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Volatility forecasting with range-based EGARCH models

Brandt, Michael W.; Jones, Christopher S. - In: Journal of business & economic statistics : JBES ; a … 24 (2006) 4, pp. 470-486

Persistent link: https://www.econbiz.de/10003385173

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

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

Nonlinearity, breaks, and long-range dependence in time-series models

Hillebrand, Eric; Medeiros, Marcelo C. - In: Journal of business & economic statistics : JBES ; a … 34 (2016) 1, pp. 23-41

Persistent link: https://www.econbiz.de/10011691143

Modeling the dependence of conditional correlations on market volatility

Bauwens, Luc; Otranto, Edoardo - In: Journal of business & economic statistics : JBES ; a … 34 (2016) 2, pp. 254-268

Persistent link: https://www.econbiz.de/10011691329

Bayesian combinations of stock price predictions with an application to the Amsterdam exchange index

Billio, Monica; Casarin, Roberto; Ravazzolo, Francesco; … - 2011

Persistent link: https://www.econbiz.de/10009126681

Nonparametric estimation and forecasting for time-varying coefficient realized volatility models

Chen, Xiangjin B.; Gao, Jiti; Li, Degui; Silvapulle, … - In: Journal of business & economic statistics : JBES ; a … 36 (2018) 1, pp. 88-100

Persistent link: https://www.econbiz.de/10011894402

Conditional correlation models of autoregressive conditional heteroscedasticity with nonstationary GARCH equations

Amado, Cristina; Teräsvirta, Timo - In: Journal of business & economic statistics : JBES ; a … 32 (2014) 1, pp. 69-87

Persistent link: https://www.econbiz.de/10010380478

Stock index returns' density prediction using GARCH models : frequentist or Bayesian estimation?

Hoogerheide, Lennart F.; Ardia, David; Corré, Nienke - 2011

Persistent link: https://www.econbiz.de/10008824705

Choosing expected shortfall over VaR in Basel III using stochastic dominance

Chang, Chia-Lin; Jiménez-Martín, Juan-Ángel; … - 2015

Bank risk managers follow the Basel Committee on Banking Supervision (BCBS) recommendations that recently proposed shifting the quantitative risk metrics system from Value-at-Risk (VaR) to Expected Shortfall (ES). The Basel Committee on Banking Supervision (2013, p. 3) noted that: "a number of...

Persistent link: https://www.econbiz.de/10011431395