Article Abstract:
New factor analysis tests developed for the arbitrage pricing theory (APT) emphasize the number of securities involved in the two stages of the APT, the number of factors that affect the pricing of the securities during both stages, and the stationarity of the APT (the model's explanation of returns realized, based on prior-period risks). The tests developed indicate that: (1) unique risk is as important in arbitrage pricing situations as is common risk, and (2) as the number of securities studied is increased, so does the number of factors affecting arbitrage pricing, which is inconsistent with the original APT. A discussion of the research presented argues that the tests developed do not refute the APT, but are useful when studying the stochastic behavior of securities' returns.
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Article Abstract:
This paper shows that the empirical tests of the Arbitrage Pricing Theory (APT) model are very sensitive to the anomalies observed in January in the stock returns data. There is a strong seasonal pattern in the estimates of the risk premia from the APT model. The most important implication of the findings in this paper is that the APT model can explain the risk-return relation mostly for January. Once the January returns are excluded from the data, there is no significant relation between the expected stock returns and the risk measures predicted by the APT model. (Reprinted by permission of the publisher.)
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Article Abstract:
The paper focuses on two countries, Japan and the U.S., to test the integration of capital markets. In Japan, the enactment of the Foreign Exchange and Foreign Trade Control Law in December of 1980 amounted to a true regime switch that virtually eliminated capital controls. Using multifactor asset pricing models, we show that the price of risk in the U.S. and Japanese stock markets was different before, but not after, the liberalization. This evidence supports the view that governments are the source of international capital market segmentation. (Reprinted by permission of the publisher.)
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