As the financial literature has documented, trading volume is generally affected by information releases, extreme returns, herd instinct, overconfidence, panic and volatility. In this study, we provide further empirical evidence that the extension of trading hours has a positive effect on trading volume. Using data from the last 12 years, during which the Tel Aviv Stock Exchange extended its trading hours on several occasions, we demonstrate that our findings hold true after controlling for proxies for world market returns and volatility, time trends, macroeconomic announcements and suicide attacks. We discuss several theories that may explain the results obtained. Furthermore, we show that cross-listed stocks attract more trading and explain the majority of the change in the volume of stocks traded. The findings may have implications for those who design policy for the exchange markets worldwide, because the majority of their revenues come from transactions and clearing fees.
This is a preview of subscription content, log in to check access.
Buy single article
Instant access to the full article PDF.
Price includes VAT for USA
Subscribe to journal
Immediate online access to all issues from 2019. Subscription will auto renew annually.
This is the net price. Taxes to be calculated in checkout.
Practitioners attributed that drop in trading volume to many factors. The leading one refers to the 2010 Dodd-Frank Act and the Basel III regulatory frameworks that reduced the banks’ ability and willingness to engage in the market and caused deep stagnation in the balance sheets of dealers (e.g., Adrian et al. 2017). The second factor refers to the diminishing role of high-speed traders, who use computer algorithms to take advantage of small price discrepancies and who have recently come to account for over half of all stock market activity. (http://www.nytimes.com/2012/05/07/business/stock-trading-remains-in-a-slide-after-08-crisis.html?_r=0).
The time difference between Tel Aviv and New York is generally seven hours. If the former advances the clocks by one hour before the US, or the US moves to daylight savings time before Israel, the time difference becomes eight hours.
We would like to thank an anonymous referee for raising this point.
The Tel Aviv Volatility Index, commonly termed the VIXTA, is derived from the option securities traded on the TASE. The VIXTA is calculated in a manner similar to that used by the CBOE to calculate the VIX.
Our data have relatively few outliers. This is because we use market rather than individual stock data. Anyway, we trimmed 5% of the tails of the dependent variable (2.5% from each side). This action guaranteed cleaning outliers in the other variables, since the majority of them took place during the 2008 crisis. By and large, the results were maintained. The results are not presented here but available upon request.
Admati, A. R., & Pfleiderer, P. (1988). A theory of intraday patterns: Volume and price variability. The Review of Financial Studies, 1(1), 3–40.
Adrian, T., Fleming, M., Shachar, O., & Vogt, E. (2017). Market liquidity after the financial crisis. Annual Review of Financial Economics, 9, 43–83.
Andersen, T. (1996). Return volatility and trading volume, an information flow interpretation of stochastic volatility. Journal of Finance, 51, 168–204.
Asem, E. (2007). Concentrated opening volume: market closure or strategic trading? Journal of Financial Research, 30(2), 321–334.
Asem, E., & Kaul, A. (2008). Trading time and trading activity: evidence from extensions of the NYSE trading day. European Journal of Finance, 14(3), 225–242.
Baker, M., & Wurgler, J. (2007). Investor sentiment in the stock market. Journal of Economic Perspectives, 21, 129–151.
Berry, T. D., & Howe, K. M. (1994). Public information arrival. Journal of Finance, 49(4), 1331–1346.
Bessembinder, H., & Seguin, P. J. (1992). Futures-trading activity and stock price volatility. The Journal of Finance, 47(5), 2015–2034.
Bessembinder, H., & Seguin, P. J. (1993). Price volatility, trading volume, and market depth: Evidence from futures markets. Journal of Financial and Quantitative Analysis, 28(01), 21–39.
Brock, W. A., & Kleidon, A. W. (1992). Periodic market closure and trading volume: A model of intraday bids and asks. Journal of Economic Dynamics and Control, 16(3–4), 451–489.
Chan, K., & Chan, Y. C. (1993). Price volatility in the Hong Kong stock market: A test of the information and trading noise hypothesis. Pacific-Basin Finance Journal, 1(2), 189–201.
Cheng, L. T., Jiang, L., & Ng, R. W. (2004). Information content of extended trading for index futures. Journal of Futures Markets, 24(9), 861–886.
Chordia, T., Roll, R., & Subrahmanyam, A. (2001). Market liquidity and trading activity. Journal of Finance, 56(2), 501–530.
Clark, P. K. (1973). A subordinated stochastic process model with finite variance for speculative prices. Econometrica: Journal of the Econometric Society, 41(1), 135–155.
Coffee, J. C. Jr. (2002). Racing towards the top? The impact of cross-listings and stock market competition on international corporate governance. Columbia Law Review, 102(7), 1757–1831.
Copeland, T. (1976). A model of asset trading under the assumption of sequential information arrival. Journal of Finance, 31, 1149–1168.
Diamond, D. W., & Verrecchia, R. E. (1991). Disclosure, liquidity, and the cost of capital. Journal of Finance, 46(4), 1325–1359.
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, 427–431.
Eldor, R., & Melnick, R. (2004). Financial markets and terrorism. European Journal of Political Economy, 20(2), 367–386.
Erenburg, G., Kurov, A., & Lasser, D. J. (2006). Trading around macroeconomic announcements: Are all traders created equal? Journal of Financial Intermediation, 15(4), 470–493.
Flannery, M. J., & Protopapadakis, A. A. (2002). Macroeconomic factors do influence aggregate stock returns. Review of Financial Studies, 15(3), 751–782.
Fleming, M. J., & Remolona, E. M. (1999). Price formation and liquidity in the US Treasury market: The response to public information. Journal of Finance, 54(5), 1901–1915.
French, K. R., & Roll, R. (1986). Stock return variances: The arrival of information and the reaction of traders. Journal of Financial Economics, 17(1), 5–26.
Frino, A., & Hill, A. (2001). Intraday futures market behavior around major scheduled macroeconomic announcements: Australian evidence. Journal of Banking & Finance, 25, 1319–1337.
Gallant, A. R., Rossi, P. E., & Tauchen, G. (1992). Stock prices and volume. Review of Financial Studies, 5(2), 199–242.
Garbade, K. D., & Silber, W. L. (1979). Dominant and satellite markets: a study of dually-traded securities. Review of Economics and Statistics, 61(3), 455–460.
Geoffrey, G., & Chowdhury, M. (1996). Information noise and stock return volatility: Evidence from Germany. Applied Economics Letters, 3(8), 537–540.
Gervais, S., Kaniel, R., & Mingelgrin, D. H. (2001). The high-volume return premium. The Journal of Finance, 56(3), 877–919.
Girard, E., & Biswas, R. (2007). Trading volume and market volatility: Developed versus emerging stock markets. Financial Review, 42(3), 429–459.
Harris, L. (1986). A transaction data study of weekly and intradaily patterns in stock returns. Journal of Financial Economics, 16, 99–117.
Harris, L. (1987). Transaction data tests of the mixture of distributions hypothesis. Journal of Financial and Quantitative Analysis, 22(2), 127–141.
Harris, M., & Raviv, A. (1993). Differences of opinion make a horse race. The Review of Financial Studies, 6(3), 473–506.
Hong, H., & Wang, J. (2000). Trading and returns under periodic market closures. Journal of Finance, 55(1), 297–354.
Houston, J. F., & Ryngaert, M. D. (1992). The links between trading time and market volatility. Journal of Financial Research, 15(2), 91–100.
Hua, R., Liu, Q., & Tse, Y. (2016). Extended trading in Chinese index markets: Informed or uninformed? Pacific-Basin Finance Journal, 36, 112–122.
Jain, A., Biswal, P. C., & Ghosh, S. (2016). Volatility–volume causality across single stock spot–futures markets in India. Applied Economics, 48(34), 3228–3243.
Jain, P. C., & Joh, G. H. (1988). The dependence between hourly prices and trading volume. Journal of Financial and Quantitative Analysis, 23(3), 269–283.
Jennings, R. H., Starks, L. T., & Fellingham, J. C. (1981). An equilibrium model of asset trading with sequential information arrival. Journal of Finance, 36(1), 143–161.
Karolyi, G. A. (1998). Why do companies list shares abroad? A survey of the evidence and its managerial implications. Financial Markets, Institutions & Instruments, 7(1), 1–60.
Karolyi, G. A. (2006). The world of cross-listings and cross-listings of the world: Challenging conventional wisdom. Review of Finance, 10(1), 99–152.
Karpoff, J. M. (1987). The relation between price changes and trading volume: A survey. Journal of Financial and Quantitative Analysis, 22(1), 109–126.
Kyle, A. S. (1985). Continuous auctions and insider trading. Econometrica: Journal of the Econometric Society, 53(6), 1315–1335.
Lee, H. C., Chien, C. Y., Chen, H. L., & Huang, Y. S. (2009). The extended opening session of the futures market and stock price behavior: Evidence from the Taiwan Stock Exchange. Review of Pacific Basin Financial Markets and Policies, 12(3), 403–416.
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.
Ljung, G. M., & Box, G. E. P. (1978). On a measure of lack of fit in time series models. Biometrika, 65, 297–303.
Lo, A. W., & Wang, J. (2000). Trading volume: definitions, data analysis, and implications of portfolio theory. Review of Financial Studies, 13(2), 257–300.
McInish, T. H., Shoesmith, G. L., & Wood, R. A. (1995). Cointegration, error correction, and price discovery on informationally linked security markets. Journal of Financial and Quantitative Analysis, 30(4), 563–579.
Newey, W. K., & West, K. D. (1987). Hypothesis testing with efficient method of moment’s estimation. International Economic Review, 28(3), 777–787.
Patel, S. A., & Sarkar, A. (1998). Crises in developed and emerging stock markets. Financial Analysts Journal, 54(6), 50–59.
Phillips, P. C., & Perron, P. (1988). Testing for a unit root in time series regression. Biometrika, 75(2), 335–346.
Qadan, M., & Kliger, D. (2016). The short trading day anomaly. Journal of Empirical Finance, 38, 62–80.
Reese, W. A., Jr., & Weisbach, M. S. (2002). Protection of minority shareholder interests, cross-listings in the United States, and subsequent equity offerings. Journal of Financial Economics, 66(1), 65–104.
Shi, Y., Liu, W. M., & Ho, K. Y. (2016). Public news arrival and the idiosyncratic volatility puzzle. Journal of Empirical Finance, 37, 159–172.
Smirlock, M., & Starks, L. (1985). A further examination of stock price changes and transaction volume. Journal of Financial Research, 8(3), 217–226.
Sohn, S., & Zhang, X. (2017). Could the extended trading of CSI 300 index futures facilitate its role of price discovery? Journal of Futures Markets, 37(7), 717–740.
Wang, J. (1994). A model of competitive stock trading volume. Journal of Political Economy, 102(1), 127–168.
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
About this article
Cite this article
Qadan, M., Aharon, D.Y. The length of the trading day and trading volume. Eurasian Bus Rev 9, 137–156 (2019). https://doi.org/10.1007/s40821-019-00119-8
- Extended trading
- Tel Aviv stock exchange
- Stock exchange revenues
- Trading hours
- Trading volume