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Constructing inverse factor volatility portfolios: A risk-based asset allocation for factor investing

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  • Shimizu, Hidehiko
  • Shiohama, Takayuki

Abstract

In this study, we investigate risk-based asset allocation approaches for factor investing strategies by constructing a multifactor portfolio based on the inverse weighting method. We propose the inverse factor volatility (IFV) strategy, which is the simplified variant of a factor risk parity, assuming constant factor correlation. In IFV portfolio construction, the portfolio's weights are determined by using scaled inverse factor volatility treated as a proxy for a targeted exposure in the optimization. Based on daily stock and index returns on global markets from 2002 to the end of 2017, we implemented the empirical analysis of IFV portfolios among three stock markets: Japan, Euro, and the US. The results obtained reveal that the IFV portfolios significantly outperformed market capitalization weighted portfolios by successfully acquiring factor risk premiums.

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  • Shimizu, Hidehiko & Shiohama, Takayuki, 2020. "Constructing inverse factor volatility portfolios: A risk-based asset allocation for factor investing," International Review of Financial Analysis, Elsevier, vol. 68(C).
    • Handle: RePEc:eee:finana:v:68:y:2020:i:c:s1057521919301371
    DOI: 10.1016/j.irfa.2019.101438
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    1. repec:dau:papers:123456789/4688 is not listed on IDEAS
    2. John H. Cochrane, 2011. "Presidential Address: Discount Rates," Journal of Finance, American Finance Association, vol. 66(4), pages 1047-1108, August.
    3. Hidehiko Shimizu & Takayuki Shiohama, 2019. "Multifactor Portfolio Construction by Factor Risk Parity Strategies: An Empirical Comparison of Global Stock Markets," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 26(4), pages 453-477, December.
    4. Fama, Eugene F. & French, Kenneth R., 2012. "Size, value, and momentum in international stock returns," Journal of Financial Economics, Elsevier, vol. 105(3), pages 457-472.
    5. Jeremiah Green & John R. M. Hand & X. Frank Zhang, 2017. "The Characteristics that Provide Independent Information about Average U.S. Monthly Stock Returns," The Review of Financial Studies, Society for Financial Studies, vol. 30(12), pages 4389-4436.
    6. Fama, Eugene F. & French, Kenneth R., 2015. "A five-factor asset pricing model," Journal of Financial Economics, Elsevier, vol. 116(1), pages 1-22.
    7. Keiichi Kubota & Hitoshi Takehara, 2018. "Does the Fama and French Five†Factor Model Work Well in Japan?," International Review of Finance, International Review of Finance Ltd., vol. 18(1), pages 137-146, March.
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    Cited by:

    1. Jung-Bin Su, 2020. "The Implementation of Asset Allocation Approaches: Theory and Evidence," Sustainability, MDPI, vol. 12(17), pages 1-28, September.
    2. Stefano Ferretti, 2023. "On the Modeling and Simulation of Portfolio Allocation Schemes: an Approach Based on Network Community Detection," Computational Economics, Springer;Society for Computational Economics, vol. 62(3), pages 969-1005, October.
    3. Li, Danyang & Zhang, Zhekai & Cerrato, Mario, 2023. "Factor investing and currency portfolio management," International Review of Financial Analysis, Elsevier, vol. 87(C).

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