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:20250330T010000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:+0300
TZOFFSETTO:+0200
TZNAME:EET
DTSTART:20251026T010000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=Europe/Helsinki:20250703T110000
DTEND;TZID=Europe/Helsinki:20250710T120000
DTSTAMP:20260710T134702
CREATED:20250321T110935Z
LAST-MODIFIED:20250702T123749Z
UID:17993-1751540400-1752148800@crest.science
SUMMARY:Paolo ZAFFARONI (Imperial College Business School)  "STATISTICAL ARBITRAGE WITHOUT ARBITRAGE"
DESCRIPTION:Finance-Insurance\nTime: 11.00 am\nDate:03th of July  2025\nRoom 3001 \nPaolo ZAFFARONI (Imperial College Business School) “STATISTICAL ARBITRAGE WITHOUT ARBITRAGE” \nAbstract : Statistical arbitrage strategies are quantitative trading strategies based on alpha\, i.e.\, on the signal extracted from the residuals when fitting an asset pricing model to re- turns data. We develop a normative theory that combines the insights of mean-variance portfolio choice with statistical arbitrage in the no-arbitrage setting of the APT\, that is we study statistical arbitrage without arbitrage . We establish a novel two-fund separation result that combines the inefficient statistical arbitrage portfolio and beta portfolio (i.e.\, the portfolio stemming from factor asset pricing models)\, showing how their combination can span the efficient frontier. In general\, as the number of assets increases\, the “statistical arbitrage portfolio” dominates the “beta portfolio” both in terms of the magnitude of its weights and in terms of its SR. Exploiting some insights of mean-variance portfolio choice\, we show how to construct a special statistical arbitrage portfolio that does not require estimating alpha\, in contrast to the common view. When statistical arbitrage is combined with factor asset pricing modelling\, alpha and the factors’ risk premia might not be jointly identified\, jeopardizing the possibility to construct a statistical arbitrage portfolio. We derive a penalized estimator under a no-arbitrage constraint that allows for the econometric identification of the statistical arbitrage portfolio\, leading to a shrinkage-type estimator. We demonstrate our theoretical insights by means of Monte Carlo experiments and empirical applications. \n[joint work with Massimo Dello Preite and Valentina Raponi]\n \nOrganizers:  Zakoian Jean-Michel \n  \n
URL:https://crest.science/event/paolo-zaffaroni-imperial-college-business-school-t-b-a/
CATEGORIES:Finance-Insurance,Seminars
ATTACH;FMTTYPE=:
END:VEVENT
END:VCALENDAR