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    An evaluation of alternative forecasting models for natural rubber prices

    13249_Lim, Jit Yang 2002.pdf (10.68Mb)
    Access Status
    Open access
    Authors
    Lim, Jit Yang
    Date
    2002
    Supervisor
    Dr Meher Manzur
    Dr Garry MacDonald
    Assoc. Prof. Ian Kerr
    Type
    Thesis
    Award
    PhD
    
    Metadata
    Show full item record
    School
    School of Economics and Finance
    URI
    http://hdl.handle.net/20.500.11937/1731
    Collection
    • Curtin Theses
    Abstract

    One of the prominent features of the Natural Rubber (NR) market is its price variability, and the aim of this study is to project accurate short-term NR prices. This is accomplished by exploiting the use of forecasting techniques and information sets to seek the combination with the best forecasts, and exploring best ways of combining forecasts. We evaluate the relative performance of 19 models based upon three different forecasting techniques, and four information sets. In addition, we compare their forecasts with 13 other forecasts combined in various different ways, and taking the Naive forecast as benchmark. The generalised autoregressive conditional heteroscedasticity regression (or ARCH-type) models, though more complex, are generally better than the simpler regression models. In general, the performance of the various techniques seems to perform consistently well (or poorly) over the forecasting horizons, with alternations in performance due mainly to the type of information set used. We also adopted a simple trading rule to find out the economic values of our forecasts, and the results are most promising. Importantly, the forecasts generated from the alternative models developed in this study can potentially be beneficial to participants in the NR futures market.

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