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Explaining Anomalies in Australia with a Five†factor Asset Pricing Model

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  • Thanh D. Huynh

Abstract

This paper compares the ability of three†factor and five†factor asset pricing models to explain the apparent profitability of a broad selection of anomalies in Australian equity returns. Rather than examining the fit of each model to common test portfolios, our focus is on the spread return to long–short trading strategies designed around so†called anomalies. After documenting significant spread returns to 16 anomalies (including several not previously studied in Australia), the empirical analysis provides cautious support that the recently†proposed investment and profitability factors have a role to play. The number of anomalies that remains after risk adjustment decreases under the five†factor model. Further, while the magnitude of reduction in alpha is modest, our testing shows that it is statistically significant in many cases. However, both three†factor and five†factor models repeatedly fail the Gibbons, Ross, and Shanken's (1989) (GRS) test, suggesting that the quest for a better asset pricing model is not yet complete.

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  • Thanh D. Huynh, 2018. "Explaining Anomalies in Australia with a Five†factor Asset Pricing Model," International Review of Finance, International Review of Finance Ltd., vol. 18(1), pages 123-135, March.
    • Handle: RePEc:bla:irvfin:v:18:y:2018:i:1:p:123-135
    DOI: 10.1111/irfi.12125
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    Cited by:

    1. Li, Nanqi & Wei, Chishen & Zhang, Linti, 2023. "Risk factors in the Indonesian stock market," Pacific-Basin Finance Journal, Elsevier, vol. 82(C).
    2. Hoang, Khoa & Cannavan, Damien & Gaunt, Clive & Huang, Ronghong, 2019. "Is that factor just lucky? Australian evidence," Pacific-Basin Finance Journal, Elsevier, vol. 57(C).
    3. Mardy Chiah & Philip Gharghori & Angel Zhong, 2020. "Comovement in Anomalies between the Australian and US Equity Markets," International Review of Finance, International Review of Finance Ltd., vol. 20(4), pages 1005-1017, December.
    4. Shi, Yangyan & Feng, Yu & Zhang, Qi & Shuai, Jing & Niu, Jiangxin, 2023. "Does China's new energy vehicles supply chain stock market have risk spillovers? Evidence from raw material price effect on lithium batteries," Energy, Elsevier, vol. 262(PA).
    5. Xiaoyue Chen & Bin Li & Andrew C. Worthington, 2022. "Economic uncertainty and Australian stock returns," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 62(3), pages 3441-3474, September.
    6. Molero-González, L. & Trinidad-Segovia, J.E. & Sánchez-Granero, M.A. & García-Medina, A., 2023. "Market Beta is not dead: An approach from Random Matrix Theory," Finance Research Letters, Elsevier, vol. 55(PA).
    7. Ang, Tze Chuan 'Chewie' & Azad, A.S.M. Sohel & Pham, Thu A.T. & Zhong, Angel, 2021. "Firm efficiency and stock returns: Australian evidence," International Review of Financial Analysis, Elsevier, vol. 78(C).
    8. Kanis Saengchote, 2020. "Profitability, Investment and Asset Pricing: Reconciling the Valuation and the q-Theory Approaches in the Thai Stock Market," PIER Discussion Papers 124, Puey Ungphakorn Institute for Economic Research.
    9. Philipp Dirkx & Franziska J. Peter, 2020. "The Fama-French Five-Factor Model Plus Momentum: Evidence for the German Market," Schmalenbach Business Review, Springer;Schmalenbach-Gesellschaft, vol. 72(4), pages 661-684, October.
    10. Cakici, Nusret & Zaremba, Adam & Bianchi, Robert J. & Pham, Nga, 2021. "False discoveries in the anomaly research: New insights from the Stock Exchange of Melbourne (1927–1987)," Pacific-Basin Finance Journal, Elsevier, vol. 70(C).

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