How smooth is the stock market integration of CEE-3?

We study the stock market integration of emerging CEE-3 stock markets (namely, the Czech, Hungarian, and Polish markets) and hypothesize that this process has been gradual over time. As a proxy for integration, co-movements with three stock market indices that represent the developed markets (i.e., MSCI Germany, the Dow Jones Euro Stoxx 50, and MSCI World) are estimated using the standard, asymmetric, and corrected DCC-GARCH model. A smooth transition logistic trend model is then fitted to the dynamic correlations to examine the integration process. Evidence of strengthening relationships among the markets under study is provided.http://deepblue.lib.umich.edu/bitstream/2027.42/132978/1/wp1079.pd

The Real Convergence of CEE Countries: A Study of Real GDP per capita

The paper examines the unconditional sigma and time-series convergence of real GDP per capita (measured in national currencies and euros) for CEE8 countries during the 1995 : Q1 – 2011 : Q1 period by applying the unit root fra-mework using the DF-GLS test and the Lee and Strazicich (2003; 2004) test, which allows for endogenous breaks in trends and constants. We selected Germany as a benchmark country for relative real GDP per capita because of its geographical and economical position relative to all CEE8 countries. We have found that both sigma convergence and time-series convergence were present for most of the CEE8 countries prior to the breaks in trends, but after the breaks, the convergence slowed or reversed and thus indicated divergence

What Drives the Stock Market Integration in the CEE-3?

In this article, we study the possible explanatory power of macroeconomic factors that may drive the stock market integration between the Czech Republic, Poland and Hungary (CEE-3) and developed countries, using Germany as a benchmark. Our findings suggest that the recent global financial crisis has affected time-varying correlations between certain stock markets more substantially than the entry of the CEE-3 into the EU. The results of our analysis of the effects of these macroeconomic factors were inconclusive. Only our proxy of exchange rate risk was significant in all cases, with positive effects on integration, thus supporting the presence of contagion among different markets

Predicting changes in the output of OECD countries: An international network perspective

We use a simple linear regression framework to present evidence, that complex relationships between stock markets and economies may be used to predict changes in the output of 27 OECD countries. We construct new unidirectional return co-exceedance networks to account for complex relationships between stock market returns, and between real economic growths. Although there is heterogeneity between individual country level results, overall our data and analysis provides evidence that topological properties of our networks are useful for in-sample prediction of next quarter changes in the output

Impact of wind and solar production on electricity prices: Quantile regression approach

This is is an Accepted Manuscript of an article published by Taylor & Francis in Journal of the Operational Research Society on 5 August 2019, available online: http://www.tandfonline.com/10.1080/01605682.2019.1634783.We study the impact of fuel prices, emission allowances, demand, past prices, wind and solar production on hourly day-ahead electricity prices in Germany over the period from January 2015 until June 2018. Working within a linear regression, ARX-EGARCH and quantile regression framework we compare how different pricing factors influence the mean and quantiles of the electricity prices. Contrary to the existing literature, we find that short-term price fluctuations on the fuel markets and emission allowances have little effect on the electricity prices. We also find that day-of-the-week as well as monthly effects have significant impact on the electricity prices in Germany and should not be ignored in model specifications. Three main factors are found to drive extreme prices: price persistence, expected demand and expected wind production. Our findings contribute to understanding of extreme price movements, which can be used in pricing models and hedging strategies.acceptedVersio

Volatility and dynamic conditional correlations of European emerging stock markets

This study examines the relationship between time-varying correlations and conditional volatility among eight European emerging stock markets and the MSCI World stock market index from January 2000 to December 2012. Correlations are estimated in the standard and asymmetric dynamic conditional correlation (DCC) model frameworks. The results can be summarized by three main findings: (1) asymmetry in volatility is not a common phenomenon in emerging markets; (2) asymmetry in correlations is found only with respect to the Hungarian stock market; and (3) the relationship between volatility and correlations is positive and significant in all countries included in the study. Thus, diversification benefits decrease during periods of higher volatility

Volatility and dynamic conditional correlations of European emerging stock markets

This study examines the relationship between time-varying correlations and conditional volatility among eight European emerging stock markets and the MSCI World stock market index from January 2000 to December 2012. Correlations are estimated in the standard and asymmetric dynamic conditional correlation (DCC) model frameworks. The results can be summarized by three main findings: (1) asymmetry in volatility is not a common phenomenon in emerging markets; (2) asymmetry in correlations is found only with respect to the Hungarian stock market; and (3) the relationship between volatility and correlations is positive and significant in all countries included in the study. Thus, diversification benefits decrease during periods of higher volatility