Search results for "GARCH model"
showing 7 items of 7 documents
Stock Returns and Exchange Rate Volatility Spillovers in the MENA Region
2010
In this article, we examine the presence of volatility spillovers between nominal exchange rates and stock returns in three MENA countries: Egypt, Morocco and Turkey. The multivariate GARCH model we use does not produce evidence of cross-market effects for the general stock indices returns. Nevertheless, bidirectional shock and volatility spillovers between exchange rates and stock returns exist at the industry sector level. These findings are more pronounced in Egypt and Turkey. The different results are due to the different exchange rate regimes/policies adopted by the three countries. While exchange rates in Egypt and Turkey were allowed to float, Morocco followed a more tightly managed…
Volatility transmission patterns and terrorist attacks
2009
The objective of this study is to analyze volatility transmission between the US and Eurozone stock markets considering the effects of the September 11, March 11 and July 7 financial crises. In order to do this, we use a multivariate GARCH model and take into account the asymmetric volatility phenomenon, the non-synchronous trading problem and the crises themselves. Moreover, a graphical analysis of the Asymmetric Volatility Impulse-Response Functions (AVIRF) is introduced, which takes into consideration the crisis effect. Results suggest that there is bidirectional and asymmetric volatility transmission and show the different impact that terrorist attacks had on both markets. El objetivo d…
Exploring the Hedging Effectiveness of European Wheat Futures Markets during the 2007-2012 Period
2014
Abstract The hypothesis that speculative behaviour was the cause of the instability of commodity prices has brought renewed interest in futures markets. In this paper, the hedging effectiveness of European and US wheat futures markets were studied to test whether they were affected by the price instability observed after 2007. Indirectly, this could also be thought as a test of whether the increasing presence of speculators in futures markets have made them divorced from physical markets. A multivariate GARCH model was applied to compute optimal hedging ratios. No important evidence was found of a change in the hedging effectiveness after 2007.
On Independent Component Analysis with Stochastic Volatility Models
2017
Consider a multivariate time series where each component series is assumed to be a linear mixture of latent mutually independent stationary time series. Classical independent component analysis (ICA) tools, such as fastICA, are often used to extract latent series, but they don't utilize any information on temporal dependence. Also financial time series often have periods of low and high volatility. In such settings second order source separation methods, such as SOBI, fail. We review here some classical methods used for time series with stochastic volatility, and suggest modifications of them by proposing a family of vSOBI estimators. These estimators use different nonlinearity functions to…
Estimation of Value-at-Risk on Romanian Stock Exchange Using Volatility Forecasting Models
2013
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 th…
ICA and stochastic volatility models
2016
We consider multivariate time series where each component series is an unknown linear combination of latent mutually independent stationary time series. Multivariate financial time series have often periods of low volatility followed by periods of high volatility. This kind of time series have typically non-Gaussian stationary distributions, and therefore standard independent component analysis (ICA) tools such as fastICA can be used to extract independent component series even though they do not utilize any information on temporal dependence. In this paper we review some ICA methods used in the context of stochastic volatility models. We also suggest their modifications which use nonlinear…
MODELING OF VOLATILITY IN THE ROMANIAN CAPITAL MARKET
2012
This paper aims to analyze the volatility of capital market in Romania by selecting a portfolio of representative indices (BET BET_FI and RASDAQ_C). In this respect, we want to identify the most appropriate model to estimate volatility by using modern econometric tools and useful GARCH models respectively. The study results highlight that EGARCH(1,1) model has managed to eliminate all traces of statistically significant autocorrelation and ARCH effects from the residuals from daily series, giving an accurate image of the Romanian capital market volatility.