Researcher ORCID Identifier

0009-0002-9907-882X

Graduation Year

2025

Date of Submission

4-2025

Document Type

Open Access Senior Thesis

Award

Robert Day School Prize for Best Senior Thesis in Finance

Degree Name

Bachelor of Arts

Department

Economics

Reader 1

Eric Hughson

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Rights Information

© 2025 Ivan Kolesnikov

Abstract

Traditional beta estimates are constructed from historical stock‑and‑market returns and therefore adjust only as fast as realized data accrue. This thesis investigates whether the forward‑looking information embedded in equity‑option prices can enhance beta forecasts. Using near‑end‑of‑day quotes for 236 S&P 500 firms between 2007 and 2024, I extract risk‑neutral variance and skewness, construct five alternative beta estimators (historical, option‑implied, and three hybrids), and evaluate them against realized betas over six‑, twelve‑, and twenty‑four‑month windows. Rolling‑OLS beta remains the most accurate benchmark at short horizons, yet option‑implied moments add economically and statistically significant value when systematic exposure is expected to change rapidly. In Utilities and Real Estate, a hybrid estimator that combines historical correlation with option‑implied volatilities reduces root‑mean‑square forecast error by roughly 10 percent at the two‑year horizon, and purely option‑based betas occasionally outperform the historical standard. In a simulation where true beta is known and the underlying assumptions for the Heston stochastic volatility model and the CAPM are satisfied, I show that the Chang et al. (2011) formula is upward-biased in theory because, contrary to their assumption, the skewness of the error term is not zero.

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