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Improving model performance with the integrated wavelet denoising method

Improving model performance with the integrated wavelet denoising method Abstract Intelligent pattern recognition imposes new challenges in high-frequency financial data mining due to its irregularities and roughness. Based on the wavelet transform for decomposing systematic patterns and noise, in this paper we propose a new integrated wavelet denoising method, named smoothness-oriented wavelet denoising algorithm (SOWDA), that optimally determines the wavelet function, maximal level of decomposition, and the threshold rule by using a smoothness score function that simultaneously detects the global and local extrema. We discuss the properties of our method and propose a new evaluation procedure to show its robustness. In addition, we apply this method both in simulation and empirical investigation. Both the simulation results based on three typical stylized features of financial data and the empirical results in analyzing high-frequency financial data from Frankfurt Stock Exchange confirm that SOWDA significantly (based on the RMSE comparison) improves the performance of classical econometric models after denoising the data with the discrete wavelet transform (DWT) and maximal overlap discrete wavelet transform (MODWT) methods. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Studies in Nonlinear Dynamics & Econometrics de Gruyter

Improving model performance with the integrated wavelet denoising method

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Publisher
de Gruyter
Copyright
Copyright © 2015 by the
ISSN
1081-1826
eISSN
1558-3708
DOI
10.1515/snde-2014-0057
Publisher site
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Abstract

Abstract Intelligent pattern recognition imposes new challenges in high-frequency financial data mining due to its irregularities and roughness. Based on the wavelet transform for decomposing systematic patterns and noise, in this paper we propose a new integrated wavelet denoising method, named smoothness-oriented wavelet denoising algorithm (SOWDA), that optimally determines the wavelet function, maximal level of decomposition, and the threshold rule by using a smoothness score function that simultaneously detects the global and local extrema. We discuss the properties of our method and propose a new evaluation procedure to show its robustness. In addition, we apply this method both in simulation and empirical investigation. Both the simulation results based on three typical stylized features of financial data and the empirical results in analyzing high-frequency financial data from Frankfurt Stock Exchange confirm that SOWDA significantly (based on the RMSE comparison) improves the performance of classical econometric models after denoising the data with the discrete wavelet transform (DWT) and maximal overlap discrete wavelet transform (MODWT) methods.

Journal

Studies in Nonlinear Dynamics & Econometrics – de Gruyter

Published: Sep 1, 2015

References

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  • Wavelet Transforms and Commodity Prices Studies in
    Connor
  • of the Intraday Effects of Economic Releases on the Currency Market of and
    Sun
  • Unit Root Tests with Wavelets
    Fan
  • Adapting to Unknown Smoothness via Wavelet Shrinkage of the
    Donoho
  • Wavelets
    Keinert
  • The Decomposition of Economic Relationships by Time Scale Using Wavelets Expenditure and Income in Nonlinear Dynamics and
    Ramsey
  • Wavelet - based Spectral Procedure for Steady - state Simulation
    Lada
  • New Approach for Using Lèvy Processes for Determining High - Frequency Value - at - Risk Predictions
    Sun
  • Estimation via Wavelet Shrinkage of
    Donoho
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    Meinl
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    Ramsey
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    Daubechies
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    Gençay
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    Aguiar
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    Mallat
  • Detection with Wavelets for High - frequency Financial Time Series
    Gençay
  • Wavelets
    Keinert
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    Sun
  • - noising Option Prices with the Wavelet Method
    Haven
  • Wavelet for Time Series University
    Percival
  • Incorporating Information on Neighboring Coefficients into Wavelet Estimation The of
    Cai
  • Asymptotic Minimax Risk for Sup - Norm Loss : Solution via Optimal Recovery and Related
    Donoho
  • An Alternative Maximum Likelihood Estimator of Long - memory Processes using Compactly Supported Wavelets of Economic Dynamics and
    Jensen
  • systematic risk of and
    Gençay
  • Sampling Theory and Wave Propagation Issues in Acoustic Signal Processing Recognition
    Morlet
  • Wavelet - based Testing for Serial Correlation of Unknown Form In Panel Models
    Hong
  • The Fractal Geometry of Co Ltd San CA
    Mandelbrot
  • Functional Data Analysis for Cash Flow and Transactions Intensity Continuous - Time Prediction Using Hilbert - Valued Autoregressive Processes
    Laukaitis
  • in High - frequency Financial Data and Hierarchical Models Studies in Nonlinear
    McCulloch
  • In Investment Effect on Asset Allocation Between Value and Growth Strategies Modelling
    Kim
  • An Introduction to Wavelets and other Filtering Methods in Finance and San Academic
    Gençay
  • Sampling Theory and Wave Propagation Issues in Acoustic Signal Processing Recognition
    Morlet
  • Wavelet - based Testing for Serial Correlation of Unknown Form In Panel Models
    Hong
  • The Fractal Geometry of Co Ltd San CA
    Mandelbrot
  • Procedures for Detecting Outlying Observations in Samples
    Grubbs
  • In The Relationship between Financial Variables and Real Economic Activity : Evidence from Spectral and Wavelet in Nonlinear Dynamics and
    Kim
  • Incorporating Information on Neighboring Coefficients into Wavelet Estimation The of
    Cai
  • Private High frequency Stochastic Volatility Studies in
    Kelly
  • Multivariate Skewed Student s t Copula in the Analysis of Nonlinear and Asymmetric Dependence in the German Equity Market Studies in Nonlinear
    Sun
  • The Yield Curve and the Macro - economy Across Time and Frequencies of Economic Dynamics and
    Aguiar
  • Procedures for Detecting Outlying Observations in Samples
    Grubbs
  • Continuous - time Growth Models with Boundary Conditions via Wavelets of Economic Dynamics and
    Esteban
  • An Alternative Maximum Likelihood Estimator of Long - memory Processes using Compactly Supported Wavelets of Economic Dynamics and
    Jensen
  • Ideal Spatial Adaptation by Wavelet Shrinkage
    Donoho
  • High Frequency Trading Liquidity Execution Cost of
    Sun
  • Guide to Wavelets for Economists of
    Crowley
  • Private High frequency Stochastic Volatility Studies in
    Kelly
  • Ten Lectures on Wavelets volume of - in for Industrial and Philadelphia PA
    Daubechies
  • Asymptotic Minimax Risk for Sup - Norm Loss : Solution via Optimal Recovery and Related
    Donoho
  • Multi scale Volatility Analysis for High - Frequency Financial Data of the
    Fan
  • Functional Data Analysis for Cash Flow and Transactions Intensity Continuous - Time Prediction Using Hilbert - Valued Autoregressive Processes
    Laukaitis
  • Estimation via Wavelet Shrinkage of
    Donoho
  • - noising Option Prices with the Wavelet Method
    Haven
  • Adapting to Unknown Smoothness via Wavelet Shrinkage of the
    Donoho
  • Detection with Wavelets for High - frequency Financial Time Series
    Gençay
  • Wavelet Transforms and Commodity Prices Studies in
    Connor
  • Minimum Contrast Estimators on Sieves Exponential Bounds and Rates of
    Birgé
  • Singularity Detection and Processing with Wavelets on
    Mallat
  • Conditional Value at Risk and Average Value at Risk Estimation Asymptotics
    Chun
  • Unit Root Tests with Wavelets
    Fan
  • systematic risk of and
    Gençay
  • Wavelet for Time Series University
    Percival
  • Systematic Risk
    Gençay
  • Ideal Spatial Adaptation by Wavelet Shrinkage
    Donoho
  • Jumps in Financial Markets New Nonparametric Test Dynamics of
    Lee
  • Conditional Value at Risk and Average Value at Risk Estimation Asymptotics
    Chun
  • Guide to Wavelets for Economists of
    Crowley
  • High Frequency Trading Liquidity Execution Cost of
    Sun
  • Singularity Detection and Processing with Wavelets on
    Mallat
  • Nonlinear Filtering Algorithm Based on Wavelet Transforms for High - frequency Financial Data in Nonlinear Dynamics and
    Meinl
  • Systematic Risk
    Gençay
  • Multi scale Volatility Analysis for High - Frequency Financial Data of the
    Fan
  • Errors - in - Variables Estimation with Wavelets of and
    Gençay
  • Wavelet - based Spectral Procedure for Steady - state Simulation
    Lada
  • Jumps in Financial Markets New Nonparametric Test Dynamics of
    Lee
  • or Evidence of Long - Range Dependence and Heavy Tailedness from Modeling German Equity Market Returns of and
    Sun
  • An Introduction to Wavelets and other Filtering Methods in Finance and San Academic
    Gençay
  • New Wavelet - based Denoising Algorithm for High - frequency Financial Data Mining
    Sun
  • Continuous - time Growth Models with Boundary Conditions via Wavelets of Economic Dynamics and
    Esteban
  • New Wavelet - based Denoising Algorithm for High - frequency Financial Data Mining
    Sun
  • Theory for Multiresolution Signal Decomposition The Wavelet Representation on and
    Mallat
  • in Past Future in and
    Ramsey
  • Multivariate Skewed Student s t Copula in the Analysis of Nonlinear and Asymmetric Dependence in the German Equity Market Studies in Nonlinear
    Sun
  • New Approach for Using Lèvy Processes for Determining High - Frequency Value - at - Risk Predictions
    Sun
  • Minimum Contrast Estimators on Sieves Exponential Bounds and Rates of
    Birgé
  • in High - frequency Financial Data and Hierarchical Models Studies in Nonlinear
    McCulloch
  • In Investment Effect on Asset Allocation Between Value and Growth Strategies Modelling
    Kim
  • The Decomposition of Economic Relationships by Time Scale Using Wavelets Expenditure and Income in Nonlinear Dynamics and
    Ramsey
  • of the Intraday Effects of Economic Releases on the Currency Market of and
    Sun