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;VALUE=DATE:20260611 DTEND;VALUE=DATE:20260613 DTSTAMP:20260709T175449 CREATED:20260507T053400Z LAST-MODIFIED:20260507T053413Z UID:18952-1781136000-1781308799@crest.science SUMMARY:4th Paris Workshop on Game Theory and Language - Half a Century of "Agreeing to Disagree" DESCRIPTION:4th Paris Workshop\non Game Theory and Language\nHalf a Century of “Agreeing to Disagree”\nJune 11-12\, 2026\nHalf a century after its publication\, Robert Aumann’s Agreement Theorem (“Agreeing to Disagree”\, The Annals of Statistics\, 1976) has not ceased to intrigue and inspire. \nThe Agreement Theorem states that if two individuals assign the same prior probability over the set of possible states of the world and if — thanks to the common knowledge of their information partitions — the posterior probabilities they attribute to an event are common knowledge\, then these posterior probabilities must be identical. \nAumann’s result builds on a conceptual innovation that is as powerful as elegant: identifying what is commonly known between the participants of an exchange with the meet — the finest common coarsening — of the information partitions. \nThe agreement result and the formal language of modeling knowledge and beliefs introduced by Aumann have generated research in multiple directions: \n\ndynamic foundations in the form of Bayesian dialogues and applications of these to betting and trading scenarios (Bacharach 1979\, Geanakoplos and Polemarchakis 1982\, Milgrom and Stokey 1982\, Sebenius and Geanakoplos 1983)\,\ngeneralizations of the result moving from partitions to σ-algebras and from knowledge of an event to knowledge of random variables (for instance\, Nielsen 1984)\nnotions of “almost” common knowledge (Halpern 1986\, Rubinstein 1989\, Halpern and Moses 1990\, Fagin et al. 1995) and approximate common knowledge in the form of common belief (Geanakoplos 1994\, Morris 1999\, Monderer and Samet 1989)\,\nrelaxations of the common prior hypothesis (Di Tillio\, Lehrer\, and Samet 2022\, Gizatulina and Hellman 2019\, Hellman and Pintér 2022).\n\nWith this workshop\, we honor the fiftieth anniversary of the publication of “Agreeing to Disagree.” \nMore information and program on the Workshop’s website. \n URL:https://crest.science/event/4th-paris-workshop-on-game-theory-and-language-half-a-century-of-agreeing-to-disagree/ CATEGORIES:Conferences and Workshops,Economics END:VEVENT BEGIN:VEVENT DTSTART;TZID=Europe/Helsinki:20260611T100000 DTEND;TZID=Europe/Helsinki:20260611T230000 DTSTAMP:20260709T175449 CREATED:20260601T055748Z LAST-MODIFIED:20260602T061327Z UID:18982-1781172000-1781218800@crest.science SUMMARY:Giuseppe CAVALIERE (Bologna University\, Italy) "Kappa = 1" DESCRIPTION:Finance-Insurance\nTime: 10.00 am\nDate:11th of June  2026\nRoom 3001 \nGiuseppe CAVALIERE (Bologna University\, Italy) “Kappa = 1” \nAbstract :Integrated autoregressive conditional duration (ACD) models serve as counterparts to integrated generalized autoregressive conditional heteroskedastic models used for financial returns. However\, despite their resemblance\, asymptotic theory for ACD is still incomplete. Central challenges arise from the facts that: (i) integrated ACD processes imply durations with tail index $\kappa = 1$ and infinite expectation; (ii) conventional asymptotic approaches break down due to the randomness in the number of durations within a fixed observation period. We fill this gap in the literature and provide a unified asymptotic theory for the (quasi)maximum likelihood estimator for integrated ACD models. Based on the new theoretical results\, we also provide a novel framework for hypothesis testing in duration models\, enabling inference on a key empirical question: whether durations possess a finite or infinite expectation. We apply our results to high-frequency cryptocurrency exchange traded fund (ETF) trading data. Motivated by parameter estimates near the integrated ACD region\, we assess whether durations between trades in these markets have finite expectation\, an assumption often made implicitly in the literature on point process models. Our empirical findings indicate infinite-mean durations for all five cryptocurrency ETFs examined\, and we reject the integrated ACD hypothesis in favour of heavier-tailed alternatives for four out of the five ETFs. \nJoint work :  T. Mikosch\, A. Rahbek and F. Vilandt\, U Copenhagen \n  \n URL:https://crest.science/event/giuseppe-cavaliere-bologna-university-italy-kappa-1/ CATEGORIES:Finance-Insurance,Seminars ATTACH;FMTTYPE=: END:VEVENT BEGIN:VEVENT DTSTART;TZID=Europe/Helsinki:20260611T110000 DTEND;TZID=Europe/Helsinki:20260611T120000 DTSTAMP:20260709T175449 CREATED:20260601T060044Z LAST-MODIFIED:20260602T061148Z UID:18985-1781175600-1781179200@crest.science SUMMARY:Alessandra LUATI (Imperial College\, UK) "On a nu-class of limit-Gaussian distributions" DESCRIPTION:Finance-Insurance\nTime: 11.00 am\nDate:11th of June  2026\nRoom 3001 \nAlessandra LUATI (Imperial College\, UK) “On a nu-class of limit-Gaussian distributions .” \nAbstract : We discuss a transformation of a Student-t random variable that arises in the field of robust filtering with score-driven models. As a function of the degrees of freedom parameter of the generating Student-t random variable\, here interpreted as a shape parameter\, 1