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1

How to define macroeconomic announcement surprises? An example of the impact of US macroeconomic news on stock prices on the Warsaw Stock Exchange

Wójtowicz Tomasz

Managerial Economics

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2022

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Vol. 23, no. 1

77--98

EN

The definition of a news surprise plays a crucial role in the analysis of the impact of unexpected macroeconomic news announcements. In this paper, we study the properties of the most commonly used measure of news surprise, defined as the difference between the announced and expected value of the indicator. Due to the high vulnerability of this measure to outliers, we consider alternative definitions of macroeconomic surprises. Based on the analysis of announcements of 15 American macroeconomic indicators, we show that taking into account the heterogeneity of analysts’ forecasts or the variability of the previous surprises, noticeably improves the properties of the distribution of surprise measures. An additional study performed with the use of a dynamic model proves a strong linear relationship between surprise measures and WIG20 returns in the first five minutes after news announcements.

2

Measurement of stock market liquidity supported by an algorithm inferring the initiator of a trade

Olbryś J., Mursztyn M.

Operations Research and Decisions

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2017

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Vol. 27, No. 4

111--127

EN

The aim of this study is to assess and analyse selected liquidity/illiquidity measures derived from high-frequency intraday data from the Warsaw Stock Exchange (WSE). As the side initiating a trade cannot be directly identified from a raw data set, firstly the Lee–Ready algorithm for inferring the initiator of a trade is employed to distinguish between so-called buyer- and seller-initiated trades. Intraday data for fifty-three WSE-listed companies divided into three size groups cover the period from January 3, 2005 to June 30, 2015. The paper provides an analysis of the robustness of the obtained results with respect to the whole sample and three consecutive subsamples, each of equal size: covering the precrisis, crisis, and post-crisis periods. The empirical results turn out to be robust to the choice of the period. Furthermore, hypotheses concerning the statistical significance of coefficients of correlation between the daily values of three liquidity proxies used in the study are tested.

3

The logarithmic ACD model: The microstructure of the German and Polish stock markets

Gurgul H., Syrek R.

Managerial Economics

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2016

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Vol. 17, no. 1

77--92

EN

The main goal of this paper is to compare the microstructure of selected stocks listed on the Frankfurt and Warsaw Stock Exchanges. We focus on the properties of duration on both markets and on fitting the appropriate ACD models. Because of the quite different levels of capitalization of stocks on these markets, we observe essential discrepancies between these stocks. While for most German companies on the DAX30, the Burr distribution fits better than generalized gamma distribution, the latter distribution is superior in the case of the largest Polish companies. Analyzing series by hazard function, we note the similarity of hazard functions for companies on both markets, which tend to have a U-shaped pattern.

4

Price duration versus trading volume in high-frequency data for selected DAX companies

Gurgul H., Syrek R., Mitterer C.

Managerial Economics

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2016

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Vol. 17, no. 2

241--260

EN

The main goal of this paper is to gain insights into the dependence structure between the duration and trading volume of selected stocks listed on the Frankfurt Stock Exchange. We demonstrate the usefulness of the copula function to describe the dependence of specific unevenly spaced time series. The properties of the time series of price durations and trading volumes under study are in line with common observations from other empirical studies. We observe clustering, overdispersion, and diurnality. For most of the stocks, the seminal model (linear parametrization with exponential or Weibull distribution) can be replaced by a logarithmic specification with more-flexible conditional distributions. The price duration and trading volume associated with this duration exhibit dependence in the tails of distribution. We may conclude that high cumulative trading volumes are associated with long duration. However, changes of price over short times are related to low cumulative volume.

5

Intraday patterns in time-varying correlations among Central European stock markets

Wójtowicz T.

Managerial Economics

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2016

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Vol. 17, no. 1

149--162

EN

In this paper we investigate intraday relationships between three Central European stock exchanges: those in Frankfurt, Vienna and Warsaw. They represent different types of stock markets: two of them are developed, while the last is an emerging market. Via DCC-GARCH models we analyze and compare time-varying conditional correlations of intraday returns of the main indices of the stock exchanges. We study the impact of important public information, US macroeconomic news announcements, on the strength of interrelationships between the markets. Additionally, we analyze diurnal patterns in time-varying correlations on different days of the week.

6

Comparison of selected trade classification algorithms on the warsaw stock exchange

Olbryś J., Mursztyn M.

Advances in Computer Science Research

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2015

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Nr 12

37--52

EN

Empirical equity market microstructure research often requires knowledge about trade sides. It is important to recognize the side that initiates the transaction and to distinguish between the so called buyer- and seller-initiated trades. Unfortunately, most data sets do not identify the trade direction. Therefore, researchers rely on indirect trade classification rules to infer trade sides. The aim of this paper is to implement and compare four trade classification algorithms on the Warsaw Stock Exchange (WSE). The high-frequency data for the selected WSE-listed companies covers the period from January 3, 2005 to June 30, 2015. To check the robustness of empirical results to the choice of sample, three adjacent sub-periods of equal size: the pre-crisis, crisis, and post-crisis period are analysed. The Global Financial Crisis on the WSE is formally established as the period June 2007-February 2009.

PL

Badania empiryczne w zakresie mikrostruktury rynku często wymagają wiedzy na temat stron transakcji. Szczególnie ważna jest identyfikacja strony inicjującej transakcje oraz podział na transakcje inicjowane przez nabywcę i sprzedającego. Niestety, większość baz danych intraday nie zawiera takich informacji. Dlatego badacze korzystają z pośrednich metod klasyfikacji. Celem pracy była implementacja i porównanie czterech algorytmów klasyfikacji transakcji na Giełdzie Papierów Wartościowych w Warszawie S.A. Badanie przeprowadzono z wykorzystaniem sróddziennych danych transakcyjnych akcji trzech reprezentatywnych firm, należących do grup spółek dużych (grupa BIG), średnich (grupa MEDIUM) i małych (grupa SMALL). Były to odpowiednio spółki: KGH, MCI oraz ENP. Wszystkie charakteryzują się stosunkowo wysoką płynnością na tle grup, do których należą. Analizy objęły okres od 3 stycznia 2005 do 30 czerwca 2015, z wyróżnieniem trzech jednakowo licznych podokresów: przed kryzysem, kryzys, po kryzysie. Okres globalnego kryzysu finansowego na giełdzie warszawskiej został ustalony w sposób formalny jako przedział czasowy czerwiec 2007-luty 2009.

7

The testing of causal stock returns-trading volume dependencies with the aid of copulas

Gurgul H., Mestel R., Syrek R.

Managerial Economics

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2013

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nr 13

21--44

EN

This paper is concerned with a dependence analysis of returns, return volatility and trading volume for five companies listed on the Vienna Stock Exchange. Taking into account the high frequency data for these companies, tests based on a comparison of Bernstein copula densities using the Hellinger distance were conducted. It is worth noting that these tests can be used in general settings since there is no restriction on the dimension of the data. The parameter which must be set up for the testing procedure is a bandwidth. It is necessary for estimation of the nonparametric copula. The paper presents some patterns of causal relationships between stock returns, realized volatility and expected and unexpected trading volume. There is linear causality running from realized volatility to expected trading volume, and a lack of nonlinear dependence in the opposite direction. The authors detected strong linear and nonlinear causality from stock returns to expected trading volume. Therefore, a knowledge of past stock returns can improve forecasts of expected trading volume. They did not find causality running in the opposite direction.

PL

W artykule przeprowadzono analizę zależności pomiędzy stopami zwrotu, ich zmiennością oraz wielkością obrotów pięciu spółek notowanych na Wiedeńskiej Giełdzie Papierów Wartościowych. Wykorzystując dane wysokiej częstotliwości, przeprowadzono testy, wykorzystując kopule Bernsteina oraz odległość Hellingera. Warto zauważyć, że testy te mogą być zastosowane dla dowolnej liczby zmiennych. Jedynym parametrem, który musi określić badacz, jest parametr określający dokładność oszacowania nieparametrycznych gęstości kopuł. W pracy zaprezentowano pewne wzory zależności przyczynowych pomiędzy stopami zwrotu, zmiennością oraz oczekiwanym i nieoczekiwanym wolumenem. Wykazano, że istnieje zależność przyczynowa od zmienności zrealizowanej do oczekiwanego wolumenu i brak takiej zależności w odwrotnym kierunku. Wykryto silną zależność przyczynową liniową oraz nieliniową od stóp zwrotu do oczekiwanego wolumenu. Oznacza to, że znajomość historycznych stóp zwrotu może być pomocna w prognozowaniu oczekiwanego wolumenu. Nie wykryto zależności w kierunku przeciwnym.