Archetypal Analysis and DEA Model, Their Application on Financial Data and Visualization with PHATE

One of the goals of macroeconomic analysis is to rank and segment enterprises described by many financial indicators. The segmentation can be used for investment strategies or risk evaluation. The aim of this research was to distinguish groups of similar objects and visualize the results in a low dimensional space. In order to obtain clusters of similar objects, the authors applied a DEA BCC model and archetypal analysis for a set of companies described by financial indicators and listed on the Warsaw Stock Exchange. The authors showed that both methods give consistent results. To get a better insight into the data structure as well as a visualization of the similarities between objects, the authors used a new approach called the PHATE algorithm. It allowed the results of DEA and archetypal analysis to be visualized in a low dimensional space.

Risk Information in Non-Financial Disclosure

This paper aims to research the topics related to risk included in non-financial disclosure (NFD) of companies listed on the Warsaw Stock Exchange (WSE) and explore factors that influence the risk topics ratio in NFD. We applied a content analysis using topic modeling to discover latent risk topics in NFD. Next, with Ward’s clustering, we identified four groups of companies with a homogenous risk topic mixture. For causal analysis, to explain the differences in risk topics ratio, we used qualitative comparative analysis (QCA), which allowed us to obtain three paths (variable configurations) leading to the high ratio of risk topics in NFD. Our results suggest that companies disclosing risk information extensively in their NFDs concentrate almost solely on social risk matters. In contrast, companies talking briefly about environmental and social (E&S) risk prepare their NFDs with a more balanced distribution of E&S topics and their financial implication. In general, the companies’ exposure to E&S risk and the use of NFD standards and guidelines as well as the type of NFD impact the space dedicated to risk information. This paper contributes to academics and regulators, filling the gap about risk disclosure in the NFD, identifying the nature of corporate risk disclosures, and upgrading research about determinants of risk information in non-financial disclosure.

The review of the financial strategies of Polish pulp and paper companies listed on the Warsaw Stock Exchange

The review of the financial strategies of Polish pulp and paper companies listed on the Warsaw Stock Exchange. The main purpose of this paper is to evaluate the financial strategy undertaken by the polish pulp and paper companies listed on Warsaw Stock Exchange in 2018 - 2020. In this paper three most frequently used indicators characterising company’s financing strategy were analysed, namely: equity capital share in total capital, equity capital share in fixed assets and long-term debt share in total debt. The calculations used data from publicly available quarterly financial statements of the analysed enterprises for the period from 1st quarter of 2018 to 3rd quarter of 2020. The calculations showed that Kompap has a more moderate policy of financing its activity. The second company, Arctic Paper, was characterized by a more risky approach to the financing strategy.

The Economic Effect of the Pandemic in the Energy Sector on the Example of Listed Energy Companies

The study posed a research question: did the situation caused by COVID-19 affect the economic position of energy companies? The aim of the study is to investigate the impact of the situation of the epidemic state introduced in 2020 on the activities of the efficiency of energy sector companies. The subject of the research will be the ten largest Polish power plants in terms of electricity production, including four capital groups to which they belong. Financial data from 2014 to 2020 will be used for the research. To test the effectiveness, the tools of the ratio analysis will be used. The analysis of the financial statements in terms of investments in manufacturing activities confirms the hypothesis that companies investing in new solutions and technologies will be best prepared for an exceptional situation. The results of the research show that those capital groups which in the period preceding the outbreak of the epidemic made the largest investment outlays and at the same time their financial ratios and market valuation on the Warsaw Stock Exchange were the highest, they also achieved the highest financial results during the pandemic—they had the most favorable economic situation.

Pyramidal Ownership and Company Value: Evidence from Polish Listed Companies

This paper examines the effects of pyramidal ownership. Using the sample of 162 non-financial companies listed on the Warsaw Stock Exchange during the period 2010-2014, we verify the relation between the adoption of a pyramidal structure and company value. Specifically, we show that the link between pyramidal ownership and company value is more complex than previously thought addressing the aspect of ownership concentration and dual class shares. Our results indicate that the use of pyramids is associated with a higher value measured by Tobin’s Q, supporting the efficient monitoring hypothesis. Contrary to our expectations the combination of pyramidal ownership and dual class shares is correlated with lower Q. Finally, while the adoption of a pyramid by a majority shareholder does not impact firm value, the combination of a pyramid, ownership concentration and dual class shares is associated with higher Q. This finding suggests that the blockholder ownership outweighs the possible cost of excessive disproportionate ownership and that pyramids and dual class shares have different effects on company value.

Artificial Neural Networks Performance in WIG20 Index Options Pricing

In this paper, the performance of artificial neural networks in option pricing was analyzed and compared with the results obtained from the Black–Scholes–Merton model, based on the historical volatility. The results were compared based on various error metrics calculated separately between three moneyness ratios. The market data-driven approach was taken to train and test the neural network on the real-world options data from 2009 to 2019, quoted on the Warsaw Stock Exchange. The artificial neural network did not provide more accurate option prices, even though its hyperparameters were properly tuned. The Black–Scholes–Merton model turned out to be more precise and robust to various market conditions. In addition, the bias of the forecasts obtained from the neural network differed significantly between moneyness states. This study provides an initial insight into the application of deep learning methods to pricing options in emerging markets with low liquidity and high volatility.

Diversification Perspectives of a Single Equity Market: Analysis on the Example of Selected CEE Countries

The study addresses the benefits of a unified stock market in terms of diversification risk for the eight CEE stock markets. For this purpose, each stock market was treated as a separate portfolio based on the companies listed during 2018–2019. Portfolio diversification techniques were used to identify risk linked with the eight Central Eastern European stock markets. The results show that the stock market with the lowest diversification risk was the Bulgarian Stock Exchange, followed by the Prague Stock Exchange, the Ljubljana Stock Exchange, and at the end stands the Zagreb Stock Exchange. The portfolio constructed from the Zagreb Stock Exchange carries the highest portfolio risk, but it also offers the highest weekly weighted average returns. Stock markets that benefit in terms of portfolio risk from unification are the Bratislava Stock Exchange, the Budapest Stock Exchange, the Bucharest Stock Exchange, the Warsaw Stock Exchange, and the Zagreb Stock Exchange. The indexes where the portfolio risk increases at the time of unification are the Bulgarian Stock Exchange, the Ljubljana Stock Exchange, and the Prague Stock Exchange. From a managerial perspective, financial investors get a novel outlook on the diversification possibilities offered within a hypothetical unified CEE stock market.

Capital Structure of Companies Listed at the Warsaw Stock Exchange and the COVID-19 Pandemic Effect on Their Risk

Subject: The financial management of companies is examined in the context of the COVID-19 pandemic. Specifically, the relationship between their capital structure and risk changes during the pandemic is scrutinised. The purpose of the article: To determine how companies’ total, systematic and idiosyncratic risks changed during the COVID-19 pandemic depending on their capital structure based on a sample of organisations listed at the Warsaw Stock Exchange. Methodology: The study involves the use of a panel data regression model. Results of the research: The COVID-19 pandemic had an impact on the risk of overleveraged companies and underleveraged ones alike. Its influence on their total risk was weaker among the underleveraged organisations. Regarding systematic risk, its levels did not generally change significantly in the wake of the pandemic, but idiosyncratic risk, only in the case of the overleveraged companies increased statistically significantly.

Changes in the Stock Market of Food Industry Companies during the COVID-19 Pandemic—A Comparative Analysis of Poland and Germany

The COVID-19 pandemic had a dramatic effect on the world economy, leading to disturbances in the global agri-food system. Disrupted supply chains caused instability in the market resulting in mixed reactions among market participants. The balance in the access and availability of food was disturbed at various levels starting from local up to international. Partial lockdowns of economies affected the equilibrium on the labor market in the food sector, the level of income and food security. The aim of this study was to determine the effect of shock caused by the COVID-19 pandemic on rates of return from shares of companies in the agri-food sector listed in Poland and Germany, as well as indicate dependencies between restrictions imposed by the investigated countries and changes in the rates of return from shares as a result of the pandemic. The source of data for the analyses of the capital markets in Poland and Germany was the Thomson Reuters database. In order to determine the effect of shock caused by the coronavirus pandemic and restrictions imposed by the states on the capital market the abnormal rates of return were calculated for shares of 24 Polish and 23 German companies from the food sector. The investigated Polish companies were listed on the Warsaw Stock Exchange, while the German companies were listed on the Frankfurt Stock Exchange and other stock exchanges in Germany. Calculations were based on stock market indexes: for the Polish stock exchange it was WIG and WIG-food, while for the German capital market it was DAX and DAX Food & Beverages. In this study the Stringency Index was also used as a tool to follow the response of the governments to the coronavirus pandemic. The results indicate that following the pandemic outbreak large reductions were observed for cumulative rates of return from shares as a consequence of the pandemic both in Poland and Germany. Abnormal cumulative rates of return for the investigated companies were comparable. Markedly greater increases in abnormal rates of return were recorded for the Polish companies of the food sector listed at the Warsaw Stock Exchange. The Stringency Index indicates that restrictions imposed by the German authorities in response to the coronavirus pandemic were slightly more radical than those introduced by the Polish government.