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选民偏好的共同变动：超越民调的美国总统选举预测市场信息AI 解读

We propose a novel time-series econometric framework to forecast U.S. Presidential election outcomes in real time by combining polling data, economic fundamentals, and political prediction market prices. Our model estimates the joint dynamics of voter preferences across states. Applying our approach to the 2024 Presidential Election, we find a two-factor structure driving the vast majority of the variation in voter preferences. We identify electorally similar state clusters…

通胀预期的期限结构AI 解读

We use information in the term structure of survey-based forecasts of inflation to estimate a factor hidden in the nominal yield curve. We construct a model that accommodates forecasts over multiple horizons from multiple surveys and Treasury real and nominal yields by allowing for differences between risk-neutral, subjective, and objective probability measures. We establish that model-based inflation expectations are driven by inflation, output, and one latent factor. We…

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风险溢价在波动率预测中的作用AI 解读

I explain why at-the-money implied volatility is a biased and inefficient forecast of future realized volatility using the insights from the empirical option-pricing literature. First, I explain how the risk premia, which manifest themselves through disparity between objective and risk-neutral probability measures, lead to the disparity between realized and implied volatilities. Second, I show that this disparity is a function of the latent spot volatility, which I estimate…

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