Inference of Spot Volatility in the presence of Infinite Variation Jumps
Date/Time:27 Jun 2018 15:30Venue: S17 #04-04 SR3Speaker: Johnson, Liu Qiang, University of MacauInference of Spot Volatility in the presence of Infinite Variation JumpsEmpirical evidences witness that the jumps appear to be very frequent in the financial markets. In this talk, we propose a kernel estimator for the spot volatility of an Ito semi-martingale at a given time point by using the high frequency data, under the circumstance that the jumps contained in the underlying driven process could be of infinite variation. The estimator is based on the representation of the characteristic function of Levy processes. The consistency of the proposed estimator is established under some mild assumptions. By assuming that the jump part of the underlying process behaves like a symmetric stable Levy process around 0, we establish the asymptotic normality of the proposed estimator. In particular, with a specific kernel function, the estimator is variance efficient. We conduct Monte Carlo simulation studies to assess our theoretical results. We also extend our theories to the estimation of spot covariation quantities between two Ito semi-martingales. Our estimators are applied to some real high frequency financial data sets for empirical analysis.Add to calendar:
