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Forecasting trends with asset prices

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  • Ahmed Bel Hadj Ayed
  • Gr'egoire Loeper
  • Fr'ed'eric Abergel

Abstract

In this paper, we consider a stochastic asset price model where the trend is an unobservable Ornstein Uhlenbeck process. We first review some classical results from Kalman filtering. Expectedly, the choice of the parameters is crucial to put it into practice. For this purpose, we obtain the likelihood in closed form, and provide two on-line computations of this function. Then, we investigate the asymptotic behaviour of statistical estimators. Finally, we quantify the effect of a bad calibration with the continuous time mis-specified Kalman filter. Numerical examples illustrate the difficulty of trend forecasting in financial time series.

Suggested Citation

  • Ahmed Bel Hadj Ayed & Gr'egoire Loeper & Fr'ed'eric Abergel, 2015. "Forecasting trends with asset prices," Papers 1504.03934, arXiv.org, revised Apr 2015.
    • Handle: RePEc:arx:papers:1504.03934
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    References listed on IDEAS

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    Cited by:

    1. Ahmed Bel Hadj Ayed & Grégoire Loeper & Sofiene El Aoud & Frédéric Abergel, 2017. "Performance Analysis Of The Optimal Strategy Under Partial Information," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 20(02), pages 1-21, March.
    2. Ahmed Bel Hadj Ayed & Gr'egoire Loeper & Fr'ed'eric Abergel, 2016. "Robustness of mathematical models and technical analysis strategies," Papers 1605.00173, arXiv.org.
    3. Ahmed Bel Hadj Ayed & Gr'egoire Loeper & Sofiene El Aoud & Fr'ed'eric Abergel, 2015. "Performance analysis of the optimal strategy under partial information," Papers 1510.03596, arXiv.org.
    4. Ahmed Belhadjayed & Grégoire Loeper & Sofiene El Aoud & Frédéric Abergel, 2017. "Performance analysis of the optimal strategy under partial information," Post-Print hal-01512432, HAL.

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