IDEAS home Printed from https://ideas.repec.org/p/qmw/qmwecw/987.html
   My bibliography  Save this paper

Are Intraday Returns Autocorrelated?

Author

Listed:
  • Yufei Li

    (King's Business School, King's College London,)

  • Liudas Giraitis

    (School of Economics and Finance, Queen Mary University of London)

  • Genaro Sucarrat

    (BI Norwegian Business School)

Abstract

The presence of autocorrelated nancial returns has major implications for investment decisions.Unsurprisingly, therefore, numerous studies have sought to shed light on whether returns areautocorrelated or not, to what extent, and when. Standard tests for autocorrelation rely onthe assumption of strict stationarity of returns, possibly after a suitable transformation. Recentstudies, however, reveal that intraday nancial returns are often characterised by a subtle formof non-stationarity that cannot be transformed away, namely non-stationary periodicity in thezero-process. Here, we propose tests for autocorrelation that are valid under this (and otherforms) of non-stationarity. The tests are simple to implement, and well-sized and powerful asdocumented in our Monte Carlo simulations. Next, in a study of the intraday returns of stocksand exchange rates, our robust tests document that returns are rarely autocorrelated. This is insharp contrast to the standard benchmark test, which spuriously detects a substantial numberof autocorrelations. Moreover, stability analyses with our robust tests suggest the signi canceof the autocorrelations is short-lived and very erratic. So it is unclear whether the short-livedautocorrelations can be used to inform decision-making.

Suggested Citation

  • Yufei Li & Liudas Giraitis & Genaro Sucarrat, 2024. "Are Intraday Returns Autocorrelated?," Working Papers 987, Queen Mary University of London, School of Economics and Finance.
  • Handle: RePEc:qmw:qmwecw:987
    as

    Download full text from publisher

    File URL: https://www.qmul.ac.uk/sef/media/econ/research/workingpapers/2025/wp987.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Valentin Patilea & Hamdi Raïssi, 2024. "Powers Correlation Analysis of Returns with a Non-stationary Zero-Process," Journal of Financial Econometrics, Oxford University Press, vol. 22(5), pages 1345-1371.
    2. Gao, Lei & Han, Yufeng & Zhengzi Li, Sophia & Zhou, Guofu, 2018. "Market intraday momentum," Journal of Financial Economics, Elsevier, vol. 129(2), pages 394-414.
    3. Giraitis, Liudas & Li, Yufei & Phillips, Peter C.B., 2024. "Robust inference on correlation under general heterogeneity," Journal of Econometrics, Elsevier, vol. 240(1).
    4. Hong, Yongmiao, 1996. "Consistent Testing for Serial Correlation of Unknown Form," Econometrica, Econometric Society, vol. 64(4), pages 837-864, July.
    5. Vincent Bogousslavsky, 2016. "Infrequent Rebalancing, Return Autocorrelation, and Seasonality," Journal of Finance, American Finance Association, vol. 71(6), pages 2967-3006, December.
    6. Kolokolov, Aleksey & Livieri, Giulia & Pirino, Davide, 2020. "Statistical inferences for price staleness," Journal of Econometrics, Elsevier, vol. 218(1), pages 32-81.
    7. Christian Francq & Genaro Sucarrat, 2022. "Volatility Estimation When the Zero-Process is Nonstationary," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 41(1), pages 53-66, December.
    8. Li, Zeming & Sakkas, Athanasios & Urquhart, Andrew, 2022. "Intraday time series momentum: Global evidence and links to market characteristics," Journal of Financial Markets, Elsevier, vol. 57(C).
    9. Moskowitz, Tobias J. & Ooi, Yao Hua & Pedersen, Lasse Heje, 2012. "Time series momentum," Journal of Financial Economics, Elsevier, vol. 104(2), pages 228-250.
    10. Campbell, John Y. & Lo, Andrew W. & MacKinlay, A. Craig & Whitelaw, Robert F., 1998. "The Econometrics Of Financial Markets," Macroeconomic Dynamics, Cambridge University Press, vol. 2(4), pages 559-562, December.
    11. Ghysels,Eric & Osborn,Denise R., 2001. "The Econometric Analysis of Seasonal Time Series," Cambridge Books, Cambridge University Press, number 9780521565882, July.
    12. Francq, Christian & Roy, Roch & Zakoian, Jean-Michel, 2005. "Diagnostic Checking in ARMA Models With Uncorrelated Errors," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 532-544, June.
    13. Kian‐Ping Lim & Robert Brooks, 2011. "The Evolution Of Stock Market Efficiency Over Time: A Survey Of The Empirical Literature," Journal of Economic Surveys, Wiley Blackwell, vol. 25(1), pages 69-108, February.
    14. Giraitis, Liudas & Li, Yufei & Phillips, Peter C.B., 2024. "Reprint of: Robust inference on correlation under general heterogeneity," Journal of Econometrics, Elsevier, vol. 244(2).
    Full references (including those not matched with items on IDEAS)

    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. Yuan, Xianghui & Li, Xiang, 2022. "Delta-hedging demand and intraday momentum: Evidence from China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 600(C).
    2. Wen, Zhuzhu & Gong, Xu & Ma, Diandian & Xu, Yahua, 2021. "Intraday momentum and return predictability: Evidence from the crude oil market," Economic Modelling, Elsevier, vol. 95(C), pages 374-384.
    3. Carlo Rosa, 2022. "Understanding intraday momentum strategies," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(12), pages 2218-2234, December.
    4. Muzhao Jin & Fearghal Kearney & Youwei Li & Yung Chiang Yang, 2020. "Intraday time‐series momentum: Evidence from China," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(4), pages 632-650, April.
    5. Xu, Yahua & Bouri, Elie & Saeed, Tareq & Wen, Zhuzhu, 2020. "Intraday return predictability: Evidence from commodity ETFs and their related volatility indices," Resources Policy, Elsevier, vol. 69(C).
    6. Gao, Ya & Han, Xing & Li, Youwei & Xiong, Xiong, 2019. "Overnight momentum, informational shocks, and late informed trading in China," International Review of Financial Analysis, Elsevier, vol. 66(C).
    7. Li, Zeming & Sakkas, Athanasios & Urquhart, Andrew, 2022. "Intraday time series momentum: Global evidence and links to market characteristics," Journal of Financial Markets, Elsevier, vol. 57(C).
    8. Baltussen, Guido & Da, Zhi & Lammers, Sten & Martens, Martin, 2021. "Hedging demand and market intraday momentum," Journal of Financial Economics, Elsevier, vol. 142(1), pages 377-403.
    9. Zhang, Yaojie & Ma, Feng & Zhu, Bo, 2019. "Intraday momentum and stock return predictability: Evidence from China," Economic Modelling, Elsevier, vol. 76(C), pages 319-329.
    10. Zhang, Xianyang, 2016. "White noise testing and model diagnostic checking for functional time series," Journal of Econometrics, Elsevier, vol. 194(1), pages 76-95.
    11. Roberto Baragona & Francesco Battaglia & Domenico Cucina, 2022. "Data-driven portmanteau tests for time series," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 31(3), pages 675-698, September.
    12. Nankervis, John C. & Savin, N. E., 2010. "Testing for Serial Correlation: Generalized Andrews–Ploberger Tests," Journal of Business & Economic Statistics, American Statistical Association, vol. 28(2), pages 246-255.
    13. Bacchetta, Philippe & Davenport, Margaret & van Wincoop, Eric, 2022. "Can sticky portfolios explain international capital flows and asset prices?," Journal of International Economics, Elsevier, vol. 136(C).
    14. Yafeng Qin & Guoyao Pan & Min Bai, 2020. "Improving market timing of time series momentum in the Chinese stock market," Applied Economics, Taylor & Francis Journals, vol. 52(43), pages 4711-4725, September.
    15. Peress, Joël & Dong, Xi & KANG, NAMHO, 2020. "Fast and Slow Arbitrage: Fund Flows and Mispricing in the Frequency Domain," CEPR Discussion Papers 15235, C.E.P.R. Discussion Papers.
    16. Fiorentini, Gabriele & Sentana, Enrique, 2021. "New testing approaches for mean–variance predictability," Journal of Econometrics, Elsevier, vol. 222(1), pages 516-538.
    17. Pedro H. C. Sant’Anna, 2017. "Testing for Uncorrelated Residuals in Dynamic Count Models With an Application to Corporate Bankruptcy," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(3), pages 349-358, July.
    18. Li, Muyi & Zhang, Yanfen, 2022. "Bootstrapping multivariate portmanteau tests for vector autoregressive models with weak assumptions on errors," Computational Statistics & Data Analysis, Elsevier, vol. 165(C).
    19. Rui Fan & Oleksandr Talavera & Vu Tran, 2023. "Social media and price discovery: The case of cross‐listed firms," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 46(1), pages 151-167, February.
    20. Dinesh Gajurel & Biplob Chowdhury, 2021. "Realized Volatility, Jump and Beta: evidence from Canadian Stock Market," Applied Economics, Taylor & Francis Journals, vol. 53(55), pages 6376-6397, November.

    More about this item

    Keywords

    robust correlation testing; zero-process; non-stationary periodicity;
    All these keywords.

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:qmw:qmwecw:987. 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: Nicholas Owen The email address of this maintainer does not seem to be valid anymore. Please ask Nicholas Owen to update the entry or send us the correct address (email available below). General contact details of provider: https://edirc.repec.org/data/deqmwuk.html .

    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.