Commonalities in Returns in the Stock Markets of the Visegrad Group: A Quantile Coherency Approach

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.

PurposeThe current paper aims to expand an empirical assessment of correlations of the stock exchange in Poland with other stock markets and foreign economies. The paper attempts to explore international spillover effects during the current financial crisis.Design/methodology/approachThe study builds upon questionnaires and interviews with practitioners associated with the Polish stock market. The interviewees represent both the advanced and emerging European economies. At this point, analyzing the notions of a cross‐section of experts from different geographical regions increases the value of the findings. The interviewees were asked to comment on a wide range of examples mirroring the reaction of the Warsaw Stock Exchange (WSE) to economic and financial information derived from foreign markets in times of the current financial crisis. An empirical model evaluating the cross‐border implications for the Polish stock market was specified. The model encompassed a wide range of variables and events influencing the performance of the Polish stock market and investors' uncertainty during the nascent financial crisis. Semi‐structured interviews complemented the quantitatively obtained findings and allowed for a gap between theory and practice to be bridged. The qualitative approach injected a dose of realism into the empirical model utilized in the paper and contributed to the value of general findings.FindingsThe current paper reports initial responses of the WIG20 indexed equity prices to 41 economic and financial information sets, originating from systemically significant markets. The influence of these sets is ranked in accordance with their influential powers. The ranking indicates which information events are more likely to be prioritized by investors associated with the WSE and which news are ignored in times of the current financial crisis. Henceforth, the findings outline the crisis‐induced changes in the uncertainty of equity investors and the implications for investment decision making processes. Comparing the responses to economic and financial information sets among different stock markets and industries delivers insight into the profitability of the international portfolio diversification based on either the country or industry specific factors.Originality/valueThe paper focuses on the Polish stock market, which is relatively under‐researched by the existing body of literate. However, Poland's stock market became a leading central European bourse during the current financial crisis. Reporting a number of useful and important implications for the practitioners associated with the WSE constitutes the core value of the paper.

Purpose – The purpose of this paper is to examine the extent to which Central European emerging stock markets (focusing on Poland) have been affected by the recent international financial crisis, and how the current investment climate (barriers, risks, challenges and opportunities) influences appetite for investments in Polish equities. In doing so, the study aims to report timely findings in relation to the determinants of the safety and profitability of international portfolio diversification to the Polish stock market. Design/methodology/approach – Based on qualitative empirical research, the authors analyse the differences between the foreign (UK) and domestic (Poland) investors' views on equity investments in Poland. The study builds on questionnaires and interviews with practitioners associated with the Polish stock market. Findings – The authors report that the global financial crisis influenced changes to domestic and international investors' appetite for risk related to equity investments in emerging stock markets: investors are more prudent about emerging markets but the Polish stock market has shown substantial growth potential and positively distinguished itself from other Central European stock exchanges; particular types of investment risks associated with equity investments in the Polish stock market have abated. Polish equities are an attractive component of the international portfolio diversification, provided that trading strategies are adjusted to the contemporary investment environment. Originality/value – This paper addresses the absence of the academic literature devoted to the analysis of equity investments in the contemporary Central European emerging stock markets. The authors discuss the differences in appetite for risk between the UK and Polish investors and assumptions about investments in Poland. The authors also contribute to the international debate on investor protection and regulations that can improve investment processes.

Semi-Strong Information Efficiency of the Polish Stock Exchange Market in Various Market Situations

This study makes a comparative assessment of the relation between four waves of the COVID-19 pandemic and the stock market in Poland. We utilize the Autoregressive Moving Average-Asymmetric Dynamic Conditional Correlation-Generalized Autoregressive Conditional Heteroskedasticity models to depict the dynamic conditional correlations between Polish stock market and the US stock market. We use the wavelet approach to investigate the time-frequency connectedness between the COVID-19 pandemic and the stock markets. The sample used covers the period from 02.01.2019 to 04.04.2022. Our findings reveal a significant relation between pandemic variables and stock market. This evidence is more pronounced in the first and second wave of infections. In contrast, the impact was considerably smaller during the third and fourth waves.

The paper explains the different causes of the economic downturn effects after Olympics in each organizing nation, analyzes the host country's main stock index reaction to economic situation after Olympics and shows the trend and rule in stock market.In the end, it analyzes the highest growth of each host country's main stock index data as well as prominent fluctuation period of them.

The paper presents selected technical trading rules on the Polish stock market along with an estimate of the market’s profitability. Technical trading rules allow one to forecast changes to a stock price and identify buy and sell signals on Warsaw Stock Exchange. To do so, variable-length moving averages are applied to the main Polish stock indexes. To evaluate the economic effectiveness of the technical trading rules, t-statistics are used for testing the significance of the differences between average returns and the bootstrap techniques.

The efficient market hypothesis suggests that there are no opportunities to gain above‑normal profits using available information, because it is all reflected in the prices. However, calendar anomalies are found to contradict the efficient market hypothesis and enable investors to predict prices during specific days. Based on a review of papers on market efficiency and market anomalies, this paper examines and compares calendar effects known as ‘the month‑of‑the year effect’ and ‘the day‑of‑the‑week effect’ between the stock markets of three Central European countries: Poland, Hungary and the Czech Republic. The study has revealed the presence of calendar anomalies in the indexes representing small‑cap stocks listed on the Polish stock market and, to some extent, in the indexes used in the Hungarian and Czech stock markets.

This article focuses on and analyzes how the full-scale invasion of Russia on the territory of Ukraine on February 24, 2022, affected and continues to affect the part of the global capital market where securities are issued, bought and sold, namely the stock market. It is determined what any price changes are based on here; how stock markets can reflect the expectations of a certain group of people, in this case investors around the world, during a period of war; sanctions and pressure on the stock market. Also, the average response of twenty companies included in the Top-500 best stocks in the Center for Research in Security Prices database to percentage changes in the weighted commodity price index was evaluated. That is, we estimated how much a 1% change in the commodity price index would change the share prices of each of the 20 companies. It is determined separately how the military conflict affected the securities of American companies operating in various industries; for whom the war helped to increase capitalization, and for whom it contributed to the deterioration of the general financial condition. How the ranking of the best-performing S&P 500 stocks has changed in 2022. Why on September 13, the share prices of many global companies decreased, and the three main stock indexes (Dow Jones Industrial Average, Nasdaq Composite and S&P 500) had their worst day since June 2020. Forecast of their further changes. Separately, in addition to the American one, the changes that took place in the stock markets of Eastern countries, using the example of China, Thailand, India and Indonesia, are highlighted. Expected changes in the Russian stock market and the possibility of its complete disappearance due to sanctions imposed by various countries of the world are described. The situation on the market of Ukraine itself and the options of what exactly to invest in for domestic investors during the period of active military operations were considered. In addition to all this, the solution to problems related to the volatility of the stock market is highlighted. Thus, the question of the influence of the war between Ukraine and Russia on the state of the world stock markets, in modern realities, is paid a lot of attention not only by Ukrainian scientists, but also by foreign ones. This is not surprising, since it is impossible to ignore that the recent events have caused a chain effect, affecting firstly the prices of goods, the volume of exports, and subsequently the capitalization and growth or decline of the prices of securities of companies around the world.

Abstract:This study examines the existence of rational speculative bubbles in three Central European stock markets. The possibility of stock bubbles arises from historical stock market inefficiency as well as from the most recent stock market boom and crash resulting from the U.S. subprime mortgage crisis. In this study, we employ the duration dependence test for bubble detection, which provides reliable results for the specific properties of the studied markets. In addition to the stock market indexes, the prices of individual blue chip stocks are investigated in order to identify the sources of bubbles. We determined that there was an asset bubble in the Polish stock market in the period 2004-7 and narrow its origins down to chemical and energy company stocks. Speculative bubbles also were detected in Hungarian renewable-energy technology stocks.

Size, Value and Liquidity: Do They Really Matter on an Emerging Stock Market?

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.

Objective The main purpose of this article is to assess the potential implications of machine learning in making investment decisions when investing capital in stock markets. The analysis carried out focuses on the so-called day-trading, i.e., investing for very short periods of time, covering only one stock market session. The hypothesis adopted by the authors is that the use of machine learning can, under certain conditions, effectively contribute to attractive rates of return for players making short-term investments. Methodology The study used Microsoft Machine Learning Studio’s Azure tool to enable machine learning-based computing. Thanks to this publicly available computing platform, any potential interested investor can create a model and test it. An important assumption of the described study is the adoption of a short investment horizon for the calculation. The calculations used data from five stock market sessions, so that the most recent data is taken into account. Findings Based on the calculations, the authors observed that the methodology adopted for applying machine learning to investment decision-making can be a valuable tool to help make short-term investment decisions. Value Added The research made can be used in a practical way by investors when they transact in the stock market. Recommendations It should be noted that the presented method requires updating the data on which the predictions are made every time. Further in-depth research is also needed to determine the impact of the number of financial instruments on the effectiveness of the learning process.

:This study examines the existence of rational speculative bubbles in three Central European stock markets. The possibility of stock bubbles arises from historical stock market inefficiency as well as from the most recent stock market boom and crash resulting from the U.S. subprime mortgage crisis. In this study, we employ the duration dependence test for bubble detection, which provides reliable results for the specific properties of the studied markets. In addition to the stock market indexes, the prices of individual blue chip stocks are investigated in order to identify the sources of bubbles. We determined that there was an asset bubble in the Polish stock market in the period 2004-7 and narrow its origins down to chemical and energy company stocks. Speculative bubbles also were detected in Hungarian renewable-energy technology stocks.

This study thoroughly analyzes the stock market efficiency hypothesis - its weak form - in the Czech Republic, Poland and Hungary in 1995-2005. It aims to reveal whether trading on historical information about stock prices or indices may lead to economically significant abnormal profits and whether the analyzed markets are comparably efficient. It also tests relative efficiency of the Central European markets compared to developed capital markets that are considered the most effective - the American NYSE, German and Netherlands stock exchanges. Complexity of the results is enhanced by analyzing daily, weekly and monthly returns of both the major regional indices - the Czech PX-50 and PX-D, Hungarian BUX and Polish WIG20 - and individual shares that constitute the indices. Moreover, consequences of the non-synchronous trading for autocorrelations are discussed. In conclusion, the Central European region must be considered as a heterogeneous market. While the Hungarian market generally complies with the hypothesis and behaves weakly efficient, significant linear dependences are typical for the Czech stock market. Some unsystematic departures from the random walk model persist in Poland and the efficiency market hypothesis can not be validated there. Any abnormally profitable investment strategy that exploits technical analysis should thus avoid Hungarian stocks and exploit short-term dependences on the Czech and, to a lesser extant, Polish stock market.