Option pricing from wavelet-filtered financial series

V.T.X. de Almeida and L. Moriconi

Physica A: Statistical Mechanics and its Applications, 2012, vol. 391, issue 20, 4850-4854

Abstract: We perform wavelet decomposition of high frequency financial time series into large and small time scale components. Taking the FTSE100 index as a case study, and working with the Haar basis, it turns out that the small scale component defined by most (≃99.6%) of the wavelet coefficients can be neglected for the purpose of option premium evaluation. The relevance of the hugely compressed information provided by low-pass wavelet-filtering is related to the fact that the non-gaussian statistical structure of the original financial time series is essentially preserved for expiration times which are larger than just one trading day.

Keywords: Dynamical hedging; Non-gaussian markets; Financial time series analysis (search for similar items in EconPapers)
Date: 2012
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:391:y:2012:i:20:p:4850-4854

DOI: 10.1016/j.physa.2012.05.030

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