Theoretical background: A share split is an operation that increases the total number of shares. The split is a technical operation and should not affect the market value of the company. The shareholding structure of the company remains unchanged when the shares are split. However, split studies around the world show the occurrence of abnormal returns. Purpose of the article: The article analyses splits based on market data from 2009 to 2021. The aim of the study is to analyse the cumulative average abnormal returns (CAARs) in the periods preceding stock splits on the Warsaw Stock Exchange (WSE). CAARs are analysed in different research variants. The influence of the stock market situation and the frequency of splits on the amount of abnormal returns is examined. Research methods: The research was carried out using event study analysis. The Market-Adjusted Return Model was used to determine abnormal returns. CAARs were calculated for each analysed event window. The statistical significance of abnormal returns was verified by the parametric t test and the non-parametric Corrado rank test. Main findings: The study showed statistically significant positive abnormal returns in the 30-day period preceding the split. The hypothesis that multiple splits cause particularly high increases in the market value of companies has not been confirmed. Research on the reaction to splits depending on the state of the stock market situation did not allow unambiguous conclusions in the case of the periods when the WSE Index (WIG) increased. Weaker reaction to planned splits in the period of worse market conditions was confirmed.
This paper studies an impact of futures expiration days on the Polish equity market. From three potential expiration effects appearing in the literature (namely, the increased trading volume of underlying assets, increased volatility of their returns, and price reversal after expiration), the latest one is researched in detail for expiration days of futures on the WIG20 index, the mWIG40 index, and individual stocks. The data covers the period from January 2001 to December 2016. The phenomenon of price reversal is studied with the use of regression models, price reversal measures, and event study methodology. The results obtained for expiration days are compared with the results from non-expiration days to check whether potential price reversal can be interpreted as an effect of expiration. No price reversals after futures expirations were found in the returns of the WIG20 nor mWIG40 indexes. In the case of individual stocks, results from all of the three methods support the assumption that price reversal occurs after expiration. The reversal is immediate and is reflected inovernight returns more than in daily returns.
Event studies make it possible to quantify the market reaction to releases of various types of information. An event study is one of the few tools that may be used to determine a causal effect. The aim of this paper is to present and explain an algorithm for conducting an event study that academics and practitioners who represent the accounting discipline may apply to investigate the market reaction to various events, such as releases of accounting information. The algorithm comprises six steps: 1) identifying the event that is going to be examined, 2) selecting companies, 3) identifying when information about the event was released and identifying the event window, 4) choosing an estimation window, 5) choosing and estimating a model of normal investor behavior, and calculating the abnormal level of investor behavior, 6)verifying statistical hypotheses with the use of parametric and non-parametric tests. The paper fills the research gap by presenting the kernel of an event study and the usefulness of event studies in empirical accounting research. Analysis and critique of the literature are used as the research method.
PL
Analiza zdarzeń umożliwia kwantyfikację reakcji rynku na ujawnienie różnego typu informacji. Analiza zdarzeń jest jednym z niewielu narzędzi, które mogą być używane do ustalenia związku przyczynowo-skutkowego. Celem artykułu jest przedstawienie i wyjaśnienie algorytmu analizy zdarzeń, który może być wykorzystany przez badaczy i praktyków reprezentujących dziedzinę rachunkowości do zbadania reakcji rynku na różne zdarzenia, takie jak ujawnienie informacji z rachunkowości. Algorytm składa się z sześciu kroków: identyfikacja zdarzenia, dobór przedsiębiorstw, identyfikacja czasu upublicznienia informacji o zdarzeniu i identyfikacja okna zdarzenia, wybór okna estymacyjnego, wybór i estymacja modelu normalnego działania inwestorów oraz obliczanie jego nietypowego poziomu, weryfikacja hipotez statystycznych z wykorzystaniem parametrycznych i nieparametrycznych testów. Artykuł wypełnia lukę badawczą poprzez przedstawienie sedna analizy zdarzeń i jej użyteczności w empirycznych badaniach w rachunkowości. W opracowaniu wykorzystano metodę analizy i krytyki piśmiennictwa.
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