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GARCH processes constitute the major area of time series variance analysis hence the limit of these processes is of considerable interest for continuous time volatility modelling. The limit of the GARCH(1,1) model is fundamental for limits of other GARCH processes yet it has been the subject of...
Persistent link: https://www.econbiz.de/10005178167
Conditional returns distributions generated by a GARCH process, which are important for many problems in market risk assessment and portfolio optimization, are typically generated via simulation. This paper extends previous research on analytic moments of GARCH returns distributions in several...
Persistent link: https://www.econbiz.de/10010838036
GARCH option pricing models have the advantage of a well-established econometric foundation. However, multiple states need to be introduced as single state GARCH and even Levy processes are unable to explain the term structure of the moments of financial data. We show that the continuous time...
Persistent link: https://www.econbiz.de/10008542351
It is widely accepted that some of the most accurate Value-at-Risk (VaR) estimates are based on an appropriately specified GARCH process. But when the forecast horizon is greater than the frequency of the GARCH model, such predictions have typically required time-consuming simulations of the...
Persistent link: https://www.econbiz.de/10010730276
The class of mixture GARCH models introduced by Haas, Mittnik and Paollela (2004) and Alexander and Lazar (2006) provides a better alternative for fitting financial data than various other GARCH models driven by the normal or skewed t-distribution. In this paper we propose different option...
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We study the empirical performance of the classical minimum-variance hedging strategy, comparing several econometric models for estimating hedge ratios of crude oil, gasoline and heating oil crack spreads. Given the great variability and large jumps in both spot and futures prices, great care is...
Persistent link: https://www.econbiz.de/10010838053
We quantify and endogenize the model risk associated with quantile estimates using a maximum entropy distribution (MED) as benchmark. Moment-based MEDs cannot have heavy tails, however generalized beta generated distributions have attractive properties for popular applications of quantiles....
Persistent link: https://www.econbiz.de/10010838057