Similar Search Results

The power of weather : some empirical evidence on predicting day-ahead power prices through weather forecasts

Huurman, Christian; Ravazzolo, Francesco; Zhou, Chen - 2007

Persistent link: https://www.econbiz.de/10003482711

Bayesian model averaging and the conditional volatility process : an application to predicting aggregate equity returns by conditioning on economic variables

Nonejad, Nima - In: Quantitative finance 21 (2021) 8, pp. 1387-1411

Persistent link: https://www.econbiz.de/10012608655

Forecasting robust value-at-risk estimates : evidence from UK banks

Sampid, Marius Galabe; Hasim, Haslifah Mohamad - In: Quantitative finance 21 (2021) 11, pp. 1955-1975

Persistent link: https://www.econbiz.de/10012696799

Jumps and oil futures volatility forecasting : a new insight

Ma, Feng; Liang, Chao; Zeng, Qing; Li, Haibo - In: Quantitative finance 21 (2021) 5, pp. 853-863

Persistent link: https://www.econbiz.de/10012500197

Backtesting expected shortfall and beyond

Deng, Kaihua; Qiu, Jie - In: Quantitative finance 21 (2021) 7, pp. 1109-1125

Persistent link: https://www.econbiz.de/10012588022

Accelerating GARCH and score-driven models : optimality, estimation and forecasting

Blasques, Francisco F.; Gorgi, Paolo; Koopman, Siem Jan S.J. - 2017

We first consider an extension of the generalized autoregressive conditional heteroskedasticity (GARCH) model that allows for a more flexible weighting of financial squared-returns for the filtering of volatility. The parameter for the squared-return in the GARCH model is time- varying with an...

Persistent link: https://www.econbiz.de/10011688512