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Subset Selection Using Frequency Decomposition with Applications

Author

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  • W. M. Tang

    (Department of Applied Mathematics, The Hong Kong Polytechnic University, Hung Hom Kowloon, Hong Kong, P. R. China)

  • K. F. C. Yiu

    (Department of Applied Mathematics, The Hong Kong Polytechnic University, Hung Hom Kowloon, Hong Kong, P. R. China)

  • H. Wong

    (Department of Applied Mathematics, The Hong Kong Polytechnic University, Hung Hom Kowloon, Hong Kong, P. R. China)

Abstract

In time series modeling, one problem is to identify a small number of influential factors to explain variations in the variable of interest. With a vast number of possible factors available, suitable features need to be identified to yield multi-factor models with good explanatory power. In this paper, we propose a novel subset selection method which makes use of the properties in the frequency domain environment. The proposed system ensures key patterns in the target variable be sought and suitable factors be selected based on frequency peaks in common. It can perform well even when the number of factors is significantly greater than the sample size. Moreover, a very important feature of the proposed system is the capability of handling factors with different timeframes, which is lacking in existing methods. We demonstrate the system via several examples with dataset from finance, economic, road traffic and air pollution.

Suggested Citation

  • W. M. Tang & K. F. C. Yiu & H. Wong, 2020. "Subset Selection Using Frequency Decomposition with Applications," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 19(01), pages 195-220, March.
    • Handle: RePEc:wsi:ijitdm:v:19:y:2020:i:01:n:s0219622019500500
    DOI: 10.1142/S0219622019500500
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    References listed on IDEAS

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    1. Ciner, Cetin, 2011. "Commodity prices and inflation: Testing in the frequency domain," Research in International Business and Finance, Elsevier, vol. 25(3), pages 229-237, September.
    2. Stephen A. Ross, 2013. "The Arbitrage Theory of Capital Asset Pricing," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 1, pages 11-30, World Scientific Publishing Co. Pte. Ltd..
    3. Alessandra Iacobucci, 2005. "Spectral Analysis for Economic Time Series," Lecture Notes in Economics and Mathematical Systems, in: Jacek Leskow & Lionello F. Punzo & Martín Puchet Anyul (ed.), New Tools of Economic Dynamics, chapter 12, pages 203-219, Springer.
    4. Costa, Michele & Gardini, Attilio & Paruolo, Paolo, 1997. "A Reduced Rank Regression Approach to Tests of Asset Pricing," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 59(1), pages 163-181, February.
    5. Burmeister, Edwin & McElroy, Marjorie B, 1988. " Joint Estimation of Factor Sensitivities and Risk Premia for the Arbitrage Pricing Theory," Journal of Finance, American Finance Association, vol. 43(3), pages 721-733, July.
    6. Cristian Gatu & Erricos Kontoghiorghes, 2002. "A branch and bound algorithm for computing the best subset regression models," Computing in Economics and Finance 2002 294, Society for Computational Economics.
    7. Fama, Eugene F. & French, Kenneth R., 1989. "Business conditions and expected returns on stocks and bonds," Journal of Financial Economics, Elsevier, vol. 25(1), pages 23-49, November.
    8. Hodrick, Robert J & Prescott, Edward C, 1997. "Postwar U.S. Business Cycles: An Empirical Investigation," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 29(1), pages 1-16, February.
    9. Gang Kou & Yanqun Lu & Yi Peng & Yong Shi, 2012. "Evaluation Of Classification Algorithms Using Mcdm And Rank Correlation," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 11(01), pages 197-225.
    10. Claeskens,Gerda & Hjort,Nils Lid, 2008. "Model Selection and Model Averaging," Cambridge Books, Cambridge University Press, number 9780521852258.
    11. Chen, Nai-Fu & Roll, Richard & Ross, Stephen A, 1986. "Economic Forces and the Stock Market," The Journal of Business, University of Chicago Press, vol. 59(3), pages 383-403, July.
    12. Priestley, Richard, 1996. "The arbitrage pricing theory, macroeconomic and financial factors, and expectations generating processes," Journal of Banking & Finance, Elsevier, vol. 20(5), pages 869-890, June.
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    Cited by:

    1. Yuancheng Si, 2020. "Pivot Property in Weighted Least Regression Based on Single Repeated Observations," Annals of Data Science, Springer, vol. 7(2), pages 291-306, June.
    2. David A. Alilah & C. O. Ouma & E. O. Ombaka, 2023. "Efficiency of Domain Mean Estimators in the Presence of Non-response Using Two-Stage Sampling with Non-linear and Linear Cost Function," Annals of Data Science, Springer, vol. 10(2), pages 291-316, April.

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