Joanna Olbryś

Interaction Between Market Depth and Market Tightness on the Warsaw Stock Exchange: A Preliminary Study

The nature of market liquidity is multidimensional. According to the literature, the majority of researchers follow Kyle (1985) and they distinguish between three dimensions of market liquidity as special liquidity characteristics: market depth, market tightness, and market resiliency. The paper presents a preliminary study of interaction between market depth and market tightness on the Warsaw Stock Exchange (WSE). The order ratio (OR) is employed as a proxy of market depth, while market tightness is approximated using the relative spread (RS). The 20 most liquid WSE-listed big companies are investigated. The high-frequency intraday data covers the period from January 3, 2005 to June 30, 2015. Moreover, the paper provides a robustness analysis of the obtained results with respect to the whole sample period and three adjacent subsamples of equal size: the pre-crisis, crisis, and post-crisis periods. The hypothesis concerning the statistical significance of the Fisher’s z-transformed correlation coefficients between daily values of the OR and RS indicators for each stock is tested. The empirical results reveal that although, in general, low daily order ratios are accompanied by narrow daily relative spreads (as both indicate high liquidity), and high daily order ratios are accompanied by wide daily relative spreads, the majority of correlation coefficients between daily values of the OR and RS indicators are not significantly different from zero. Furthermore, the results turn out to be robust to the choice of the sample. Our findings indicate that both ratios seem to capture various sources of market liquidity, which is consistent with the literature.

Asymmetric Impact of Innovations on Volatility in the Case of the US and CEEC-3 Markets: EGARCH Based Approach

The main goal of this study is to investigate the asymmetric impact of innovations on volatility in the case of the US and three biggest emerging CEEC–3 markets, using univariate EGARCH approach. We compare empirical results for both the whole sample from Jan 3, 2007 to Dec 30, 2011, and two equal subsamples: the ‘down market’ period, and the ‘up market’ period. Pronounced negative asymmetry effects are presented in the case of all markets, and are especially strong in the ‘down market’ period, which is closely connected with the 2007 US subprime crisis period.

ARCH Effect in Classical Market-Timing Models with Lagged Market Variable: the Case of Polish Market

The main goal of this study is to present the regressions of the GARCH versions of classical market-timing models of Polish equity funds. We examine the models with lagged values of the market factor as an additional variable because of the Fisher’s effect1 in the case of the main Warsaw Stock Exchange indexes. The market-timing and selectivity abilities of fund managers are evaluated for the period Jan 2003 – June 2011. Results on both the HAC and the GARCH estimates are qualitatively similar, and even better in the case of the simpler HAC method. For this reason, it is not necessary to estimate the GARCH versions of market-timing models in the case of Polish mutual funds, even despite the strong ARCH effects that exist in these models.

Testing Integration Effects Between the Cee and U.S. Stock Markets During the 2007–2009 Global Financial Crisis

Abstract The main goal of this paper is to explicitly test a research hypothesis that there was no integration effect among the U.S. and the eight Central and Eastern European (CEE) stock markets during the 2007-2009 Global Financial Crisis (GFC). As growing international integration could lead to a progressive increase in cross-market correlations, the evaluation of integration was carried out by applying equality tests of correlation matrices computed over non-overlapping subsamples: the pre-crisis and crisis periods, in the group of investigated markets. The crisis periods are formally established based on a statistical method of dividing market states into bullish and bearish markets. The sample period May 2004-April 2014 includes the 2007 U.S. subprime financial crisis. The robustness analysis of the integration tests with respect to various data frequencies is provided. The empirical results are not homogeneous and they depend both on the integration test and data frequency. Consequently, it is not possible to conclude whether integration between the investigated markets is present.

Components of the Effective Spread: Evidence from the Warsaw Stock Exchange

The paper provides empirical investigation of the effective spread and its two components complementing each other: (1) the realized spread and (2) the price impact component. The estimated liquidity measures are derived from high-frequency intraday data on the Warsaw Stock Exchange (WSE). Daily proxies of percentage effective spread, percentage realized spread, and percentage price impact values are analysed for 53 WSE-traded companies divided into three size groups. As the raw dataset does not identify the trade direction, the trade classification Lee and Ready (J Financ 46:733–746, 1991) algorithm is employed to infer the trade side and to distinguish between the so-called buyer- and seller-initiated trades. Moreover, the paper provides a robustness analysis of the obtained results with respect to the whole sample and three adjacent sub-samples, each of equal size: the pre-crisis, Global Financial Crisis (GFC), and post-crisis periods. The evidence is that the empirical results rather do not depend on a firm size and turn out to be robust to the choice of the period. Furthermore, the hypothesis concerning statistical significance of correlation coefficients between daily values of three estimated measures employed in the study is tested.

Testing Stability of Correlations Between Liquidity Proxies Derived from Intraday Data on the Warsaw Stock Exchange

The aim of this paper is to investigate relationships based on correlations between alternative liquidity measures derived from intraday data on the Warsaw Stock Exchange (WSE). Analyses of correlations help to find an answer to important question whether different liquidity proxies capture various sources of market liquidity/illiquidity or not. The main research hypothesis states that correlations are stable in specified periods. The hypothesis is verified by applying equality tests of correlation matrices computed over non-overlapping subsamples. The dataset consists of daily proxies of four liquidity measures for 53 WSE-traded companies divided into three size groups. The whole sample covers the period from January 3, 2005 to June 30, 2015, and it includes three adjacent subsamples, each of equal size: the pre-crisis, crisis, and post-crisis periods. To calculate several liquidity measures based on intraday data it is essential to recognize a side initiating the transaction and to distinguish between buyer- and seller-initiated trades. In this paper, the Lee and Ready (J Financ 46(2):733–746, 1991) trade classification algorithm is employed to infer trade sides. The obtained empirical results concerning the stability of correlations between liquidity proxies in the whole group of companies are not homogeneous.

The Evolution of Financial Integration on Selected European Stock Markets: a Dynamic Principal Component Approach

Abstract The goal of this paper is to recognize the dynamics of financial integration across the European stock markets over the last two decades. We investigate two groups of markets: (1) three developed European markets in the U.K., France, and Germany; and (2) three emerging Central and Eastern European markets in Poland, the Czech Republic, and Hungary (CEE-3). The evolution of the integration process is analyzed using a dynamic principal component approach. The index of integration serves as a robust measure of integration. The empirical results reveal that the dynamics of integration across the whole group of markets increased significantly following the CEEC-3’s accession to the European Union. An inverted U‑shape in the index of integration has been found in this case. Moreover, the average index of integration was significantly different during the Global Financial Crisis compared to the pre‑crisis period.

Day-of-the-Week Effects in Liquidity on the Warsaw Stock Exchange

The purpose of this study is to explore the day-of-the-week patterns in liquidity on the Warsaw Stock Exchange (WSE) using daily turnover as a liquidity measure. The existence of an inverted U-shape in the stock turnover across the trading days is examined. The research sample covers 2502 daily observations in the period January 2005 – December 2014. 53 WSE-listed companies divided into three size groups are investigated. In the study the OLS method with the HAC covariance matrix estimation and the GARCH-type models are employed. The results indicate that liquidity on the WSE tends to be significantly lower on Mondays and higher on Wednesdays in comparison with the other days of the week. However, the inverted U-shape in daily turnover occurs only among the companies with the largest market capitalization.