This paper empirically investigates the relationship between CPI inflation uncertainty, and private investment in the Iranian economy from 1988 to 2010 by using quarterly data. We employ a bivariate VAR(5)-GARCH(1,1)-in-mean with diagonal BEKK model to discover in a unified framework how are the interactions between the variables. In the model, conditional variance of inflation and private inve...

This paper introduces the scalar DCC-HEAVY and DECO-HEAVY models for conditional variances correlations of daily returns based on measures realized built from intraday data. Formulas multi-step forecasts are provided. Asymmetric versions developed. An empirical study shows that in terms HEAVY outperform BEKK-HEAVY model covariances BEKK, DCC, DECO multivariate GARCH exclusively

Tests of causality in variance in multiple time series have been proposed recently, based on residuals of estimated univariate models. Although such tests are applied frequently little is known about their power properties. In this paper we show that a convenient alternative to residual based testing is to specify a multivariate volatility model, such as multivariate GARCH (or BEKK), and constr...

This paper investigates the hedging effectiveness of time-varying hedge ratios in the agricultural commodities futures markets based on four different versions of the GARCH models. The GARCH models applied are the standard bivariate GARCH, the bivariate BEKK GARCH, the bivariate GARCH-X and the bivariate BEKK GARCH-X. The GARCH-X and the BEKK GARCH-X models are uniquely different from the other...

Abstract Estimating time-varying conditional covariance matrices of financial returns play important role in portfolio analysis, risk management, and econometrics research. The availability high-frequency data can provide an additional source for dynamic modeling. In this paper, we propose to use the information asset return vector realized measures simultaneously develop a new matrix model. We...

This paper derives the statistical properties of a two-step approach to estimating multivariate rotated GARCH-BEKK (RBEKK) models. From definition RBEKK, unconditional covariance matrix is estimated in first step rotate observed variables order have identity for its sample matrix. In second step, remaining parameters are by maximizing quasi-log-likelihood function. For this quasi-maximum likeli...

Motivated by recent developments in light of the sub-prime and subsequent financial crisis we fit two different vector autoregressive generalized conditional heteroscedastic (VAR-GARCH) models to three financial indices with the aim of understanding the development of dependency structures between credit spreads and other macroeconomic variables. Our analysis includes daily quotes from June 200...

Multivariate GARCH (MGARCH) models are usually estimated under multivariate normality. In this paper, for non-elliptically distributed financial returns, we propose copula-based multivariate GARCH (C-MGARCH) model with uncorrelated dependent errors, which are generated through a linear combination of dependent random variables. The dependence structure is controlled by a copula function. Our ne...

agricultural activities are risky activities. in these activities, various natural, social and economic risks have created fragile and vulnerable situation for producers. price risk in agricultural products has caused financial problems for many producers and farmers. to deal with these price risks and price fluctuations, there are varieties of tools. this paper focused on futures markets instr...

A joint fractionally integrated, error-correction andmultivariateGARCH (FIEC-BEKK) approach is applied to investigate hedging effectiveness using daily data 1995–2005. The findings reveal the proxied error-correction term has a long memory component that theoretically should affect hedging effectiveness.When the FIECmodel empirical conditions are satisfied, the FIEC-BEKK hedging strategy outper...