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UID:1700@i2m.univ-amu.fr
DTSTART;TZID=Europe/Paris:20170410T153000
DTEND;TZID=Europe/Paris:20170410T163000
DTSTAMP:20170326T133000Z
URL:https://www.i2m.univ-amu.fr/evenements/a-flexible-state-space-model-wi
 th-application-to-stochastic-volatility/
SUMMARY: (...): A Flexible State-Space Model with Application to Stochastic
  Volatility
DESCRIPTION:: We introduce a general state-space (or latent factor) model f
 or time series and panel data. The state process has a polynomial expansio
 n based dynamics that can approximate any Markov dynamics arbitrarily well
 \, and has a latent\, endogenous switching regime interpretation. The resu
 lting state-space model is associated with simulation-free\, recursive for
 mulas for prediction and filtering\, as well as the maximum composite like
 lihood estimation method\, which has an extremely low computational cost. 
 When applied to the stochastic volatility (SV) of asset returns\, the mode
 l captures\, in a unified framework\, stylized facts such as heavy tailed 
 return\, volatility feedback\, as well as time irreversibility. The method
 ology is illustrated using Apple stock return data\, which confirms the im
 provement of our model with respect to a benchmark SV model.https://www.gr
 eqam.fr/en/users/lu
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