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Forecasting trends with asset prices

Author

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  • Ahmed Bel Hadj Ayed
  • Grégoire Loeper
  • Frédéric Abergel

Abstract

The question of interest in this paper is the estimation of the trend of a financial asset, and the impact of its misspecification on investment strategies. The setting we consider is that of a stochastic asset price model where the trend follows an unobservable Ornstein–Uhlenbeck process. Motivated by the use of Kalman filtering as a forecasting tool, we address the problem of parameter estimation, and measure the effect of parameter misspecification. Numerical examples illustrate the difficulty of trend forecasting in financial time series.

Suggested Citation

  • Ahmed Bel Hadj Ayed & Grégoire Loeper & Frédéric Abergel, 2017. "Forecasting trends with asset prices," Quantitative Finance, Taylor & Francis Journals, vol. 17(3), pages 369-382, March.
    • Handle: RePEc:taf:quantf:v:17:y:2017:i:3:p:369-382
    DOI: 10.1080/14697688.2016.1206959
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    Cited by:

    1. Ivan Guo & Nicolas Langrené & Gregoire Loeper & Wei Ning, 2020. "Robust utility maximization under model uncertainty via a penalization approach," Working Papers hal-02910261, HAL.
    2. Valeriy Zakamulin & Javier Giner, 2020. "Trend following with momentum versus moving averages: a tale of differences," Quantitative Finance, Taylor & Francis Journals, vol. 20(6), pages 985-1007, June.

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