Economy – Quantitative Finance – Statistical Finance
Scientific paper
2011-03-18
Economy
Quantitative Finance
Statistical Finance
Scientific paper
We perform wavelet decomposition of high frequency financial time series into high and low-energy spectral sectors. Taking the FTSE100 index as a case study, and working with the Haar basis, it turns out, very unsuspectedly, that the high-energy component and a fraction of the low-energy contribution, defined {\it{in toto}} by most ($\simeq$ 98%) of the wavelet coefficients, can be neglected for the purpose of option premium evaluation with expiration times in the range of a few days to one month. The relevant low-energy component, which has attenuated volatility (reduction by a factor $\simeq$ 1/10), is (i) normally distributed, (ii) long-range correlated for intraday prices and volatility, and (iii) time-reversal asymmetric. Our results indicate that the usual non-gaussian profiles of log-return distributions contain much more information than needed for option pricing, which is essentially dependent on hidden self-correlation properties of the underlying asset fluctuations.
de Almeida T. X. V.
Moriconi L.
No associations
LandOfFree
Denoising Surprises in Option Pricing does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with Denoising Surprises in Option Pricing, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Denoising Surprises in Option Pricing will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-185375