We analyze the impact of Eurozone/Germany and U.S. macroeconomic news announcements and the communication of the monetary policy settings of the ECB and the Fed on the forex markets of new EU members. We employ an Event Study Methodology to analyze intra-day data from 2011-2015. Our...

We examine the predictability of expected stock returns across horizons using machine learning. We use neural networks, and gradient boosted regression trees on the U.S. and international equity datasets. We find that predictability of returns using neural networks models decreases with longer...

A prominent factor used in most models predicting stock returns is firm size. Yet no consensus has emerged on the magnitude and stability of the size premium, with some researchers even questioning the usefulness of the factor. To take stock of the voluminous academic literature on the size...

We introduce a methodology for dynamic modelling and forecasting of realized covariance matrices based on generalization of the heterogeneous autoregressive model (HAR) for realized volatility. Multivariate extensions of popular HAR framework leave substantial information unmodeled in residuals....

We study volatility spillovers among commodity and equity markets by employing a recently developed approach based on realized measures and forecast error variance decomposition invariant to the variable ordering from vector-autoregressions. This enables us to measure total, directional and net...

In the paper, we research on the presence of long-range dependence in returns and volatility of BUX, PX and WIG between years 1997 and 2009 with use of classical and modified rescaled range. Moving block bootstrap with pre-whitening and postblackening is used for the construction of confidence...

In the paper we test for the different reactions of stock markets to the current financial crisis. We focus on Central European stock markets, namely the Czech, Polish and Hungarian ones, and compare them to the German and U.S. benchmark stock markets. Using wavelet analysis, we decompose a time...

Estimates of U.S. returns differentials have ranged from exorbitant to quite small, in part because of their volatility coupled with the relatively short time series available. We shed light on underlying drivers of returns differentials by presenting a number of decompositions: a by-asset-class...

We study the impact of news embedded in scheduled macroeconomic announcements on the government bond market in Poland and the Czech Republic. We conduct an event study on intraday data and time-series regressions using daily data over an eight-year period, distinguishing between effects under...