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Reference: Ysusi Mendoza, Carla Mariana., (2005). Estimation of the variation of prices using high-frequency financial data. DPhil. University of Oxford.Citable link to this page:


Estimation of the variation of prices using high-frequency financial data

Abstract: When high-frequency data is available, realised variance and realised absolute variation can be calculatedfrom intra-day prices. In the context of a stochastic volatility model, realised variance andrealised absolute variation can estimate the integrated variance and the integrated spot volatility respectively.A central limit theory enables us to do filtering and smoothing using model-based andmodel-free approaches in order to improve the precision of these estimators.When the log-price process involves a finite activity jump process, realised variance estimates thequadratic variation of both continuous and jump components. Other consistent estimators of integratedvariance can be constructed on the basis of realised multipower variation, i.e., realised bipower, tripowerand quadpower variation. These objects are robust to jumps in the log-price process. Therefore, givenadequate asymptotic assumptions, the difference between realised multipower variation and realisedvariance can provide a tool to test for jumps in the process.Realised variance becomes biased in the presence of market microstructure effect, meanwhile realisedbipower, tripower and quadpower variation are more robust in such a situation. Neverthelessthere is always a trade-off between bias and variance; bias is due to market microstructure noise whensampling at high frequencies and variance is due to the asymptotic assumptions when sampling at lowfrequencies. By subsampling and averaging realised multipower variation this effect can be reduced,thereby allowing for calculations with higher frequencies.

Type of Award:DPhil Level of Award:Doctoral Awarding Institution: University of Oxford Notes:The digital copy of this thesis has been made available thanks to the generosity of Dr Leonard Polonsky


Shephard, NeilMore by this contributor



Prof. Neil ShephardMore by this contributor


 Bibliographic Details

Issue Date: 2005Identifiers

Urn: uuid:1b520271-2a63-428d-b5a0-e7e9c4afdc66

Source identifier: 603849540 Item Description

Type: Thesis;

Language: eng Subjects: Central limit theorem Stochastic processes Finance Mathematical models Tiny URL: td:603849540


Autor: Ysusi Mendoza, Carla Mariana. - institutionUniversity of Oxford facultyMathematical and Physical Sciences Division - - - - Contri



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