IDEAS home Printed from https://ideas.repec.org/a/eee/proeco/v165y2015icp194-214.html
   My bibliography  Save this article

Generalized optimal wavelet decomposing algorithm for big financial data

Author

Listed:
  • Sun, Edward W.
  • Chen, Yi-Ting
  • Yu, Min-Teh

Abstract

Using big financial data for the price dynamics of U.S. equities, we investigate the impact that market microstructure noise has on modeling volatility of the returns. Based on wavelet transforms (DWT and MODWT) for decomposing the systematic pattern and noise, we propose a new wavelet-based methodology (named GOWDA, i.e., the generalized optimal wavelet decomposition algorithm) that allows us to deconstruct price series into the true efficient price and microstructure noise, particularly for the noise that induces the phase transition behaviors. This approach optimally determines the wavelet function, level of decomposition, and threshold rule by using a multivariate score function that minimizes the overall approximation error in data reconstruction. The data decomposition method enables us to estimate and forecast the volatility in a more efficient way than the traditional methods proposed in the literature. Through the proposed method we illustrate our simulation and empirical results of improving the estimation and forecasting performance.

Suggested Citation

  • Sun, Edward W. & Chen, Yi-Ting & Yu, Min-Teh, 2015. "Generalized optimal wavelet decomposing algorithm for big financial data," International Journal of Production Economics, Elsevier, vol. 165(C), pages 194-214.
  • Handle: RePEc:eee:proeco:v:165:y:2015:i:c:p:194-214
    DOI: 10.1016/j.ijpe.2014.12.033
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0925527314004277
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ijpe.2014.12.033?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Ramsey James B. & Lampart Camille, 1998. "The Decomposition of Economic Relationships by Time Scale Using Wavelets: Expenditure and Income," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 3(1), pages 1-22, April.
    2. Jianqing Fan & Yingying Li & Ke Yu, 2012. "Vast Volatility Matrix Estimation Using High-Frequency Data for Portfolio Selection," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 107(497), pages 412-428, March.
    3. Qiu, Xuan & Luo, Hao & Xu, Gangyan & Zhong, Runyang & Huang, George Q., 2015. "Physical assets and service sharing for IoT-enabled Supply Hub in Industrial Park (SHIP)," International Journal of Production Economics, Elsevier, vol. 159(C), pages 4-15.
    4. Sun, Edward W. & Rezania, Omid & Rachev, Svetlozar T. & Fabozzi, Frank J., 2011. "Analysis of the intraday effects of economic releases on the currency market," Journal of International Money and Finance, Elsevier, vol. 30(4), pages 692-707, June.
    5. Sun, Edward W. & Meinl, Thomas, 2012. "A new wavelet-based denoising algorithm for high-frequency financial data mining," European Journal of Operational Research, Elsevier, vol. 217(3), pages 589-599.
    6. Laukaitis, Algirdas, 2008. "Functional data analysis for cash flow and transactions intensity continuous-time prediction using Hilbert-valued autoregressive processes," European Journal of Operational Research, Elsevier, vol. 185(3), pages 1607-1614, March.
    7. Fan, Jianqing & Wang, Yazhen, 2007. "Multi-Scale Jump and Volatility Analysis for High-Frequency Financial Data," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 1349-1362, December.
    8. Ramsey, James B. & Lampart, Camille, 1998. "Decomposition Of Economic Relationships By Timescale Using Wavelets," Macroeconomic Dynamics, Cambridge University Press, vol. 2(1), pages 49-71, March.
    9. Edward Sun & Timm Kruse & Min-Teh Yu, 2014. "High frequency trading, liquidity, and execution cost," Annals of Operations Research, Springer, vol. 223(1), pages 403-432, December.
    10. Ramsey, J.B., 2002. "Wavelets in Economics and Finance: Past and Future," Working Papers 02-02, C.V. Starr Center for Applied Economics, New York University.
    11. Fan, Yanqin & Gençay, Ramazan, 2010. "Unit Root Tests With Wavelets," Econometric Theory, Cambridge University Press, vol. 26(5), pages 1305-1331, October.
    12. Meinl Thomas & Sun Edward W., 2012. "A Nonlinear Filtering Algorithm based on Wavelet Transforms for High-Frequency Financial Data Analysis," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 16(3), pages 1-24, September.
    13. Ramazan Gencay & Nikola Gradojevic & Faruk Selcuk & Brandon Whitcher, 2010. "Asymmetry of information flow between volatilities across time scales," Quantitative Finance, Taylor & Francis Journals, vol. 10(8), pages 895-915.
    14. Tangsucheeva, Rattachut & Prabhu, Vittaldas, 2014. "Stochastic financial analytics for cash flow forecasting," International Journal of Production Economics, Elsevier, vol. 158(C), pages 65-76.
    15. He, Feng & Shu, Lianjie & Tsui, Kwok-Leung, 2014. "Adaptive CUSUM charts for monitoring linear drifts in Poisson rates," International Journal of Production Economics, Elsevier, vol. 148(C), pages 14-20.
    16. Patrick M. Crowley, 2007. "A Guide To Wavelets For Economists," Journal of Economic Surveys, Wiley Blackwell, vol. 21(2), pages 207-267, April.
    17. Ferbar, Liljana & Creslovnik, David & Mojskerc, Blaz & Rajgelj, Martin, 2009. "Demand forecasting methods in a supply chain: Smoothing and denoising," International Journal of Production Economics, Elsevier, vol. 118(1), pages 49-54, March.
    18. Yongmiao Hong & Chihwa Kao, 2004. "Wavelet-Based Testing for Serial Correlation of Unknown Form in Panel Models," Econometrica, Econometric Society, vol. 72(5), pages 1519-1563, September.
    19. Siu-Tong Au & Rong Duan & Siamak Hesar & Wei Jiang, 2010. "A framework of irregularity enlightenment for data pre-processing in data mining," Annals of Operations Research, Springer, vol. 174(1), pages 47-66, February.
    20. Ramsey James B., 2002. "Wavelets in Economics and Finance: Past and Future," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 6(3), pages 1-29, November.
    21. Sun Wei & Rachev Svetlozar & Stoyanov Stoyan V. & Fabozzi Frank J., 2008. "Multivariate Skewed Student's t Copula in the Analysis of Nonlinear and Asymmetric Dependence in the German Equity Market," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 12(2), pages 1-37, May.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yi-Ting Chen & Edward W. Sun & Min-Teh Yu, 2018. "Risk Assessment with Wavelet Feature Engineering for High-Frequency Portfolio Trading," Computational Economics, Springer;Society for Computational Economics, vol. 52(2), pages 653-684, August.
    2. Chen Yi-Ting & Sun Edward W. & Yu Min-Teh, 2015. "Improving model performance with the integrated wavelet denoising method," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 19(4), pages 445-467, September.
    3. Sun, Edward W. & Meinl, Thomas, 2012. "A new wavelet-based denoising algorithm for high-frequency financial data mining," European Journal of Operational Research, Elsevier, vol. 217(3), pages 589-599.
    4. Lin, Fu-Lai & Yang, Sheng-Yung & Marsh, Terry & Chen, Yu-Fen, 2018. "Stock and bond return relations and stock market uncertainty: Evidence from wavelet analysis," International Review of Economics & Finance, Elsevier, vol. 55(C), pages 285-294.
    5. Christian M. Hafner, 2012. "Cross-correlating wavelet coefficients with applications to high-frequency financial time series," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(6), pages 1363-1379, December.
    6. Luís Aguiar-Conraria & Maria Joana Soares, 2014. "The Continuous Wavelet Transform: Moving Beyond Uni- And Bivariate Analysis," Journal of Economic Surveys, Wiley Blackwell, vol. 28(2), pages 344-375, April.
    7. Habimana, Olivier, 2017. "The multiscale relationship between exchange rates and fundamentals differentials: Empirical evidence from Scandinavia," MPRA Paper 75956, University Library of Munich, Germany.
    8. Chakrabarty, Anindya & De, Anupam & Gunasekaran, Angappa & Dubey, Rameshwar, 2015. "Investment horizon heterogeneity and wavelet: Overview and further research directions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 429(C), pages 45-61.
    9. Mundra, Sruti & Bicchal, Motilal, 2024. "Financial cycle comovement with monetary and macroprudential policy and global factors: Evidence from India," The North American Journal of Economics and Finance, Elsevier, vol. 71(C).
    10. George Tzagkarakis & Frantz Maurer, 2020. "An energy-based measure for long-run horizon risk quantification," Annals of Operations Research, Springer, vol. 289(2), pages 363-390, June.
    11. Huang, Yuting & Li, Qiang & Liow, Kim Hiang & Zhou, Xiaoxia, 2020. "Is Housing the Business Cycle? A Multiresolution Analysis for OECD Countries," Journal of Housing Economics, Elsevier, vol. 49(C).
    12. Gandjon Fankem, Gislain Stéphane & Fouda Mbesa, Lucien Cédric, 2023. "Business cycle synchronization and African monetary union: A wavelet analysis," Journal of Macroeconomics, Elsevier, vol. 77(C).
    13. repec:rza:wpaper:503 is not listed on IDEAS
    14. Stan Plessis & Gideon Rand & Kevin Kotzé, 2015. "Measuring Core Inflation in South Africa," South African Journal of Economics, Economic Society of South Africa, vol. 83(4), pages 527-548, December.
    15. Fernandez, Viviana, 2007. "A postcard from the past: The behavior of U.S. stock markets during 1871–1938," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 386(1), pages 267-282.
    16. Patrick M. Crowley, 2007. "A Guide To Wavelets For Economists," Journal of Economic Surveys, Wiley Blackwell, vol. 21(2), pages 207-267, April.
    17. Ryuta Sakemoto, 2022. "Multi‐scale inter‐temporal capital asset pricing model," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(4), pages 4298-4317, October.
    18. Rua, António, 2017. "A wavelet-based multivariate multiscale approach for forecasting," International Journal of Forecasting, Elsevier, vol. 33(3), pages 581-590.
    19. Hassan Farazmand & Amin Mansouri & Morteza Afghah, 2014. "Choosing the best type of wavelet: Case study-business cycle in Iran," Asian Journal of Empirical Research, Asian Economic and Social Society, vol. 4(5), pages 293-314, May.
    20. Viviana Fernandez, 2005. "Time-Scale Decomposition of Price Transmission in International Markets," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 41(4), pages 57-90, August.
    21. Crowley, Patrick M., 2005. "An intuitive guide to wavelets for economists," Bank of Finland Research Discussion Papers 1/2005, Bank of Finland.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:proeco:v:165:y:2015:i:c:p:194-214. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/ijpe .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.