• Corpus ID: 18121590

A Branching Particle Approximation to the Filtering Problem with Counting Process Observations ∗

@inproceedings{Xiong2006ABP,
  title={A Branching Particle Approximation to the Filtering Problem with Counting Process Observations ∗},
  author={Jie Xiong and Yong Zeng},
  year={2006}
}
Recently, the filtering model with counting process observations has been demonstrated as a sensible framework for modeling the micromovement of asset price (or ultra-high frequency data). In this paper, we first construct a branching particle system for such a nonlinear filtering model. Then, we show the weighted empirical measures in the constructed branching system converges to the optimal filters uniformly in time by deriving sharp upper bounds for the mean square error. Furthermore, we… 

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Trade- by-trade stochastic volatility estimates for a Microsoft transaction data set are obtained and they provide strong affirmative evidence that volatility changes even more dramatically at trade-by-trade level.