Forecasting High-Frequency Futures Returns Using Online Langevin Dynamics

  title={Forecasting High-Frequency Futures Returns Using Online Langevin Dynamics},
  author={Hugh L. Christensen and James K. Murphy and Simon J. Godsill},
  journal={IEEE Journal of Selected Topics in Signal Processing},
Forecasting the returns of assets at high frequency is the key challenge for high-frequency algorithmic trading strategies. In this paper, we propose a jump-diffusion model for asset price movements that models price and its trend and allows a momentum strategy to be developed. Conditional on jump times, we derive closed-form transition densities for this model. We show how this allows us to extract a trend from high-frequency finance data by using a Rao-Blackwellized variable rate particle… 
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