- Autor
- Skoczylas Tomasz (University of Warsaw)
- Tytuł
- Log-Volatility Enhanced GARCH Models for Single Asset Returns
- Źródło
- Bank i Kredyt, 2015, nr 5, s. 411-431, aneks, bibliogr. 20 poz.
Bank & Credit - Słowa kluczowe
- Zmienność, Analiza wartości zagrożonej, Model GARCH, Prognozowanie
Variability, Value at Risk Analysis, GARCH model, Forecasting - Uwagi
- summ.
- Abstrakt
- This paper presents an alternative approach to modelling and forecasting single asset return volatility. A new, flexible framework is proposed, one which may be considered a development of single-equation GARCH-type models. In this approach an additional equation is added, which binds logarithms of conditional volatility and observed volatility, as measured by the Garman-Klass variance estimator. It enables more information to be retrieved from data. Proposed models are compared with benchmark GARCH and range-based GARCH (RGARCH) models in terms of prediction accuracy. All models are estimated with the maximum likelihood method, using time series of EUR/PLN, EUR/USD, EUR/GBP spot rates quotations as well as WIG20, Dow Jones industrial and DAX indexes. Results are encouraging, especially for foreasting Value-at-Risk. Log-volatility enhanced models achieved lesser rates of VaR exception, as well as lower coverage test statistics, without being more conservative than their single-equation counterparts, as their forecast error measures are to some degree similar.(original abstract)
- Dostępne w
- Biblioteka Główna Uniwersytetu Ekonomicznego w Krakowie
Biblioteka SGH im. Profesora Andrzeja Grodka
Biblioteka Główna Uniwersytetu Ekonomicznego w Katowicach
Biblioteka Główna Uniwersytetu Ekonomicznego w Poznaniu
Biblioteka Główna Uniwersytetu Ekonomicznego we Wrocławiu - Pełny tekst
- Pokaż
- Bibliografia
-
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- Cytowane przez
- ISSN
- 0137-5520
- Język
- eng
