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股票与债券风险—收益权衡中的非线性与避险转移AI 解读

ABSTRACT We document a highly significant, strongly nonlinear dependence of stock and bond returns on past equity market volatility as measured by the VIX. We propose a new estimator for the shape of the nonlinear forecasting relationship that exploits variation in the cross‐section of returns. The nonlinearities are mirror images for stocks and bonds, revealing flight‐to‐safety: expected returns increase for stocks when volatility increases from moderate to high levels…

动态资产定价模型的回归估计AI 解读

We propose regression-based estimators for beta representations of dynamic asset pricing models with an affine pricing kernel specification. We allow for state variables that are cross-sectional pricing factors, forecasting variables for the price of risk, and factors that are both. The estimators explicitly allow for time-varying prices of risk, time-varying betas, and serially dependent pricing factors. Our approach nests the Fama-MacBeth two-pass estimator as a special…

用线性回归为利率期限结构定价AI 解读

We show how to price the time series and cross section of the term structure of interest rates using a three-step linear regression approach. Our method allows computationally fast estimation of term structure models with a large number of pricing factors. We present specification tests favoring a model using five principal components of yields as factors. We demonstrate that this model outperforms the Cochrane and Piazzesi (2008) four-factor specification in out-of-sample…