A Markov Model of Heteroskedasticity, Risk, and Learning in the Stock Market
提出一个模型，用一阶马尔可夫过程描述股票超额收益的方差变化，估计了投资者已知或未知状态时的风险溢价，发现风险溢价随收益方差上升而下降。
Risk prenila in t lie stock titarket are assumed to move svitlm ti ume varying risk. We present a model in which the variance of time excess return of a portfolio depends ott a state variable generated by a first—order Markov process. A model in which the realization of the state is knosvn to economic agents, hut uuknosvn to the econometrician. is estimimated. 'l'lme paraumeter estimates are found to iimmply that time risk premium declines as time variance of returns rises. We then extend the nmodel to allosc agents to he uncertain about time state. Agents make their decisions in tseriod I using a prior distribution of time state based only on past realizations of the excess return t hrouglm period / — I plus knowledge of the structure of the model. TIse paraisseter estimates from this imsodel are consistent witis asset pricing theory.