academic Sidequests

On January 27, 2025, my friend Aadil invited me to join him in competing at the Bay Area Decision Science Summit, an industrial engineering case competition. Although I wasn't fully aware of what this entailed, I accepted, trusting that sometimes embracing uncertainty leads to rewarding experiences.

The challenge we received was to develop and implement an options trading strategy aimed at minimizing premium costs while maintaining a daily exposure of at least $10 million. Going into this, I had minimal knowledge of options trading or related optimization techniques, and only two weeks to formulate a competitive strategy.

To bridge my knowledge gap, I began reading "Option Volatility and Pricing" by McGraw Hill, quickly acquainting myself with essential trading terminology. Further exploration led me to Mixed Integer Linear Programming approaches, prompting me to study convex optimization methods in greater depth to establish effective formulations. Ultimately, we crafted a robust trading strategy that consistently met the exposure requirement and minimized premium costs, securing second place in the competition.

Super grateful for the opportunity and this very practical introduction to linear programming. Thank you to professor Kerger and my team for the support. If you're interested in checking out our work, just click the button below!

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