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Optimal investment in markets with over and under-reaction to information

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Abstract

In this paper we introduce a jump-diffusion model of shot-noise type for stock prices, taking into account over and under-reaction of the market to incoming news. We work in a partial information setting, by supposing that standard investors do not have access to the market direction, the drift, (modeled via a random variable) after a jump. We focus on the expected (logarithmic) utility maximization problem by providing the optimal investment strategy in explicit form, both under full (i.e., from the insider point of view, aware of the right kind of market reaction at any time) and under partial information (i.e., from the standard investor viewpoint, who needs to infer the kind of market reaction from data). We test our results on market data relative to Enron and Ahold. The three main contributions of this paper are: the introduction of a new market model dealing with over and under-reaction to news, the explicit computation of the optimal filter dynamics using an original approach combining enlargement of filtrations with Innovation Theory and the application of the optimal portfolio allocation rule to market data.

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Article Open access 05 November 2018

Clifford S. Asness, Andrea Frazzini & Lasse Heje Pedersen

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Authors and Affiliations

  1. Dipartimento di Matematica, Università di Padova, Padova, Italy

    Giorgia Callegaro

  2. LAMSIN, Université de Tunis El Manar, Tunis, Tunisia

    M’hamed Gaïgi

  3. LPMA, CNRS UMR 7599, Université Paris Diderot, Paris, France

    Simone Scotti

  4. Dipartimento di Matematica, Politecnico di Milano, Milano, Italy

    Carlo Sgarra

Authors
  1. Giorgia Callegaro
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  2. M’hamed Gaïgi
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  3. Simone Scotti
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  4. Carlo Sgarra
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Correspondence to Carlo Sgarra.

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Callegaro, G., Gaïgi, M., Scotti, S. et al. Optimal investment in markets with over and under-reaction to information. Math Finan Econ 11, 299–322 (2017). https://doi.org/10.1007/s11579-016-0182-8

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  • DOI: https://doi.org/10.1007/s11579-016-0182-8

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