The purpose of this statistical Report is to present financial and behavioral situation of Polish stock companies.
The report consists of 2 parts:
• first part presents financial situation of the companies during 2020 with comparison to 2019;
• second part covers behavioral situation of the companies during 2020.
Additionally, the situation of Polish listed companies was compared with all non-financial enterprises in Poland and EU countries.
The first dataset is derived from the EMIS (formerly known as ISI Emerging Markets) website, with information on over 147 emerging markets. Formerly known as ISI Emerging Markets, the company was established in 1994, so it should be noted that its data for listed companies in Poland dates back to 1996.
The second database comes from World Bank and covers behavioral situation of enterprises during pandemic COVID-19: https://www.enterprisesurveys.org/en/survey-datasets
Additionally in order to compare the situation of the Polish stock companies with all non-financial enterprises in Poland and countries in EU was used BACH (Bank for the Accounts of Companies Harmonized) database.
The selected sample excludes all firms related to finance (section K of the Polish Classification of Activities 2007) as these inter alia feature different kinds of balance-sheet items, e.g. where assets and liabilities are concerned.
We can take a quick introductory look at the data. The structure of WSE companies by economic sections is as follows in 2020, compared to 2019, the number of enterprises decreased due to the bankruptcy of companies due to the COVID-19 pandemic. The largest number of enterprises were from the industrial sector (see Graph 1).
Let’s analyze the basic financial data of listed companies such as turnover and gross value added.
Not surprisingly, over the years we see a growing trend in average sales for companies, however, we see a sharp increase in 2020 (see Graph 2).
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Let’s take a closer look at the differences between 2018-2020 for our companies and how the sales project for different sectors.
Immediately we see that the increase in sales for construction and other services sectors was not that high. However, with the empirical knowledge, we should probably expect them to go down. The results could be attributed to the fact that the pandemic hit at the end of the first quarter of the year, and no one really could predict its impact, therefore, the effect was not immediate and the sales over the first months were probably not that reflective of the pandemic, especially in construction (longer contracts etc). Tourism could be a sector which saw an immediate response, however, we are not going to look that closely at sub-sectors of other services.
The highest increases can be observed for industry and trade, with trade more than doubling the mean sales in 2020 compared to the years before (see Graph 3).
We will look closer at the turnover of the companies across the countries and years for different sized companies based on Bach dataset.
In 2020, the growth rate of turnover slowed down in most countries, irrespective of the size class. The turnover growth rate decreased in manufacturing, construction, trade and accommodation and food services in most of the countries. This behavior was also more characteristic of medium-sized enterprises. Particularly large declines in the growth rate of sales revenues occurred for Belgium and Spain (see Graph 4).
Let’s analyze the gross value added for listed companies and compare it with the situation of companies in the EU.
Compared to sales, the gross value added measure already shows significant drops in all sectors, regardless of size. On the other hand, smaller companies are definitely the worst. Industry is most fragmented, especially before the pandemic.
Let’s analyze the above measure of gross value added for non-financial enterprises in Poland and in selected EU countries.
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Similar observations occurred also in the case of gross value added. All countries recorded a decline in the measure in 2020 across all enterprise sizes.
Return on Equity (ROE) measures profitability from the shareholder perspective as it measures the earnings of shareholders. After decomposing return on capital, this ratio can be linked to other measures of profitability such as return on assets (ROA), which measures the operating profit earned by the monetary unit of assets employed by firms, thus analyzing the overall profitability of firms, regardless of the asset financing structure. The above indicators have been considered in this note.
The ROE indicator in 2020 for small and medium-sized companies shows a downward trend as compared to large companies. The COVID-19 pandemic has fostered increased profitability for large listed companies (see Graph 7). For comparison, we will analyze the profitability of non-financial enterprises in EU countries.
No global ROE change pattern is clearly defined for all company groups by sector and size. However, large enterprises showed a marked decline in this indicator (see Graph 8).
To compare the financial situation of enterprises, the return on assets (ROA) was additionally analyzed.
When considering the ROA indicator for SMEs as for large enterprises, a general tendency to decline in all countries, except Poland, should be noticed.
The equity ratio indicates the percentage of all assets that are funded with equity. If a company resorts to more equity to pay for its assets, it exhibits a lower leverage ratio and therefore a more conservative capital structure.
Equity ratio in all groups of listed companies related to size in 2020 - the year of the pandemic - was higher compared to 2019 (see Graph 10).
The main exceptions were some countries with higher equity ratios in 2019, such as Poland and the Czech Republic and Spain. The main exceptions were some countries with higher equity ratios in 2019, such as Poland and the Czech Republic and Spain. The above trends were also maintained in 2020.
In 2020, weight of amounts owed to credit institutions in total liabilities showed a growing tendency in all industries except in construction industry (see Graph 12).
The weight of liabilities to credit institutions in total liabilities decreased in most countries in 2007-2019. Keeping the weight of total bank loans down liabilities were some countries whose equity ratios increased the most: Spain, Portugal, these decreases were mainly compensated by an increase in the weight of intra-group loans in total liabilities. France and Germany still belonged to the group of countries with the lowest weights of liabilities related to liabilities to credit institutions. In turn, Austria and Poland were the countries where the weight of liabilities to credit institutions in total liabilities was higher in 2019, while Slovakia and the Czech Republic were the countries with the highest increase in this ratio in 2007-2019, mostly balanced by a decrease in the weight of trade liabilities in total liabilities.
The ratio of EBITDA over interest on financial debt measures how easily a company can pay interest on unpaid financial debt with the help of the EBITDA it generates. When analyzing these indicators in 2007 and 2019, most countries also saw an improvement in their financial situation. This increase has generally been broken down by sector and size class. Slovakia, Spain and Italy were the countries where the EBITDA ratio over interest on financial debt increased the most, as their ratios more than doubled. The only exception was Germany, which recorded a decrease in this ratio, despite the fact that its companies’ EBITDA covered more than four times the interest paid in 2019. A country with a higher EBITDA than interest on financial debt in the following year, Slovakia stood out because the EBITDA generated by its companies was more than eighteen times the interest paid in 2019.
All companies which fully completed the questionnaires are open now. In each sector, less than 25% closed temporarily due to the outbreak. Majority did not file for bankruptcy. Across all sector, the surveyed companies received, or expect to receive some form of aid from the government.
To sum up, the observed patterns through the data in most cases confirmed our expectations of the behaviour of the companies during the outbreak, especially when considering the respective behaviours separately for different sectors and company sizes. The data was very interesting to work with, having three different datasets allowed us to create different plots and visualise the data in a clear way.