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Method of moment estimation in time-changed Lévy models
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Jan Kallsen
Published/Copyright:
May 31, 2011
Abstract
This paper introduces a method of moment estimator for the time-changed Lévy processes proposed by Carr, Geman, Madan and Yor (2003). By establishing that the returns sequence is strongly mixing with exponentially decreasing rate, we prove consistency and asymptotic normality of the resulting estimators. In addition, we fit parametrized versions of the model to real data and examine the quality of our estimators by performing a simulation study. Finally, we also show how to estimate the current level of volatility.
Published Online: 2011-05-31
Published in Print: 2011-05
© by Oldenbourg Wissenschaftsverlag, Zürich, Germany
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Articles in the same Issue
- Expansions for the risk of Stein type estimates for non-normal data
- Mean-risk tests of stochastic dominance
- Non-parametric drift estimation for diffusions from noisy data
- Comparison of Markov processes via infinitesimal generators
- Method of moment estimation in time-changed Lévy models
Keywords for this article
time-changed Lévy models;
moment estimator;
mixing property;
volatility estimation
Articles in the same Issue
- Expansions for the risk of Stein type estimates for non-normal data
- Mean-risk tests of stochastic dominance
- Non-parametric drift estimation for diffusions from noisy data
- Comparison of Markov processes via infinitesimal generators
- Method of moment estimation in time-changed Lévy models
