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Time-Series Analysis: Components, Models, and Forecasting

In: HANDBOOK OF FINANCIAL ECONOMETRICS, MATHEMATICS, STATISTICS, AND MACHINE LEARNING

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  • Cheng Few Lee

Abstract

In this chapter, we first discuss the classical time-series component model, then we discuss the moving average and seasonally adjusted time-series. A discussion on linear and log-linear time trend regressions follows. The autoregressive forecasting model as well as the ARIMA model are both reviewed. Finally, composite forecasting is discussed.

Suggested Citation

  • Cheng Few Lee, 2020. "Time-Series Analysis: Components, Models, and Forecasting," World Scientific Book Chapters, in: Cheng Few Lee & John C Lee (ed.), HANDBOOK OF FINANCIAL ECONOMETRICS, MATHEMATICS, STATISTICS, AND MACHINE LEARNING, chapter 26, pages 979-1024, World Scientific Publishing Co. Pte. Ltd..
    • Handle: RePEc:wsi:wschap:9789811202391_0026
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    More about this item

    Keywords

    Financial Econometrics; Financial Mathematics; Financial Statistics; Financial Technology; Machine Learning; Covariance Regression; Cluster Effect; Option Bound; Dynamic Capital Budgeting; Big Data;
    All these keywords.

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill

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