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Multivariate GARCH Models (multivariate + garch_models)

Distribution by Scientific Domains
Business, Economics, Finance and Accounting100%

Selected Abstracts

Multivariate GARCH Modeling of Exchange Rate Volatility Transmission in the European Monetary System

FINANCIAL REVIEW, Issue 1 2000
Colm Kearney
C32/F31/G15 Abstract We construct a series of 3-, 4- and 5-variable multivariate GARCH models of exchange rate volatility transmission across the important European Monetary System (EMS) currencies including the French franc, the German mark, the Italian lira, and the European Currency Unit. The models are estimated without imposing the common restriction of constant correlation on both daily and weekly data from April 1979,March 1997. Our results indicate the importance of checking for specification robustness in multivariate Generalized Autoregressive Conditional Heleroskedasticity (GARCH) modeling, we find that increased temporal aggregation reduces observed volatility transmission, and that the mark plays a dominant position in terms of volatility transmission. [source]

Average conditional correlation and tree structures for multivariate GARCH models

JOURNAL OF FORECASTING, Issue 8 2006
Francesco Audrino
Abstract We propose a simple class of multivariate GARCH models, allowing for time-varying conditional correlations. Estimates for time-varying conditional correlations are constructed by means of a convex combination of averaged correlations (across all series) and dynamic realized (historical) correlations. Our model is very parsimonious. Estimation is computationally feasible in very large dimensions without resorting to any variance reduction technique. We back-test the models on a six-dimensional exchange-rate time series using different goodness-of-fit criteria and statistical tests. We collect empirical evidence of their strong predictive power, also in comparison to alternative benchmark procedures.,,Copyright © 2006 John Wiley & Sons, Ltd. [source]

Value at risk from econometric models and implied from currency options

JOURNAL OF FORECASTING, Issue 8 2004
James ChongArticle first published online: 3 DEC 200
Abstract This paper compares daily exchange rate value at risk estimates derived from econometric models with those implied by the prices of traded options. Univariate and multivariate GARCH models are employed in parallel with the simple historical and exponentially weighted moving average methods. Overall, we find that during periods of stability, the implied model tends to overestimate value at risk, hence over-allocating capital. However, during turbulent periods, it is less responsive than the GARCH-type models, resulting in an under-allocation of capital and a greater number of failures. Hence our main conclusion, which has important implications for risk management, is that market expectations of future volatility and correlation, as determined from the prices of traded options, may not be optimal tools for determining value at risk. Therefore, alternative models for estimating volatility should be sought. Copyright © 2004 John Wiley & Sons, Ltd. [source]

A simplified approach to modeling the co-movement of asset returns

THE JOURNAL OF FUTURES MARKETS, Issue 6 2007
Richard D. F. Harris
The authors propose a simplified multivariate GARCH (generalized autoregressive conditional heteroscedasticity) model (the S-GARCH model), which involves the estimation of only univariate GARCH models, both for the individual return series and for the sum and difference of each pair of series. The covariance between each pair of return series is then imputed from these variance estimates. The proposed model is considerably easier to estimate than existing multivariate GARCH models and does not suffer from the convergence problems that characterize many of these models. Moreover, the model can be easily extended to include more complex dynamics or alternative forms of the GARCH specification. The S-GARCH model is used to estimate the minimum-variance hedge ratio for the FTSE (Financial Times and the London Stock Exchange) 100 Index portfolio, hedged using index futures, and compared to four of the most widely used multivariate GARCH models. Using both statistical and economic evaluation criteria, it was found that the S-GARCH model performs at least as well as the other models that were considered, and in some cases it was better. © 2007 Wiley Periodicals, Inc. Jrl Fut Mark 27:575,598, 2007 [source]