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Estimating and forecasting conditional risk measures with extreme value theory : a review
Bee, Marco; Trapin, Luca - In: Risks : open access journal 6 (2018) 2, pp. 1-16
One of the key components of financial risk management is risk measurement. This typically requires modeling, estimating and forecasting tail-related quantities of the asset returns’ conditional distribution. Recent advances in the financial econometrics literature have developed several...
Persistent link: https://www.econbiz.de/10011866456
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Assessing nowcast accuracy of US GDP growth in real time: the role of booms and busts
Siliverstovs, Boriss - 2019
Persistent link: https://www.econbiz.de/10011990793
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Modeling time-varying uncertainty of multiple-horizon forecast errors
Clark, Todd E.; McCracken, Michael W.; Mertens, Elmar - 2017 - This draft: August 31, 2017
We develop uncertainty measures for point forecasts from surveys such as the Survey of Professional Forecasters, Blue Chip, or the Federal Open Market Committee's Summary of Economic Projections. At a given point of time, these surveys provide forecasts for macroeconomic variables at multiple...
Persistent link: https://www.econbiz.de/10011780949
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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 … models GARCH, EGARCH, GARCH-M and TGARCH with specification (1.1). The research covers the net balance sheet value of forty … of the models GARCH, EGARCH and GARCH-M with the highest risk concentration the investment fund "Golden Lev Index 30 …
Persistent link: https://www.econbiz.de/10014436423
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GFC-robust risk management under the Basel Accord using extreme value methodologies
Santos, Paulo Araújo; Jiménez-Martín, Juan-Ángel; … - 2011
Persistent link: https://www.econbiz.de/10009413652