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Dynamic factors and asset pricing: International and further U.S. evidence

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  • He, Zhongzhi (Lawrence)
  • Zhu, Jie
  • Zhu, Xiaoneng

Abstract

The Fama–French pricing model with dynamic factors (DFPM) extracted via the Kalman filter from the six size and book-to-market portfolios has a good performance in understanding stock returns. Using international stock market data, we find that the DFPM significantly improves the cross-sectional explanatory power of the Fama–French three-factor model. In the out-of-sample exercise, we find that the DFPM predicts portfolio returns more accurately than other competing models. The good forecasting performance of the DFPM is economically meaningful because the DFPM generally delivers significant utility gains in asset allocation.

Suggested Citation

  • He, Zhongzhi (Lawrence) & Zhu, Jie & Zhu, Xiaoneng, 2015. "Dynamic factors and asset pricing: International and further U.S. evidence," Pacific-Basin Finance Journal, Elsevier, vol. 32(C), pages 21-39.
    • Handle: RePEc:eee:pacfin:v:32:y:2015:i:c:p:21-39
    DOI: 10.1016/j.pacfin.2015.02.002
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    Cited by:

    1. He, Zhongzhi (Lawrence) & Zhu, Jie & Zhu, Xiaoneng, 2015. "Multi-factor volatility and stock returns," Journal of Banking & Finance, Elsevier, vol. 61(S2), pages 132-149.
    2. Chen, Junping & Xiong, Xiong & Zhu, Jie & Zhu, Xiaoneng, 2017. "Asset prices and economic fluctuations: The implications of stochastic volatility," Economic Modelling, Elsevier, vol. 64(C), pages 128-140.
    3. Jiang, Minqi & Liu, Jiapeng & Zhang, Lu, 2021. "An extended regularized Kalman filter based on Genetic Algorithm: Application to dynamic asset pricing models," The Quarterly Review of Economics and Finance, Elsevier, vol. 79(C), pages 28-44.
    4. Amendola, Alessandra & Candila, Vincenzo & Gallo, Giampiero M., 2019. "On the asymmetric impact of macro–variables on volatility," Economic Modelling, Elsevier, vol. 76(C), pages 135-152.
    5. Yao, Haixiang & Xia, Shenghao & Liu, Hao, 2022. "Six-factor asset pricing and portfolio investment via deep learning: Evidence from Chinese stock market," Pacific-Basin Finance Journal, Elsevier, vol. 76(C).

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    More about this item

    Keywords

    International stock markets; Cross-sectional returns; Out-of-sample predictability; Asset allocation;
    All these keywords.

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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