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Beating the Random Walk: a Performance Assessment of Long-term Interest Rate Forecasts

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Author Info

  • Frank A.G. den Butter

    ()
    (VU University Amsterdam)

  • Pieter W. Jansen

    (Aegon Investment Management)

Abstract

This paper assesses the performance of a number of long-term interest rate forecast approaches, namely time series models, structural economic models, expert forecasts and combinations thereof. The predictive performance of these approaches is compared using out of sample forecast errors, where a random walk forecast acts as benchmark. It is found that for five major OECD countries, namely United States, Germany, United Kingdom, The Netherlands and Japan, the other forecasting approaches do not outperform the random walk, or a somewhat more sophisticated time series model, on a 3 month forecast horizon. On a 12 month forecast horizon the random walk model can be outperformed by a model that combines economic data and expert forecasts. Here several methods of combination are considered: equal weights, optimized weights and weights based on forecast error. It appears that the additional information contents of the structural models and expert knowledge is only relevant for forecasting 12 months ahead.

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Bibliographic Info

Paper provided by Tinbergen Institute in its series Tinbergen Institute Discussion Papers with number 08-102/3.

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Date of creation: 28 Oct 2008
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Handle: RePEc:dgr:uvatin:20080102

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Keywords: interest rate forecasting; expert knowledge; combining forecasts; optimizing forecast errors;

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