High Quantile Estimation for some Stochastic Volatility Models
In this thesis we consider estimation of the tail index for heavy tailed stochastic volatility models with long memory. We prove a central limit theorem for a Hill estimator. In particular, it is shown that neither the rate of convergence nor the asymptotic variance is affected by long memory. The t...
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ndltd-LACETR-oai-collectionscanada.gc.ca-OOU.#10393-202952013-10-04T04:23:02ZHigh Quantile Estimation for some Stochastic Volatility ModelsLuo, Lingstochastic volatilitylong memoryIn this thesis we consider estimation of the tail index for heavy tailed stochastic volatility models with long memory. We prove a central limit theorem for a Hill estimator. In particular, it is shown that neither the rate of convergence nor the asymptotic variance is affected by long memory. The theoretical findings are verified by simulation studies.2011-10-05T20:26:40Z2011-10-05T20:26:40Z20112011-10-05Thèse / Thesishttp://hdl.handle.net/10393/20295en |
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en |
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stochastic volatility long memory |
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stochastic volatility long memory Luo, Ling High Quantile Estimation for some Stochastic Volatility Models |
description |
In this thesis we consider estimation of the tail index for heavy tailed stochastic volatility models with long memory. We prove a central limit theorem for a Hill estimator. In particular, it is shown that neither the rate of convergence nor the asymptotic variance is affected by long memory. The theoretical findings are verified by simulation studies. |
author |
Luo, Ling |
author_facet |
Luo, Ling |
author_sort |
Luo, Ling |
title |
High Quantile Estimation for some Stochastic Volatility Models |
title_short |
High Quantile Estimation for some Stochastic Volatility Models |
title_full |
High Quantile Estimation for some Stochastic Volatility Models |
title_fullStr |
High Quantile Estimation for some Stochastic Volatility Models |
title_full_unstemmed |
High Quantile Estimation for some Stochastic Volatility Models |
title_sort |
high quantile estimation for some stochastic volatility models |
publishDate |
2011 |
url |
http://hdl.handle.net/10393/20295 |
work_keys_str_mv |
AT luoling highquantileestimationforsomestochasticvolatilitymodels |
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1716603548723052544 |