نتایج جستجو برای: bekk 1
تعداد نتایج: 2752752 فیلتر نتایج به سال:
This paper aims to investigate and measure Bitcoin the five largest stablecoin market volatilities by incorporating various range-based volatility estimators BEKK- GARCH Copula-DCC-GARCH models. Specifically, we further Bitcoins’ related major stablecoins examine connectedness between stablecoins. Our empirical findings document that behaviors exhibits presence of stable interconnection. study ...
The asymmetric price volatility transmission issue in agricultural supply chains has been ignored the previous literature. This paper applies an asymmetrical MGARCH-BEKK model to investigate with application Chinese pork market. Additionally, we use Zivot–Andrews unit root test a structural break examine whether piglet, hog, and prices have breaks. results show that pork’s market breakpoint 200...
The economies of West African Monetary Zone (WAMZ) countries have recorded a long trend currency devaluation and hiking instability in oil prices. We estimated the covariance volatilities global prices caused by COVID-19 outbreak on WAMZ from January 30 to December 30, 2020. BEKK model was for analysis. results generalized autoregressive conditional heteroskedasticity (GARCH) show that all vari...
This study analyzes the volatility spillover effects in US stock market (S&P500) and cryptocurrency (BGCI) using intraday data during COVID-19 pandemic. As potential drivers of portfolio diversification, we measure asymmetric transmission on both markets. We apply MGARCH-BEKK algorithm-based GA2M machine learning model. The negative shocks to returns impact S&P500 more than positive als...
This paper investigates the forecasting ability of four different GARCH models and the Kalman filter method. The four GARCH models applied are the bivariate GARCH, BEKK GARCH, GARCH-GJR and the GARCH-X model. The paper also compares the forecasting ability of the non-GARCH model the Kalman method. Forecast errors based on twenty UK company weekly stock return (based on timevary beta) forecasts ...
W.D. Apel, J. C. Arteaga-Velàzquez, K. Bekk, M. Bertaina, J. Blümer, H. Bozdog, I.M. Brancus, E. Cantoni,* A. Chiavassa, F. Cossavella, K. Daumiller, V. de Souza, F. Di Pierro, P. Doll, R. Engel, J. Engler, M. Finger, B. Fuchs, D. Fuhrmann, H. J. Gils, R. Glasstetter, C. Grupen, A. Haungs, D. Heck, J. R. Hörandel, D. Huber, T. Huege, K.-H. Kampert, D. Kang, H.O. Klages, K. Link, P. Łuczak, M. L...
Article history: Received 10 April 2006 Received in revised form 4 August 2009 Accepted 20 August 2009 Available online 28 August 2009 This paper uses both linear and nonlinear causality tests to reexamine the causal relationship between the returns on large and small firms. Consistent with previous results, we find that large firms linearly lead small firms. We also find a significant linear c...
In the empirical analysis of nancial time series, multivariate GARCH models have been used in various forms. In most cases it is not well understood how the use of a restricted model has to be paid with loss of valuable information. We investigate the structural implications of the alternative models for the response of the conditional (co{)variances to independent shocks. The impulse response ...
The purpose of the paper is to discuss ten things potential users should know about the limits of the Dynamic Conditional Correlation (DCC) representation for estimating and forecasting time-varying conditional correlations. The reasons given for caution about the use of DCC include the following: DCC represents the dynamic conditional covariances of the standardized residuals, and hence does n...
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