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Important Factors of Estimated Return and Risk: The Taiwan Evidence

Department of Finance and Applications, Tamkang University, Taipei, Taiwan, R.O.C

Address for Correspondence: Kuang-Ping Ku, Department of Finance and Applications, Tamkang University, 5, Ln. 199, King-Hwa St., Taipei 106, Taiwan; An earlier draft of this paper was presented at the International Conference on e-Commerce in the 21st Century, Tamkang University, October 20–21, 2000. We are especially grateful to an anonymous referee for helpful comments and suggestions. We thank the National Science Council, Republic of China for financial support (NSC89-2416-H-032-007), and we would like to thank Hsin-Ying Tsai for assistance.

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William T. Lin

Department of Finance and Applications, Tamkang University, Taipei, Taiwan, R.O.C

An earlier draft of this paper was presented at the International Conference on e-Commerce in the 21st Century, Tamkang University, October 20–21, 2000. We are especially grateful to an anonymous referee for helpful comments and suggestions. We thank the National Science Council, Republic of China for financial support (NSC89-2416-H-032-007), and we would like to thank Hsin-Ying Tsai for assistance.

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https://doi.org/10.1142/S0219091502000675Cited by:0 (Source: Crossref)

Abstract

This paper seeks to identify which factors are important for estimating portfolio's expected return and standard deviation in the Taiwan stock market. We have summarized from the existing empirical literature a total of 26 factors that may have explanatory power. The results of our evaluation show that except for the trading volume, the remaining 25 factors do not seem to help explain the average stock returns during the July 1985–June 1999 period. However, the power of the trading volume to account for the expected returns on the stock is affected by any changes in the sample or by the use of a different evaluation model. We suggest three potential explanations of why all 26 factors show no stable power to explain average returns on Taiwan stocks: high volatility, selection bias, and market differences. Moreover, we find that all of the 26 factors are important in capturing the systematic covariation in stock returns.

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