Market Efficiency of the Next 11 Countries’ Stock Markets: Evidences From the Price–Volume Relationship

Year 2025, Volume: 13 Issue: 3, 392 - 404, 30.11.2025

Gökhan Berk Özbek

https://doi.org/10.22139/jobs.1672385

Abstract

The Efficient Market Hypothesis (EMH), first proposed by Eugene Fama, has been the subject of numerous academic studies since its inception. Market efficiency holds great significance for ensuring accurate pricing mechanisms and reducing information asymmetry among economic units. This, in turn, can create a domino effect by enhancing investor confidence, thereby enabling the financial system to operate more efficiently. This study investigates the efficiency of stock markets in Next 11 countries within the context of the price-volume relationship. To this end, benchmark indices representing the stock markets of the relevant countries have been utilized. The study covers the year 2024 and analyzes data at 30-minute intervals. The causal relationship between price and volume data of the indices was examined using the Toda-Yamamoto test. According to the research findings, a causality from volume to price was identified for the benchmark indices of the Philippines and Vietnam, whereas a causality from price to volume was observed for the benchmark indices of Egypt and South Korea. For the benchmark index of Türkiye, a bidirectional relationship was found. These results particularly provide evidence regarding the efficiency of stock markets in the Philippines and Vietnam.

Keywords

Next 11 , Market Efficiency , Price , Volume , Toda-Yamamoto

References

• Abinaya, P., Kumar, V. S., Balasubramanian, P., & Menon, V. K. (2016, September). Measuring stock price and trading volume causality among Nifty50 stocks: The Toda Yamamoto method. In 2016 International Conference on Advances in Computing, Communications and Informatics (ICACCI) (pp. 1886-1890). IEEE.
• Akbar, M., Ullah, I., Ali, S., & Rehman, N. (2024). Adaptive market hypothesis: A comparison of Islamic and conventional stock indices. International Review of Economics & Finance, 89, 460-477. https://doi.org/10.1016/j.iref.2023.06.020
• Alkan, S. (2023). Multi-scale sample entropy analysis of the Turkish stock market efficiency. Nicel Bilimler Dergisi, 5(1), 51-63. https://doi.org/10.51541/nicel.1191317
• Balcilar, M., Bouri, E., Gupta, R., & Roubaud, D. (2017). Can volume predict Bitcoin returns and volatility? A quantiles-based approach. Economic Modelling, 64, 74-81. https://doi.org/10.1016/j.econmod.2017.03.019
• Ball, R. (2009). The global financial crisis and the efficient market hypothesis: What have we learned? Journal of Applied Corporate Finance, 21(4), 8-16. https://doi.org/10.1111/j.1745-6622.2009.00246.x
• Blume, L., Easley, D., & O'hara, M. (1994). Market statistics and technical analysis: The role of volume. The Journal of Finance, 49(1), 153-181. https://doi.org/10.1111/j.1540-6261.1994.tb04424.x
• Borges, M. R. (2010). Efficient market hypothesis in European stock markets. The European Journal of Finance, 16(7), 711-726. https://doi.org/10.1080/1351847X.2010.495477
• Chen, G. M., Firth, M., & Rui, O. M. (2001). The dynamic relation between stock returns, trading volume, and volatility. Financial Review, 36(3), 153-174. https://doi.org/10.1111/j.1540-6288.2001.tb00024.x
• Chen, S. S. (2012). Revisiting the empirical linkages between stock returns and trading volume. Journal of Banking & Finance, 36(6), 1781-1788. https://doi.org/10.1016/j.jbankfin.2012.02.003
• Choi, S. Y. (2021). Analysis of stock market efficiency during crisis periods in the US stock market: Differences between the global financial crisis and COVID-19 pandemic. Physica A: Statistical Mechanics and Its Applications, 574, 125988. https://doi.org/10.1016/j.physa.2021.125988
• Chordia, T., & Swaminathan, B. (2000). Trading volume and cross‐autocorrelations in stock returns. The Journal of Finance, 55(2), 913-935. https://doi.org/10.1111/0022-1082.00231
• Copeland, T. E. (1976). A model of asset trading under the assumption of sequential information arrival. The Journal of Finance, 31(4), 1149-1168. https://doi.org/10.2307/2326280
• Çıralı, S. (2022). A comparison of international market indices for measuring market efficiency based on price-volume relationship. Journal of Capital Markets Studies, 6(1), 90-105.
• Dickey, D. A., & Fuller, W. A. (1979). Distribution of the estimators for autoregressive time series with a unit root. Journal of the American Statistical Association, 74(1), 427-431. https://doi.org/10.1080/01621459.1979.10482531 Dickey, D. A., & Fuller, W. A. (1981). Likelihood ratio tests for autoregressive time series with a unit root. Econometrica, 49, 1057–1072. https://doi.org/10.2307/1912517
• Eken, H., & Adalı, S. (2008). Piyasa etkinliği ve İMKB: Zayıf formda etkinliğe ilişkin ekonometrik bir analiz. Muhasebe ve Finansman Dergisi, (37), 74-87.
• Fama, E. F. (1970). Efficient capital markets: A review of theory andempirical work. The Journal of Finance, 25(2), 383–417. https://doi.org/10.2307/2325486
• Gagnon, L., & Karolyi, G. A. (2009). Information, trading volume, and international stock return comovements: Evidence from cross-listed stocks. Journal of Financial and Quantitative Analysis, 44(4), 953-986. https://doi.org/10.1017/S0022109009990196
• Ghysels, E., Gourieroux, C., & Jasiak, J. (2000). Causality between returns and traded volumes. Annales d'Economie et de Statistique, 60, 189-206. https://doi.org/10.2307/20076260
• Goldman Sachs. (2007). Beyond The BRICS: A look at the next 11. https://www.goldmansachs.com/pdfs/insights/archive/archive-pdfs/brics-book/brics-chap-13.pdf
• Granger, C. W. (1969). Investigating causal relations by econometric models and cross-spectral methods. Econometrica: Journal of the Econometric Society, 37(3), 424-438. https://doi.org/10.2307/1912791
• Gündüz, L., & Hatemi-J, A. (2014). Stock price and volume relation in emerging markets. Emerging Markets Finance and Trade, 41(1), 29–44. https://doi.org/10.1080/1540496X.2005.11052599
• He, L. Y., & Wen, X. C. (2015). Predictability and market efficiency in agricultural futures markets: A perspective from price–volume correlation based on wavelet coherency analysis. Fractals, 23(02), 1550003. https://doi.org/10.1142/S0218348X15500036
• Hiemstra, C., & Jones, J. D. (1994). Testing for linear and nonlinear Granger causality in the stock price‐volume relation. The Journal of Finance, 49(5), 1639-1664. https://doi.org/10.1111/j.1540-6261.1994.tb04776.x
• Karpoff, J. M. (1987). The relation between price changes and trading volume: A survey. Journal of Financial and Quantitative Analysis, 22(1), 109-126. https://doi.org/10.2307/2330874
• Kumar, M. A., Swathi, J., Pallavi, T. A., & Bavana, S. (2023). Volume progression and price–volume relationship of commodity futures: Case of bullion and base metals. NMIMS Management Review, 31(4), 265-274. https://doi.org/10.1177/09711023241230463
• Kurihara, Y. & Fukushima, A. (2017). The market efficiency of Bitcoin: A weekly anomaly perspective. Journal of Applied Finance and Banking, 7(3), 57.
• Kwiatkowski, D., Phillips, P. C., Schmidt, P., & Shin, Y. (1992). Testing the null hypothesis of stationarity against the alternative of a unit root: How sure are we that economic time series have a unit root? Journal of Econometrics, 54(1-3), 159-178. https://doi.org/10.1016/0304-4076(92)90104-Y
• Lao, P., & Singh, H. (2011). Herding behaviour in the Chinese and Indian stock markets. Journal of Asian Economics, 22(6), 495-506. https://doi.org/10.1016/j.asieco.2011.08.001
• Lee, B. S., & Rui, O. M. (2002). The dynamic relationship between stock returns and trading volume: Domestic and cross-country evidence. Journal of Banking & Finance, 26(1), 51-78. https://doi.org/10.1016/S0378-4266(00)00173-4
• Li, C., Huang, W., Wang, W. S., & Chia, W. M. (2021). Price change and trading volume: Behavioral heterogeneity in stock market. Computational Economics, 1-37. https://doi.org/10.1007/s10614-021-10224-4
• Li, P., Li, W., Yang, M., & Zhao, D. (2024). Measuring the dynamics of the stock market’s volume-price relationship: A new Hurst-based market-trend index. Applied Economics, 1-18. https://doi.org/10.1080/00036846.2024.2376775
• Malcıoğlu, G., & Aydın, M. (2016). Borsa İstanbul'da piyasa etkinliginin analizi: Harvey Doğrusallık testi Journal of Accounting, Finance and Auditing Studies, 2(1), 112.
• Malkiel, B. G. (2005). Reflections on the efficient market hypothesis: 30 years later. Financial Review, 40(1), 1-9. https://doi.org/10.1111/j.0732-8516.2005.00090.x
• Moyo, C., & Phiri, A. (2023). Re-examining bitcoin’s price–volume relationship: A time-varying spectral analysis. Journal of Risk and Financial Management, 16(7), 324. https://doi.org/10.3390/jrfm16070324
• Nasiri, S., Bektas, E., & Jafari, G. R. (2018). The impact of trading volume on the stock market credibility: Bohmian quantum potential approach. Physica A: Statistical Mechanics and Its Applications, 512, 1104-1112. https://doi.org/10.1016/j.physa.2018.08.026
• Rashid, A. (2007). Stock prices and trading volume: An assessment for linear and nonlinear Granger causality. Journal of Asian Economics, 18(4), 595-612. https://doi.org/10.1016/j.asieco.2007.03.003
• Saatcioglu, K., & Starks, L. T. (1998). The stock price–volume relationship in emerging stock markets: The case of Latin America. International Journal of Forecasting, 14(2), 215-225. https://doi.org/10.1016/S0169-2070(98)00028-4
• Sahoo, P. K., & Sethi, D. (2024). Market efficiency of the cryptocurrencies: Some new evidence based on price–volume relationship. International Journal of Finance & Economics, 29(2), 1569-1580. https://doi.org/10.1002/ijfe.2744
• Timmermann, A., & Granger, C. W. (2004). Efficient market hypothesis and forecasting. International Journal of Forecasting, 20(1), 15-27. https://doi.org/10.1016/S0169-2070(03)00012-8
• Toda, H. Y., & Yamamoto, T. (1995). Statistical inference in vector autoregressions with possibly integrated processes. Journal of Econometrics, 66(1-2), 225-250. https://doi.org/10.1016/0304-4076(94)01616-8 Wang, X., & Hui, X. (2024). Price‐volume relationship in bitcoin futures ETF market: An information perspective. Discrete Dynamics in Nature and Society, 2024(1), 8066742. https://doi.org/10.1155/2024/8066742
• Yang, J., Tong, M., & Yu, Z. (2023). Can volume be more informative than prices? Evidence from Chinese housing markets. Review of Quantitative Finance and Accounting, 61(2), 633-672. https://doi.org/10.1007/s11156-023-01161-4
• Yücel, Ö. (2016). Finansal piyasa etkinliği: Borsa İstanbul üzerine bir uygulama. International Review of Economics and Management, 4(3), 107-123. https://dergipark.org.tr/tr/pub/iremjournal/issue/15725/285491
• Zeren, F., Kara, H., & Arı, A. (2013). Piyasa etkinliği hipotezi: İMKB için ampirik bir analiz. Dumlupınar Üniversitesi Sosyal Bilimler Dergisi, (36), 141-148.