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Continuous Time Model Estimation

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Abstract

This paper introduces an easy to follow method for continuous time model estimation. It serves as an introduction on how to convert a state space model from continuous time to discrete time, how to decompose a hybrid stochastic model into a trend model plus a noise model, how to estimate the trend model by simulation, and how to calculate standard errors from estimation of the noise model. It also discusses the numerical difficulties involved in discrete time models that bring about the unit roots illusion in econometrics.

Suggested Citation

  • Carl Chiarella & Shenhuai Gao, 2004. "Continuous Time Model Estimation," Working Paper Series 138, Finance Discipline Group, UTS Business School, University of Technology, Sydney.
  • Handle: RePEc:uts:wpaper:138
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    File URL: http://www.finance.uts.edu.au/research/wpapers/wp138.pdf
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    1. Carl Chiarella & Shenhuai Gao, 2002. "Modelling the Value of the S&P 500 - A System Dynamics Perspective," Working Paper Series 115, Finance Discipline Group, UTS Business School, University of Technology, Sydney.
    2. Harvey, Andrew, 1997. "Trends, Cycles and Autoregressions," Economic Journal, Royal Economic Society, vol. 107(440), pages 192-201, January.
    3. Carl Chiarella & Shenhuai Gao, 2002. "Type I Spurious Regression in Econometrics," Working Paper Series 114, Finance Discipline Group, UTS Business School, University of Technology, Sydney.
    4. Chiarella, Carl & Gao, Shenhuai, 2004. "The value of the S&P 500--A macro view of the stock market adjustment process," Global Finance Journal, Elsevier, vol. 15(2), pages 171-196, August.
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    Cited by:

    1. Carl Chiarella & Shenhuai Gao, 2002. "Modelling the Value of the S&P 500 - A System Dynamics Perspective," Working Paper Series 115, Finance Discipline Group, UTS Business School, University of Technology, Sydney.
    2. Chiarella, Carl & Gao, Shenhuai, 2004. "The value of the S&P 500--A macro view of the stock market adjustment process," Global Finance Journal, Elsevier, vol. 15(2), pages 171-196, August.

    More about this item

    Keywords

    Continuous time model; Estimation; Trend and noise decomposition; Unit roots illusion;

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation

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