Particle Filter-Based On-Line Estimation of Spot Volatility with Nonlinear Market Microstructure Noise Models

Details Particle Filter-Based On-Line Estimation of Spot Volatility with Nonlinear Market Microstructure Noise Models Particle Filter-Based On-Line Estimation of Spot Volatility with Nonlinear Market Microstructure Noise Models

2010-06-09

arxiv.org/abs/1006.1860v2

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A new technique for the on-line estimation of spot volatility for high-frequency data is developed. The algorithm works directly on the transaction data and updates the volatility estimate immediately after the occurrence of a new transaction. Furthermore, a new nonlinear market microstructure noise model is proposed that reproduces several stylized facts of high-frequency data. A computationally efficient particle filter is used that allows for the approximation of the unknown efficient prices and, in combination with a recursive EM algorithm, for the estimation of the volatility curve. We neither assume that the transaction times are equidistant nor do we use interpolated prices. We also make a distinction between volatility per time unit and volatility per transaction and provide estimators for both.

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