Nonnormalities and tests of asset pricing theories
Article Abstract:
The robustness of the multivariate test of Gibbons, Ross, and Shanken (1986) to nonnormalities in the residual covariance mix is examined. After considering the relative performance of various tests of normality, simulation techniques are used to determine the effects of nonnormalities on the multivariate test. It is found that, where the sample nonnormalities are severe, the size and/or power of the test can be seriously misstated. However, it is also shown that these extreme sample values may overestimate the population parameters. Hence,we conclude that the multivariate test is reasonably robust with respect to typical levels of nonnormality. (Reprinted by permission of the publisher.)
Publication Name: Journal of Finance
Subject: Business
ISSN: 0022-1082
Year: 1989
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Are stock returns predictable? A test using Markov chains
Article 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. (Reprinted by permission of the publisher.)
Publication Name: Journal of Finance
Subject: Business
ISSN: 0022-1082
Year: 1991
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