Asymmetric GARCH and the financial crisis: a preliminary study

The paper deals with estimation of both general GARCH as well as asymmetric EGARCH and TGARCH models, used to model the leverage effect of good news and bad news on market volatility. We estimate the models using daily returns of S&P 500 stock index and describe the news impact curves (NICs) for these models. When estimating the crisis series, we show the possibility of using a news impact surface to describe the results from models of higher orders.volatility modeling, financial crisis, asymmetric GARCH class models, news impact curve

Stock Market Integration: Granger Causality Testing with Respect to Nonsynchronous Trading Effects

In this paper, we perform Granger causality analysis on stock market indices from several Asian, European, and U.S. markets. Using daily data, we point out the potential problems caused by the presence of nonsynchronous trading effects. We deal with two kinds of nonsynchronicity – one induced by differing numbers of observations in the series being analyzed and the other related to the different time zones in which the markets operate. To address the first problem, we propose a data-matching process. To address the second problem, we modify the regressions used in the Granger causality testing. When comparing the empirical results obtained using the standard technique and our modified methodology, we find substantially different results. Most of the relationships that are subject to nonsynchronous trading are not significant in the general case. However, when we use the adjusted methodology, the null hypothesis of a Granger non-causal relationship is rejected in all cases.stock market integration, nonsynchronous trading, Granger causality

Stationarity of time series and the problem of spurious regression

The goal of this paper was to introduce some general issues of non-stationarity for practitioners, students and beginning researchers. Using elementary techniques we examined the effect of non-stationary data on the results of regression analysis. We further shoved the effect of larger sample sizes on the spuriousness of regressions and we also examined the well known “rule of thumb” of how to identify spurious regressions. We also demonstrated the problem of spurious regression on a practical example, using closing prices of stock market indices from CEE markets.stationarity, time series data, various unit root tests, spurious regression, the R-squared and the Durbin – Watson statistics “rule of thumb”, CEE stock markets

On the relationship of persistence and number of breaks in volatility: new evidence for three CEE countries

In this article, we contribute to the discussion of volatility persistence in the presence of sudden changes. We follow previous research, particularly Wang and Moore (2009), who analysed stock market returns in five Central and Eastern European countries using the Iterated Cumulative Sum of Squares (ICSS) algorithm for detecting multiple breaks and the test (IT) proposed by Inclán and Tiao (1994). We complement this analysis by using the κ1 and κ2 statistic introduced by Sansó et al. (2004), which lead us to the hypothesis that the estimated persistence in volatility depends inversely on the number of breakpoints in volatility. We explored this claim through a simulation study, where by randomizing an increasing number of breakpoints over the sample, we estimated kernel density of the persistence measure. The results confirmed the relationship between persistence and the number of breakpoints. It also showed that the use of break detection algorithms leads to lower persistence estimates, even within the class of models with an equal number of breaks. Therefore, the overall decrease in persistence can be attributed both to the number of breaks and their position, as suggested by the chosen break detection tests.volatility persistence, GARCH model, ICSS procedure, CEE stock markets

Asymmetric GARCH and the financial crisis: a preliminary study

The paper deals with estimation of both general GARCH as well as asymmetric EGARCH and TGARCH models, used to model the leverage effect of good news and bad news on market volatility. We estimate the models using daily returns of S&P 500 stock index and describe the news impact curves (NICs) for these models. When estimating the crisis series, we show the possibility of using a news impact surface to describe the results from models of higher orders.volatility modeling, financial crisis, asymmetric GARCH class models, news impact curve

Volatility Regimes in Macroeconomic Time Series: The Case of the Visegrad Group

The authors analyze several monthly and quarterly macroeconomic time series for the Czech Republic, Poland, Hungary, and Slovakia. These countries embarked on an economic transition in the early 1990s which ultimately led to their membership in the European Union, with Slovakia joining the euro area in 2009. It is natural to assume that changes of such a magnitude should also influence the major macroeconomic indicators. The authors explore the characteristics of these series by endogenously identifying their volatility regimes. In the course of their analysis, they show the difficulties in the handling of unit roots as a necessary step preceding volatility modeling. The final set of breaks identified shows very few changes near the beginning of the series, which corresponds to the transition period.macroeconomic fluctuations, economic transition, structural breaks, volatility regimes, cumulative sum of squares, unit root testing

Are we able to capture the EU debt crisis? Evidence from PIIGGS countries in panel unit root framework

We assess the issue of fiscal sustainability in the selected EU countries. Our sample includes those showing the highest government debts, which are nowadays known under the somewhat degrading acronym – PIIGGS (Portugal, Ireland, Italy, Greece, Great Britain and Spain). Assuming the so-called present value borrowing constraint, stationarity of debts presents a sufficient condition for fiscal sustainability. Utilizing various standard panel unit root tests and the test by Im et al. (2010), we examine this condition on quarterly debt-to-GDP ratios over the period 2000 to 2010. Results provide evidence, that when trend breaks in the series are incorporated, not all of these countries exhibit non-stationarity behavior of their debt-to-GDP ratios.Fiscal sustainability, Government debt, Panel unit-root tests

Unit-root and stationarity testing with empirical application on industrial production of CEE-4 countries

The purpose of this paper is to explain both the need and the procedures of unit-root testing to a wider audience. The topic of stationarity testing in general and unit root testing in particular is one that covers a vast amount of research. We have been discussing the problem in four different settings. First we investigate the nature of the problem that motivated the study of unit-root processes. Second we present a short list of several traditional as well as more recent univariate and panel data tests. Third we give a brief overview of the economic theories, in which the testing of the underlying research hypothesis can be expressed in a form of a unit-root / stationary test like the issues of purchasing power parity, economic bubbles, industry dynamic, economic convergence and unemployment hysteresis can be formulated in a form equivalent to the testing of a unit root within a particular series. The last, fourth aspect is dedicated to an empirical application of testing for the non-stationarity in industrial production of CEE-4 countries using a simulation based unit-root testing methodology.Unit-root, Stationarity, Univariate tests, Panel tests, Simulation based unit root tests, Industrial production

Stock market integration between the CEE-4 and the G7 markets: Asymmetric DCC and smooth transition approach.

We study the transition process of emerging CEE-4 stock markets from segmented to integrated markets and hypothesize that this process has been gradual over time. As a proxy for integration, co-movements with developed G7 markets are estimated using the asymmetric 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. In the case of Czech stock market, the results suggest that the transition began between the end of 2005 and first half of 2006. The transition midpoints for the Hungarian and Polish markets seem to overlap with the recent financial crisis. Correlations between CEE-4 and G7 markets have been approximately 0.6 in the last few years. The only exception is the Slovak stock market, which still appears to be more segmented and isolated from others in the CEE region and from the developed markets of the G7

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