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UID:20250804T054827EDT-1201U32gUU@132.216.98.100
DTSTAMP:20250804T094827Z
DESCRIPTION:A new approach to model financial data: The Factorial Hidden Ma
 rkov Volatility Model\n\nA new process\, the factorial hidden Markov volat
 ility (FHMV) model\, is proposed to model financial returns or realized va
 riances. This process is constructed based on a factorial hidden Markov mo
 del structure and corresponds to a parsimoniously parametrized hidden Mark
 ov model that includes thousands of volatility states. The transition prob
 ability matrix of the underlying Markov chain is structured so that the mu
 ltiplicity of its second largest eigenvalue can be greater than one. This 
 distinctive feature allows for a better representation of volatility persi
 stence in financial data. Jumps and a leverage effect are also incorporate
 d into the model and statistical properties are discussed. An empirical st
 udy on six financial time series shows that the FHMV process compares favo
 rably to state-of-the-art volatility models in terms of in-sample fit and 
 out-of-sample forecasting performance over time horizons ranging from one 
 to one hundred days.\n
DTSTART:20180202T203000Z
DTEND:20180202T213000Z
LOCATION:Room 1205\, Burnside Hall\, CA\, QC\, Montreal\, H3A 0B9\, 805 rue
  Sherbrooke Ouest
SUMMARY:Maciej Augustyniak  Assistant Professor Université de Montréal
URL:/mathstat/channels/event/maciej-augustyniak-assist
 ant-professor-universite-de-montreal-284419
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