IDEAS home Printed from https://ideas.repec.org/a/wly/complx/v2022y2022i1n2248731.html

Economic Policy Uncertainty and Sectoral Trading Volume in the U.S. Stock Market: Evidence from the COVID‐19 Crisis

Author

Listed:
  • Dohyun Pak
  • Sun-Yong Choi

Abstract

We empirically analyze the impact of economic uncertainty due to the COVID‐19 pandemic on the trading volume of each sector in the S&P 500 index. Wavelet coherence analysis is carried out using economic policy uncertainty data and the trading volume of each sector in the S&P 500 index from July 2004 to September 2020. Furthermore, we apply multifractal detrended fluctuation (MF‐DFA) analysis to the trading volume series of all sectors. The wavelet coherence analysis shows that the COVID‐19 pandemic has substantially influenced trading volume in all sectors. However, the impact of the pandemic is different from that during the global financial crisis in some sectors, such as information technology, consumer discretionary, and communication services. Because of the lockdown taken to suppress COVID‐19, increased remote working and remote learning are the main reasons for these results. Additionally, according to the MF‐DFA analysis, the trading volume of all the sectors has clear multifractal characteristics, and they are all nonpersistent. Specifically, trading volumes of the real estate and materials sector are highly correlated, whereas the trading volumes of industry and information technology sectors are comparatively less correlated.

Suggested Citation

  • Dohyun Pak & Sun-Yong Choi, 2022. "Economic Policy Uncertainty and Sectoral Trading Volume in the U.S. Stock Market: Evidence from the COVID‐19 Crisis," Complexity, John Wiley & Sons, vol. 2022(1).
  • Handle: RePEc:wly:complx:v:2022:y:2022:i:1:n:2248731
    DOI: 10.1155/2022/2248731
    as

    Download full text from publisher

    File URL: https://doi.org/10.1155/2022/2248731
    Download Restriction: no

    File URL: https://libkey.io/10.1155/2022/2248731?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
    ---><---

    References listed on IDEAS

    as
    1. Cai, Xiao Jing & Tian, Shuairu & Yuan, Nannan & Hamori, Shigeyuki, 2017. "Interdependence between oil and East Asian stock markets: Evidence from wavelet coherence analysis," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 48(C), pages 206-223.
    2. Demir, Ender & Gozgor, Giray & Lau, Chi Keung Marco & Vigne, Samuel A., 2018. "Does economic policy uncertainty predict the Bitcoin returns? An empirical investigation," Finance Research Letters, Elsevier, vol. 26(C), pages 145-149.
    3. Khuntia, Sashikanta & Pattanayak, J.K., 2020. "Adaptive long memory in volatility of intra-day bitcoin returns and the impact of trading volume," Finance Research Letters, Elsevier, vol. 32(C).
    4. Aguiar-Conraria, LuI´s & Joana Soares, Maria, 2011. "Business cycle synchronization and the Euro: A wavelet analysis," Journal of Macroeconomics, Elsevier, vol. 33(3), pages 477-489, September.
    5. Stanis{l}aw Dro.zd.z & Rafa{l} Kowalski & Pawe{l} O'swic{e}cimka & Rafa{l} Rak & Robert Gc{e}barowski, 2018. "Dynamical variety of shapes in financial multifractality," Papers 1809.06728, arXiv.org.
    6. Ko, Jun-Hyung & Lee, Chang-Min, 2015. "International economic policy uncertainty and stock prices: Wavelet approach," Economics Letters, Elsevier, vol. 134(C), pages 118-122.
    7. repec:idn:journl:v:21:y:2018:i:2:p:1-18 is not listed on IDEAS
    8. Tiwari, Aviral Kumar, 2013. "Oil prices and the macroeconomy reconsideration for Germany: Using continuous wavelet," Economic Modelling, Elsevier, vol. 30(C), pages 636-642.
    9. Jinliang Li & Chunchi Wu, 2006. "Daily Return Volatility, Bid-Ask Spreads, and Information Flow: Analyzing the Information Content of Volume," The Journal of Business, University of Chicago Press, vol. 79(5), pages 2697-2740, September.
    10. Fenghua Wen & Yupei Zhao & Minzhi Zhang & Chunyan Hu, 2019. "Forecasting realized volatility of crude oil futures with equity market uncertainty," Applied Economics, Taylor & Francis Journals, vol. 51(59), pages 6411-6427, December.
    11. Boudt, Kris & Petitjean, Mikael, 2014. "Intraday liquidity dynamics and news releases around price jumps: Evidence from the DJIA stocks," Journal of Financial Markets, Elsevier, vol. 17(C), pages 121-149.
    12. Rossi, Eduardo & Santucci de Magistris, Paolo, 2013. "Long memory and tail dependence in trading volume and volatility," Journal of Empirical Finance, Elsevier, vol. 22(C), pages 94-112.
    13. Chen, Gong-meng & Firth, Michael & Rui, Oliver M, 2001. "The Dynamic Relation between Stock Returns, Trading Volume, and Volatility," The Financial Review, Eastern Finance Association, vol. 36(3), pages 153-173, August.
    14. Liu, Li & Zhang, Tao, 2015. "Economic policy uncertainty and stock market volatility," Finance Research Letters, Elsevier, vol. 15(C), pages 99-105.
    15. Zied Ftiti & Fredj Jawadi & Waël Louhichi, 2017. "Modelling the relationship between future energy intraday volatility and trading volume with wavelet," Applied Economics, Taylor & Francis Journals, vol. 49(20), pages 1981-1993, April.
    16. Copeland, Thomas E, 1976. "A Model of Asset Trading under the Assumption of Sequential Information Arrival," Journal of Finance, American Finance Association, vol. 31(4), pages 1149-1168, September.
    17. Darolles, Serge & Fol, Gaëlle Le & Mero, Gulten, 2015. "Measuring the liquidity part of volume," Journal of Banking & Finance, Elsevier, vol. 50(C), pages 92-105.
    18. Stanisław Drożdż & Rafał Kowalski & Paweł Oświȩcimka & Rafał Rak & Robert Gȩbarowski, 2018. "Dynamical Variety of Shapes in Financial Multifractality," Complexity, Hindawi, vol. 2018, pages 1-13, September.
    19. Solikin M. Juhro & Dinh Hoang Bach Phan, 2018. "Can Economic Policy Uncertainty Predict Exchange Rate and Its Volatility? Evidence from Asean Countries," Bulletin of Monetary Economics and Banking, Bank Indonesia, vol. 21(2), pages 251-268, October.
    20. Cheng, Hui-Pei & Yen, Kuang-Chieh, 2020. "The relationship between the economic policy uncertainty and the cryptocurrency market," Finance Research Letters, Elsevier, vol. 35(C).
    21. Marcus Alexander Ong, 2015. "An information theoretic analysis of stock returns, volatility and trading volumes," Applied Economics, Taylor & Francis Journals, vol. 47(36), pages 3891-3906, August.
    22. Bartsch, Zachary, 2019. "Economic policy uncertainty and dollar-pound exchange rate return volatility," Journal of International Money and Finance, Elsevier, vol. 98(C), pages 1-1.
    23. Hanke, Michael & Kosolapova, Maria & Weissensteiner, Alex, 2020. "COVID-19 and market expectations: Evidence from option-implied densities," Economics Letters, Elsevier, vol. 195(C).
    24. Karpoff, Jonathan M., 1987. "The Relation between Price Changes and Trading Volume: A Survey," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 22(1), pages 109-126, March.
    25. T. Ane & L. Ureche-Rangau, 2008. "Does Trading Volume Really Explain Stock Returns Volatility ?," Post-Print hal-00260668, HAL.
    26. Kramer, Charles, 1999. "Noise trading, transaction costs, and the relationship of stock returns and trading volume," International Review of Economics & Finance, Elsevier, vol. 8(4), pages 343-362, November.
    27. Funashima, Yoshito, 2017. "Time-varying leads and lags across frequencies using a continuous wavelet transform approach," Economic Modelling, Elsevier, vol. 60(C), pages 24-28.
    28. Andrew J. Foster, 1995. "Volume‐volatility relationships for crude oil futures markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 15(8), pages 929-951, December.
    29. Ané, Thierry & Ureche-Rangau, Loredana, 2008. "Does trading volume really explain stock returns volatility?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 18(3), pages 216-235, July.
    30. Nagar, Venky & Schoenfeld, Jordan & Wellman, Laura, 2019. "The effect of economic policy uncertainty on investor information asymmetry and management disclosures," Journal of Accounting and Economics, Elsevier, vol. 67(1), pages 36-57.
    31. Flor, Michael A. & Klarl, Torben, 2017. "On the cyclicity of regional house prices: New evidence for U.S. metropolitan statistical areas," Journal of Economic Dynamics and Control, Elsevier, vol. 77(C), pages 134-156.
    32. Gagnon, Louis & Karolyi, G. Andrew, 2009. "Information, Trading Volume, and International Stock Return Comovements: Evidence from Cross-Listed Stocks," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 44(4), pages 953-986, August.
    33. Pal, Debdatta & Mitra, Subrata K., 2019. "Oil price and automobile stock return co-movement: A wavelet coherence analysis," Economic Modelling, Elsevier, vol. 76(C), pages 172-181.
    34. Li, Tao & Ma, Feng & Zhang, Xuehua & Zhang, Yaojie, 2020. "Economic policy uncertainty and the Chinese stock market volatility: Novel evidence," Economic Modelling, Elsevier, vol. 87(C), pages 24-33.
    35. Lee A. Smales, 2020. "Investor attention and the response of US stock market sectors to the COVID-19 crisis," Review of Behavioral Finance, Emerald Group Publishing Limited, vol. 13(1), pages 20-39, December.
    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. Yusri Yahya & Abdul Hafizh Mohd Azam & Zulkefly Abdul Karim & Mohd Azlan Shah Zaidi & Mohammad Bintang Pamuncak, 2026. "Does geopolitical risk influence foreign investors’ decisions in the stock market? An ARDL approach," Future Business Journal, Springer, vol. 12(1), pages 1-12, December.

    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. Choi, Sun-Yong, 2020. "Industry volatility and economic uncertainty due to the COVID-19 pandemic: Evidence from wavelet coherence analysis," Finance Research Letters, Elsevier, vol. 37(C).
    2. Fredj Jawadi & Waël Louhichi & Abdoulkarim Idi Cheffou & Rivo Randrianarivony, 2016. "Intraday jumps and trading volume: a nonlinear Tobit specification," Review of Quantitative Finance and Accounting, Springer, vol. 47(4), pages 1167-1186, November.
    3. Loredana Ureche-Rangau & Fabien Collado & Ulysse Galiay, 2011. "The dynamics of the volatility – trading volume relationship: New evidence from developed and emerging markets," Economics Bulletin, AccessEcon, vol. 31(3), pages 2569-2583.
    4. Yamani, Ehab, 2023. "Return–volume nexus in financial markets: A survey of research," Research in International Business and Finance, Elsevier, vol. 65(C).
    5. Kumar, Brajesh & Singh, Priyanka & Pandey, Ajay, 2009. "The Dynamic Relationship between Price and Trading Volume:Evidence from Indian Stock Market," IIMA Working Papers WP2009-12-04, Indian Institute of Management Ahmedabad, Research and Publication Department.
    6. Brajesh Kumar, 2010. "The Dynamic Relationship between Price and Trading Volume: Evidence from Indian Stock Market," Working Papers id:2379, eSocialSciences.
    7. Carroll, Rachael & Kearney, Colm, 2015. "Testing the mixture of distributions hypothesis on target stocks," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 39(C), pages 1-14.
    8. Jawadi Fredj & Ureche-Rangau Loredana, 2013. "Threshold linkages between volatility and trading volume: evidence from developed and emerging markets," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 17(3), pages 313-333, May.
    9. Alizadeh, Amir H. & Tamvakis, Michael, 2016. "Market conditions, trader types and price–volume relation in energy futures markets," Energy Economics, Elsevier, vol. 56(C), pages 134-149.
    10. Saswat Patra & Malay Bhattacharyya, 2021. "Does volume really matter? A risk management perspective using cross‐country evidence," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 118-135, January.
    11. Saumya Ranjan Dash & Debasish Maitra & Byomakesh Debata & Jitendra Mahakud, 2021. "Economic policy uncertainty and stock market liquidity: Evidence from G7 countries," International Review of Finance, International Review of Finance Ltd., vol. 21(2), pages 611-626, June.
    12. Cheng, Sheng & Zhang, Zongyou & Cao, Yan, 2022. "Can precious metals hedge geopolitical risk? Fresh sight using wavelet coherence analysis," Resources Policy, Elsevier, vol. 79(C).
    13. Jiranyakul, Komain, 2016. "Dynamic relationship between stock return, trading volume, and volatility in the Stock Exchange of Thailand: does the US subprime crisis matter?," MPRA Paper 73791, University Library of Munich, Germany.
    14. Navarro, Roberto Mota & Leyvraz, Francois & Larralde, Hernán, 2025. "Empirical properties of volume dynamics in the limit order book," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 658(C).
    15. João Martins, 2022. "Bond Yields Movement Similarities and Synchronization in the G7: A Time–Frequency Analysis," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 18(2), pages 189-214, July.
    16. Phan, Dinh Hoang Bach & Sharma, Susan Sunila & Narayan, Paresh Kumar, 2015. "Stock return forecasting: Some new evidence," International Review of Financial Analysis, Elsevier, vol. 40(C), pages 38-51.
    17. Abhinava Tripathi, 2021. "The Arrival of Information and Price Adjustment Across Extreme Quantiles: Global Evidence," IIM Kozhikode Society & Management Review, , vol. 10(1), pages 7-19, January.
    18. Ngo Thai Hung, 2021. "Directional Spillover Effects Between BRICS Stock Markets and Economic Policy Uncertainty," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 28(3), pages 429-448, September.
    19. Doojin RYU & Hyein SHIM, 2017. "Intraday Dynamics of Asset Returns, Trading Activities, and Implied Volatilities: A Trivariate GARCH Framework," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 45-61, June.
    20. Funashima Yoshito, 2021. "Time–Frequency Regression," Journal of Econometric Methods, De Gruyter, vol. 10(1), pages 21-32, January.

    More about this item

    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:wly:complx:v:2022:y:2022:i:1:n:2248731. 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: Wiley Content Delivery (email available below). General contact details of provider: https://onlinelibrary.wiley.com/journal/8503 .

    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.