Joanna Olbrys

Price and Volatility Spillovers in the Case of Stock Markets Located in Different Time Zones

This paper investigates the interdependence of price volatility across the U.S. stock market and two emerging markets: Poland and Hungary. Using daily data for countries located in different time zones, we point out the problems caused by the presence of nonsynchronous trading effects. To address this problem we use open-to-close logarithmic returns of major stock market indexes. The asymmetric impact of good and bad news is described by a multivariate exponential general autoregressive conditional heteroskedastic model. We investigate the sample from May 2004 to December 2011. The evidence is that the U.S. prices spill over to other markets. Our results show no pronounced volatility spillovers among the three examined markets. Moreover, we observe the presence of negative asymmetry in the case of all markets.

Direct Identification of Crisis Periods on the CEE Stock Markets: The Influence of the 2007 U.S. Subprime Crisis

The main goal of this paper is a direct identification of crisis periods on the eight Central and Eastern European (CEE) stock markets, and, for comparison, on the U.S. market. We employ a statistical procedure of dividing market states into up and down markets. Our aim is to examine whether crisis periods are common in various countries, and the results confirm Oct 2007 – Feb 2009 as the common period of the recent global financial crisis, except for Slovakia. Moreover, we investigate the effect of increasing cross–market correlations in the crisis period in the context of contagion, applying both standard contemporaneous correlations and volatility-adjusted correlation coefficients. Our results confirm that accommodating heteroskedasticity is crucial for detecting contagion across stock markets. The data consists of monthly logarithmic returns of the major CEE and the U.S. stock market indexes, in the period May 2004 – April 2013.

Dimensions of Market Liquidity: The Case of the Polish Stock Market

Liquidity in a financial market is not a one-dimensional variable but it includes several dimensions. The main aim of this paper is an empirical analysis of market liquidity dimensions on the Warsaw Stock Exchange (WSE). We investigate market depth and market tightness for the 53 WSE-listed companies divided into three size groups. The high-frequency data covers the period from January 3, 2005 to June 30, 2015. The additional goal is robustness analysis of the results obtained with respect to the whole sample period and three adjacent subsamples of equal size: the pre-crisis, crisis, and post-crisis periods. The order ratio (OR) is employed as a proxy of market depth, while market tightness is approximated using the relative spread (RS). In line with the expectations, the empirical results indicate that the OR values rather do not depend on firm size, while the RS estimates are slightly higher for small companies. Moreover, the results turn out to be robust to the choice of the sample. Furthermore, an initial research concerning interaction between liquidity dimensions on the WSE is provided by analyzing the degree of correlation between market depth and market tightness. In general, the correlation results are consistent with the literature. The majority of correlation coefficients between daily estimates of the order ratio and the relative spread indicators are not significantly different from zero.

Asymmetry Effects in Volatility on the Major European Stock Markets: the EGARCH Based Approach

The main goal of this paper is to investigate the asymmetric impact of innovations on volatility in the case of the largest European stock markets in the United Kingdom, France and Germany by using the EGARCH based approach. The sample period begins in January 2003 and ends in December 2016, and it includes the 2007 U.S. subprime crisis. The robustness analysis of empirical results is provided with respect to the whole sample and three adjacent subsamples, each of equal size: 1) the pre-crisis, 2) the Global Financial Crisis (GFC) and 3) the post-crisis periods. The GFC periods are formally detected by using a statistical method of dividing market states into bullish and bearish markets. Moreover, the common trading window procedure is employed to avoid the nonsynchronous trading problem in the group of investigated markets and to get the overlapping information set. We estimate univariate EGARCH models based on daily percentage logarithmic returns of major stock market indexes: FTSE100 (London), CAC40 (Paris), and DAX (Frankfurt). Pronounced negative asymmetry effects in volatility are presented in the case of all markets and are rather robust to the choice of the period. Our findings are consistent with the literature and suggest that the major European stock markets are more sensitive to ’bad’ than ‘good’ news.

Formal Identification of Crises on the Euro Area Stock Markets, 2004–2015

In this paper, crisis periods on the 19 euro area stock markets are formally detected and explored. A statistical method of dividing market states into bullish and bearish markets based on monthly logarithmic returns of major stock market indexes is employed. The sample period begins on January 2004, ends on December 2015, and includes the 2007–2009 Global Financial Crisis (GFC) and the subsequent euro area crises. Moreover, correctness of formal identification of down market periods is discussed utilizing two methods for verifying the bear market conditions. The empirical results indicate February 2009 as the end of the GFC for almost all countries investigated, except for Slovenia, Lithuania, Malta, Estonia, and Latvia, for which March 2009 is obtained as the end of the GFC. Furthermore, the findings concerning the European crises during the period beginning from late 2009 are in accord with the existing literature.

Liquidity Proxies Based on Intraday Data: The Case of the Polish Order-Driven Stock Market

The objective of this paper is to estimate selected liquidity measures based on high-frequency intraday data and to examine their magnitude on the Warsaw Stock Exchange (WSE). We construct and analyze a panel of data which consists of daily proxies of five liquidity estimates for 53 WSE-traded companies divided into three size groups. Although the WSE is classified as an order-driven market with an electronic order book, the raw data set does not identify trade direction. Therefore, the trade classification Lee and Ready (J Finance 46(2):733–746, 1991) algorithm is employed to infer trade sides and to distinguish between 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 subsamples each of equal size: the precrisis, global financial crisis (GFC), and postcrisis periods. The constructed panel of data would be utilized in further investigation concerning commonality in liquidity on the Polish stock market.

Measuring Dynamics of Financial Integration on the Euro Area Stock Markets, 2000–2016

The goal of this paper is to measure the dynamics of financial integration between the euro area stock markets over the long time period 2000–2016. The panel of data consists of monthly logarithmic returns of 19 major euro area stock market indexes. The evolution of the integration process is analyzed using a dynamic principal component approach. The index of integration, which measures the proportion of total variation in individual stock index logarithmic returns explained by the first principal component, serves as a measure of integration. The empirical results reveal that the dynamics of integration across the whole group of markets increased significantly after January 2008, during the global financial crisis (GFC). An inverted U-shaped pattern in the index of integration has been found in this period. The GFC and the subsequent euro area crises were formally detected based on the statistical procedure for an identification of down markets. Moreover, the estimation results of the index of integration turn out to be robust to the choice of a rolling window length.

Crisis periods and contagion effects in the CEE stock markets: the influence of the 2007 US subprime crisis

The main goal of this paper is a direct identification of crisis periods in the eight Central and Eastern European (CEE) equity markets, and, for comparison, in the US market. A statistical procedure of dividing market states into up and down markets is employed. The results confirm October 2007-February 2009 as the common period of the recent global financial crisis in the CEE markets, except for Slovakia. Moreover, the effect of increasing cross-market correlations in the crisis period in the context of contagion is investigated, applying both standard contemporaneous correlations and volatility-adjusted correlation coefficients. A research hypothesis that there was no contagion effect among the US and the CEE stock markets during the 2007-2009 crisis is explicitly tested. The robustness analysis of contagion tests based on monthly, weekly and daily data is provided. The results reveal that the utilised tests are rather less sensitive with respect to the choice of data frequency.