The Ross recovery theorem shows that option data can reveal the market’s true (physical) expectations. We adapt this approach to international index options data (S&P, FTSE, CAC, SMI, and DAX) to improve volatility forecasting. We separate implied volatility into Ross-recovered expected volatility and a risk preference proxy. We investigate the performance of these variables, constructed domestically or globally, to forecast realized volatility as well as index excess returns. The results show evidence of significantly improved forecasts and yield new insights on the international dynamics of risk expectations and preferences. Across indexes, models using Ross-recovered, value-weighted global measures of risk preferences perform best. The findings suggest that the recovery theorem is empirically useful.

罗斯恢复定理表明，期权数据可以揭示市场的真实（实物）预期。我们将这种方法应用于国际指数期权数据（S&P、FTSE、CAC、SMI 和 DAX），以改进波动率预测。我们将隐含波动率分为罗斯恢复的预期波动率和风险偏好代理。我们调查这些在国内或全球构建的变量的表现，以预测已实现的波动性以及指数超额收益。结果显示了预测显着改善的证据，并对风险预期和偏好的国际动态产生了新的见解。在所有指数中，使用罗斯恢复的、价值加权的全球风险偏好度量的模型表现最好。研究结果表明，恢复定理在经验上是有用的。