De-noising option prices with the wavelet method

► Wavelets de-noise perturbed option prices very well. ► Wavelet de-noising is necessary for density estimation from the option prices. ► Wavelet de-noising improves density estimation and forecasting ability. Financial time series are known to carry noise. Hence, techniques to de-noise such data de...

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Published inEuropean journal of operational research Vol. 222; no. 1; pp. 104 - 112
Main Authors Haven, Emmanuel, Liu, Xiaoquan, Shen, Liya
Format Journal Article
LanguageEnglish
Published Amsterdam Elsevier B.V 01.10.2012
Elsevier
Elsevier Sequoia S.A
Subjects
Applied sciences
De-noise
Exact sciences and technology
Mathematical functions
Monte Carlo simulation
Operational research and scientific management
Operational research. Management science
Option pricing
Planning. Forecasting
Portfolio theory
Securities prices
Studies
Time series
Wavelet analysis
Wavelet transforms
Wavelet analysis
Option pricing
Monte Carlo simulation
De-noise
Monte Carlo method
Noise reduction
Time series
Financial market
Modeling
Forecasting
Wavelet transformation
Stock exchange
Pricing
Density function
Financial data
Financial option
Tariffication
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Abstract ► Wavelets de-noise perturbed option prices very well. ► Wavelet de-noising is necessary for density estimation from the option prices. ► Wavelet de-noising improves density estimation and forecasting ability. Financial time series are known to carry noise. Hence, techniques to de-noise such data deserve great attention. Wavelet analysis is widely used in science and engineering to de-noise data. In this paper we show, through the use of Monte Carlo simulations, the power of the wavelet method in the de-noising of option price data. We also find that the estimation of risk-neutral density functions and out-of-sample price forecasting is significantly improved after noise is removed using the wavelet method.
AbstractList ► Wavelets de-noise perturbed option prices very well. ► Wavelet de-noising is necessary for density estimation from the option prices. ► Wavelet de-noising improves density estimation and forecasting ability. Financial time series are known to carry noise. Hence, techniques to de-noise such data deserve great attention. Wavelet analysis is widely used in science and engineering to de-noise data. In this paper we show, through the use of Monte Carlo simulations, the power of the wavelet method in the de-noising of option price data. We also find that the estimation of risk-neutral density functions and out-of-sample price forecasting is significantly improved after noise is removed using the wavelet method.
Financial time series are known to carry noise. Hence, techniques to de-noise such data deserve great attention. Wavelet analysis is widely used in science and engineering to de-noise data. In this paper we show, through the use of Monte Carlo simulations, the power of the wavelet method in the de-noising of option price data. We also find that the estimation of risk-neutral density functions and out-of-sample price forecasting is significantly improved after noise is removed using the wavelet method. [PUBLICATION ABSTRACT]
Author Shen, Liya
Liu, Xiaoquan
Haven, Emmanuel
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  fullname: Haven, Emmanuel
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  givenname: Xiaoquan
  surname: Liu
  fullname: Liu, Xiaoquan
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  givenname: Liya
  surname: Shen
  fullname: Shen, Liya
  email: lshenb@essex.ac.uk
  organization: Essex Business School, University of Essex, Colchester CO4 3SQ, UK
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Issue 1
Keywords Wavelet analysis
Option pricing
Monte Carlo simulation
De-noise
Monte Carlo method
Noise reduction
Time series
Financial market
Modeling
Forecasting
Wavelet transformation
Stock exchange
Pricing
Density function
Financial data
Financial option
Tariffication
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Snippet ► Wavelets de-noise perturbed option prices very well. ► Wavelet de-noising is necessary for density estimation from the option prices. ► Wavelet de-noising...
Financial time series are known to carry noise. Hence, techniques to de-noise such data deserve great attention. Wavelet analysis is widely used in science and...
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SubjectTerms Applied sciences
De-noise
Exact sciences and technology
Mathematical functions
Monte Carlo simulation
Operational research and scientific management
Operational research. Management science
Option pricing
Planning. Forecasting
Portfolio theory
Securities prices
Studies
Time series
Wavelet analysis
Wavelet transforms
Title De-noising option prices with the wavelet method
URI https://dx.doi.org/10.1016/j.ejor.2012.04.020
http://www.econis.eu/PPNSET?PPN=720438098
https://www.proquest.com/docview/1021014435
Volume 222
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