IDEAS home Printed from https://ideas.repec.org/a/eee/intfin/v85y2023ics1042443123000501.html
   My bibliography  Save this article

Factor-timing in the Chinese factor zoo: The role of economic policy uncertainty

Author

Listed:
  • Li, Zhiyong
  • Wan, Yifan
  • Wang, Tianyi
  • Yu, Mei

Abstract

In this study, we investigate the predictive power of economic policy uncertainty (EPU) on factor returns in the Chinese market. We find that EPU can significantly but negatively predict the size premium (i.e., small-minus-big returns) at short and long horizons. However, such results are not evident in the prediction of 15 other characteristic-related factor returns, including the market, momentum, value, profitability, investment, and a range of mispricing or risk factors. The results are robust to various control variables and out-of-sample tests. Evidence further confirms that EPU can contribute to factor timing, especially size timing, in stark contrast with the evidence found in the US market. Economically, the cash flow and flight-to-safety channels may account for the predictive power of EPU.

Suggested Citation

  • Li, Zhiyong & Wan, Yifan & Wang, Tianyi & Yu, Mei, 2023. "Factor-timing in the Chinese factor zoo: The role of economic policy uncertainty," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 85(C).
  • Handle: RePEc:eee:intfin:v:85:y:2023:i:c:s1042443123000501
    DOI: 10.1016/j.intfin.2023.101782
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1042443123000501
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.intfin.2023.101782?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Ivo Welch & Amit Goyal, 2008. "A Comprehensive Look at The Empirical Performance of Equity Premium Prediction," The Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1455-1508, July.
    2. Lieven Baele & Geert Bekaert & Koen Inghelbrecht & Min Wei, 2020. "Flights to Safety," The Review of Financial Studies, Society for Financial Studies, vol. 33(2), pages 689-746.
    3. Marquering, Wessel & Verbeek, Marno, 2004. "The Economic Value of Predicting Stock Index Returns and Volatility," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 39(2), pages 407-429, June.
    4. Robert F. Stambaugh & Yu Yuan, 2017. "Mispricing Factors," The Review of Financial Studies, Society for Financial Studies, vol. 30(4), pages 1270-1315.
    5. Lubos Pástor & Pietro Veronesi, 2012. "Uncertainty about Government Policy and Stock Prices," Journal of Finance, American Finance Association, vol. 67(4), pages 1219-1264, August.
    6. Kent Daniel & David Hirshleifer & Lin Sun, 2020. "Short- and Long-Horizon Behavioral Factors," The Review of Financial Studies, Society for Financial Studies, vol. 33(4), pages 1673-1736.
    7. Joachim Freyberger & Andreas Neuhierl & Michael Weber & Andrew KarolyiEditor, 2020. "Dissecting Characteristics Nonparametrically," Review of Financial Studies, Society for Financial Studies, vol. 33(5), pages 2326-2377.
    8. Carhart, Mark M, 1997. "On Persistence in Mutual Fund Performance," Journal of Finance, American Finance Association, vol. 52(1), pages 57-82, March.
    9. Joseph Chen & Samuel Hanson & Harrison Hong & Jeremy C. Stein, 2008. "Do Hedge Funds Profit From Mutual-Fund Distress?," NBER Working Papers 13786, National Bureau of Economic Research, Inc.
    10. Scott R. Baker & Nicholas Bloom & Steven J. Davis, 2016. "Measuring Economic Policy Uncertainty," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 131(4), pages 1593-1636.
    11. Dai, Yiqing & Haque, Tariq & Zurbruegg, Ralf, 2020. "Factor return forecasting using cashflow spreads," International Review of Economics & Finance, Elsevier, vol. 69(C), pages 917-931.
    12. Clark, Todd E. & West, Kenneth D., 2007. "Approximately normal tests for equal predictive accuracy in nested models," Journal of Econometrics, Elsevier, vol. 138(1), pages 291-311, May.
    13. Berk, Jonathan B, 1995. "A Critique of Size-Related Anomalies," The Review of Financial Studies, Society for Financial Studies, vol. 8(2), pages 275-286.
    14. Christopher J. Neely & David E. Rapach & Jun Tu & Guofu Zhou, 2014. "Forecasting the Equity Risk Premium: The Role of Technical Indicators," Management Science, INFORMS, vol. 60(7), pages 1772-1791, July.
    15. Kent Daniel & David Hirshleifer & Lin Sun, 2020. "Short- and Long-Horizon Behavioral Factors," Review of Finance, European Finance Association, vol. 33(4), pages 1673-1736.
    16. Robin Greenwood & Samuel G. Hanson, 2012. "Share Issuance and Factor Timing," Journal of Finance, American Finance Association, vol. 67(2), pages 761-798, April.
    17. Lei Jiang & Jinyu Liu & Lin Peng & Baolian Wang, 2022. "Investor Attention and Asset Pricing Anomalies [Synchronization risk and delayed arbitrage]," Review of Finance, European Finance Association, vol. 26(3), pages 563-593.
    18. Jiang, Fuwei & Lee, Joshua & Martin, Xiumin & Zhou, Guofu, 2019. "Manager sentiment and stock returns," Journal of Financial Economics, Elsevier, vol. 132(1), pages 126-149.
    19. John Y. Campbell & Samuel B. Thompson, 2008. "Predicting Excess Stock Returns Out of Sample: Can Anything Beat the Historical Average?," The Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1509-1531, July.
    20. Kewei Hou & Chen Xue & Lu Zhang, 2015. "Editor's Choice Digesting Anomalies: An Investment Approach," The Review of Financial Studies, Society for Financial Studies, vol. 28(3), pages 650-705.
    21. Ali, Fahad & Ülkü, Numan, 2020. "Weekday seasonality of stock returns: The contrary case of China," Journal of Asian Economics, Elsevier, vol. 68(C).
    22. Ashiq Ali & Xuanjuan Chen & Tong Yao & Tong Yu, 2008. "Do Mutual Funds Profit from the Accruals Anomaly?," Journal of Accounting Research, Wiley Blackwell, vol. 46(1), pages 1-26, March.
    23. repec:bla:jfinan:v:59:y:2004:i:2:p:831-868 is not listed on IDEAS
    24. Li, Zhiyong & Rao, Xiao, 2022. "Evaluating asset pricing models: A revised factor model for China," Economic Modelling, Elsevier, vol. 116(C).
    25. Shefrin, Hersh & Statman, Meir, 1994. "Behavioral Capital Asset Pricing Theory," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 29(3), pages 323-349, September.
    26. Zakamulin, Valeriy, 2013. "Forecasting the size premium over different time horizons," Journal of Banking & Finance, Elsevier, vol. 37(3), pages 1061-1072.
    27. Hanauer, Matthias X. & Lauterbach, Jochim G., 2019. "The cross-section of emerging market stock returns," Emerging Markets Review, Elsevier, vol. 38(C), pages 265-286.
    28. Fahiz Baba Yara & Martijn Boons & Andrea Tamoni, 2021. "Value Return Predictability across Asset Classes and Commonalities in Risk Premia [Financial intermediaries and the cross-section of asset returns]," Review of Finance, European Finance Association, vol. 25(2), pages 449-484.
    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. Jinghua Wang & Geoffrey M. Ngene & Yan Shi & Ann Nduati Mungai, 2023. "An Investigation of the Predictability of Uncertainty Indices on Bitcoin Returns," JRFM, MDPI, vol. 16(10), pages 1-12, October.

    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. Xue Gong & Weiguo Zhang & Yuan Zhao & Xin Ye, 2023. "Forecasting stock volatility with a large set of predictors: A new forecast combination method," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(7), pages 1622-1647, November.
    2. Fabian Hollstein & Marcel Prokopczuk, 2023. "Managing the Market Portfolio," Management Science, INFORMS, vol. 69(6), pages 3675-3696, June.
    3. Hansen, Erwin, 2022. "Economic evaluation of asset pricing models under predictability," Journal of Empirical Finance, Elsevier, vol. 68(C), pages 50-66.
    4. Long, Huaigang & Chiah, Mardy & Zaremba, Adam & Umar, Zaghum, 2024. "Changes in shares outstanding and country stock returns around the world," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 90(C).
    5. Long, Huaigang & Zaremba, Adam & Zhou, Wenyu & Bouri, Elie, 2022. "Macroeconomics matter: Leading economic indicators and the cross-section of global stock returns," Journal of Financial Markets, Elsevier, vol. 61(C).
    6. Huang, Yisu & Ma, Feng & Bouri, Elie & Huang, Dengshi, 2023. "A comprehensive investigation on the predictive power of economic policy uncertainty from non-U.S. countries for U.S. stock market returns," International Review of Financial Analysis, Elsevier, vol. 87(C).
    7. Ma, Feng & Liu, Jing & Wahab, M.I.M. & Zhang, Yaojie, 2018. "Forecasting the aggregate oil price volatility in a data-rich environment," Economic Modelling, Elsevier, vol. 72(C), pages 320-332.
    8. Phan, Dinh Hoang Bach & Sharma, Susan Sunila & Tran, Vuong Thao, 2018. "Can economic policy uncertainty predict stock returns? Global evidence," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 55(C), pages 134-150.
    9. Qiu, Rui & Liu, Jing & Li, Yan, 2023. "Long-term adjusted volatility: Powerful capability in forecasting stock market returns," International Review of Financial Analysis, Elsevier, vol. 86(C).
    10. He, Mengxi & Zhang, Yaojie, 2022. "Climate policy uncertainty and the stock return predictability of the oil industry," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 81(C).
    11. Nusret Cakici & Christian Fieberg & Daniel Metko & Adam Zaremba, 2024. "Do Anomalies Really Predict Market Returns? New Data and New Evidence," Review of Finance, European Finance Association, vol. 28(1), pages 1-44.
    12. Xu, Yongan & Wang, Jianqiong & Chen, Zhonglu & Liang, Chao, 2021. "Economic policy uncertainty and stock market returns: New evidence," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    13. Li, Yan & Huo, Jiale & Xu, Yongan & Liang, Chao, 2023. "Belief-based momentum indicator and stock market return predictability," Research in International Business and Finance, Elsevier, vol. 64(C).
    14. Ma, Feng & Guo, Yangli & Chevallier, Julien & Huang, Dengshi, 2022. "Macroeconomic attention, economic policy uncertainty, and stock volatility predictability," International Review of Financial Analysis, Elsevier, vol. 84(C).
    15. Jonathan A. Batten & Harald Kinateder & Niklas Wagner, 2022. "Beating the Average: Equity Premium Variations, Uncertainty, and Liquidity," Abacus, Accounting Foundation, University of Sydney, vol. 58(3), pages 567-588, September.
    16. Shi, Qi & Li, Bin, 2022. "Further evidence on financial information and economic activity forecasts in the United States," The North American Journal of Economics and Finance, Elsevier, vol. 60(C).
    17. Söhnke M. Bartram & Harald Lohre & Peter F. Pope & Ananthalakshmi Ranganathan, 2021. "Navigating the factor zoo around the world: an institutional investor perspective," Journal of Business Economics, Springer, vol. 91(5), pages 655-703, July.
    18. Chen, Juan & Ma, Feng & Qiu, Xuemei & Li, Tao, 2023. "The role of categorical EPU indices in predicting stock-market returns," International Review of Economics & Finance, Elsevier, vol. 87(C), pages 365-378.
    19. Xu, Yongan & Liang, Chao & Li, Yan & Huynh, Toan L.D., 2022. "News sentiment and stock return: Evidence from managers’ news coverages," Finance Research Letters, Elsevier, vol. 48(C).
    20. Dunbar, Kwamie, 2021. "Pricing the hedging factor in the cross-section of stock returns," The North American Journal of Economics and Finance, Elsevier, vol. 56(C).

    More about this item

    Keywords

    Economic policy uncertainty; Size premium; Factor timing;
    All these keywords.

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

    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:eee:intfin:v:85:y:2023:i:c:s1042443123000501. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/intfin .

    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.