IDEAS home Printed from https://ideas.repec.org/a/jfr/afr111/v8y2019i3p48.html
   My bibliography  Save this article

Price-Volume Granger Causality Tests in the Egyptian Stock Exchange (EGX)

Author

Listed:
  • Kobana Abukari
  • Tov Assogbavi

Abstract

Using weekly Egyptian stock exchange data on the 34 most active companies stretching from 2011 to 2017, this study finds that price changes Granger cause trading volume up to 8 weeks (lags), supporting the sequential information arrival model in the EGX. We also find a robust contemporaneously positive asymmetric relationship between price change and trading volume, confirming two well-documented characteristics of the price-volume relationship as well as two major adages of Wall Street- “it takes volume to move prices†and “volume in bull markets is heavier than volume in bear markets†. Overall, our results imply that although there is some sequential diffusion of information, the EGX’s efforts at improving its microstructure through initiatives such as the 2009 Presidential Degree on structure and governance, appear to have helped in improving instantaneous access to information – as exemplified by our evidence of strong contemporaneous positive price-volume relationship.

Suggested Citation

  • Kobana Abukari & Tov Assogbavi, 2019. "Price-Volume Granger Causality Tests in the Egyptian Stock Exchange (EGX)," Accounting and Finance Research, Sciedu Press, vol. 8(3), pages 1-48, August.
    • Handle: RePEc:jfr:afr111:v:8:y:2019:i:3:p:48
    as

    Download full text from publisher

    File URL: https://www.sciedupress.com/journal/index.php/afr/article/download/15620/9824
    Download Restriction: no
    File URL: https://www.sciedupress.com/journal/index.php/afr/article/view/15620
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Li, Haiqi & Zhong, Wanling & Park, Sung Y., 2016. "Generalized cross-spectral test for nonlinear Granger causality with applications to money–output and price–volume relations," Economic Modelling, Elsevier, vol. 52(PB), pages 661-671.
    2. Aravind Sampath & Parth Garg, 2019. "Contemporaneous and Causal Relationship between Returns and Volumes: Evidence from Nifty Futures," International Review of Finance, International Review of Finance Ltd., vol. 19(3), pages 653-664, September.
    3. Epps, Thomas W & Epps, Mary Lee, 1976. "The Stochastic Dependence of Security Price Changes and Transaction Volumes: Implications for the Mixture-of-Distributions Hypothesis," Econometrica, Econometric Society, vol. 44(2), pages 305-321, March.
    4. Wang, Zijun & Qian, Yan & Wang, Shiwen, 2018. "Dynamic trading volume and stock return relation: Does it hold out of sample?," International Review of Financial Analysis, Elsevier, vol. 58(C), pages 195-210.
    5. Mai Ahmed Abdelzaher, 2019. "The Impact of January Events on Stock Performance in the Egyptian Stock Market," Accounting and Finance Research, Sciedu Press, vol. 8(1), pages 174-174, February.
    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. Panpan Wang & Tsungwu Ho & Yishi Li, 2020. "The Price-Volume Relationship of the Shanghai Stock Index: Structural Change and the Threshold Effect of Volatility," Sustainability, MDPI, vol. 12(8), pages 1-17, April.
    2. Patel, Harihar & Guidi, Francesco, 2024. "The effect of the 2008–09 short selling sales ban on UK security equities in relation to market metrics of volatility, liquidity, and price discovery," Research in International Business and Finance, Elsevier, vol. 70(PA).
    3. Kao, Yu-Sheng & Zhao, Kai & Chuang, Hwei-Lin & Ku, Yu-Cheng, 2024. "The asymmetric relationships between the Bitcoin futures’ return, volatility, and trading volume," International Review of Economics & Finance, Elsevier, vol. 89(PA), pages 524-542.
    4. Harjoto, Maretno Agus & Rossi, Fabrizio & Lee, Robert & Sergi, Bruno S., 2021. "How do equity markets react to COVID-19? Evidence from emerging and developed countries," Journal of Economics and Business, Elsevier, vol. 115(C).
    5. Kapil Gupta & Balwinder Singh, 2009. "Information Memory and Pricing Efficiency of Futures Contracts," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 8(2), pages 191-250, May.
    6. Cornelis A. Los, 2004. "Nonparametric Efficiency Testing of Asian Stock Markets Using Weekly Data," Finance 0409033, University Library of Munich, Germany.
    7. Michelle B Graczyk & Sílvio M Duarte Queirós, 2017. "Intraday seasonalities and nonstationarity of trading volume in financial markets: Collective features," PLOS ONE, Public Library of Science, vol. 12(7), pages 1-23, July.
    8. Zou, Yongjie & Li, Honggang, 2014. "Time spans between price maxima and price minima in stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 395(C), pages 303-309.
    9. Do, Hung Xuan & Brooks, Robert & Treepongkaruna, Sirimon & Wu, Eliza, 2014. "How does trading volume affect financial return distributions?," International Review of Financial Analysis, Elsevier, vol. 35(C), pages 190-206.
    10. 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.
    11. Chan, Kam C. & Cheng, Louis T. W. & Lung, Peter P., 2003. "Moneyness and the response of the implied volatilities to price changes: The empirical evidence from HSI options," Pacific-Basin Finance Journal, Elsevier, vol. 11(4), pages 527-553, September.
    12. Karthigai Prakasam Chellaswamy & Natchimuthu N & Muhammadriyaj Faniband, 2021. "Stock Market Reforms and Stock Market Performance," International Journal of Financial Research, International Journal of Financial Research, Sciedu Press, vol. 12(2), pages 202-209, April.
    13. Markus Haas & Stefan Mittnik & Marc Paolella, 2006. "Modelling and predicting market risk with Laplace-Gaussian mixture distributions," Applied Financial Economics, Taylor & Francis Journals, vol. 16(15), pages 1145-1162.
    14. Li, Yifan & Nolte, Ingmar & Vasios, Michalis & Voev, Valeri & Xu, Qi, 2022. "Weighted Least Squares Realized Covariation Estimation," Journal of Banking & Finance, Elsevier, vol. 137(C).
    15. Rashmi Ranjan Paital & Naresh Kumar Sharma, 2016. "Bid-Ask Spreads, Trading Volume and Return Volatility: Intraday Evidence from Indian Stock Market," Eurasian Journal of Economics and Finance, Eurasian Publications, vol. 4(1), pages 24-40.
    16. Wei-Xing Zhou, 2012. "Universal price impact functions of individual trades in an order-driven market," Quantitative Finance, Taylor & Francis Journals, vol. 12(8), pages 1253-1263, June.
    17. Joocheol Kim, 2005. "An investigation of the relationship between bond market volatility and trading activities: Korea treasury bond futures market," Applied Economics Letters, Taylor & Francis Journals, vol. 12(11), pages 657-661.
    18. Wen-Ling Lin & Takatoshi Ito, 1994. "Price Volatility and Volume Spillovers between the Tokyo and New York Stock Markets," NBER Chapters, in: The Internationalization of Equity Markets, pages 309-343, National Bureau of Economic Research, Inc.
    19. Sangram K. Jena, 2016. "Sequential Information Arrival Hypothesis: More Evidence from the Indian Derivatives Market," Vision, , vol. 20(2), pages 101-110, June.
    20. Michael J. Fleming & Eli M. Remolona, 1997. "What moves the bond market?," Economic Policy Review, Federal Reserve Bank of New York, vol. 3(Dec), pages 31-50.

    More about this item

    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

    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:jfr:afr111:v:8:y:2019:i:3:p:48. 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: Sciedu Press (email available below). General contact details of provider: https://edirc.repec.org/data/cepflch.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.