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SUMMARY:Bayesian inference for integer-valued Lévy processes with Non-Gau
 ssian Ornstein-Uhlenbeck volatility modelling - Andrea Cremaschi (Kent)
DTSTART:20140516T093000Z
DTEND:20140516T103000Z
UID:TALK52699@talks.cam.ac.uk
CONTACT:Zoubin Ghahramani
DESCRIPTION:Financial data are usually modelled as continuous\, often invo
 lving geometric Brownian motion with drift\, leverage and possibly jump co
 mponents. A more practical description enlightens the discrete nature of t
 he financial observations\, as integer multiples of a fixed quantity\, the
  ticksize\, the monetary value associated with a single change during the 
 evolution of the price. The class of integer-valued Lévy processes is use
 d to model the observations\, yielding desirable flexibility in the choice
  of the marginal distribution for a fixed time interval. Time deformation 
 is achieved including stochastic volatility as Non-Gaussian Ornstein-Uhlen
 ebeck processes. Bayesian inference is performed on application to real st
 ock market indices.
LOCATION:Engineering Department\, CBL Room BE-438
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