Results for the first estimation of the GARCH models (GJR-GARCH).. Results for the final estimation of the GARCH models.. Ljung-Box test results for the standardized residuals

The relative size, accuracy and efficiency of the models are assessed using mean relative bias, backtesting, likelihood ratio tests, loss function, mean

In this paper we model and estimate the static next day VaR, ES and different return period Risk Levels for the ASX-All Ordinaries and the S&P-500 stock exchange index series

Based on an average accuracy improvement of 4.6% over the baseline parallel SMO, Fig.16 shows that using the ontology augmented approach, the MapReduce based parallel

For the first objective, this research suggested further research could be extended to SZSE data. The daily returns of the SZSE index are different compared to the

Classification matrix based on linear discriminant analysis of Procrustes coordinates derived from adult male Blueback Herring caught in North Carolina (Chowan and Yeopim rivers)

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Using copulas, we examine the impact of dependence structure between market risk and underwriting risk of insurance portfolio on the insurer’s economic capital, particularly

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Keywords: Copula, dependence modelling, missing values, multivariate extreme value theory and.. spatial ood

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Keywords and Phrases: Extreme-value copula, minimum distance estimation, Pickands dependence function, weak convergence, copula process, test for extreme-value dependence.. AMS

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The stress stiffening parameter is shown to allow loading in structural frames to be identified from dynamic data even with no a priori knowledge of load state.. The rigid

Extreme Value Theory (EVT) is applied in both researches to model tail distributions of the market condition and Value-at-Risk (VaR) values were found to be more sensible

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3 Forecasting Value-at-Risk estimates using multivariate GARCH(1,1) Dynamic Conditional Correlation models, copula functions and Extreme Value Theory: Evidence from EU banks 27