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Forecasting VaR models under different volatility processes and distributions of return innovations

Dendramis, Yiannis; Spungin, Giles E.; Tzavalis, Elias - In: Journal of forecasting 33 (2014) 7, pp. 515-531

Persistent link: https://www.econbiz.de/10011282095

Volatility timing in CPF investment funds in Singapore : do they outperform non-CPF funds?

Shen, Xiaoyi; Tsui, Albert K.; Zhang, Zhaoyong - In: Risks : open access journal 7 (2019) 4/106, pp. 1-16

will provide the CPF board with a new method for risk classification. We employ the GARCH models and modified factor models …

Persistent link: https://www.econbiz.de/10012127925

Modeling and forecasting realized volatility in German-Austrian continuous intraday electricity prices

Ciarreta, Aitor; Muniain, Peru; Zarraga, Ainhoa - In: Journal of forecasting 36 (2017) 6, pp. 680-690

Persistent link: https://www.econbiz.de/10011861404

Empirical testing of models of autoregressive conditional heteroscedasticity used for prediction of the volatility of Bulgarian investment funds

Petrova, Mariana; Todorov, Teodor - In: Risks : open access journal 11 (2023) 11, pp. 1-30

investment decisions. The used risk attribution quantification models GARCH (1.1), EGARCH (1.1), GARCH-M (1.1) and TGARCH (1 … concentration of investment funds (in Bulgaria) through the testing of complex, analytical and specialized models from the GARCH … models GARCH, EGARCH, GARCH-M and TGARCH with specification (1.1). The research covers the net balance sheet value of forty …

Persistent link: https://www.econbiz.de/10014436423

Evaluating risk measures and capital allocations based on multi-losses driven by a heavy-tailed background risk : the multivariate Pareto-II model

Asimit, Alexandru V.; Vernic, Raluca; Zitikis, Riċardas - In: Risks : open access journal 1 (2013) 1, pp. 14-33

Evaluating risk measures, premiums, and capital allocation based on dependent multi-losses is a notoriously difficult task. In this paper, we demonstrate how this can be successfully accomplished when losses follow the multivariate Pareto distribution of the second kind, which is an attractive...

Persistent link: https://www.econbiz.de/10009754682

When the US stock market becomes extreme?

Aboura, Sofiane - In: Risks : open access journal 2 (2014) 2, pp. 211-225

Over the last three decades, the world economy has been facing stock market crashes, currency crisis, the dot-com and real estate bubble burst, credit crunch and banking panics. As a response, extreme value theory (EVT) provides a set of ready-made approaches to risk management analysis....

Persistent link: https://www.econbiz.de/10010399734

Dynamic density forecasts for multivariate asset returns

Polanski, Arnold; Stoja, Evarist - In: Journal of forecasting 30 (2011) 6, pp. 523-540

Persistent link: https://www.econbiz.de/10009354712

Tail dependence in financial markets : a dynamic copula approach

Cortese, Federico Pasquale - In: Risks : open access journal 7 (2019) 4/116, pp. 1-14

This article is concerned with the study of the tail correlation among equity indices by means of dynamic copula functions. The main idea is to consider the impact of the use of copula functions in the accuracy of the model´s parameters and in the computation of Value-at-Risk (VaR). Results...

Persistent link: https://www.econbiz.de/10012127765

Forecasting based on decomposed financial return series : a wavelet analysis

Berger, Theo - In: Journal of forecasting 35 (2016) 5, pp. 419-433

Persistent link: https://www.econbiz.de/10011580976

Risk model validation : an intraday VaR and ES approach using the multiplicative component GARCH

Summinga-Sonagadu, Ravi; Narsoo, Jason - In: Risks : open access journal 7 (2019) 1/10, pp. 1-23

assess the competency of the Multiplicative Component Generalised Autoregressive Heteroskedasticity (MC-GARCH) models based … that non-normal distributions are best suited for both model fitting and forecasting. The MC-GARCH(1,1) model under the …’ knowledge) in: (1) forecasting the intraday Expected Shortfall (ES) under different distributional assumptions for the MC-GARCH …

Persistent link: https://www.econbiz.de/10012018629