Nothing Special   »   [go: up one dir, main page]
IDEAS home Printed from https://ideas.repec.org/p/uts/wpaper/138.html
   My bibliography  Save this paper

Continuous Time Model Estimation

Author

Listed:
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
    as

    Download full text from publisher

    File URL: http://www.finance.uts.edu.au/research/wpapers/wp138.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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.

    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. Carl Chiarella & Shenhuai Gao, 2002. "Solving the Price-Earnings Puzzle," Working Paper Series 116, Finance Discipline Group, UTS Business School, University of Technology, Sydney.
    2. Maravall, A. & del Rio, A., 2007. "Temporal aggregation, systematic sampling, and the Hodrick-Prescott filter," Computational Statistics & Data Analysis, Elsevier, vol. 52(2), pages 975-998, October.
    3. Moreno, Manuel & Novales, Alfonso & Platania, Federico, 2019. "Long-term swings and seasonality in energy markets," European Journal of Operational Research, Elsevier, vol. 279(3), pages 1011-1023.
    4. Suzanne McCoskey & Chihwa Kao, 1997. "A Monte Carlo Comparison of Tests for Cointegration in Panel Data," Econometrics 9712002, University Library of Munich, Germany.
    5. Zietz, Joachim A. & Penn, David A., 2008. "An Unobserved Components Forecasting Model of Non-Farm Employment for the Nashville MSA," Journal of Regional Analysis and Policy, Mid-Continent Regional Science Association, vol. 38(1), pages 1-10.
    6. Neha Seth & Monica Sighania, 2017. "Financial market contagion: selective review of reviews," Qualitative Research in Financial Markets, Emerald Group Publishing Limited, vol. 9(4), pages 391-408, November.
    7. Stanova, Nadja, 2015. "Effects of fiscal shocks in new EU members estimated from a SVARX model with debt feedback," MPRA Paper 63148, University Library of Munich, Germany.
    8. Bruno Chiarini, 1998. "Cyclicality of real wages and adjustment costs," Applied Economics, Taylor & Francis Journals, vol. 30(9), pages 1239-1250.
    9. Hunt, Lester C. & Judge, Guy & Ninomiya, Yasushi, 2003. "Underlying trends and seasonality in UK energy demand: a sectoral analysis," Energy Economics, Elsevier, vol. 25(1), pages 93-118, January.
    10. B. Bhaskara Rao, 2010. "Deterministic and stochastic trends in the time series models: a guide for the applied economist," Applied Economics, Taylor & Francis Journals, vol. 42(17), pages 2193-2202.
    11. Bhaskara Rao, B. & Rao, Gyaneshwar, 2009. "Cointegration and the demand for gasoline," Energy Policy, Elsevier, vol. 37(10), pages 3978-3983, October.
    12. Kitov, Ivan & Kitov, Oleg & Dolinskaya, Svetlana, 2007. "Inflation as a function of labor force change rate: cointegration test for the USA," MPRA Paper 2734, University Library of Munich, Germany.
    13. Tehreem Fatima & Enjun Xia & Muhammad Ahad, 2019. "Oil demand forecasting for China: a fresh evidence from structural time series analysis," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 21(3), pages 1205-1224, June.
    14. Ivan O. KITOV & Oleg I. KITOV & Svetlana A. DOLINSKAYA, 2009. "Modelling Real Gdp Per Capita In The Usa:Cointegration Tests," Journal of Applied Economic Sciences, Spiru Haret University, Faculty of Financial Management and Accounting Craiova, vol. 4(1(7)_ Spr).
    15. Li, Jing, 2012. "Economic segregation and urban growth," MPRA Paper 41050, University Library of Munich, Germany.
    16. Rangan GUPTA & Roula INGLESI-LOTZ, 2012. "Macro Shocks and Real US Stock Prices with Special Focus on the “Great Recession”," Applied Econometrics and International Development, Euro-American Association of Economic Development, vol. 12(2).
    17. Aldubyan, Mohammad & Gasim, Anwar, 2021. "Energy price reform in Saudi Arabia: Modeling the economic and environmental impacts and understanding the demand response," Energy Policy, Elsevier, vol. 148(PB).
    18. Broadstock, David C. & Hunt, Lester C., 2010. "Quantifying the impact of exogenous non-economic factors on UK transport oil demand," Energy Policy, Elsevier, vol. 38(3), pages 1559-1565, March.
    19. Zietz, Joachim & Traian, Anca, 2014. "When was the U.S. housing downturn predictable? A comparison of univariate forecasting methods," The Quarterly Review of Economics and Finance, Elsevier, vol. 54(2), pages 271-281.
    20. Homagni Choudhury & Zoltan Laszlo Kopacsi & Gunjan Saxena & Nishikant Mishra, 2021. "The Ethical Dimension in Political Market Orientation: A Framework for Evaluating the Impact of India’s Look East Policy on Regional Income Convergence," Journal of Business Ethics, Springer, vol. 168(2), pages 353-372, January.

    More about this item

    Keywords

    Continuous time model; Estimation; Trend and noise decomposition; Unit roots illusion;
    All these keywords.

    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

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    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:uts:wpaper:138. 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: Duncan Ford (email available below). General contact details of provider: https://edirc.repec.org/data/sfutsau.html .

    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.