BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//CREST - ECPv5.1.3//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-WR-CALNAME:CREST
X-ORIGINAL-URL:https://crest.science
X-WR-CALDESC:Events for CREST
BEGIN:VTIMEZONE
TZID:Europe/Helsinki
BEGIN:DAYLIGHT
TZOFFSETFROM:+0200
TZOFFSETTO:+0300
TZNAME:EEST
DTSTART:20260329T010000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:+0300
TZOFFSETTO:+0200
TZNAME:EET
DTSTART:20261025T010000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=Europe/Helsinki:20260402T110000
DTEND;TZID=Europe/Helsinki:20260402T120000
DTSTAMP:20260709T193643
CREATED:20260330T073238Z
LAST-MODIFIED:20260330T073238Z
UID:18895-1775127600-1775131200@crest.science
SUMMARY:Gilles DE TRUCHIS DE VARENNE (LEO) "Prediction of bubbles in presence of alpha-stable aggregates moving averages"
DESCRIPTION:Finance-Insurance\nTime: 11.00 am\nDate:02th of April 2026\nRoom 3001 \nGilles DE TRUCHIS DE VARENNE (LEO) “Prediction of bubbles in presence of alpha-stable aggregates moving averages” \nAbstract : Financial markets frequently exhibit dramatic episodes where asset prices undergo rapid growth followed by abrupt collapses\, that are incompatible with standard linear time series models. While anticipative heavy-tailed linear processes offer a promising alternative for modeling such phenomena\, they impose uniform bubble patterns across different episodes\, contradicting empirical evidence. This paper introduces a new model\, based on $\alpha$-stable moving average aggregates\, that accommodates heterogeneous bubble dynamics. We establish the theoretical properties of this model\, demonstrating that it admits a semi-norm representation on a unit cylinder\, thereby enabling the prediction of extreme trajectories with varying growth dynamics. We develop a minimum distance estimation procedure based on the joint characteristic function and establish its asymptotic properties. Monte Carlo simulations confirm the estimator’s good finite-sample performance across various specifications\, and we implement a subsampling methodology to empirically verify the convergence to asymptotic normality. Our empirical application to the CBOE Crude Oil ETF Volatility Index successfully decomposes observed volatility dynamics into distinct components with different persistence properties\, revealing that what appears as a single bubble episode actually consists of multiple superimposed processes with heterogeneous growth rates and crash probabilities. \nOrganizers:  Jean-Michel ZAKOIAN & Christian FRANCQ \n  \n
URL:https://crest.science/event/gilles-de-truchis-de-varenne-leo-prediction-of-bubbles-in-presence-of-alpha-stable-aggregates-moving-averages/
CATEGORIES:Finance-Insurance,Seminars
ATTACH;FMTTYPE=:
END:VEVENT
END:VCALENDAR