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Forecasting market risk of portfolios: copula-Markov switching multifractal approach
Segnon, Mawuli; Trede, Mark - In: The European journal of finance 24 (2018) 14, pp. 1123-1143
Persistent link: https://www.econbiz.de/10012258877
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Forecasting cryptocurrencies under model and parameter instability
Catania, Leopoldo; Grassi, Stefano; Ravazzolo, Francesco - In: International journal of forecasting 35 (2019) 2, pp. 485-501
Persistent link: https://www.econbiz.de/10012300691
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Forecasting value-at-risk using high-frequency information
Huang, Huiyu; Lee, Tae-hwy - In: Econometrics : open access journal 1 (2013) 1, pp. 127-140
forecasting the daily S&P 500 index return quantile (Value-at-Risk or VaR is simply the negative of it), using high …
Persistent link: https://www.econbiz.de/10009776365
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Bootstrap multi-step forecasts of non-Gaussian VAR models
Fresoli, Diego; Ruiz, Esther; Pascual, Lorenzo - In: International journal of forecasting 31 (2015) 3, pp. 834-848
Persistent link: https://www.econbiz.de/10011474590
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On business cycle fluctuations in USA macroeconomic time series
Kiani, Khurshid M. - In: Economic modelling 53 (2016), pp. 179-186
Persistent link: https://www.econbiz.de/10011640993
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Macroeconomic tail events with non-linear Bayesian VARs
Chiu, Ching Wai Jeremy; Hacıoǧlu Hoke, Sinem - 2016
Persistent link: https://www.econbiz.de/10011557391
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Asymmetric conjugate priors for large Bayesian VARs
Chan, Joshua - 2019
Persistent link: https://www.econbiz.de/10012224053
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Marginalized predictive likelihood comparisons of linear gaussian state-space models with applications to DSGE, DSGE-VAR, and VAR models
Warne, Anders; Coenen, Günter; Christoffel, Kai - In: Journal of applied econometrics 32 (2017) 1, pp. 103-119
Persistent link: https://www.econbiz.de/10011688267
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Forecasting with VAR models : fat tails and stochastic volatility
Chiu, Ching Wai Jeremy; Mumtaz, Haroon; Pintér, Gábor - In: International journal of forecasting 33 (2017) 4, pp. 1124-1143
Persistent link: https://www.econbiz.de/10011746951
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A severity function approach to scenario selection
Mokinski, Frieder - 2017
The severity function approach (abbreviated SFA) is a method of selecting adverse scenarios from a multivariate density. It requires the scenario user (e.g. an agency that runs banking sector stress tests) to specify a "severity function", which maps candidate scenarios into a scalar severity...
Persistent link: https://www.econbiz.de/10011755965