Multivariate Volatility Models
نویسنده
چکیده
Multivariate volatility models are widely used in finance to capture both volatility clustering and contemporaneous correlation of asset return vectors. Here, we focus onmultivariate GARCHmodels. In this commonmodel class, it is assumed that the covariance of the error distribution follows a time dependent process conditional on information which is generated by the history of the process. To provide a particular example, we consider a system of exchange rates of two currencies measured against the US Dollar (USD), namely the Deutsche Mark (DEM) and the British Pound Sterling (GBP). For this process, we compare the dynamic properties of the bivariate model with univariate GARCH specifications where cross sectional dependencies are ignored. Moreover, we illustrate the scope of the bivariate model by ex-ante forecasts of bivariate exchange rate densities.
منابع مشابه
Do Jumps Matter? Forecasting Multivariate Realized Volatility Allowing for Common Jumps * Do Jumps Matter? Forecasting Multivariate Realized Volatility Allowing for Common Jumps *
Realized volatility of stock returns is often decomposed into two distinct components that are attributed to continuous price variation and jumps. This paper proposes a tobit multivariate factor model for the jumps coupled with a standard multivariate factor model for the continuous sample path to jointly forecast volatility in three Chinese Mainland stocks. Out of sample forecast analysis show...
متن کاملMultivariate volatility models
Correlations between asset returns are important in many financial applications. In recent years, multivariate volatility models have been used to describe the time-varying feature of the correlations. However, the curse of dimensionality quickly becomes an issue as the number of correlations is k(k− 1)/2 for k assets. In this paper, we review some of the commonly used models for multivariate v...
متن کاملComparison of Multivariate GARCH Models with Application to Zero-Coupon Bond Volatility
The purpose of this thesis is to investigate different formulations of multivariate GARCH models and to apply two of the popular ones – the BEKKGARCH model and the DCCGARCH model – in evaluating the volatility of a portfolio of zero-coupon bonds. Multivariate GARCH models are considered as one of the most useful tools for analyzing and forecasting the volatility of time series when volatility f...
متن کاملConsistent Ranking of Multivariate Volatility Models
A large number of parameterizations have been proposed to model conditional variance dynamics in a multivariate framework. This paper examines the ranking of multivariate volatility models in terms of their ability to forecast out-of-sample conditional variance matrices. We investigate how sensitive the ranking is to alternative statistical loss functions which evaluate the distance between the...
متن کاملAnalytic pricing of volatility-equity options within Wishart-based stochastic volatility models
We price for different affine stochastic volatility models some derivatives that recently appeared in the market. These products are characterized by payoffs depending on both stock and its volatility. We provide closed-form solution for different products and two multivariate Wishartbased stochastic volatility models. The methodology turns out to be independent of the dimension of the problem....
متن کاملPortfolio Single Index (PSI) Multivariate Volatility Models
The paper introduces the structure of parsimonious Portfolio Single Index (PSI) multivariate conditional and stochastic constant correlation volatility models, and methods for estimation of the underlying parameters. These multivariate estimates of volatility can be used for more accurate portfolio and risk management, to enable efficient forecasting of Value-at-Risk (VaR) thresholds, and to de...
متن کامل