Options as a predictor of common stock price changes

Dirk Emma Baestaens, Willem Max Van Den Bergh and Herve Vaudrey

The European Journal of Finance, 1995, vol. 1, issue 4, 325-343

Abstract: Since rather novel techniques such as neural nets allow investigation of nonlinear model specification previously untested, it may be that traditional models of price formation underperform through misspecification rather than market efficiency. This paper explores whether a multilayer backpropagation model offers exploitable profit opportunities for some limited period. Using an intradaytransaction dataset obtained from the European Options Exchange (Amsterdam), We attempted to predict the return on Philips. Two neural nets are contrasted to ordinary linear regression analysis on the basis of three benchmarks (MSE, and net realized returns). An adaptively trained 33-14-1 architecture scored best on all criteria and yielded an annualized 11% return following a simple one-period trading strategy.

Keywords: option pricing; intraday transaction data; stock return prediction; multilayer backpropagation algorithm (search for similar items in EconPapers)
Date: 1995
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DOI: 10.1080/13518479500000023

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