This novel approach forecasts electoral outcomes in the 2024 U.S. presidential race, suggesting innovative market insights.
This paper presents a novel approach to forecasting U.S. presidential election outcomes by extracting market-implied probabilities from S&P 500 options prices. Leveraging a structural mixture model of Black–Scholes option pricing, I quantify the jump risk premium associated with electoral uncertainty, producing dynamic, risk-neutral probability estimates for Donald Trump's 2024 victory. The option-implied probabilities demonstrate remarkable stability and closely track winning chances observed in prediction markets and public opinion polls, while offering economically grounded signals that integrate both discrete electoral events and broader market risk.
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Sebastian M. Saiegh (2026) studied this question.
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