Browsing by Subject "intraday data"

Now showing 1 - 5 of 5

Access status: Open Access ,
How to define macroeconomic announcement surprises? An example of the impact of US macroeconomic news on stock prices on the Warsaw Stock Exchange
(Wydawnictwa AGH, 2022) Wójtowicz, Tomasz
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.
Access status: Open Access ,
Intraday patterns in time-varying correlations among Central European stock markets
(2016) Wójtowicz, Tomasz
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.
Access status: Open Access ,
Price duration versus trading volume in high-frequency data for selected DAX companies
(2016) Gurgul, Henryk; Syrek, Robert; Mitterer, Christoph
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.
Access status: Open Access ,
The logarithmic ACD model - the microstructure of the German and Polish stock markets
(2016) Gurgul, Henryk; Syrek, Robert
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.
Access status: Open Access ,
The testing of causal stock returns-trading volume dependencies with the aid of copulas
(2013) Gurgul, Henryk; Mestel, Roland; Syrek, Robert
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.