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Certificate of Completion

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THIS ACKNOWLEDGES THAT

HAS COMPLETED THE FALL 2023 DATA SCIENCE BOOT CAMP

Yiyang Liu

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Roman Holowinsky, PhD

DECEMBER 07, 2023

DIRECTOR

DATE

TEAM

Volatility Surface Estimation

Amey Kaloti, Dushyanth Sirivolu, Ergun Kacar, Yiyang Liu, Martin Molina-Fructuoso

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In stock trading, one wants to have an estimate on the future volatility of the stock. Options on a stock are hedging instruments which derive their values from the stock price. Option prices depend on various parameters, but the most important being the stock price, time to expiry and the volatility of the stock. By the mathematical theory behind option pricing, option prices on the stock imply market participants current view of the future volatility. So in theory if one had option prices for a continuum of stock prices and the expiry times, one can get a good estimate of future volatility. Options are only available for a discrete set of stock values and finite set of expiry dates. So traders have to estimate the volatility values for the missing stock values and the expiry dates. Standard practices in financial institutions have been to use interpolation. The project will involve estimating the volatility surface for a given stock using machine learning.

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