IDEAS home Printed from https://ideas.repec.org/a/jaf/journl/v16y2025i1n947.html

Volume-Returns Nexus in Emerging Gulf Markets

Author

Listed:
  • Ahlem NAJAH

Abstract

Purpose: The aim of this study is to examine the relationship between trading volume and stock returns in the Saudi Stock Exchange (Tadawul) and Dubai Financial Market (DFM) for 2018-2024. \n Method: Using a sample of 84 monthly observations for both markets from Investing.com, the research employs advanced econometric techniques, including cointegration analysis, linear regression, Granger causality testing, and Vector Autoregression (VAR) models. \n Results: Results exhibit a weak positive association between returns and trading volume in both markets, slightly more in Dubai. Cointegration tests identify a strong long-run equilibrium in the Saudi market, while Dubai displays several complex relationships prone to external impacts. Granger causality tests reveal no significant predictive causality in either direction, indicating that past values of returns and volume do not effectively forecast future movement. VAR analysis highlights that trading volumes are largely determined by their previous values. \n Originality: This study offers new insights into the dynamics of GCC markets by comparing the oil economy of Saudi Arabia with the diverse financial hub of Dubai. The findings challenge conventional volume-return models seen in developed economies, suggesting that regional structural forces dominate informational efficiency.

Suggested Citation

  • Ahlem NAJAH, 2025. "Volume-Returns Nexus in Emerging Gulf Markets," Journal of Academic Finance, RED research unit, university of Gabes, Tunisia, vol. 16(1), pages 36-51, June.
  • Handle: RePEc:jaf:journl:v:16:y:2025:i:1:n:947
    as

    Download full text from publisher

    File URL: https://www.scientific-society.com/AF/article/view/947
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Barberis, Nicholas & Shleifer, Andrei & Vishny, Robert, 1998. "A model of investor sentiment," Journal of Financial Economics, Elsevier, vol. 49(3), pages 307-343, September.
    2. Amihud, Yakov, 2002. "Illiquidity and stock returns: cross-section and time-series effects," Journal of Financial Markets, Elsevier, vol. 5(1), pages 31-56, January.
    3. Daouda Lawa tan Toe & Salifou Ouedraogo, 2022. "Dynamic relationship between trading volume, returns and returns volatility: an empirical investigation on the main African’s stock markets," Journal of Asset Management, Palgrave Macmillan, vol. 23(5), pages 429-444, September.
    4. Jean-Pierre Gueyie & Mouhamadou Saliou Diallo & Mamadou Fadel Diallo, 2022. "Relationship between Stock Returns and Trading Volume at the Bourse Régionale des Valeurs Mobilières, West Africa," IJFS, MDPI, vol. 10(4), pages 1-16, December.
    5. Joel Hasbrouck, 2009. "Trading Costs and Returns for U.S. Equities: Estimating Effective Costs from Daily Data," Journal of Finance, American Finance Association, vol. 64(3), pages 1445-1477, June.
    6. Malcolm Baker & Jeffrey Wurgler, 2007. "Investor Sentiment in the Stock Market," Journal of Economic Perspectives, American Economic Association, vol. 21(2), pages 129-152, Spring.
    7. Mamdouh Abdulaziz Saleh Al-Faryan & Everton Dockery, 2021. "Testing for efficiency in the Saudi stock market: does corporate governance change matter?," Review of Quantitative Finance and Accounting, Springer, vol. 57(1), pages 61-90, July.
    8. Jiayu Huang & Yifan Wang & Yaojun Fan & Hexuan Li, 2022. "Gauging the effect of investor overconfidence on trading volume from the perspective of the relationship between lagged stock returns and current trading volume," International Finance, Wiley Blackwell, vol. 25(1), pages 103-123, April.
    9. Fama, Eugene F. & French, Kenneth R., 1988. "Dividend yields and expected stock returns," Journal of Financial Economics, Elsevier, vol. 22(1), pages 3-25, October.
    10. Charles M.C. Lee & Bhaskaran Swaminathan, 2000. "Price Momentum and Trading Volume," Journal of Finance, American Finance Association, vol. 55(5), pages 2017-2069, October.
    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. Zhu, Zhaobo & Duan, Xinrui & Sun, Licheng & Tu, Jun, 2019. "Momentum and reversal: The role of short selling," Journal of Economic Dynamics and Control, Elsevier, vol. 104(C), pages 95-110.
    2. Qian, Xiaolin, 2014. "Small investor sentiment, differences of opinion and stock overvaluation," Journal of Financial Markets, Elsevier, vol. 19(C), pages 219-246.
    3. Finter, Philipp & Niessen-Ruenzi, Alexandra & Ruenzi, Stefan, 2010. "The impact of investor sentiment on the German stock market," CFR Working Papers 10-03, University of Cologne, Centre for Financial Research (CFR).
    4. Alexander Barinov, 2014. "Turnover: Liquidity or Uncertainty?," Management Science, INFORMS, vol. 60(10), pages 2478-2495, October.
    5. Stéphane Goutte & David Guerreiro & Bilel Sanhaji & Sophie Saglio & Julien Chevallier, 2019. "International Financial Markets," Post-Print halshs-02183053, HAL.
    6. Khasawneh, Maher & McMillan, David G. & Kambouroudis, Dimos, 2024. "Left-tail risk and UK stock return predictability: Underreaction, overreaction, and arbitrage difficulties," International Review of Financial Analysis, Elsevier, vol. 95(PA).
    7. Hou, Yang & Meng, Jiayin, 2018. "The momentum effect in the Chinese market and its relationship with the simultaneous and the lagged investor sentiment," MPRA Paper 94838, University Library of Munich, Germany.
    8. Hadhri, Sinda & Younus, Mehak & Naeem, Muhammad Abubakr & Yarovaya, Larisa, 2025. "Listening to the Market: Music sentiment and cryptocurrency returns," Journal of International Money and Finance, Elsevier, vol. 157(C).
    9. Alexander Barinov & Shawn Saeyeul Park & Çelim Yıldızhan, 2024. "Firm complexity and post-earnings announcement drift," Review of Accounting Studies, Springer, vol. 29(1), pages 527-579, March.
    10. Hao, Ying & Chou, Robin K. & Ko, Kuan-Cheng & Yang, Nien-Tzu, 2018. "The 52-week high, momentum, and investor sentiment," International Review of Financial Analysis, Elsevier, vol. 57(C), pages 167-183.
    11. Jorgensen, Bjorn & Li, Jing & Sadka, Gil, 2012. "Earnings dispersion and aggregate stock returns," Journal of Accounting and Economics, Elsevier, vol. 53(1), pages 1-20.
    12. Chen, Haozhi & Zhang, Yue, 2023. "Research on the effect of firm-specific investor sentiment on the idiosyncratic volatility anomaly: Evidence from the Chinese market," Pacific-Basin Finance Journal, Elsevier, vol. 81(C).
    13. Bashir, Hajam Abid & Kumar, Dilip, 2025. "Unveiling investor sentiment, attention, and speed of price adjustment in Indian market," International Review of Economics & Finance, Elsevier, vol. 101(C).
    14. Ramiah, Vikash & Xu, Xiaoming & Moosa, Imad A., 2015. "Neoclassical finance, behavioral finance and noise traders: A review and assessment of the literature," International Review of Financial Analysis, Elsevier, vol. 41(C), pages 89-100.
    15. Deven Bathia & Don Bredin & Dirk Nitzsche, 2016. "International Sentiment Spillovers in Equity Returns," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 21(4), pages 332-359, October.
    16. Smimou, K. & Khallouli, W., 2015. "Does the Euro affect the dynamic relation between stock market liquidity and the business cycle?," Emerging Markets Review, Elsevier, vol. 25(C), pages 125-153.
    17. Fernandez-Perez, Adrian & Fuertes, Ana-Maria & Gonzalez-Fernandez, Marcos & Miffre, Joelle, 2020. "Fear of hazards in commodity futures markets," Journal of Banking & Finance, Elsevier, vol. 119(C).
    18. Andrew Ang & Assaf A. Shtauber & Paul C. Tetlock, 2013. "Asset Pricing in the Dark: The Cross-Section of OTC Stocks," The Review of Financial Studies, Society for Financial Studies, vol. 26(12), pages 2985-3028.
    19. Qian, Meifen & Sun, Ping-Wen & Yu, Bin, 2017. "High turnover with high price delay? Dissecting the puzzling phenomenon for China's A-shares," Finance Research Letters, Elsevier, vol. 22(C), pages 105-113.
    20. Cui, Xudong & Gong, Pu & Liu, Tong, 2025. "The disposition effect and market volatility prediction," International Review of Financial Analysis, Elsevier, vol. 108(PB).

    More about this item

    JEL classification:

    • M1 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration
    • N8 - Economic History - - Micro-Business History
    • G3 - Financial Economics - - Corporate Finance and Governance

    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:jaf:journl:v:16:y:2025:i:1:n:947. 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: Oussama Quentin Kasseh (email available below). General contact details of provider: https://edirc.repec.org/data/urredtn.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.