Intra-market commonality in liquidity: new evidence from the Polish stock exchange
Keywords:commonality in liquidity, OLS-HAC, GARCH, time rolling-window approach, Warsaw Stock Exchange
Research background: Empirical market microstructure research has recently shifted its focus from the examination of liquidity of individual securities towards analyses of the common determinants and components of liquidity. The identification of commonality in liquidity emerged as a new and fast growing strand of the literature on liquidity. However, the results around the world are ambiguous and rather depend on a specific stock market.
Purpose of the article: The aim of this study is to explore intra-market commonality in liquidity on the Warsaw Stock Exchange (WSE) by using daily proxies of six liquidity estimates: percentage relative spread, percentage realized spread, percentage price impact, percentage order ratio, modified turnover, and modified version of the Amihud measure. The sample covers a period from January 2005 to December 2016. The database contains the group of eighty-six WSE-listed companies.
Methods: The research hypothesis that there is commonality in liquidity on the Polish stock market is tested. The OLS with the HAC covariance matrix estimation and the GARCH-type models are employed to infer the patterns of liquidity co-movements on the WSE. Moreover, because the sample period is quite long, the stability of the empirical results by time period is examined. Seven 6-year time windows are utilized in the study.
Findings & Value added: The regression results reveal weak evidence of co-movements in liquidity on the WSE, regardless of the choice of the liquidity proxy. Furthermore, the robustness tests based on the time rolling-window approach do not unambiguously support the research hypothesis that there is commonality in liquidity on the Polish stock market. To the best of the author?s knowledge, the empirical findings presented here are novel and have not been reported in the literature thus far.
Acharya, V. V., & Pedersen, L. H. (2005). Asset pricing with liquidity risk. Journal of Financial Economics, 77(2). doi: 10.1016/j.jfineco.2004.06.007.
Adkins, L. C. (2014). Using Gretl for principles of econometric. Version 1.041.
Amihud, Y. (2002). Illiquidity and stock returns: cross-section and time-series effects. Journal of Financial Markets, 5(1). doi: 10.1016/S1386-4181(01) 00024-6.
Bai, M., & Qin, Y. (2015). Commonality in liquidity in emerging markets: another supply-side explanation. International Review of Economics & Finance, 39. doi: 10.1016/j.iref.2015.06.005.
Bekaert, G., Harvey, C. R., & Lundblad, C. (2007). Liquidity and expected returns: Lessons from emerging markets. Review of Financial Studies, 20(6). doi: 10.1093/rfs/hhm030.
Będowska-Sójka, B. (2016). Liquidity dynamics around jumps. The evidence from the Warsaw Stock Exchange. Emerging Markets Finance & Trade, 52(2). doi: 10.1080/1540496X.2016.1216937.
Będowska-Sójka, B. (2018). The coherence of liquidity measures. The evidence from the emerging market. Finance Research Letters, 27. doi: 10.1016/j.frl. 2018.02.014.
Będowska-Sójka, B. (2019). Commonality in liquidity measures. The evidence from the Polish stock market. Hradec Economic Days, 9(1).
Bollerslev, T., & Wooldridge, J. M. (1992). Quasi-maximum likelihood estimation and inference in dynamic models with time-varying covariances. Econometric Reviews, 11. doi: 10.1080/07474939208800229.
Breusch, T. S., & Pagan, A. R. (1980). The Lagrange multiplier test and its applications to model specification in econometrics. Review of Economic Studies, 47. doi: 10.2307/2297111.
Brockman, P., & Chung, D. Y. (2002). Commonality in liquidity: evidence from an order-driven market structure. Journal of Financial Research, 25(4). doi: 10.1111/1475-6803.00035.
Brockman, P., & Chung, D. Y. (2006). Index inclusion and commonality in liquidity: evidence from the Stock Exchange of Hong Kong. International Review of Financial Analysis, 15(4-5). doi: 10.1016/j.irfa.2005.09.003.
Brockman, P., Chung, D. Y., & Perignon, C. (2009). Commonality in liquidity: a global perspective. Journal of Financial and Quantitative Analysis, 44(4). doi: 10.1017/S0022109009990123.
Campbell, J. Y., Lo, A. W., & MacKinlay, A. C. (1997). The econometrics of financial markets. New Jersey: Princeton University Press.
Chan, K., & Fong, W.-M. (2000). Trade size, order imbalance, and the volatility-volume relation. Journal of Financial Economics, 57. doi: 10.1016/S0304-405X(00)00057-X.
Chen, J. (2005). Pervasive liquidity risk and asset pricing. Job Market Paper. Columbia University.
Chordia, T., Roll, R., & Subrahmanyam, A. (2000). Commonality in liquidity. Journal of Financial Economics, 56(1). doi: 10.1016/S0304-405X(99)00057-4.
Chordia, T., Roll, R., & Subrahmanyam, A. (2002). Order imbalance, liquidity, and market returns. Journal of Financial Economics, 65. doi: 10.1016/S0304-405X(02)00136-8.
Cook, S., & Manning, N. (2004). Lag optimization and finite-sample size distortion of unit root tests. Economics Letters, 84(2). doi: 10.1016/j.econlet. 2004.02.010.
Coughenour, J. F., & Saad, M. M. (2004). Common market makers and commonality in liquidity. Journal of Financial Economics, 73. doi: 10.1016/j.jfineco. 2003.05.006.
Dickey, D. A., & Fuller, W. A. (1981). Likelihood ratio statistics for autoregressive time series with a unit root. Econometrica, 49(4). doi: 10.2307/1912517.
Dimson, E. (1979). Risk measurement when shares are subject to infrequent trading. Journal of Financial Economics, 7. doi: 10.1016/0304-405X(79)90013-8.
Elliott, G., Rothenberg, T. J., & Stock, J. H. (1996). Efficient tests for an autoregressive unit root. Econometrica, 64(4). doi: 10.2307/2171846.
Engle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflations. Econometrica, 50. doi: 10.2307/ 1912773.
Fabre, J., & Frino, A. (2004). Commonality in liquidity: evidence from the Australian Stock Exchange. Accounting and Finance, 44. doi: 10.1111/j.1467-629x.20 04.00117.x.
Fong, K. Y. L., Holden, C. W., & Trzcinka, C. (2017). What are the best liquidity proxies for global research? Review of Finance, 21. doi: 10.1093/rof/rfx003.
Foran, J., Hutchinson, M. C., & O’Sullivan, N. (2015). Liquidity commonality and pricing in UK. Research in International Business and Finance, 34. doi: 10.1016/j.ribaf.2015.02.006.
Glosten, L. R. (1987). Components of the bid-ask spread and the statistical properties of transaction prices. Journal of Finance, 42(4). doi: 10.1111/j.1540-6261.1987.tb04367.x.
Goyenko, R. Y., Holden, C. W., & Trzcinka, C. A. (2009). Do liquidity measures measure liquidity? Journal of Financial Economics, 92(2). doi: 10.1016/j. jfineco.2008.06.002.
Hameed, A., Kang, W., & Viswanathan, S. (2010). Stock market decline and liquidity. Journal of Finance, 65(1). doi: 10.1111/j.1540-6261.2009.01529.x.
Hamilton, J. D. (2008). Macroeconomics and ARCH. NBER Working Paper Series, 14151.
Hasbrouck, J., & Seppi, D. J. (2001). Common factors in prices, order flows, and liquidity. Journal of Financial Economics, 59(3). doi: 10.1016/S0304-405X(00)00091-X.
Ho, T. W., & Chang, S. H. (2015). The pricing of liquidity risk on the Shanghai stock market. International Review of Economics and Finance, 38. doi: 10.1016/j.iref.2014.12.006.
Huang, R. D., & Stoll, H. R. (1996). Dealer versus auction markets: a paired comparison of execution costs on NASDAQ and the NYSE. Journal of Financial Economics, 41. doi: 10.1016/0304-405X(95)00867-E.
Huberman, G., & Halka, D. (2001). Systematic liquidity. Journal of Financial Research, 24(2). doi: 10.1111/j.1475-6803.2001.tb00763.x.
Kamara, A., Lou, X., & Sadka, R. (2008). The divergence of liquidity commonality in the cross-section of stocks. Journal of Financial Economics, 89(3). doi: 10.1016/j.jfineco.2007.10.004.
Kang, W., & Zhang, H. (2013). Limit order book and commonality in liquidity. Financial Review, 48(1). doi: 10.1111/j.1540-6288.2012.00348.x.
Karolyi, G. A., Lee, K.-H., & van Dijk, M. A. (2012). Understanding commonality in liquidity around the world. Journal of Financial Economics, 105(1). doi: 10.1016/j.jfineco.2011.12.008.
Kempf, A., & Mayston, D. (2008). Liquidity commonality beyond best prices. Journal of Financial Research, 31(1). doi: 10.1111/j.1475-6803.2008.00230.x.
Korajczyk, R., & Sadka, R. (2008). Pricing the commonality across alternative measures of liquidity. Journal of Financial Economics, 87(1). doi: 10.1016/j.jfineco.2006.12.003.
Kyle, A. S. (1985). Continuous auctions and insider trading. Econometrica, 53(6). doi: 10.2307/1913210.
Lee, C. M. C., & Ready, M. J. (1991). Inferring trade direction from intraday data. Journal of Finance, 46(2). doi: 10.1111/j.1540-6261.1991.tb02683.x.
Lee, K.-H. (2011). The world price of liquidity risk. Journal of Financial Economics, 99(1). doi: 10.1016/j.jfineco.2010.08.003.
Lesmond, D. A. (2005). Liquidity of emerging markets. Journal of Financial Economics, 77(2). doi: 10.1016/j.jfineco.2004.01.005.
MacKinnon, J. G. (2010). Critical values for cointegration tests. Queen’s Economics Department Working Paper, 1227.
Martinez, M. A., Nieto, B., Rubio, G., & Tapia, M. (2005). Asset pricing and systematic liquidity risk: an empirical investigation of the Spanish stock market. International Review of Economics and Finance, 14(1). doi: 10.1016/j.iref. 2003.12.001.
Miralles Marcelo, J. L., Miralles Quirós, M., & Oliveira, C. (2015). Systematic liquidity: commonality and intertemporal variation in the Portuguese stock market. Cuadernos de Gestion, 15(2). doi: 10.5295/cdg.140472mm.
Narayan, P. K., Zhang, Z., & Zheng, X. (2015). Some hypotheses on commonality in liquidity: new evidence from the Chinese stock market. Emerging Markets Finance & Trade, 51. doi: 10.1080/1540496X.2015.1061799.
Newey, W. K., & West, K. D. (1987). A simple, positive semi-define, heteroskesticity and autocorrelation consistent covariance matrix. Econometrica, 55(3). doi: 10.2307/1913610.
Nowak, S. (2017). Order imbalance indicators in asset pricing: evidence from the Warsaw Stock Exchange. In K. Jajuga, L. Orlowski & K. Staehr (Eds.). Contemporary trends and challenges in finance. Springer proceedings in business and economics. Cham: Springer. doi: 10.1007/978-3-319-54885-2_9.
Nowak, S., & Olbryś, J. (2015). Day-of-the-week effects in liquidity on the Warsaw Stock Exchange. Dynamic Econometric Models, 15. doi: 10.12775/DEM. 2015.003.
Nowak, S., & Olbryś J. (2016). Direct evidence of non-trading on the Warsaw Stock Exchange. Research Papers of Wroclaw University of Economics. Wroclaw Conference in Finance: Contemporary Trends and Challenges, 428..
Olbryś, J. (2014). Is illiquidity risk priced? The case of the Polish medium-size emerging stock market. Bank i Kredyt, 45(6).
Olbryś, J. (2018a). Testing stability of correlations between liquidity proxies derived from intraday data on the Warsaw Stock Exchange. In K. Jajuga, H. Locarek-Junge & L. Orlowski (Eds.). Contemporary trends and challenges in finance. Springer proceedings in business and economics. Cham: Springer. doi: 10.1007/978-3-319-76228-9_7.
Olbryś, J. (2018b) The non-trading problem in assessing commonality in liquidity on emerging stock markets. Dynamic Econometric Models, 18. doi: 10.12775/ DEM.2018.004.
Olbryś, J., & Mursztyn, M. (2015). Comparison of selected trade classification algorithms on the Warsaw Stock Exchange. Advances Computer Science Research, 12.
Olbryś, J., & Mursztyn, M. (2017). Measurement of stock market liquidity supported by an algorithm inferring the initiator of a trade. Operations Research and Decisions, 27(4). doi: 10.5277/ord170406.
Olbrys, J., & Mursztyn, M. (2018a). Liquidity proxies based on intraday data: the case of the Polish order driven stock market. In N. Tsounis & A. Vlachvei (Eds.). Advances in panel data analysis in applied economic research. Springer proceedings in business and economics. Cham: Springer. doi: 10.1007/978-3-319-70055-7_9.
Olbrys, J., & Mursztyn, M. (2018b). On some characteristics of liquidity proxy time series. Evidence from the Polish stock market. In N. Tsounis & A. Vlachvei (Eds.). Advances in time series data methods in applied economic research. Springer proceedings in business and economics. Cham: Springer, doi: 10.1007/978-3-030-02194-8_13.
Olbryś, J., & Mursztyn, M. (2018c). Assessing accuracy of trade side classification rules. Methods, data, and problems. In M. Papież & S. Śmiech (Eds.) The 12th Professor Aleksander Zelias international conference on modelling and forecasting of socio-economic phenomena. Conference proceedings. Cracow: Foundation of the Cracow University of Economics.
Pastor, L., & Stambaugh, R. (2003). Liquidity, risk and expected stock returns. Journal of Political Economy, 111(3). doi: 10.1086/374184.
Pukthuanthong-Le, K., & Visaltanachoti, N. (2009). Commonality in liquidity: evidence from the Stock Exchange of Thailand. Pacific-Basin Finance Journal, 17(1). doi: 10.1016/j.pacfin.2007.12.004.
Sadka, R. (2006). Momentum and post-earnings announcement drift anomalies: the role of liquidity risk. Journal of Financial Economics, 80(2). doi: 10.1016/j.jfineco.2005.04.005.
Stereńczak, S. (2019). State-dependent stock liquidity premium: the case of the Warsaw Stock Exchange. Available at SSRN 3349268, doi: 10.2139/ssrn.3349268.
Stoll, H. R. (2000). Friction. Journal of Finance, 55(4). doi: 10.1111/0022-1082. 00259.
Theissen, E. (2001). A test of the accuracy of the Lee/Ready trade classification algorithm. Journal of International Financial Markets, Institutions and Money, 11. doi: 10.1016/S1042-4431(00)00048-2.
Vidović, J., Poklepović, T., & Aljinović, Z. (2014). How to measure illiquidity on European emerging stock markets? Business Systems Research, 5(3). doi: 10.2478/bsrj-2014-0020.
Tsay, R. S. (2010). Analysis of financial time series. New York: John Wiley.
Watanabe, A., & Watanabe, M. (2008). Time varying liquidity risk and the cross-section of stock returns. Review of Financial Studies, 21(6). doi: 10.1093 /rfs/hhm054.
Zellner, A. (1962). An efficient method of estimating seemingly unrelated regressions and tests for aggregation bias. Journal of American Statistical Association, 57. doi: 10.1080/01621459.1962.10480664.