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Risk Neutral Forecasting

  • Spyros Skouras

    (University of Cambridge Gonville and Caius College)

Any mapping that has the same sign as the conditional mean of returns is a risk neutral investor's best predictor so it may be difficult to estimate the conditional mean yet easy to estimate a `risk neutral best predictor'. An asymptotically consistent estimator for risk neutral best predictors is proposed and is characterised both analytically and using simulations. Our results suggest that there are broad circumstances in which an investor should prefer forecasts based on this estimator to those generated by maximum likelihood estimation of the conditional mean. To facilitate the estimator's computation, a tailor-made algorithm is proposed and its properties are investigated.The decision problem we choose to focus on leads to the development of statistical and computational methods which can be applied to the estimation of `investment rules' and of `economically valuable' forecasting models.

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Paper provided by Society for Computational Economics in its series Computing in Economics and Finance 2000 with number 117.

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Date of creation: 05 Jul 2000
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Handle: RePEc:sce:scecf0:117
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