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The impact of sovereign yield curve differentials on value-at-risk forecasts for foreign exchange rates

Fink, Holger Maria; Fuest, Andreas; Port, Henry - In: Risks : open access journal 6 (2018) 3, pp. 1-19

A functional ARMA-GARCH model for predicting the value-at-risk of the EURUSD exchange rate is introduced. The model … August 2005–30 September 2016. As a benchmark, we take an ARMA-GARCH and an ARMAX-GARCHX with the 2y-yield difference as the …

Persistent link: https://www.econbiz.de/10011890808

Inflation and unemployment forecasting with genetic support vector regression

Sermpinis, Georgios; Stasinakis, Charalampos; … - In: Journal of forecasting 33 (2014) 6, pp. 471-487

Persistent link: https://www.econbiz.de/10010426238

A hybrid model for forecasting realized volatility based on heterogeneous autoregressive model and support vector regression

Zhuo, Yue; Morimoto, Takayuki - In: Risks : open access journal 12 (2024) 1, pp. 1-16

In this study, we proposed two types of hybrid models based on the heterogeneous autoregressive (HAR) model and support vector regression (SVR) model to forecast realized volatility (RV). The first model is a residual-type model, where the RV is first predicted using the HAR model, and the...

Persistent link: https://www.econbiz.de/10014480965

Bayesian assessment of dynamic quantile forecasts

Gerlach, Richard; Chen, Cathy W. S.; Lin, Edward M. H. - In: Journal of forecasting 35 (2016) 8, pp. 751-764

Persistent link: https://www.econbiz.de/10011633826

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

Forecasting the daily time‐varying beta of European banks during the crisis period : comparison between GARCH models and the Kalman filter

Zhang, Yuanyuan; Choudhry, Taufiq - In: Journal of forecasting 36 (2017) 8, pp. 956-973

Persistent link: https://www.econbiz.de/10011860929

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

Nonlinear modeling of mortality data and its implications for longevity bond pricing

Li, Huijing; Rui, Zhou; Ji, Min - In: Risks : open access journal 11 (2023) 12, pp. 1-25

Human mortality has been improving faster than expected over the past few decades. This unprecedented improvement has caused significant financial stress to pension plan sponsors and annuity providers. The widely recognized Lee-Carter model often assumes linearity in its period effect as an...

Persistent link: https://www.econbiz.de/10014446511

Using CAViaR models with implied volatility for value-at-risk estimation

Jeon, Jooyoung; Taylor, James W. - In: Journal of forecasting 32 (2013) 1, pp. 62-74

Persistent link: https://www.econbiz.de/10009758719