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Commodity value-at-risk modeling : comparing riskmetrics, historic simulation and quantile regression
Steen, Marie; Westgaard, Sjur; Gjølberg, Ole - In: The journal of risk model validation 9 (2015) 2, pp. 49-78
Persistent link: https://www.econbiz.de/10011326305
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Value-at-risk and extreme returns
Daníelsson, Jón; Vries, Casper G. de - 1997
Accurate prediction of the frequency of extreme events is of primary importance in many financialapplications such as Value-at-Risk (VaR) analysis. We propose a semi-parametric method for VaRevaluation. The largest risks are modelled parametrically, while smaller risks are captured by the...
Persistent link: https://www.econbiz.de/10010533206
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Testing for Granger causality in distribution tails : an application to oil markets integration
Candelon, Bertrand; Joëts, Marc; Tokpavi, Sessi - In: Economic modelling 31 (2013), pp. 276-285
Persistent link: https://www.econbiz.de/10009729103
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Forecasting volatility in global food commodity prices
Onour, Ibrahim A.; Sergi, Bruno S. - 2011
Persistent link: https://www.econbiz.de/10009412851
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Revisiting value-at-risk and expected shortfall in oil markets under structural breaks : the role of fat-tailed distributions
Patra, Saswat - In: Energy economics 101 (2021), pp. 1-11
Persistent link: https://www.econbiz.de/10013161743
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Forecasting Value-at-Risk and Expected Shortfall Using Fractionally Integrated Models of Conditional Volatility : International Evidence
Degiannakis, Stavros Antonios - 2018
forecasting horizons. Therefore, a long memory volatility model compared to a short memory GARCH model does not appear to improve …
Persistent link: https://www.econbiz.de/10012910119
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Extreme spillovers of VIX fear index to international equity markets
Massaporn Cheuathonghua; Chaiyuth Padungsaksawasdi; … - In: Financial markets and portfolio management 33 (2019) 1, pp. 1-38
Persistent link: https://www.econbiz.de/10012018353
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Best fitting fat tail distribution for the volatilities of energy futures : gev, gat and stable distributions in GARCH and APARCH models
Gunay, Samet; Khaki, Audil Rashid - In: Journal of risk and financial management : JRFM 11 (2018) 2, pp. 1-19
Precise modeling and forecasting of the volatility of energy futures is vital to structuring trading strategies in spot … measurement of risk. This paper is an attempt to model volatility of energy futures under different distributions. In empirical … analysis, we estimate the volatility of Natural Gas Futures, Brent Oil Futures and Heating Oil Futures through GARCH and APARCH …
Persistent link: https://www.econbiz.de/10011857131
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The importance of time‐varying volatility and country interactions in forecasting economic activity
Trypsteen, Steven - In: Journal of forecasting 36 (2017) 6, pp. 615-628
Persistent link: https://www.econbiz.de/10011861398
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Forecasting the VaR of crude oil market: do alternative distributions help?
Lyu, Yongjian; Wang, Peng; Wei, Yu; Ke, Rui - In: Energy economics 66 (2017), pp. 523-534
Persistent link: https://www.econbiz.de/10011896562