Estimation of Value-at-Risk on Romanian Stock Exchange Using Volatility Forecasting Models


This paper aims to analyse the market risk (estimated by Value-at-Risk) on the Romanian capital market using modern econometric tools to estimate volatility, such as EWMA, GARCH models. In this respect, I want to identify the most appropriate volatility forecasting model to estimate the Value-at-Risk (VaR) of a portofolio of representative indices (BET, BET-FI and RASDAQ-C). VaR depends on the volatility, time horizon and confidence interval for the continuous returns under analysis. Volatility tends to happen in clusters. The assumption that volatility remains constant at all times can be fatal. It is determined that the most recent data have asserted more influence on future volatility than past data. To emphasize this fact, recently, EWMA and GARCH models have become critical tools in financial applications. The outcome of this study is that GARCH provides more accurate analysis than EWMA.This approach is useful for traders and risk managers to be able to forecast the future volatility on a certain market.


Value-at-Risk, volatility forecasting, EWMA, GARCH models, autocorrelation