IDEAS home Printed from https://ideas.repec.org/a/wsi/serxxx/v50y2005i02ns0217590805001962.html
   My bibliography  Save this article

Assessing Pre-Crisis Fundamentals In Selected Asian Stock Markets

Author

Listed:
  • EE LENG LAU

    (Division of Economics, School of Humanities and Social Sciences, Nanyang Technological University, Nanyang Avenue, Singapore 639798, Singapore)

  • G. K. RANDOLPH TAN

    (Division of Economics, School of Humanities and Social Sciences, Nanyang Technological University, Nanyang Avenue, Singapore 639798, Singapore)

  • SHAHIDUR RAHMAN

    (Division of Economics, School of Humanities and Social Sciences, Nanyang Technological University, Nanyang Avenue, Singapore 639798, Singapore)

Abstract

In the folklore of emerging markets, there is a popular belief that bubbles are inevitable. In this paper, our objective is to estimate a state-space model for rational bubbles in selected Asian economies with the aid of the Kalman Filter. For each economy, we derive a possible picture of the bubble formation process that is implied by the state-space formulation. The estimation is based on the rational valuation formula for stock prices. Our results provide a possible way of defining the presence of rational bubbles in the stock markets of Taiwan, Singapore, Korea, and Malaysia.

Suggested Citation

  • Ee Leng Lau & G. K. Randolph Tan & Shahidur Rahman, 2005. "Assessing Pre-Crisis Fundamentals In Selected Asian Stock Markets," The Singapore Economic Review (SER), World Scientific Publishing Co. Pte. Ltd., vol. 50(02), pages 175-196.
  • Handle: RePEc:wsi:serxxx:v:50:y:2005:i:02:n:s0217590805001962
    DOI: 10.1142/S0217590805001962
    as

    Download full text from publisher

    File URL: http://www.worldscientific.com/doi/abs/10.1142/S0217590805001962
    Download Restriction: Access to full text is restricted to subscribers

    File URL: https://libkey.io/10.1142/S0217590805001962?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. Harvey,Andrew C., 1991. "Forecasting, Structural Time Series Models and the Kalman Filter," Cambridge Books, Cambridge University Press, number 9780521405737.
    2. Behzad T. Diba & Herschel I. Grossman, 1984. "Rational Bubbles in the Price of Gold," NBER Working Papers 1300, National Bureau of Economic Research, Inc.
    3. Mathias Binswanger, 1999. "Stock Markets, Speculative Bubbles and Economic Growth," Books, Edward Elgar Publishing, number 1749.
    4. Harvey, Andrew & Snyder, Ralph D., 1990. "Structural time series models in inventory control," International Journal of Forecasting, Elsevier, vol. 6(2), pages 187-198, July.
    5. Franses, Philip Hans, 1996. "Periodicity and Stochastic Trends in Economic Time Series," OUP Catalogue, Oxford University Press, number 9780198774549.
    6. Steven Radelet & Jeffrey Sachs, 1998. "The Onset of the East Asian Financial Crisis," NBER Working Papers 6680, National Bureau of Economic Research, Inc.
    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. Tsaubin Chen & Chiang Ku Fan, 2019. "Non-performing Loans and Housing Prices in Taiwan," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 9(6), pages 1-4.

    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. Avanzi, Benjamin & Taylor, Greg & Vu, Phuong Anh & Wong, Bernard, 2020. "A multivariate evolutionary generalised linear model framework with adaptive estimation for claims reserving," Insurance: Mathematics and Economics, Elsevier, vol. 93(C), pages 50-71.
    2. Ying Shu & Chengfu Ding & Lingbing Tao & Chentao Hu & Zhixin Tie, 2023. "Air Pollution Prediction Based on Discrete Wavelets and Deep Learning," Sustainability, MDPI, vol. 15(9), pages 1-19, April.
    3. Azumah Karim & Ananda Omotukoh Kube & Bashiru Imoro Ibn Saeed, 2020. "Modeling of Monthly Meteorological Time Series," Journal of Statistical and Econometric Methods, SCIENPRESS Ltd, vol. 9(4), pages 1-8.
    4. Yossi Aviv, 2003. "A Time-Series Framework for Supply-Chain Inventory Management," Operations Research, INFORMS, vol. 51(2), pages 210-227, April.
    5. Syntetos, A.A. & Teunter, R.H., 2014. "On the calculation of safety stocks," Research Report 14003-OPERA, University of Groningen, Research Institute SOM (Systems, Organisations and Management).
    6. Riezebos, Jan & Zhu, Stuart X., 2020. "Inventory control with seasonality of lead times," Omega, Elsevier, vol. 92(C).
    7. Pavel Vidal & Gilberto Ramírez & Lya Paola Sierra, 2018. "¿Por qué el Valle del Cauca ha crecido más que el promedio nacional? Un análisis regional de los ciclos y los choques económicos," Working Papers 33, Faculty of Economics and Management, Pontificia Universidad Javeriana Cali.
    8. Cartea, Álvaro & Karyampas, Dimitrios, 2011. "Volatility and covariation of financial assets: A high-frequency analysis," Journal of Banking & Finance, Elsevier, vol. 35(12), pages 3319-3334.
    9. Agnieszka Gehringer & Thomas Mayer, 2021. "Measuring the Business Cycle Chronology with a Novel Business Cycle Indicator for Germany," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 17(1), pages 71-89, April.
    10. Gianluca Cubadda, 2007. "A Reduced Rank Regression Approach to Coincident and Leading Indexes Building," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 69(2), pages 271-292, April.
    11. 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).
    12. Jesús Fernández-Villaverde & Pablo A. Guerrón-Quintana, 2021. "Estimating DSGE Models: Recent Advances and Future Challenges," Annual Review of Economics, Annual Reviews, vol. 13(1), pages 229-252, August.
    13. Vegard H. Larsen & Leif Anders Thorsrud, 2018. "Business cycle narratives," Working Paper 2018/3, Norges Bank.
    14. Thomas Chiang & Lin Tan & Jiandong Li & Edward Nelling, 2013. "Dynamic Herding Behavior in Pacific-Basin Markets: Evidence and Implications," Multinational Finance Journal, Multinational Finance Journal, vol. 17(3-4), pages 165-200, September.
    15. Marios Poulos, 2016. "Determining the Stationarity Distance via a Reversible Stochastic Process," PLOS ONE, Public Library of Science, vol. 11(10), pages 1-23, October.
    16. Sergio Contreras-Espinoza & Francisco Novoa-Muñoz & Szabolcs Blazsek & Pedro Vidal & Christian Caamaño-Carrillo, 2022. "COVID-19 Active Case Forecasts in Latin American Countries Using Score-Driven Models," Mathematics, MDPI, vol. 11(1), pages 1-17, December.
    17. Agnieszka Kleszcz & Krzysztof Rusek, 2022. "Has EU accession boosted patents performance in the EU-13? -- A critical evaluation using causal impact analysis with Bayesian structural time-series models," Papers 2201.09878, arXiv.org.
    18. Agnieszka Kleszcz & Krzysztof Rusek, 2022. "Has EU Accession Boosted Patent Performance in the EU-13? A Critical Evaluation Using Causal Impact Analysis with Bayesian Structural Time-Series Models," Forecasting, MDPI, vol. 4(4), pages 1-16, October.
    19. William Gatt, 2022. "MEDSEA-FIN: an estimated DSGE model with housing and financial frictions for Malta," CBM Working Papers WP/05/2022, Central Bank of Malta.
    20. Jorge Barrientos Marin & Elkin Tabares Orozco & Esteban Velilla, 2018. "Forecasting electricity price in Colombia: A comparison between Neural Network, ARMA process and Hybrid Models," International Journal of Energy Economics and Policy, Econjournals, vol. 8(3), pages 97-106.

    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:wsi:serxxx:v:50:y:2005:i:02:n:s0217590805001962. 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: Tai Tone Lim (email available below). General contact details of provider: http://www.worldscinet.com/ser/ser.shtml .

    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.