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多因子线性资产定价模型 GMM 估计中的效率与定价精度权衡AI 解读

Even though a multi-factor linear asset pricing model can be equivalently represented in a Beta or in a stochastic discount factor (SDF) form, its inferential efficiency and pricing accuracy features may differ when estimated by the generalized method of moments (GMM), both in small and in large samples. We derive the analytical asymptotic variance of the Beta and the SDF estimators under GMM and find that the SDF approach is likely to be less efficient but to yield more…

用马尔可夫转换图结构SUR模型刻画系统性风险AI 解读

We propose a Markov Switching Graphical Seemingly Unrelated Regression (MS-GSUR) model to investigate time-varying systemic risk based on a range of multi-factor asset pricing models. Methodologically, we develop a Markov Chain Monte Carlo (MCMC) scheme in which latent states are identified on the basis of a novel weighted eigenvector centrality measure. An empirical application to the constituents of the S&P100 index shows that cross-firm connectivity significantly…

宏观因子再显作用：美国资产横截面时变风险暴露与溢价的贝叶斯变点模型AI 解读

This article proposes a Bayesian estimation framework for a typical multi-factor model with time-varying risk exposures to macroeconomic risk factors and corresponding premia to price U.S. publicly traded assets. The model assumes that risk exposures and idiosyncratic volatility follow a break-point latent process, allowing for changes at any point on time but not restricting them to change at all points. The empirical application to 40 years of U.S. data and 23 portfolios…

不同计量设定下风险的期限结构AI 解读

This paper characterizes the term structure of risk measures such as value at risk (VaR) and expected shortfall under different econometric approaches including multivariate regime switching, GARCH-in-mean models with Student-t errors, two-component GARCH models and a nonparametric bootstrap. We show how to derive the risk measures for each of these models and document large variations in term structures across econometric specifications. An out-of-sample forecasting…

股票与债券收益联合分布非线性动态的计量模型AI 解读

Abstract This paper considers a variety of econometric models for the joint distribution of US stock and bond returns in the presence of regime switching dynamics. While simple two‐ or three‐state models capture the univariate dynamics in bond and stock returns, a more complicated four‐state model with regimes characterized as crash, slow growth, bull and recovery states is required to capture their joint distribution. The transition probability matrix of this model has a…