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VERSION:2.0
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SUMMARY:Volatility is rough
DTSTART:20141104T123000
DTEND:20141104T133000
DTSTAMP:20260407T110530Z
UID:30d7d31117ff9a56bb73ee92c82dd399ec8ef0a3def820ea48be97bb
CATEGORIES:Conferences - Seminars
DESCRIPTION:Mathieu ROSENBAUM (Ecole Polytechnique\, Paris)\nEstimating vo
 latility from recent high frequency data\, we revisit the question of the 
 smoothness of the volatility process. We obtain that the regularity of the
  log-volatility corresponds to that of a fractional Brownian motion with H
 urst exponent of H order 0.15. This leads us to model the log-volatility a
 s a fractional Brownian motion with H<1/2\; specifically we adopt the frac
 tional stochastic volatility (FSV) model of Comte and Renault. We call our
  model Rough FSV (RSFV) to underline that\, in contrast to FSV\, H<1/2 and
  log-volatility behaves as fractional Brownian motion at all reasonable ti
 me scales. We demonstrate that our RFSV model is remarkably consistent wit
 h financial time series data\; one application is that it enables us to ob
 tain improved forecasts of realized volatility. Furthermore\, we find that
  although volatility is not long memory in the RFSV model\, classical stat
 istical procedures aiming at detecting volatility persistence tend to conc
 lude the presence of long memory in data generated from it.\nThis sheds li
 ght on why long memory of volatility has been widely accepted as a stylize
 d fact. Finally\, we provide a quantitative market microstructure-based fo
 undation for our findings. This is joint work with Jim Gatheral and Thibau
 lt Jaisson.
LOCATION:UNIL\, Extranef\, room 118 https://planete.unil.ch/plan/?local=EX
 T-118.1
STATUS:CONFIRMED
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