IDEAS home Printed from https://ideas.repec.org/a/gam/jrisks/v11y2023i12p215-d1297867.html
   My bibliography  Save this article

The Estimation of Risk Premia with Omitted Variable Bias: Evidence from China

Author

Listed:
  • Jie Mao

    (School of Economics, Shanghai University, No. 333 Nanchen Road Baoshan District, Shanghai 200444, China)

  • Tianliang Xia

    (School of Economics, Shanghai University, No. 333 Nanchen Road Baoshan District, Shanghai 200444, China)

Abstract

The Chinese stock market is replete with numerous omitted variables that can introduce biases in the standard estimation of risk premiums when traditional linear asset pricing models are applied. The three-pass method enables the estimation of risk premiums for observable factors even when not all relevant factors are explicitly specified or observed within the model. Accordingly, we have applied this method to construct portfolios with stocks from China’s A-share market as the test assets. Empirical research findings indicate that the three-pass method could be more effective than traditional linear asset pricing models in estimating risk premiums.

Suggested Citation

  • Jie Mao & Tianliang Xia, 2023. "The Estimation of Risk Premia with Omitted Variable Bias: Evidence from China," Risks, MDPI, vol. 11(12), pages 1-9, December.
  • Handle: RePEc:gam:jrisks:v:11:y:2023:i:12:p:215-:d:1297867
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-9091/11/12/215/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2227-9091/11/12/215/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Liu, Jianan & Stambaugh, Robert F. & Yuan, Yu, 2019. "Size and value in China," Journal of Financial Economics, Elsevier, vol. 134(1), pages 48-69.
    2. Johnson, Travis L. & So, Eric C., 2012. "The option to stock volume ratio and future returns," Journal of Financial Economics, Elsevier, vol. 106(2), pages 262-286.
    3. Thomas J. Chemmanur & An Yan, 2019. "Advertising, Attention, and Stock Returns," Quarterly Journal of Finance (QJF), World Scientific Publishing Co. Pte. Ltd., vol. 9(03), pages 1-51, September.
    4. Kang, Sang Hoon & Jiang, Zhuhua & Lee, Yeonjeong & Yoon, Seong-Min, 2010. "Weather effects on the returns and volatility of the Shanghai stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(1), pages 91-99.
    5. Jushan Bai, 2003. "Inferential Theory for Factor Models of Large Dimensions," Econometrica, Econometric Society, vol. 71(1), pages 135-171, January.
    6. Novy-Marx, Robert, 2014. "Predicting anomaly performance with politics, the weather, global warming, sunspots, and the stars," Journal of Financial Economics, Elsevier, vol. 112(2), pages 137-146.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Mao, Jie & Shao, Jingjing & Wang, Weiguan, 2025. "Risk premium principal components for the Chinese stock market," Pacific-Basin Finance Journal, Elsevier, vol. 89(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Kim, Jae H., 2017. "Stock returns and investors' mood: Good day sunshine or spurious correlation?," International Review of Financial Analysis, Elsevier, vol. 52(C), pages 94-103.
    2. LIN, Fengjiao & QIU, Zhigang & ZHENG, Weinan, 2023. "Cranes among chickens: The general-attention‐grabbing effect of daily price limits in China's stock market," Journal of Banking & Finance, Elsevier, vol. 150(C).
    3. Yin, Libo & Xin, Yu, 2024. "China's cognitive bias premium: An exploration of innovation information," International Review of Economics & Finance, Elsevier, vol. 96(PA).
    4. Bonhomme, Stphane & Robin, Jean-Marc, 2009. "Consistent noisy independent component analysis," Journal of Econometrics, Elsevier, vol. 149(1), pages 12-25, April.
    5. Claudio Morana, 2010. "Heteroskedastic Factor Vector Autoregressive Estimation of Persistent and Non Persistent Processes Subject to Structural Breaks," ICER Working Papers - Applied Mathematics Series 36-2010, ICER - International Centre for Economic Research.
    6. Eric Hillebrand & Huiyu Huang & Tae-Hwy Lee & Canlin Li, 2018. "Using the Entire Yield Curve in Forecasting Output and Inflation," Econometrics, MDPI, vol. 6(3), pages 1-27, August.
    7. Claudio Morana, 2014. "Factor Vector Autoregressive Estimation of Heteroskedastic Persistent and Non Persistent Processes Subject to Structural Breaks," Working Papers 273, University of Milano-Bicocca, Department of Economics, revised May 2014.
    8. Cem Ertur & Antonio Musolesi, 2017. "Weak and Strong Cross‐Sectional Dependence: A Panel Data Analysis of International Technology Diffusion," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(3), pages 477-503, April.
    9. Klaus Grobys & James W. Kolari & Jere Rutanen, 2022. "Factor momentum, option-implied volatility scaling, and investor sentiment," Journal of Asset Management, Palgrave Macmillan, vol. 23(2), pages 138-155, March.
    10. Chen, Qitong & Hong, Yongmiao & Li, Haiqi, 2024. "Time-varying forecast combination for factor-augmented regressions with smooth structural changes," Journal of Econometrics, Elsevier, vol. 240(1).
    11. Tomohiro Ando & Ruey S. Tsay, 2009. "Model selection for generalized linear models with factor‐augmented predictors," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 25(3), pages 207-235, May.
    12. Anastasiia Timofeeva, 2015. "On endogeneity of consumer expenditures in the estimation of households demand system," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 37(1), pages 87-106.
    13. Simplice A. Asongu & Nicholas M. Odhiambo, 2019. "Governance, capital flight and industrialisation in Africa," Journal of Economic Structures, Springer;Pan-Pacific Association of Input-Output Studies (PAPAIOS), vol. 8(1), pages 1-22, December.
    14. Huang, Jiexiang & Guo, Wei & Zhang, Jin E., 2020. "Do stocks outperform bank deposits in China?," Pacific-Basin Finance Journal, Elsevier, vol. 64(C).
    15. Yu, Qing & Hui, Eddie Chi-Man & Shen, Jianfu, 2024. "The real impacts of third-party certification on green bond issuances: Evidence from the Chinese green bond market," Journal of Corporate Finance, Elsevier, vol. 89(C).
    16. Matteo Barigozzi & Antonio M. Conti & Matteo Luciani, 2014. "Do Euro Area Countries Respond Asymmetrically to the Common Monetary Policy?," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 76(5), pages 693-714, October.
    17. Brian Du & Alejandro Serrano & Andre C. Vianna, 2024. "Are stock and option trades substitutes or complements? evidence from the 2008 short-sale ban," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 48(1), pages 166-185, March.
    18. Byron Botha & Rulof Burger & Kevin Kotzé & Neil Rankin & Daan Steenkamp, 2023. "Big data forecasting of South African inflation," Empirical Economics, Springer, vol. 65(1), pages 149-188, July.
    19. Bowen Fu & Mengheng Li & Qazi Haque, 2025. "Exchange Rates, Uncovered Interest Parity, and Time‐Varying Fama Regressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 40(3), pages 310-324, April.
    20. Gloria González‐Rivera & C. Vladimir Rodríguez‐Caballero & Esther Ruiz, 2024. "Expecting the unexpected: Stressed scenarios for economic growth," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(5), pages 926-942, August.

    More about this item

    Keywords

    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jrisks:v:11:y:2023:i:12:p:215-:d:1297867. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.