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Analysis of ultra-high-frequency financial data using advanced Fourier transforms

Giampaoli, Iacopo and Constantinou, Nick and Ng, Wing Lon (2009) 'Analysis of ultra-high-frequency financial data using advanced Fourier transforms.' Finance Research Letters, 6 (1). pp. 47-53. ISSN 1544-6123

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Abstract

This paper presents a novel application of advanced methods from Fourier analysis to the study of ultra-high-frequency financial data. The use of Lomb–Scargle Fourier transform, provides a robust framework to take into account the irregular spacing in time, minimising the computational effort. Likewise, it avoids complex model specifications (e.g. ACD or intensity models) or resorting to traditional methods, such as (linear or cubic) interpolation and regular resampling, which not only cause artifacts in the data and loss of information, but also lead to the generation and use of spurious information.

Item Type: Article
Uncontrolled Keywords: Ultra-high frequency data; Irregularly spaced data; Fourier analysis
Subjects: H Social Sciences > HG Finance
Divisions: Faculty of Science and Health > Computer Science and Electronic Engineering, School of > Centre for Computational Finance and Economic Agents
Depositing User: Nick Constantinou
Date Deposited: 04 Nov 2011 17:03
Last Modified: 16 Dec 2014 11:20
URI: http://repository.essex.ac.uk/id/eprint/1283

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