Wszystkie pola: Będowska-Sójka, Barbara - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: Macroeconomic News Effects on the Stock Markets in Intraday Data
Autorzy:: Będowska-Sójka, Barbara
Powiązania:: https://bibliotekanauki.pl/articles/483253.pdf
Data publikacji:: 2013
Wydawca:: Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:: intraday returns
macro surprises
news effect
periodicity
volatility
Opis:: The aim of the paper is to compare reactions of two stock markets, the German and the French, to releases of macroeconomic fundamentals emanating from Germany and the U.S. We examine the reaction of intraday returns and volatility of the CAC40 and the DAX indices to macroeconomic surprises. We find that both American and German macroeconomic releases cause an immediate response in returns and volatility of the German and the French stock market sampled at a five-minute frequency. The reaction to the American macroeconomic surprises is stronger than to the German ones.
Źródło:: Central European Journal of Economic Modelling and Econometrics; 2013, 5, 4; 249-269
2080-0886
2080-119X
Pojawia się w:: Central European Journal of Economic Modelling and Econometrics
Dostawca treści:: Biblioteka Nauki

Artykuł

Skocz do pozycji: 2.

Tytuł:: Do mixed-data sampling models help forecast liquidity and volatility?
Autorzy:: Będowska-Sójka, Barbara
Kliber, Agata
Powiązania:: https://bibliotekanauki.pl/articles/2139332.pdf
Data publikacji:: 2022-10-31
Wydawca:: Główny Urząd Statystyczny
Tematy:: liquidity
volatility
effective spread estimator
MIDAS
Opis:: This paper aims to contribute to the existing studies on the Granger-causal relationship between volatility and liquidity in the stock market. We examine whether liquidity improves volatility forecasts and whether volatility allows the improvement of liquidity forecasts. The forecasts based on the mixed-data sampling models, MIDAS, are compared to those obtained from models based on daily data. Our results show that volatility and liquidity forecasts from MIDAS models outperform naive forecasts. On the other hand, the application of mixed-data sampling models does not significantly improve the performance of the forecasts of either liquidity or volatility based on a univariate autoregressive model or a vectorautoregressive one. We found that in terms of the forecasting ability, the VAR models and the AR models seem to perform equally well, as the differences in forecasting errors generated by these two types of models are not statistically significant.
Źródło:: Przegląd Statystyczny; 2022, 69, 2; 1-19
0033-2372
Pojawia się w:: Przegląd Statystyczny
Dostawca treści:: Biblioteka Nauki

Artykuł

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