The aim of this paper is to investigate the performance of Value at Risk (VaR) models in selected Central and Eastern European (CEE) emerging capital markets. Daily returns of Croatian (CROBEX), Czech (PX50), Hungarian (BUX) and Romanian (BET) stock exchange indices are analysed for the period January, 2000 -February, 2012, while daily returns of the Serbian (BELEX15) index is examined for the period September, 2005 -February, 2012. In recent years there has been much research conducted into VaR in developed markets, while papers dealing with VaR calculation in CEE are rare. Furthermore, VaR models created and suited for liquid and welldeveloped markets that assume normal distribution are less reliable for capital markets in emerging economies, such as Central and Eastern European Union member and candidate states. Since capital markets in European emerging economies are highly volatile, less liquid and strongly dependent on the unexpected external shocks, market risk estimation based on normality assumption in CEE countries is more problematic. This motivates us to implement GARCH-type methods that involve time varying volatility and heavy tails of the empirical distribution of returns. We test the hypothesis that using the assumption of heavy tailed distribution it is possible to forecast market risk more precisely, especially in times of crisis, than under the assumption of normal distribution or using historical simulations method. Our backtesting results for the last 500 observations are based on the Kupiec POF and Christoffersen independence test. They show that GARCH-type models with t error distribution in most analysed cases give better VaR estimation than GARCH type models with normal errors in the case of a 99% confidence level, while in the case of a 95% confidence level it is the opposite. The results of backtesting analysis for the crisis period (after the collapse of Lehman Brothers) show that GARCH-type models with t-distribution of residuals provide better VaR estimates compared with GARCH-type models with normal distribution, historical simulations and RiskMetrics methods. The RiskMetrics method in the most cases underestimates market risk.

The aim of this study is to envisage the impact of global financial (GFC) and European sovereign debt crisis (ESDC) on foreign exchange markets of emerging countries in Central and Eastern Europe CEEC countries (Czech Republic, Hungary, Romania, poland and Serbia). The daily returns of exchange rates on Czech Republic koruna (CZK), Hungarian forint (HuF), Romanian lea (RoL), polish zloty (pLZ) and Serbian dinar (RSD), all against the Euro are analyzed during the period from 3 rd January 2000 to15 th April 2013, in respect. To examine the impact of global financial crisis and European sovereign debt crisis, dummy variables were adopted. overall results imply that global financial crisis has no impact on exchange rate returns in selected CEEC countries, while European sovereign debt crisis influencing in depreciation of polish zloty by 8% and Romanian lea by 6%. obtained results by our calculation, imply that global financial crisis increased enhanced volatility on exchange rate returns of Czech koruna, Romanian lea and polish zloty. Moreover, results of empirical analysis imply that this impact has the strongest influence in volatility on exchange rate returns of polish zloty.

The main objective of this study is to test the hypothesis that exchange rates in emerging countries are more sensitive to negative shocks than positive ones, and that developed ones do not exhibit this same pattern, at least not with the same intensity. In order to measure the involved risk, symmetric and asymmetric GARCH models are applied. The accuracy of exchange rate volatility forecast is evaluated using the Mincer-Zarnowitz regression based test and Diebold and Mariano test (DM test). The daily exchange rate returns of HUF/USD, RON/USD and RSD/USD for EEC countries and, the EUR/USD, GBP/USF and JPY/USD for developed countries are analysed for the period January 3, 2000 to April 15, 2013, in respect. Estimation results confirmed superiority of GARCH model in comparison to asymmetric GARCH models. Results of predictability of conditional variance indicate that GARCH model offers superior performance of forecasting in both of EEC and developed countries. Only in case of Romanian lei TGARCH outperformed GARCH model.

This main objective of this paper is to examine the properties of the GARCHmodel and its usefulness in modeling and forecasting the volatility of exchange ratemovements in selected EEC countries (Romania, Hungary and Serbia). The dailyreturns of exchange rates on Hungarian forint (HUF), Romanian lei (ROL) andSerbian dinar (RSD), all against the US dollar are analyzed during the period 03.January 2000 to 15. April 2013 in respect. In order to measure the involved risk,symmetric and asymmetric GARCH models are applied. The accuracy of exchangerate volatility forecast is evaluated through reference to the most commonly usedcriteria. These include a Mincer-Zarnowitz regression based test, Mean AbsoluteError (MAE), Root Mean Square Error (RMSE) and Diebold and Mariano test (DMtest). The results of Mincer-Zarnowitz regression test for selected exchange ratereturn series showed a clear lack of explanotory power and sub-optimality of theTGARCH model. The results of the Mean Absolute Error (MAE) and the Root MeanSquare Error (RMSE) for the forecasted volatility showed that symmetric modelbetter predict conditional variance of the exchange rate returns, but estimating resultsindicating that the parameters of forecasts are not satisfactory, i.e. models have littlepredictive power. Results for Diebold-Mariano test results for Diebold-Mariano testshowed that symmetric model outperforming TGRACH forecast in case of Hungarianforint and Serbian dinar sample series, and that only in case of Romania lei TGARCHoutperforming the GARCH forecast.

In this paper, we analyzed inflation persistence in Serbia, both at the aggregate level as well as for the different components of the consumer price index. The analysis was done for the series of prices given on the quarterly basis for the period from 2002q1 to 2013q2. We applied univariate autoregression model (AR) of order p, whereby sum of autoregression coefficients was used as a measure of inflation persistence. In addition, special attention was paid to the problem of structural breaks in the series of inflation as it may overestimate the level of inflation persistence and could give misleading signals. The importance of appropriate assessment of the inflation persistence stems from the fact that the impossibility of faster return of inflation to the long-run equilibrium level, after external or domestic shock, has implications on the conducting of monetary policy and represents a major challenge for its effectiveness, especially in emerging countries like Serbia. If the persistence of inflation is higher, monetary policy reaction should be stronger and proactive. If the estimated level and persistence of inflation is lower in comparison with previous empirical analysis, this could suggest that inflation expectations are now better anchored, which is particularly important for countries with inflation targeting regime. Results of the analysis indicate that the inflation persistence in the Serbia is modest and that is higher at the aggregate level compared to the simple average of the components of the consumer price index. This is probably consequence of so-called aggregation effect, since the highest persistency have the prices of those products with the largest share in the consumer basket. In the case of Serbia, food prices have the highest degree of persistence and the largest share in the consumer basket.