Are Stock Returns Predictable? A Test Using Markov Chains
用马尔可夫链模型检验股票价格的随机游走假说，发现战后美国年度实际收益存在显著的非随机游走行为，即低收益往往跟随高收益的连续出现。
ABSTRACT This paper uses a Markov chain model to test the random walk hypothesis of stock prices. Given a time series of returns, a Markov chain is defined by letting one state represent high returns and the other represent low returns. The random walk hypothesis restricts the transition probabilities of the Markov chain to be equal irrespective of the prior years. Annual real returns are shown to exhibit significant nonrandom walk behavior in the sense that low (high) returns tend to follow runs of high (low) returns in the postwar period.