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Cross-Sectional Return Predictability in Taiwan Stock Exchange: An Empirical Investigation

Author

Listed:
  • Nusret Cakici

    (Fordham University, Graduate School of Business, 113 West 60th Street, New York, NY 10023, United States)

  • Kudret Topyan

    (Manhattan College, School of Business, Department of Economics and Finance, Manhattan College Parkway, Riverdale, NY 10471-4098, United States)

  • Chia-Jane Wang

    (Manhattan College, School of Business, Department of Economics and Finance, Manhattan College Parkway, Riverdale, NY 10471-4098, United States)

Abstract

This paper provides an analysis of the effectiveness of certain return predictors in Taiwan Stock Exchange (TWSE) from January 1990 to December 2011 by employing both portfolio method and cross-sectional regressions. While we found no statistically significant predictive power of beta, total volatility, and idiosyncratic volatility the two cheapness variables, book-to-market (BKMT) and cash-flow-to-price (FPR) ratios showed strong consistent economically and statistically significant predictive powers. In addition, our multiple regressions found predictive power in total volatility, short-term reversal (STREV), and market capitalization in the set ofsmallstocks, while ourallstock set showed predictive power only in total volatility and STREV.

Suggested Citation

  • Nusret Cakici & Kudret Topyan & Chia-Jane Wang, 2014. "Cross-Sectional Return Predictability in Taiwan Stock Exchange: An Empirical Investigation," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 17(02), pages 1-44.
    • Handle: RePEc:wsi:rpbfmp:v:17:y:2014:i:02:n:s0219091514500106
    DOI: 10.1142/S0219091514500106
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    Citations

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    Cited by:

    1. Robert J. Bianchi & Michael E. Drew & Timothy Whittaker, 2016. "The Predictive Performance of Asset Pricing Models: Evidence from the Australian Securities Exchange," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 19(04), pages 1-18, December.
    2. Nektarios Aslanidis & Charlotte Christiansen & Neophytos Lambertides & Christos S. Savva, 2019. "Idiosyncratic volatility puzzle: influence of macro-finance factors," Review of Quantitative Finance and Accounting, Springer, vol. 52(2), pages 381-401, February.
    3. Md. Saifur Rahman & Farihana Shahari, 2019. "Does the Financial Integration in ASEAN+3 Respond to Financial Cooperation Agreement and Influence the Real Sectors?," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 22(01), pages 1-18, March.
    4. Eero J. Pätäri & Timo H. Leivo & Janne Hulkkonen & J. V. Samuli Honkapuro, 2018. "Enhancement of value investing strategies based on financial statement variables: the German evidence," Review of Quantitative Finance and Accounting, Springer, vol. 51(3), pages 813-845, October.
    5. Ahmad Abu-Alkheil & Walayet A. Khan & Bhavik Parikh, 2020. "Risk-Reward Trade-Off and Volatility Performance of Islamic Versus Conventional Stock Indices: Global Evidence," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 23(01), pages 1-29, March.
    6. Bin Liu & Monica Tan & Marie-Anne Cam, 2019. "Reinvestigate the Bid–Ask Bounce Effect and Pricing of Idiosyncratic Volatility: The Case of the Australian Market," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 22(01), pages 1-23, March.

    More about this item

    Keywords

    Taiwan stock exchange; TWSE; stock return predictors; book-to-market ratio; momentum; stock cheapness; G10; G11; G12;
    All these keywords.

    JEL classification:

    • G1 - Financial Economics - - General Financial Markets
    • G2 - Financial Economics - - Financial Institutions and Services
    • G3 - Financial Economics - - Corporate Finance and Governance

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