Intra-market commonality in liquidity: new evidence from the Polish stock exchange
Abstract
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.
Keywords
commonality in liquidity, OLS-HAC, GARCH, time rolling-window approach, Warsaw Stock Exchange
References
- 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. DOI: https://doi.org/10.1016/j.jfineco.2004.06.007
View in Google Scholar - Adkins, L. C. (2014). Using Gretl for principles of econometric. Version 1.041.
View in Google Scholar - 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. DOI: https://doi.org/10.1016/S1386-4181(01)00024-6
View in Google Scholar - 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. DOI: https://doi.org/10.1016/j.iref.2015.06.005
View in Google Scholar - 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. DOI: https://doi.org/10.1093/rfs/hhm030
View in Google Scholar - 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. DOI: https://doi.org/10.1080/1540496X.2016.1216937
View in Google Scholar - 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. DOI: https://doi.org/10.1016/j.frl.2018.02.014
View in Google Scholar - Będowska-Sójka, B. (2019). Commonality in liquidity measures. The evidence from the Polish stock market. Hradec Economic Days, 9(1). DOI: https://doi.org/10.36689/uhk/hed/2019-01-003
View in Google Scholar - 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. DOI: https://doi.org/10.1080/07474939208800229
View in Google Scholar - 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. DOI: https://doi.org/10.2307/2297111
View in Google Scholar - 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. DOI: https://doi.org/10.1111/1475-6803.00035
View in Google Scholar - 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. DOI: https://doi.org/10.1016/j.irfa.2005.09.003
View in Google Scholar - 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. DOI: https://doi.org/10.1017/S0022109009990123
View in Google Scholar - Campbell, J. Y., Lo, A. W., & MacKinlay, A. C. (1997). The econometrics of financial markets. New Jersey: Princeton University Press. DOI: https://doi.org/10.1515/9781400830213
View in Google Scholar - 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. DOI: https://doi.org/10.1016/S0304-405X(00)00057-X
View in Google Scholar - Chen, J. (2005). Pervasive liquidity risk and asset pricing. Job Market Paper. Columbia University.
View in Google Scholar - Chordia, T., Roll, R., & Subrahmanyam, A. (2000). Commonality in liquidity. Journal of Financial Economics, 56(1). doi: 10.1016/S0304-405X(99)00057-4. DOI: https://doi.org/10.1016/S0304-405X(99)00057-4
View in Google Scholar - 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. DOI: https://doi.org/10.1016/S0304-405X(02)00136-8
View in Google Scholar - 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. DOI: https://doi.org/10.1016/j.econlet.2004.02.010
View in Google Scholar - 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. DOI: https://doi.org/10.1016/j.jfineco.2003.05.006
View in Google Scholar - 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. DOI: https://doi.org/10.2307/1912517
View in Google Scholar - 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. DOI: https://doi.org/10.1016/0304-405X(79)90013-8
View in Google Scholar - Elliott, G., Rothenberg, T. J., & Stock, J. H. (1996). Efficient tests for an autoregressive unit root. Econometrica, 64(4). doi: 10.2307/2171846. DOI: https://doi.org/10.2307/2171846
View in Google Scholar - Engle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflations. Econometrica, 50. doi: 10.2307/ 1912773. DOI: https://doi.org/10.2307/1912773
View in Google Scholar - 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. DOI: https://doi.org/10.1111/j.1467-629x.2004.00117.x
View in Google Scholar - 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. DOI: https://doi.org/10.1093/rof/rfx003
View in Google Scholar - 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. DOI: https://doi.org/10.1016/j.ribaf.2015.02.006
View in Google Scholar - 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. DOI: https://doi.org/10.1111/j.1540-6261.1987.tb04367.x
View in Google Scholar - 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. DOI: https://doi.org/10.1016/j.jfineco.2008.06.002
View in Google Scholar - 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. DOI: https://doi.org/10.1111/j.1540-6261.2009.01529.x
View in Google Scholar - Hamilton, J. D. (2008). Macroeconomics and ARCH. NBER Working Paper Series, 14151. DOI: https://doi.org/10.3386/w14151
View in Google Scholar - 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. DOI: https://doi.org/10.1016/S0304-405X(00)00091-X
View in Google Scholar - 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. DOI: https://doi.org/10.1016/j.iref.2014.12.006
View in Google Scholar - 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. DOI: https://doi.org/10.1016/0304-405X(95)00867-E
View in Google Scholar - Huberman, G., & Halka, D. (2001). Systematic liquidity. Journal of Financial Research, 24(2). doi: 10.1111/j.1475-6803.2001.tb00763.x. DOI: https://doi.org/10.1111/j.1475-6803.2001.tb00763.x
View in Google Scholar - 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. DOI: https://doi.org/10.1016/j.jfineco.2007.10.004
View in Google Scholar - 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. DOI: https://doi.org/10.1111/j.1540-6288.2012.00348.x
View in Google Scholar - 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. DOI: https://doi.org/10.1016/j.jfineco.2011.12.008
View in Google Scholar - 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. DOI: https://doi.org/10.1111/j.1475-6803.2008.00230.x
View in Google Scholar - 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. DOI: https://doi.org/10.1016/j.jfineco.2006.12.003
View in Google Scholar - Kyle, A. S. (1985). Continuous auctions and insider trading. Econometrica, 53(6). doi: 10.2307/1913210. DOI: https://doi.org/10.2307/1913210
View in Google Scholar - 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. DOI: https://doi.org/10.1111/j.1540-6261.1991.tb02683.x
View in Google Scholar - Lee, K.-H. (2011). The world price of liquidity risk. Journal of Financial Economics, 99(1). doi: 10.1016/j.jfineco.2010.08.003. DOI: https://doi.org/10.1016/j.jfineco.2010.08.003
View in Google Scholar - Lesmond, D. A. (2005). Liquidity of emerging markets. Journal of Financial Economics, 77(2). doi: 10.1016/j.jfineco.2004.01.005. DOI: https://doi.org/10.1016/j.jfineco.2004.01.005
View in Google Scholar - MacKinnon, J. G. (2010). Critical values for cointegration tests. Queen’s Economics Department Working Paper, 1227.
View in Google Scholar - 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. DOI: https://doi.org/10.1016/j.iref.2003.12.001
View in Google Scholar - 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. DOI: https://doi.org/10.5295/cdg.140472mm
View in Google Scholar - 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. DOI: https://doi.org/10.1080/1540496X.2015.1061799
View in Google Scholar - 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. DOI: https://doi.org/10.2307/1913610
View in Google Scholar - 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. DOI: https://doi.org/10.1007/978-3-319-54885-2_9
View in Google Scholar - 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. DOI: https://doi.org/10.12775/DEM.2015.003
View in Google Scholar - 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..
View in Google Scholar - Olbryś, J. (2014). Is illiquidity risk priced? The case of the Polish medium-size emerging stock market. Bank i Kredyt, 45(6).
View in Google Scholar - 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. DOI: https://doi.org/10.1007/978-3-319-76228-9_7
View in Google Scholar - 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. DOI: https://doi.org/10.12775/DEM.2018.004
View in Google Scholar - Olbryś, J., & Mursztyn, M. (2015). Comparison of selected trade classification algorithms on the Warsaw Stock Exchange. Advances Computer Science Research, 12.
View in Google Scholar - 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.
View in Google Scholar - 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. DOI: https://doi.org/10.1007/978-3-319-70055-7_9
View in Google Scholar - 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. DOI: https://doi.org/10.1007/978-3-030-02194-8_13
View in Google Scholar - 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.
View in Google Scholar - Pastor, L., & Stambaugh, R. (2003). Liquidity, risk and expected stock returns. Journal of Political Economy, 111(3). doi: 10.1086/374184. DOI: https://doi.org/10.1086/374184
View in Google Scholar - 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. DOI: https://doi.org/10.1016/j.pacfin.2007.12.004
View in Google Scholar - 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. DOI: https://doi.org/10.1016/j.jfineco.2005.04.005
View in Google Scholar - Stereńczak, S. (2019). State-dependent stock liquidity premium: the case of the Warsaw Stock Exchange. Available at SSRN 3349268, doi: 10.2139/ssrn.3349268. DOI: https://doi.org/10.2139/ssrn.3349268
View in Google Scholar - Stoll, H. R. (2000). Friction. Journal of Finance, 55(4). doi: 10.1111/0022-1082. 00259. DOI: https://doi.org/10.1111/0022-1082.00259
View in Google Scholar - 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. DOI: https://doi.org/10.1016/S1042-4431(00)00048-2
View in Google Scholar - 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. DOI: https://doi.org/10.2478/bsrj-2014-0020
View in Google Scholar - Tsay, R. S. (2010). Analysis of financial time series. New York: John Wiley. DOI: https://doi.org/10.1002/9780470644560
View in Google Scholar - 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. DOI: https://doi.org/10.1093/rfs/hhm054
View in Google Scholar - 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. DOI: https://doi.org/10.1080/01621459.1962.10480664
View in Google Scholar