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Forecasting trends with asset prices
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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.
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Cited by 1 Pith paper
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Stochastic Price Dynamics in Response to Order Flow Imbalance: Evidence from CSI 300 Index Futures
Order flow imbalance can be modeled as a mean-reverting Levy-driven shock to the price drift, giving closed-form mean and variance for future log returns.
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