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Seminario PRISMA lun 3 giu 2024
by Francesco Caravenna 27 May '24

27 May '24

Seminari on-line del gruppo UMI - PRISMA (http://www.umi-prisma.polito.it/ <http://www.umi-prisma.polito.it/>) I seminari PRISMA hanno un formato di "colloquium" per creare un'occasione di scambio e discussione con tutta la comunità dei probabilisti e statistici italiani. Ogni giornata comprende due relatori che tengono due seminari di 30 minuti strettamente connessi, per presentare alla comunità una prospettiva sul proprio ambito di ricerca. Da quest'anno le registrazioni dei seminari vengono pubblicate sul canale YouTube dell'UMI: https://youtube.com/playlist?list=PLmySpc-jrtAMq84VH71evyqPc1hl6eEQb <https://youtube.com/playlist?list=PLmySpc-jrtAMq84VH71evyqPc1hl6eEQb> Il prossimo appuntamento è per lunedì 3 giugno 2024. I relatori saranno Alessandro De Gregorio (Sapienza Università di Roma) e Stefano Iacus (Harvard University) che parleranno di Stimatori regolarizzati per equazioni differenziali stocastiche osservate a tempi discreti con il seguente orario: 16:00 Primo seminario 16:30 Pausa e discussione 16:45 Secondo seminario 17:15 Conclusione e discussione Trovate di seguito il riassunto. I seminari verranno trasmessi via Zoom al seguente link: https://uniroma1.zoom.us/j/82939128330 <https://uniroma1.zoom.us/j/82939128330> Meeting ID: 829 3912 8330 Vi aspettiamo numerosi! Valentina Cammarota e Francesco Caravenna %%%%%%%%%%%%%%%%%%%%%%%%%%%% RELATORI: Alessandro De Gregorio (Sapienza Università di Roma) e Stefano Iacus (Harvard University) TITOLO: Stimatori regolarizzati per equazioni differenziali stocastiche osservate a tempi discreti RIASSUNTO: Gli stimatori regolarizzati, cioè quegli stimatori che presentano dei termini di penalizzazione nella funzione di perdita, rappresentano uno strumento fondamentale nell'ambito della moderna teoria dell'apprendimento statistico. In questo seminario discuteremo problemi di stima parametrica penalizzata per equazioni differenziali stocastiche osservate a tempi discreti. Tale tema di ricerca è di recente interesse nell'ambito della statistica per processi stocastici. Nella prima parte del seminario, dopo una breve panoramica sulle tecniche di stima per equazioni differenziali stocastiche, introdurremo i modelli stocastici sparsi; ovvero si ipotizza che solo un piccolo numero di parametri determini il "vero" modello. In questo contesto è cruciale considerare degli stimatori regolarizzati che consentano di effettuare la stima e contemporaneamente la selezione del processo di diffusione. In particolare, saranno introdotti gli stimatori LASSO ed Elastic-Net e verranno discusse le loro proprietà asintotiche. La seconda parte dell'intervento sarà dedicata alle equazioni differenziali stocastiche su reti, in cui ciascun nodo della rete è un un'equazione stocastica che dipende dai nodi vicini. Questi modelli vengono introdotti poiché consentono di analizzare serie storiche ad altissima dimensione, sfruttando la struttura sparsa del grafo. Anche in questo contesto saranno introdotti e studiati stimatori penalizzati per la stima dei parametri del modello. Inoltre, la performance degli stimatori mediante sarà analizzate tramite alcune applicazioni. %%%%%%%%%%%%%%%%%%%%%%%%%%%%

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Fwd: Deadline extended for ESOBE 2024
by Roberto CASARIN 27 May '24

27 May '24

fyi ---------- Forwarded message --------- Da: Sune Karlsson <Sune.Karlsson(a)oru.se> Date: lun 27 mag 2024 alle ore 14:27 Subject: Deadline extended for ESOBE 2024 To: <ECONOMETRIC-RESEARCH(a)jiscmail.ac.uk> The deadline for submitting papers to ESOBE 2024 (European Seminar on Bayesian Econometrics) has been extended to June 9, 2024. Submit a paper or an extended abstract by sending an e-mail to ESOBE2024(a)oru.se We welcome submissions from all fields of applied Bayesian econometrics (macro, micro and financial), as well as papers on statistical methodology, machine learning and computing. The conference will feature both plenary and poster sessions. The conference will take place on August 22-24 at Örebro University. Please see the conference website https://www.oru.se/esobe2024 for additional information. --- Sune Karlsson Professor of Statistics Handelshögskolan/Örebro University School of Business Phone: +46 19 301257 https://www.oru.se/hh/sune_karlsson https://econpapers.repec.org/RAS/pka1.htm E-mailing Örebro University will result in the university processing your personal data, for more information on how this is done, see https://www.oru.se/english/about-us/processing-of-personal-data-at-orebro-u…. E-mail correspondence with Örebro University may be classified as official and public documents and are handled according to archive regulations. ######################################################################## To unsubscribe from the ECONOMETRIC-RESEARCH list, click the following link: https://www.jiscmail.ac.uk/cgi-bin/WA-JISC.exe?SUBED1=ECONOMETRIC-RESEARCH&… This message was issued to members of www.jiscmail.ac.uk/ECONOMETRIC-RESEARCH, a mailing list hosted by www.jiscmail.ac.uk, terms & conditions are available at https://www.jiscmail.ac.uk/policyandsecurity/ -- Roberto Casarin, PhD Professor of Econometrics Ca' Foscari University of Venice San Giobbe 873/b - 30121 Venezia, Italy http://sites.google.com/view/robertocasarin/ https://www.unive.it/vera <https://www.unive.it/isba2024> https://www.unive.it/isba2024

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Fwd: [owps] Reminder next OWPS
by Faggionato, Alessandra 27 May '24

27 May '24

Buongiorno ricevo e con piacere inoltro. Saluti Alessandra ---------- Forwarded message --------- From: One World Probability <ow.probability(a)gmail.com> Date: Mon, 27 May 2024 at 08:40 Subject: [owps] Reminder next OWPS To: <owps(a)lists.bath.ac.uk> This is a gentle reminder that the next OWPS will be *today* from *15:00* to *17:00* *CEST *time. There will be two talks on the topic of exploration driven analysis of random graphs. The talks will touch upon general techniques and specific applications of these techniques. Title, abstract and the zoom link are below the signature and can be found on the website https://www.owprobability.org/one-world-probability-seminar <https://protect-eu.mimecast.com/s/-zGkCWqjZFlpkVlsnEyR_?domain=eur01.safeli…> . ----------------------- Talk 1 :* Mariana Olvera-Cravioto, University of North Carolina at Chapel Hill* Local limits and preferential attachment graphs This talk is meant to provide an overview of local weak convergence techniques for a large class of directed random graphs, including static models such as the Erdos-Renyi, Chung-Lu, stochastic block model, and configuration models, as well as dynamic models such as the collapsed branching process and the directed preferential attachment graph. We explain how local limits can be used to study important structural graph properties, including centrality measures such as the PageRank distribution. We further use the insights obtained from our analysis of centrality measures to explain how static models and evolving models differ in how large degree vertices are distributed within the graph and how they shape their neighborhoods. In particular, we show that the empirically accepted “power-law hypothesis” on scale-free graphs, which states that the PageRank distribution follows a power-law with the same tail index as the in-degree distribution, holds in most static models but not in the dynamic models we study. This is joint work with: Sayan Banerjee and Prabhanka Deka. Talk 2 : Sayan Banerjee, *University of North Carolina at Chapel Hill* Exploration-driven networks We propose and investigate a class of random networks where incoming vertices locally explore the graph before attaching to an existing vertex. Specific instances of these networks correspond to uniform attachment, linear preferential attachment and attachment with probability proportional to vertex PageRanks. We obtain local weak limits for such networks and use them to derive asymptotics for the limiting empirical degree and PageRank distribution. We also quantify asymptotics for the degree and PageRank of fixed vertices, including the root, and the height of the network. Two distinct regimes are seen to emerge, based on the expected exploration distance of incoming vertices, which we call the ‘fringe’ and ‘non-fringe’ regimes. These regimes are shown to exhibit different qualitative and quantitative properties. In particular, networks in the non-fringe regime undergo ‘condensation’ where the root degree grows at the same rate as the network size. Networks in the fringe regime do not exhibit condensation. Interesting phase transition phenomena are exhibited for the height of the tree and the limiting PageRank distribution. The latter connects to the well-known power-law hypothesis and the proposed class of models `interpolate’ between the PageRank behavior of static and dynamic graphs discussed in Mariana’s talk. Based on joint works with Mariana Olvera-Cravioto, Shankar Bhamidi and Xiangying (Zoe) Huang. Zoom-link: https://zoom.us/j/3766827761 Meeting ID: 376 682 7761 Passcode: sPNKq1 -- ************************************************* Prof. Alessandra Faggionato https://www1.mat.uniroma1.it/people/faggionato/ Department of Mathematics University "La Sapienza" Piazzale Aldo Moro, 5 00185 - Rome Office 123, first floor *************************************************

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talk Prof. Domenico Marinucci on May 27 - DIMA - UNIGE
by Ernesto De Vito 24 May '24

24 May '24

Dear all, this is a kind reminder of the following seminar Speaker : Domenico Marinucci (https://sites.google.com/view/domenicomarinucci/home) Affiliation: Dipartimento di Matematica - Università Roma Tor Vergata Title: Spectral complexity of deep neural networks Date: Monday, May 27, 2024 at 11.30 Place: Aula 704 (7th floor) , Dipartimento di Matematica at University of Genova, Via Dodencaneso 35, Teams link: https://teams.microsoft.com/l/meetup-join/19%3ameeting_NTEyMmU4MWEtZjIwOC00… Abstract: It is well-known that randomly initialized, push-forward, fully-connected neural networks weakly converge to isotropic Gaussian processes, in the limit where the width of all layers goes to infinity. In this paper, we propose to use the angular power spectrum of the limiting fields to characterize the complexity of the network architecture. In particular, we define sequences of random variables associated with the angular power spectrum, and provide a full characterization of the network complexity in terms of the asymptotic distribution of these sequences as the depth diverges. On this basis, we classify neural networks as low-disorder, sparse, or high-disorder; we show how this classification highlights a number of distinct features for standard activation functions, and in particular, sparsity properties of ReLU networks. Our theoretical results are also validated by numerical simulations. Joint work with Simmaco Di Lillo, Michele Salvi e Stefano Vigogna Best wishes, Ernesto --------------------- Ernesto De Vito DIMA - Dipartimento di Matematica MaLGa - Machine Learning Genoa center Via Dodecaneso 35 16146 Genova Italy e-mail: ernesto.devito(a)unige.it tel: +390103536783

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talk Dott. Marco Tarsia on May 29, 2024
by Mastrogiacomo Elisa 24 May '24

24 May '24

Dear all, you are invited to participate to the following seminar on Wednesday 29th of May 2024 at 12:00: Title: STOCHASTIC ORDERINGS FOR SET-VALUED RISK MEASURES Abstract: We introduce and analyze from an axiomatic point of view an extension to the set-valued scenario of the maximal correlation risk measure as defined by Burgert and Rüschendorf (2006). Furthermore, we present the notion of stochastic ordering for random vectors, utilizing the upper expectation operator - introduced in Hamel and Heyde (2021) - in conjunction with extensive classes of multidimensional functions. We then explore the consistency of such stochastic orderings for appropriate set-valued risk measures. These measures resemble the maximal correlation risk measure, offering flexibility regarding adherence to all the axioms of a portfolio aggregator and a proper set-valued risk measure. A remarkable example within this category is represented by law-invariant set-valued risk measures, such as the set-valued distortion risk measure as defined, for example, in Chen and Hu (2019). The in-person presentation will be held in Room 3 Padiglione Morselli, Via Ottorino Rossi, 9, 21100 Varese VA<https://www.google.com/maps/place//data=!4m2!3m1!1s0x478681f7697827db:0x771…>, Insubria University. Scan the QR code in the attached file to join the seminar online in MS Teams. Best regards, Elisa Mastrogiacomo Elisa Mastrogiacomo ----------------------------------------- Professore Ordinario di Metodi matematici dell'economia e delle scienze attuariali e finanziarie DIPARTIMENTO D'ECCELLENZA 2023/2027 Università degli Studi dell'Insubria Dipartimento di Economia Via Monte Generoso, 71 – 21100 Varese tel. +39 0332/395528 web: www.uninsubria.it<http://www.uninsubria.it/> mail: elisa.mastrogiacomo(a)uninsubria.it<mailto:mario.rossi@uninsubria.it> Chiaramente Insubria! [LOGO-ATENEO-FONDO TRASPARENTE]<http://www.uninsubria.it/> [Facebook] <https://www.facebook.com/uninsubria> [Twitter] <https://twitter.com/Uni_Insubria> [Instagram] <https://instagram.com/uninsubria> [YouTube] <https://www.youtube.com/user/LabVAMultimedia>

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JOB: Research Associate in Bayesian Statistics, Newcastle University
by Fabrizio Leisen 24 May '24

24 May '24

Con preghiera di diffusione. IMPORTANTE: Il candidato deve gia avere un dottorato di ricerca. Non sono considerati candidati che non hanno ancora ottenuto (o stanno per ottenere) un dottorato di ricerca. È richiesta buona conoscenza di Statistica Bayesiana e metodi computazionali. È una posizione di due anni basata a Newcastle. Il progetto sarà supervisionato da me, Prof. Cristiano Villa e Prof. Kevin Wilson. Cordiali Saluti, Fabrizio -- Fabrizio Leisen Professor of Statistics King’s College London Department of Mathematics Strand | WC2R 2LS | London JOB: Research Associate in Bayesian Statistics School of Mathematics, Statistics and Physics, Newcastle University Full advert: https://jobs.ncl.ac.uk/job/Newcastle-Research-Associate-in-Bayesian-Statist… Applications are invited from outstanding individuals for a Research Associate in Bayesian Statistics, to start from August/September 2024 for a period of two years. The project is at the forefront of Bayesian inference and aims to design a novel Bayesian methodology to implement Bayesian Additive Regression Trees (BART) models to deal with non-linear phenomena. In particular, the aim is to bridge the Loss-based methodology to the framework of BART, building on the previous works of Dr Cristiano Villa and Prof. Fabrizio Leisen on model selection, linear regression models and Gaussian graphical models. The successful candidate will work on developing prior distributions to estimate the structure of the trees and the number of trees in a BART model, and building scalable and efficient computational tools to ease the implementation of the methodology. The candidate must have a solid background in computational methods for Bayesian inference to develop efficient algorithms for the new proposed modelling framework. Within the project, the candidate will also perform theoretical modelling and data analysis, as well as disseminate the outputs through publications and presentations at scientific meetings. The successful candidate will join the growing Statistics group at Newcastle University and interact with the Statistics group at King's College London. The position is offered on a fixed term basis for two years from the start date, or tenable until the project end date, whichever is soonest. Generous funds are available for travel, training and other support. To apply, please complete the online application and attach a CV and covering letter by the deadline of 23rd June 2024. In your covering letter, please outline how you are either working towards, meet or exceed all the essential requirements for the role holder as outlined in the full advertisement, and highlight any expertise relevant to the project. For all information enquiries about the position, please contact Dr Kevin Wilson (kevin.wilson(a)newcastle.ac.uk<mailto:kevin.wilson@newcastle.ac.uk>), Prof Cristiano Villa (cristiano.villa(a)dukekunshan.edu.cn<mailto:cristiano.villa@dukekunshan.edu.cn>) or Prof. Fabrizio Leisen (fabrizio.leisen(a)kcl.ac.uk<mailto:fabrizio.leisen@kcl.ac.uk>). Kind Regards Kevin Dr Kevin Wilson Reader in Applied Statistics School of Mathematics, Statistics & Physics Newcastle University kevin.wilson(a)newcastle.ac.uk You may leave the list at any time by sending the command SIGNOFF allstat to listserv(a)jiscmail.ac.uk, leaving the subject line blank. -- Fabrizio Leisen Professor of Statistics King’s College London Department of Mathematics Strand | WC2R 2LS | London

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UPDATED: Time Series Models for Financial and Environmental Risk - May 30 - Ca' Foscari University
by Roberto CASARIN 21 May '24

21 May '24

Dear Colleagues, On Thursday the 30th of May you are all warmly invited to our one-day workshop organised under the GRINS Project on *Time Series Models for Financial and Environmental Risk* Participation is free. However, for organizational purposes, you are kindly asked to register by May the 27th here https://bit.ly/form-workshop-timeseriesmodels . Ca’ Foscari University, San Giobbe Economics Campus, Meeting Room 1, Venezia *Program:* 10.00am Registration 10.45am *Welcome Remarks: Prof. Monica Billio, Ca’ Foscari University of Venice, Project Leder of the Grins Spoke 4, Sustainable Finance.* *1st Session* 11.00am *Prof.* *Giacomo Bormetti, University of Pavia*, *Measuring price impact and information content of trades in a time-varying setting.* 11.45am *Dr. Giuseppe Buccheri, University of Verona*, *Semiparametric Estimation of Volatility in the Presence of Intraday Drift Dynamics.* 12.30pm Lunch *2nd Session* 2.00pm* Dr. Dario Palumbo, Ca' Foscari University of Venice*, *An Observation-Driven Generalized Poisson Model*. 2.45pm *Dr. Enzo D'Innocenzo, University of Bologna, **Limit results for score-driven filters**.* 3.30pm Coffee break 4.00pm *Keynote speech**: Prof. Andrew Harvey, University of Cambridge. **Score-driven models: overview and recent developments.* *Abstracts*: *Prof.* *Giacomo Bormetti,*University of Pavia, Italy https://unipv.unifind.cineca.it/get/person/021642 *Measuring price impact and information content of trades in a time-varying setting* We propose a non-linear observation-driven version of the Hasbrouck (1991) model for dynamically estimating trades' market impact and information content. We find that market impact displays an intraday pattern superimposed with large fluctuations. Some of them are exogenous, and, as an example, we investigate market impact dynamics around FOMC announcements. Contrary to Hasbrouck (1991), we find that the information content of trades depends on the local liquidity level and the recent history of prices and trades. Finally, we use the model to estimate the time-varying permanent impact parameter, which allows performing a dynamic transaction cost analysis. Joint work with Francesco Campigli and Fabrizio Lillo. *Dr. Giuseppe Buccheri,*University of Verona, Italy https://sites.google.com/view/giuseppe-buccheri/home *Semiparametric Estimation of Volatility in the Presence of Intraday Drift Dynamics* In the conventional semimartingale representation of the log-price of a financial security, the volatility of daily log-returns is consistently estimated by their ex-post quadratic variation. A crucial assumption underlying this result is that the drift dynamics are negligible or pre-determined given past information. Recent empirical evidences of intraday unanticipated variations of mean returns call into doubt the validity of this assumption. We propose a semiparametric estimator of the daily return volatility incorporating the effect of stochastic intraday dynamics of the drift process. This framework allows us to test for the presence of drift dynamics in the data and to assess their impact on the daily return volatility. Our empirical analysis shows three main results: (i) there exists compelling evidence of intraday drift dynamics across various asset classes; (ii) when the drift moves significantly, our measure of volatility provides a better description of the return distribution; (iii) the component of the return variance associated with drift dynamics is non-negligible and possesses predictive power. Joint work with Giorgio Vocalelli. *Dr. Dario Palumbo,* Ca' Foscari University of Venice, Italy https://www.unive.it/data/people/22437798 *An Observation-Driven Generalized Poisson Model for Environmental Variables* Based on the Generalised Poisson (GP) conditional distribution, a new general class of observation-driven models for count data is presented and their theoretical properties are derived. The GP is a flexible distribution which allows for both under- and over-dispersion. As a special member of this class, a score-driven model version is introduced. We show that this specification is robust to the presence of outliers and can be extended to allow for time varying over-dispersion. For the estimation of the model we provide a Bayesian inference framework and an efficient posterior approximation procedure based on Markov Chain Monte Carlo. The applications on environmental variables show that the proposed model is well suited for capturing the over-dispersion feature of the data. *Dr. Enzo D'Innocenzo,* University of Bologna, Italy https://www.enzodinnocenzo.com/ *Limit results for score-driven filters* A study of the filtering approximation-theoretic properties of score-driven time series models. The new results are derived under a set of Lipschitz-type and tail conditions, from which I obtain maximal and deviation inequalities for the filtering approximation error. For the latter, I use techniques from empirical process theory. The novel proposed approach allows, for the first time, to study the asymptotic behavior of the empirical distribution function and the empirical processes of the approximated residuals. Since score-driven models encompasses the well-known generalized autoregressive conditional heteroskedasticity, it is proved that the results obtained in this paper extends those of Francq and Zakoian (2022) for this class of nonlinear models. In conclusion, I also give an application of these results to a popular score-driven time series models, namely, the Beta-t-GARCH(1,1) model. *Prof. Andrew Harvey,*University of Cambridge, UK *https://www.econ.cam.ac.uk/people/emeritus/ach34 <https://www.econ.cam.ac.uk/people/emeritus/ach34>* *Score-driven models: overview and recent developments* Score-driven <ach34(a)cam.ac.uk)Score-driven> time series models were introduced into the literature more than a decade ago. Since then progress has been made on the theory and a variety of new models have been introduced. I begin by reviewing theoretical results on stationarity and invertibility and show how these apply to moment-driven and score-driven models for dynamic location and/or scale parameters from a wide range of distributions. Issues of robustness are discussed and it is argued that quasi score-driven (QSD) models have an important role to play. The advantages of an exponential link function are stressed. In particular it is argued that (Q)SD-EGARCH models are much better than standard (moment-driven) GARCH models. I finish by showing how the score-driven approach solves two difficult problems: constructing time series models for censored observations and circular data. -- Roberto Casarin, PhD Professor of Econometrics Ca' Foscari University of Venice San Giobbe 873/b - 30121 Venezia, Italy http://sites.google.com/view/robertocasarin/ https://www.unive.it/vera <https://www.unive.it/isba2024> https://www.unive.it/isba2024

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Time Series Models for Financial and Environmental Risk - May 30 - Ca' Foscari University
by Roberto CASARIN 21 May '24

21 May '24

Dear Colleagues, On Thursday the 30th of May you are all warmly invited to our one-day workshop organised under the GRINS Project on *Time Series Models for Financial and Environmental Risk* *https://www.unive.it/data/33113/3/88487 <https://www.unive.it/data/agenda/3/88487>* Participation is free. However, for organizational purposes, you are kindly asked to register by May the 27th here https://bit.ly/form-workshop-timeseriesmodels . Ca’ Foscari University, San Giobbe Economics Campus, Meeting Room 1, Venezia *Program:* 10.00am Registration 10.45am *Welcome Remarks: Prof. Monica Billio, Ca’ Foscari University of Venice, Project Leder of the Grins Spoke 4, Sustainable Finance.* *1st Session* 11.00am *Prof.* *Giacomo Bormetti, University of Pavia*, *Measuring price impact and information content of trades in a time-varying setting.* 11.45am *Dr. Giuseppe Buccheri, University of Verona*, *Semiparametric Estimation of Volatility in the Presence of Intraday Drift Dynamics.* 12.30pm Lunch *2nd Session* 2.00pm* Dr. Dario Palumbo, Ca' Foscari University of Venice*, *An Observation-Driven Generalized Poisson Model*. 2.45pm *Dr. Enzo D'Innocenzo, University of Bologna, **Limit results for score-driven filters**.* 3.30pm Coffee break 4.00pm *Keynote speech**: Prof. Andrew Harvey, University of Cambridge. **Score-driven models: overview and recent developments.* *Abstracts*: *Prof.* *Giacomo Bormetti,*University of Pavia, Italy https://unipv.unifind.cineca.it/get/person/021642 <https://warwick.ac.uk/dfirth> *Measuring price impact and information content of trades in a time-varying setting* We propose a non-linear observation-driven version of the Hasbrouck (1991) model for dynamically estimating trades' market impact and information content. We find that market impact displays an intraday pattern superimposed with large fluctuations. Some of them are exogenous, and, as an example, we investigate market impact dynamics around FOMC announcements. Contrary to Hasbrouck (1991), we find that the information content of trades depends on the local liquidity level and the recent history of prices and trades. Finally, we use the model to estimate the time-varying permanent impact parameter, which allows performing a dynamic transaction cost analysis. Joint work with Francesco Campigli and Fabrizio Lillo. *Dr. Giuseppe Buccheri,*University of Verona, Italy https://sites.google.com/view/giuseppe-buccheri/home <https://www.ikosmidis.com/> *Semiparametric Estimation of Volatility in the Presence of Intraday Drift Dynamics* In the conventional semimartingale representation of the log-price of a financial security, the volatility of daily log-returns is consistently estimated by their ex-post quadratic variation. A crucial assumption underlying this result is that the drift dynamics are negligible or pre-determined given past information. Recent empirical evidences of intraday unanticipated variations of mean returns call into doubt the validity of this assumption. We propose a semiparametric estimator of the daily return volatility incorporating the effect of stochastic intraday dynamics of the drift process. This framework allows us to test for the presence of drift dynamics in the data and to assess their impact on the daily return volatility. Our empirical analysis shows three main results: (i) there exists compelling evidence of intraday drift dynamics across various asset classes; (ii) when the drift moves significantly, our measure of volatility provides a better description of the return distribution; (iii) the component of the return variance associated with drift dynamics is non-negligible and possesses predictive power. Joint work with Giorgio Vocalelli. *Dr. Dario Palumbo,* Ca' Foscari University of Venice, Italy https://www.unive.it/data/people/22437798 *An Observation-Driven Generalized Poisson Model for Environmental Variables* Based on the Generalised Poisson (GP) conditional distribution, a new general class of observation-driven models for count data is presented and their theoretical properties are derived. The GP is a flexible distribution which allows for both under- and over-dispersion. As a special member of this class, a score-driven model version is introduced. We show that this specification is robust to the presence of outliers and can be extended to allow for time varying over-dispersion. For the estimation of the model we provide a Bayesian inference framework and an efficient posterior approximation procedure based on Markov Chain Monte Carlo. The applications on environmental variables show that the proposed model is well suited for capturing the over-dispersion feature of the data. *Dr. Enzo D'Innocenzo,* University of Bologna, Italy https://www.enzodinnocenzo.com/ <https://researchportal.uc3m.es/display/inv16189> *Limit results for score-driven filters* A study of the filtering approximation-theoretic properties of score-driven time series models. The new results are derived under a set of Lipschitz-type and tail conditions, from which I obtain maximal and deviation inequalities for the filtering approximation error. For the latter, I use techniques from empirical process theory. The novel proposed approach allows, for the first time, to study the asymptotic behavior of the empirical distribution function and the empirical processes of the approximated residuals. Since score-driven models encompasses the well-known generalized autoregressive conditional heteroskedasticity, it is proved that the results obtained in this paper extends those of Francq and Zakoian (2022) for this class of nonlinear models. In conclusion, I also give an application of these results to a popular score-driven time series models, namely, the Beta-t-GARCH(1,1) model. *Prof. Andrew Harvey,*University of Cambridge, UK *https://www.econ.cam.ac.uk/people/emeritus/ach34 <https://www.econ.cam.ac.uk/people/emeritus/ach34>* *Score-driven models: overview and recent developments* Score-driven <ach34(a)cam.ac.uk)Score-driven> time series models were introduced into the literature more than a decade ago. Since then progress has been made on the theory and a variety of new models have been introduced. I begin by reviewing theoretical results on stationarity and invertibility and show how these apply to moment-driven and score-driven models for dynamic location and/or scale parameters from a wide range of distributions. Issues of robustness are discussed and it is argued that quasi score-driven (QSD) models have an important role to play. The advantages of an exponential link function are stressed. In particular it is argued that (Q)SD-EGARCH models are much better than standard (moment-driven) GARCH models. I finish by showing how the score-driven approach solves two difficult problems: constructing time series models for censored observations and circular data. -- Roberto Casarin, PhD Professor of Econometrics Ca' Foscari University of Venice San Giobbe 873/b - 30121 Venezia, Italy http://sites.google.com/view/robertocasarin/ https://www.unive.it/vera <https://www.unive.it/isba2024> https://www.unive.it/isba2024

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Summer School on "Computational Methods in Finance and Economics", 9-13 September 2024, San Miniato, Italy.
by Giulio Bottazzi 21 May '24

21 May '24

Dear Colleagues, the Centro de Giorgi, Scuola Normale Superiore, and the Institute of Economics of Scuola Superiore Sant'Anna, are jointly organizing the Ph.D.Summer School on "Computational Methods in Finance and Economics". The school is aimed at graduate students in Economics, Finance and related disciplines. For information and application please check https://crm.sns.it/event/528/ Best Regards, Giulio Bottazzi -- Giulio Bottazzi PGP Key ID:BAB0A33F Professor of Economics Faculty of Social Sciences Advanced Calculus for Economics and Finance Theory and Methods https://link.springer.com/book/10.1007/978-3-031-30316-6 Scuola Superiore Sant'Anna 56127 - Pisa, Italy Phone:(+39)-050-883365 email:bottazzi@santannapisa.it Fax: (+39)-050-883344 http://www.sssup.it/~bottazzi The information transmitted is intended only for the person or entity to which it is addressed and may contain confidential and/or privileged material. Any review of, re-transmission, dissemination or other use of, or taking of any action in reliance upon, this information by persons or entities other than the intended recipient, is prohibited. If you received this in error, please inform the sender by e-mail and delete the content. Il contenuto e gli allegati di questo messaggio sono strettamente confidenziali e ad uso esclusivo del destinatario. Ne sono vietati la diffusione, l'inoltro e l'uso non autorizzato da parte di utenti diversi dal destinatario. Qualora il presente messaggio Le fosse pervenuto per errore, La preghiamo di distruggerlo e darcene comunicazione a mezzo e-mail.

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seminar PESCE
by Stefano Pagliarani 20 May '24

20 May '24

Dear all, On May 22nd, in the classroom Aula Arzelà, Department of Mathematics of the University of Bologna, the following seminars will take place: * 11:00-12:00: Antonello PESCE "OPTIMAL IRREVERSIBLE INVESTMENTS WITH PRICE IMPACT IN A COMPETING MARKET: A SINGULAR STOCHASTIC GAME" * 12:00-13:00: Fabrizio LILLO "A NOISY DYNAMICAL SYSTEM MODEL OF FINANCIAL SYSTEMIC RISK" as part of the cycle Stochastics and Applications. The abstracts are available at https://www.dm.unibo.it/seminari/mat/serials/36 For any question, please contact the organizers: Lorenzo Cerboni Baiardi and Stefano Pagliarani. ------------------------------------------------------------------------------------------------------------------------ Stefano Pagliarani, Associate Professor Piazza di Porta S. Donato, 5 University of Bologna (Alma Mater) 40126 Bologna (BO), Italy Department of Mathematics Cell. Phone +39 366 5013755 Email: stepagliara1(a)gmail.com<mailto:stepagliara1@gmail.com>, <mailto:stefano.pagliarani9@unibo.it> stefano.pagliarani9(a)unibo.it<mailto:stefano.pagliarani9@unibo.it> Zoom: https://unibo.zoom.us/j/3755841669 -----------------------------------------------------------------------------------------------------------------------

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Seminario 4 giugno e visita a Milano Bandyopadhyay Antar
by Giacomo Aletti 20 May '24

20 May '24

Nell’ambito dei progetti di eccellenza, il Prof. Bandyopadhyay Antar Theoretical Statistics and Mathematics Unit Head of Indian Statistical Institute, Delhi Centre, New Delhi, India sarà a Milano nella settimana 2-9 giugno. È stato organizzato un seminario per il 4 giugno 2024 dalle ore 14.30 alle ore 15.30 in Aula Maggiore, via Celoria 2, Milano, dal titolo A classical random reinforcement model viewed differently! Abstract: In this talk, we will start by explaining a classical random reinforcement model introduced by Pólya back in 1920 which is widely known as the Pólya's urn scheme. We will then indicate several unrelated examples can be thought as following Pólya's model provided we allow ourselves a novel infinite dimensional generalization. After indicating the difficulties which arise due to absence of good mathematical (mostly algebraic) techniques to deal with infinite dimensional matrices (or appropriate linear operators), we will explain a new probabilistic technique to handle the infinite dimensional generalization. We shall define a novel stochastic process which will turn out to be Markov with respect to a new type of "time'' parameter, which instead of deterministic and unidirectional, will be random and will have a tree-type structure. We shall show that this new process and the infinite dimensional generalization of Pólya's balanced urn scheme have the same law. This will enable us to derive fairly general scaling limits for the infinite dimensional scheme and show that classical results can be easily derived without much difficulties and completely avoiding algebraic techniques. Moreover, we will show that apparently unrelated problems arising from a variety of different fields such as combinatorics, statistical physics and statistics, can be solved by using this new generalization. Il seminario è pensato per un pubblico non specialistico ed è aperto a tutti.

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talk Prof. Nacira Agram on May 23, 2024 - REMINDER
by Emanuela Rosazza Gianin 20 May '24

20 May '24

Dear all, you are all invited to participate to the following seminar on *Thursday 23th of May 2024 at 15:00* in Aula Seminari Demografica 2062 at University of Milano Bicocca (via degli Arcimboldi 8, Milano - building U7, 2nd floor): Speaker: *Nacira Agram (KTH Stockholm)* Titolo: *Deep learning for conditional McKean-Vlasov Jump diffusions* Abstract: My talk focuses on using deep learning methods to optimize the control of conditional McKean-Vlasov jump diffusions. We begin by exploring the dynamics of multi-particle jump-diffusion and presenting the propagation of chaos. The optimal control problem in the context of conditional McKean-Vlasov jump-diffusion is introduced along with the verification theorem (HJB equation). A linear quadratic conditional mean-field (LQ CMF) is discussed to illustrate these theoretical concepts. Then, we introduce a deep-learning algorithm that combines neural networks for optimization with path signatures for conditional expectation estimation. The algorithm is applied to practical examples, including LQ CMF and interbank systemic risk, and we share the resulting numerical outcomes. Based on joint work with Jan Rems. Best wishes, Emanuela ****************************************** Emanuela Rosazza Gianin Dipartimento di Statistica e Metodi Quantitativi Università di Milano-Bicocca Tel. 02 64483208 e-mail: emanuela.rosazza1(a)unimib.it ******************************************

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Seminario Padova - Marta Leocata
by alekos.cecchin＠unipd.it 20 May '24

20 May '24

Buongiorno a tutti, Vorremmo segnalarvi che venerdì prossimo (24 Maggio) alle ore 14:30 in aula 2AB45 (Torre Archimede, Università di Padova) ci sarà un seminario per il ciclo di seminari in Probabilità e Finanza di: Marta Leocata (Luiss University) https://sites.google.com/view/martaleocata/ Title: A MFG approach for competing firms in the Emission Trading System Date: May 24, 2024, at 14:30, 2AB45 Abstract: In this talk I will consider the problem of reducing the carbon emissions of a set of firms over a finite time horizon. Firms can trade allowances in a way that minimizes the total expected costs from abatement and trading plus a terminal quadratic penalty, and they can also choose which type of energy to use (fossil or green) to produce their goods and thus maximize profits from production. Using mean-field game theory and mean field control theory, we aim to understand how different types of market competition can influence the energy transition. This is a joint work with Giulia Livieri (LSE) and Gianmarco Del Sarto (SNS). Vi aspettiamo numerosi! Alberto Chiarini e Alekos Cecchin Sito web del seminario: https://www.math.unipd.it/~chiarini/seminars/

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Seminar in Statistics - SAMUEL LIVINGSTON
by Pierpaolo De Blasi 20 May '24

20 May '24

SEMINARS IN STATISTICS @ COLLEGIO CARLO ALBERTO <https://www.carloalberto.org/events/category/seminars/seminars-in-statistic…> Venerdi 24 Maggio 2024, alle ore 12.00, presso il Collegio Carlo Alberto, in Piazza Arbarello 8, Torino, si terrà il seguente seminario: ------------------------------------------------ Speaker: Samuel Livingston (UCL UK) Title: *Robust gradient-based sampling algorithms using skew-symmetric numerical schemes* Abstract: State-of-the-art sampling algorithms for smooth continuous distributions are typically gradient-based, e.g. Langevin or Hamiltonian Monte Carlo. It is known, however, that particular features of the distribution to be sampled can cause them to be unstable/work poorly. The algorithms are typically based on a numerical simulation of some stochastic process (e.g. the overdamped Langevin diffusion), and the instability comes from the choice of numerical scheme. I will introduce a new explicit numerical scheme for diffusions, which has skew-symmetric increments, and can be used to design simple and fast sampling algorithms that are provably more robust. I will show that the resulting 'unadjusted Barker algorithm', so called because of its connection to the Barker Metropolis—Hastings algorithm of Livingstone & Zanella (JRSS B, 2022) is well-defined and converges at a geometric rate to an equilibrium which is close to the distribution of interest in many cases when the unadjusted Langevin algorithm is transient. ------------------------------------------------ Sarà possibile seguire il seminario anche in streaming: Join Zoom Meeting <https://us02web.zoom.us/j/81530120491?pwd=YUV4Y2dtb1creEMvRkR5SkpmeW1sQT09> Il seminario è organizzato dalla "de Castro" Statistics Initiative www.carloalberto.org/stats -- Pierpaolo De Blasi University of Torino & Collegio Carlo Alberto carloalberto.org/pdeblasi <https://sites.google.com/a/carloalberto.org/pdeblasi/>

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Posizioni Postdoc all'Università di Granada
by Antonio DI CRESCENZO 18 May '24

18 May '24

Buongiorno, invio notizia di 2 posizioni Postdoc all'Università di Granada su argomenti: - "Modelling and differential equations" e "Statistics and operational research". _____________________________________________________________ To all interested candidates: The Institute of Mathematics of the University of Granada (IMAG) offers two postdoctoral positions, to start in September-October 2024, and with an end date of December 31, 2025. These positions are in the areas of "*Modelling and differential equations*" and "*Statistics and operational research*" (one position per area). The application deadline is *June 10, 2024*. Further details can be found at IMAG's website https://wpd.ugr.es/~imag/imag-maria-de-maeztu-postdocs-2024/ These contracts are supported by IMAG's Excellence Seal "María de Maeztu" with reference CEX2020-001105-M. --

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6-year assistant professor position (non-tenured) in probability, TU Vienna
by Toninelli, Fabio Lucio 18 May '24

18 May '24

Dear colleague, the Technical University of Vienna is advertising a 6-year assistant professor position (non-tenured) in probability theory, within the Probability research group (https://www.tuwien.at/en/mg/proba)<https://www.tuwien.at/en/mg/mstoch> <https://www.tuwien.at/en/mg/mstoch> Deadline for applications: June 27th, 2024. Earliest possible starting date: September 2024 For the official announcement, the link to the application portal and details on the position, see here: https://jobs.tuwien.ac.at/Job/233239 The teaching load is 4 hours/week. Please forward this to potentially interested candidates Best wishes Fabio Toninelli (head of the Probability group) --------------------------------------------------------------------- Prof. Fabio Toninelli Technical University of Vienna Institut für Stochastik und Wirtschaftsmathematik Wiedner Hauptstrasse 8-10, 1040 Wien, Austria https://sites.google.com/view/fabio-toninelli/home Office: 6th floor, green area. tel: +43-1-58801-10570

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Open Postdoc Position in the are of mathematical Finance at the University of Vienna
by viktoria.schildhammer＠univie.ac.at 17 May '24

17 May '24

Dear All, this is to inform about an open Postdoc position at the department of Statistics and Operations Research at the University of Vienna, in the working group of Prof. Cuchiero. The University of Vienna, Department of Statistics and Operations Research, invites applications for the position of a Post-Doc (2 years, 40h) at the intersection of Mathematical Finance, Stochastic Analysis and Machine Learning. The post-doctoral researcher will work in the group of the START research project "Universal structures in Mathematical Finance", led by Prof. Christa Cuchiero. The focus of the project lies on universal structures that pertain literally to both, mathematics and finance. *Deadline for applications: June 15, 2024.* Further information can be found here: https://jobs.univie.ac.at/job-invite/2493/ Please foward this message to any interested person. Thank you and best wishes Viktoria Schildhammer

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Open Praedoc Position in the are of mathematical Finance at the University of Vienna
by viktoria.schildhammer＠univie.ac.at 17 May '24

17 May '24

Dear All, this is to inform about an open Praedoc position at the department of Statistics and Operations Research at the University of Vienna, in the working group of Prof. Cuchiero. The University of Vienna, Department of Statistics and Operations Research, invites applicants for the position of one to two Prae-Docs (3 year appointment, 30 hours) at the intersection of Mathematical Finance, Stochastic Analysis and Machine Learning. The pre-doctoral researcher will work in the group of the START research project "Universal structures in Mathematical Finance", led by Prof. Christa Cuchiero. The focus of the project lies on universal structures that pertain literally to both, mathematics and finance *Deadline for applications: June 15, 2024.* Further information can be found here: https://jobs.univie.ac.at/job-invite/2491/ Please foward this message to any interested person. Thank you and best wishes Viktoria Schildhammer

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3-year Post-doctoral Position on Stochastic Games at Bielefeld University
by Ferrari, Giorgio 17 May '24

17 May '24

Dear All, this is to inform about a *3-year post-doctoral position* in my group at the Center for Mathematical Economics of Bielefeld University (salary level TVL-13, 100%). The post-doctoral researcher will conduct research on stochastic games (with N players or of mean-field type) wiith singular controls, as well as on mean-field control problems. *Deadline for applications: June 12, 2024.* Further information can be found here: https://jobs.uni-bielefeld.de/job/view/3392/research-position-postdoc?page_… Please foward this message to any interested person. Best wishes and thanks, Giorgio Ferrari

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23 mag 2024 - Seminario Dr. Ivana Pavlu
by Enea Bongiorno 17 May '24

17 May '24

Carissimi colleghi, scusandomi per eventuali invii multipli, vi inoltro il seguente annuncio di seminario. Tutti gli interessati sono invitati a partecipare. Cordialmente, Enea Bongiorno -------------------------------- - data e orario: 23 maggio 2024 ore 15.00 - aula 204, campus Perrone, via Perrone, 18, Novara. Università del Piemonte Orientale. - on-line: meet.google.com/iap-gjcr-bkb Title: *Regression analysis with density functions in Bayes spaces* *Ivana Pavlů*, Palacký University Olomouc, Czech Republic *Abstract*: Regression analysis offers tools for explaining the relation between (a set of) dependent and independent variables. Recent advances extend the available response types from uni- or multivariate to functional, and more recently also distributional responses. For functional distributions, often represented through probability density functions, the Bayes space framework was developed to respect the relative information they carry. The Hilbert space structure of Bayes space enables one to utilize standard methods of functional data analysis for the use on - properly transformed - density functions. Focusing on regression analysis, it is possible to construct adequate models with densities on the side of both the dependent and independent variables. In this seminar, a brief overview of regression models for univariate densities will be presented. A closer attention will be given to the possible generalization of additive regression model for bivariate distributions. Finally, an outlook at the Bayesian inference in linear regression with probability densities will be discussed. All proposed methods will be demonstrated on real data from the fields of geochemistry and demographics. ----------------------------------- Locandina dell'evento <https://drive.google.com/file/d/1AW4P1_HNdVO7Ot70mjM-KCQLhnSSVmRi/view?usp=…> Seminari Matematici Statistici <https://seminari-ms.uniupo.it/home-page> ----------------------------------- -- Enea G. Bongiorno, Università degli Studi del Piemonte Orientale - Amedeo Avogadro Via Perrone 18, 28100, Novara, Italia Phone: +390321375317 enea.bongiorno(a)uniupo.it upobook.uniupo.it/enea.bongiorno ------ Math-Stat Seminars at UPO seminari-ms.uniupo.it/home-page ------

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talk Prof. Domenico Marinucci on May 29 - DIMA - UNIGE
by Ernesto De Vito 16 May '24

16 May '24

Dear all, you are all invited to participate to the following seminar. Speaker : Domenico Marinucci (https://sites.google.com/view/domenicomarinucci/home) Affiliation: Dipartimento di Matematica - Università Roma Tor Vergata Title: Spectral complexity of deep neural networks Date: Monday, May 29, 2024 at 11.30 Place: Aula 704 (7th floor) , Dipartimento di Matematica at University of Genova, Via Dodencaneso 35, Abstract: It is well-known that randomly initialized, push-forward, fully-connected neural networks weakly converge to isotropic Gaussian processes, in the limit where the width of all layers goes to infinity. In this paper, we propose to use the angular power spectrum of the limiting fields to characterize the complexity of the network architecture. In particular, we define sequences of random variables associated with the angular power spectrum, and provide a full characterization of the network complexity in terms of the asymptotic distribution of these sequences as the depth diverges. On this basis, we classify neural networks as low-disorder, sparse, or high-disorder; we show how this classification highlights a number of distinct features for standard activation functions, and in particular, sparsity properties of ReLU networks. Our theoretical results are also validated by numerical simulations. Joint work with Simmaco Di Lillo, Michele Salvi e Stefano Vigogna Best wishes, Ernesto --------------------- Ernesto De Vito DIMA - Dipartimento di Matematica MaLGa - Machine Learning Genoa center Via Dodecaneso 35 16146 Genova Italy e-mail: ernesto.devito(a)unige.it tel: +390103536783

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assegno con Fincantieri su algoritmi quantistici per Navier Stokes
by Giacomo De Palma 15 May '24

15 May '24

Cari tutti, ho appena pubblicato il seguente bando per un assegno di ricerca di 15 mesi all’università di Bologna su un progetto in collaborazione con Fincantieri (https://www.fincantieri.com/it/) riguardante simulazioni numeriche di algoritmi quantistici per le equazioni di Navier-Stokes: https://bandi.unibo.it/ricerca/assegni-ricerca?id_bando=67830 L’assegno prevede uno stipendio competitivo di circa 2000€ netti al mese. È richiesta solo la laurea magistrale, ma un’esperienza in simulazioni numeriche di algoritmi quantistici è preferibile. I candidati possono allegare alla domanda fino a due lettere di referenza. La presa di servizio è prevista per il 1° giugno, e la scadenza del bando è il 21 aprile. Vi sarei grato se inoltraste l’avviso a potenziali interessati. Un caro saluto, Giacomo

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ISBA World 2024 - Regular Registration Closing May, 31
by Roberto CASARIN 15 May '24

15 May '24

Dear Colleagues, We kindly remind you that the ISBA 2024 World Meeting is approaching. *The regular registration fee will remain available until May 31*. More detailed information is available at: https://www.unive.it/isba2024 ISBA2024 is organized by the International Society for Bayesian Analysis ( ISBA <https://u8042292.ct.sendgrid.net/ls/click?upn=u001.VwavI53V6vcw3NkZZaT5c3BC…>) in collaboration with the Venice Centre in Economic and Risk Analytics (VERA <https://u8042292.ct.sendgrid.net/ls/click?upn=u001.VwavI53V6vcw3NkZZaT5c3BC…>) at Ca’ Foscari University of Venice. Looking forward to meeting you in Venice! Best regards, The ISBA World 2024, Local Organizing Committee. ------------------------------ 31st World Meeting ISBA 2024July 1st - July 7th, 2024Ca’ Foscari University, San Giobbe Campus, Venice, Italy The ISBA world meetings bring together the international statistical community of researchers and professionals who develop Bayesian methods and apply them to challenging problems in different fields, ranging from economics and finance to business, industry, biostatistics, pharmaceutical statistics, environmental statistics, etc. *Supported by*: Ca' Foscari University of Venice, Department of Economics, Venice Centre in Economic and Risk Analytics (VERA), Fondazione Università Ca' Foscari. *Under the auspices of:* Ministero dell'Università e della Ricerca (MUR), Regione del Veneto, Città Metropolitana di Venezia, Città di Venezia, Istituto Veneto di Scienze, Lettere ed Arti, Società Italiana di Econometria (SIdE), Società Italiana di Matematica Applicata e Industriale (SIMAI), Società Italiana di Statistica (SIS), Gruppo Nazionale per l'Analisi Matematica la Probabilità e le loro Applicazioni (INDAM-GNAMPA). *Main Sponsors*: Eurizon Asset Management, Generali, University of Michigan School of Public Health (Dept. of Biostatistics), United States National Sciences Foundation, University of California Los Angeles (Dept. of Biostatistics). *Other Sponsors:* Collegio Carlo Alberto (de Castro Statistics Initiative), University of Texas at Austin (Dept. of Statistics and Data Sciences), Duke University (Dept. of Statistical Science), G-Research, SAS, STATA, Università Bocconi (Dept. of Decision Sciences), European Datawarehouse, Pfizer, Posit, Brown University School of Public Health, INDAM-GNAMPA, CRC press, Springer Verlag. *Scientific Committee**:* Sinead Williamson <https://u8042292.ct.sendgrid.net/ls/click?upn=u001.VwavI53V6vcw3NkZZaT5c3BC…> (Chair), University of Texas at Austin/Apple Sergios Agapiou <https://u8042292.ct.sendgrid.net/ls/click?upn=u001.VwavI53V6vcw3NkZZaT5c3BC…>, University of Cyprus Trevor Campbell <https://u8042292.ct.sendgrid.net/ls/click?upn=u001.VwavI53V6vcw3NkZZaT5c3BC…>, University of British Columbia Roberto Casarin <https://u8042292.ct.sendgrid.net/ls/click?upn=u001.VwavI53V6vcw3NkZZaT5c3BC…>, Ca’ Foscari University of Venice Luis Mauricio Castro Cepero <https://u8042292.ct.sendgrid.net/ls/click?upn=u001.VwavI53V6vcw3NkZZaT5c3BC…>, Pontificia Universidad Católica de Chile Christopher Drovandi <https://u8042292.ct.sendgrid.net/ls/click?upn=u001.VwavI53V6vcw3NkZZaT5c3BC…>, Queensland University of Technology Daniele Durante <https://u8042292.ct.sendgrid.net/ls/click?upn=u001.VwavI53V6vcw3NkZZaT5c3BC…>, Bocconi University Hedibert Freitas Lopes <https://u8042292.ct.sendgrid.net/ls/click?upn=u001.VwavI53V6vcw3NkZZaT5c3BC…>, Institute of Educatio and Research Emtiyaz Khan <https://u8042292.ct.sendgrid.net/ls/click?upn=u001.VwavI53V6vcw3NkZZaT5c3BC…>, RIKEN Center Matthias Katzfuss <https://u8042292.ct.sendgrid.net/ls/click?upn=u001.VwavI53V6vcw3NkZZaT5c3BC…>, University of Wisconsin-Madison Juhee Lee <https://u8042292.ct.sendgrid.net/ls/click?upn=u001.VwavI53V6vcw3NkZZaT5c3BC…>, University of California Santa Cruz David Nott <https://u8042292.ct.sendgrid.net/ls/click?upn=u001.VwavI53V6vcw3NkZZaT5c3BC…>, National University of Singapore Stéphanie van der Pas <https://u8042292.ct.sendgrid.net/ls/click?upn=u001.VwavI53V6vcw3NkZZaT5c3BC…>, Amsterdam UMC Bruno Sansó <https://u8042292.ct.sendgrid.net/ls/click?upn=u001.VwavI53V6vcw3NkZZaT5c3BC…>, University of California Mike West <https://u8042292.ct.sendgrid.net/ls/click?upn=u001.VwavI53V6vcw3NkZZaT5c3BC…>, Duke University -- Roberto Casarin, PhD Professor of Econometrics Ca' Foscari University of Venice San Giobbe 873/b - 30121 Venezia, Italy http://sites.google.com/view/robertocasarin/ https://www.unive.it/vera <https://www.unive.it/isba2024> https://www.unive.it/isba2024

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Seminar: Bayesian network structural learning from complex survey data - P. Vicard
by Mira Antonietta 15 May '24

15 May '24

On behalf of Prof Di Serio I am sharing the following announcement ———————- The Statistical Network Science committee of the Bernoulli Society invites you to an online talk this week Thursday: Thursday May 16 2-3 pm UK time Title: Bayesian network structural learning from complex survey data Statistical Network Science Seminar Series- Bernoulli Society Speaker: Paola Vicard (Department of Economics, Università Roma Tre, Rome, Italy) Abstract: The association structure of a Bayesian network can be known in advance by subject matter knowledge or have to be learned from a database. One of the most widely used procedures is the PC algorithm consisting in carrying out several independence tests on the available data set and in building a Bayesian network according to the tests results. In case of data driven learning, the PC algorithm is based on the irremissible assumption that data are independent and identically distributed. Unfortunately, official statistics data are generally collected through complex sampling designs, then the aforementioned assumption is not met. In such a context the PC algorithm fails in learning the structure. To avoid this, the sample selection must be taken into account in the structural learning process. A modified version of the PC algorithm is proposed for inferring causal structure from complex survey data. It is based on resampling techniques for finite populations. A simulation experiment showing the robustness with respect to departures from the assumptions and the good performance of the proposed algorithm is carried out. (Joint work with Daniela Marella, Sapienza Università di Roma) Zoom link https://eur02.safelinks.protection.outlook.com/?url=https%3A%2F%2Fzoom.us%2…<https://zoom.us/j/99820613967> Meeting ID: 998 2061 3967 Passcode: 850644 All welcome Clelia Di Serio and Gesine Reinert

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avviso di seminario di A. Buonocore e L. Caputo
by Antonio DI CRESCENZO 14 May '24

14 May '24

scusandomi per invii multipli... ---------- Forwarded message --------- *UNIVERSITA' DI SALERNO* *Dipartimento di Matematica* AVVISO DI SEMINARIO *Speaker*: *Aniello* *BUONOCORE *e *Luigia* *CAPUTO* (Dipartimento di Matematica e Applicazioni, Università di Napoli Federico II) *Titolo*: *Il tema "Dati e Previsioni" presente nelle Indicazioni Nazionali e nelle Linee Guida è: un problema oppure una risorsa da valorizzare?* *Data*: mercoledì 15 maggio 2024, ore 11:30 *Luogo*: Sala Riunioni, Edificio F2, piano 1, stanza 36, e su Teams, al link: https://teams.microsoft.com/l/meetup-join/19%3ameeting_ Yjc2NjU5ZDEtOTQ3YS00YzcyLTg3MTItNzRlMDg4YWU2Nzli%40thread. v2/0?context=%7b%22Tid%22%3a%22c30767db-3dda-4dd4-8a4d- 097d22cb99d3%22%2c%22Oid%22%3a%2261e4e421-60a6-4cb9-8153-d04cb91c1edf%22%7d *Abstract* Per il tema "Dati e Previsioni" si propone l'impostazione didattica basata sui problemi. In particolare, si propone di utilizzare, in maniera appropriata e con la finalità di sollecitare le abilità comunicative ed argomentative, alcuni problemi e paradossi della probabilità condizionata che nel corso del tempo sono stati occasione di discussioni vivaci e intriganti. I problemi selezionati e sperimentati nel corso degli ultimi anni in classi della scuola secondaria, nei quali l'enfasi è posta soprattutto sul significato dei simboli e delle formule, forniscono anche un modo per stimolare gli obiettivi di "processo" (argomentare e dimostrare, comunicare, rappresentare, collegare) spesso trascurati a favore dei soli obiettivi di "contenuto". Una tale modalità operativa può essere d'aiuto sia agli insegnanti per mitigare le difficoltà che loro stessi soventemente riscontrano nella concettualizzazione (ovvero quella discontinuità tra i processi cognitivi degli studenti e l'astrazione) e sia agli stessi studenti per meglio orientarsi quando le circostanze della vita quotidiana sicuramente lo richiederanno. Gli interessati sono cordialmente invitati a partecipare, *Antonio Di Crescenzo* *Barbara Martinucci* *Alessandra Meoli* *Serena Spina*

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SAVE THE DATE - Tavola rotonda su "Iperautorialità e riviste predatorie" - 29 maggio 2024 - ore 15
by ANDREA CONSIGLIO 14 May '24

14 May '24

Cari Colleghi, vi ricordiamo l’appuntamento per tavola rotonda su "Iperautorialità e Riviste Predatorie" L’evento è fissato per il 29 maggio alle ore 15:00 CET, presso l'Aula delle lauree della Facoltà di Economia. Potrete seguire la discussione online tramite una piattaforma telematica: https://uniroma1.zoom.us/j/84228305285 Per la partecipazione in presenza, si prega di registrarsi entro e non oltre il 20/05/2024 https://bit.ly/AMASES-TavolaRotonda Contiamo sulla vostra numerosa partecipazione. Cordiali saluti, Il Comitato Scientifico AMASES %%%%%%%%%%%%%%%%%%%%%%%%%%%%%% Tavola Rotonda: Iperautorialità e Riviste Predatorie Data e Luogo: 29 maggio 2024, ore 15.00, Aula delle lauree, Facoltà di Economia, via Castro Laurenziano 9, Roma. Saluti Istituzionali: Giovanni Di Bartolomeo, Preside Facoltà di Economia, Università di Roma "La Sapienza" Andrea Consiglio, Presidente AMASES, Università di Palermo Partecipanti: Santo Fortunato, Indiana University Giulia Iori, Università di Venezia "Cà Foscari" Marco Malgarini, ANVUR Angelo Pezzullo, Università Cattolica Angela Santoni, Commissione Etica, Università di Roma "La Sapienza" Francesco Sylos Labini, CREF Moderatore: Marco Li Calzi, Università di Venezia "Cà Foscari" Andrea Consiglio Università di Palermo Dipartimento di Scienze Economiche, Aziendali e Statistiche. Viale delle Scienze, Edificio 13 90128 Palermo, Italy tel:++39-09123895228 fax:++39-091485726 skype: conan_66 email:andrea.consiglio@unipa.it<mailto:email%3Aandrea.consiglio@unipa.it> pec:andrea.consiglio@pec.it<mailto:pec%3Aandrea.consiglio@pec.it> www:http://bit.ly/AndreaConsiglio

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PhD courses at Roma Tre University
by Francesco Cesarone 14 May '24

14 May '24

Dear All, I am happy to announce a new upcoming series of PhD courses organized by the Research Group on Quantitative Finance, Department of Business Studies – Roma Tre University. Below are some details on the different topics covered, speakers, and dates: * Introduction to Graph Theory and Applications Andrea Scozzari - Full Professor of Mathematical Methods of Economics, Finance and Actuarial Sciences at University Niccolò Cusano, Department of Economics. Date: Monday 20th May, h: 14:30 - 17:30; Wednesday 22nd May, h: 14:30 - 17:30; Friday 24th May, h: 14:30 - 17:30; Monday 27th May, h: 14:30 - 17:30. * AI Algorithms Valerio Giuseppe Sasso - Scholar in Operations Research at Sapienza University of Rome, Department of Computer, Control and Management Engineering Antonio Ruberti (DIAG). Date: Wednesday 29th May, h: 14:30 - 17:30; Friday 31st May, h: 14:30 - 17:30; Monday 3rd June, h: 14:30 - 17:30; Wednesday 5th June, h: 14:30 - 17:30; Friday 7th June, h: 10:00 - 12:00/14:30 - 16:30. * Stochastic Dynamic Optimization Massimiliano Corradini, Researcher at Roma Tre University. Date: Monday 10th June, h: 11:00 - 14:00; Friday 14th June, h: 11:00 - 14:00; Monday 17th June, h: 11:00 - 14:00; Thursday 20th June, h: 11:00 - 14:00. The seminars can be attended either physically at the Computer lab (small room), ground floor (Department of Business Studies - Roma Tre University, Via Silvio D'Amico, 77, 00145 Rome, Italy) or online via teams. For more information I refer to the following web page<https://www.francescocesarone.com/phd/phd-courses>. Best regards, Francesco Cesarone F Cesarone (2020), Computational Finance. MATLAB oriented modeling, Routledge-Giappichelli Studies in Business and Management, ISBN 978-0-367-49303-5<https://www.giappichelli.it/computational-finance> For more info: https://www.francescocesarone.com/books -- Francesco Cesarone - Ph.D. Associate Professor Department of Business Studies Roma Tre University Via Silvio D'Amico, 77 00145 - Roma, Italy tel: +39 06 57335744 Skype: francesco.cesarone email: francesco.cesarone(a)uniroma3.it<mailto:francesco.cesarone@uniroma3.it> Studio n. 20 piano V WWW: https://www.francescocesarone.com/

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OWABC Seminar: Mark Beaumont - 30th May 9am UK time
by Massimiliano Tamborrino 14 May '24

14 May '24

Dear all, the last OWABC www.warwick.ac.uk/oneworldabc<http://www.warwick.ac.uk/oneworldabc> seminar of Season 5 is quickly approaching. We are glad to announce that our next speaker is Mark Beaumont (University of Bristol), who will talk about "Model misspecification in population genomic" on Thursday the 30th May at 9am UK time. Abstract: In likelihood-free settings, problematic effects of model misspecification can manifest themselves during computation, leading to nonsensical answers, particularly causing convergence problems in sequential algorithms. This issue has been well studied in the last 10 years, leading to a number of methods for robust inference. In practical applications, likelihood-free methods tend to be applied to the output of complex simulations where there is a choice of summary statistics that can be computed. One approach to handling misspecification is to simply not use summary statistics computed from simulations of the model under the prior that cannot be matched with those observed in the data. This presentation gives a brief review of methods for observing and handling misspecification in ABC and SBI, and then discusses approaches that we have explored in a population genomic modelling framework. The talk will be streamed on MS Teams, at the link https://teams.microsoft.com/l/meetup-join/19%3ameeting_NWFkYmE2MTgtZTNiNS00… Meeting ID: 349 104 341 838 Passcode: YxPUhR We are looking forward to seeing you at the next OWABC Seminar, best, Massimiliano on the behalf of the OWABC Seminar Organisers ------ Dr. Massimiliano Tamborrino Associate Professor and Warwick International Higher Education Academy (WIHEA) Fellow Department of Statistics University of Warwick https://warwick.ac.uk/tamborrino

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Richiesta annullamento iscrizione
by Fabiana Mancini 14 May '24

14 May '24

Salve, Potrei gentilmente essere tolta dalla mailing list di random? L'indirizzo è fabiana.mancini(a)hotmail.it Grazie! Inviato da Outlook per Android<https://aka.ms/AAb9ysg>

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talk Prof. Nacira Agram on May 23, 2024
by Emanuela Rosazza Gianin 14 May '24

14 May '24

Dear all, you are all invited to participate to the following seminar on *Thursday 23th of May 2024 at 15:00* in Aula Seminari Demografica 2062 at University of Milano Bicocca (via degli Arcimboldi 8, Milano - building U7, 2nd floor): Speaker: *Nacira Agram (KTH Stockholm)* Titolo: *Deep learning for conditional McKean-Vlasov Jump diffusions* Abstract: My talk focuses on using deep learning methods to optimize the control of conditional McKean-Vlasov jump diffusions. We begin by exploring the dynamics of multi-particle jump-diffusion and presenting the propagation of chaos. The optimal control problem in the context of conditional McKean-Vlasov jump-diffusion is introduced along with the verification theorem (HJB equation). A linear quadratic conditional mean-field (LQ CMF) is discussed to illustrate these theoretical concepts. Then, we introduce a deep-learning algorithm that combines neural networks for optimization with path signatures for conditional expectation estimation. The algorithm is applied to practical examples, including LQ CMF and interbank systemic risk, and we share the resulting numerical outcomes. Based on joint work with Jan Rems. Best wishes, Emanuela ****************************************** Emanuela Rosazza Gianin Dipartimento di Statistica e Metodi Quantitativi Università di Milano-Bicocca Tel. 02 64483208 e-mail: emanuela.rosazza1(a)unimib.it ******************************************

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Advances in Time Series Econometrics, Venice, May 17th, 2024
by Roberto CASARIN 14 May '24

14 May '24

Dear you all, the Econometrics group and the VERA centre of the Ca’ Foscari University ( https://www.unive.it/pag/35190) invite you to *Advances in Time Series Econometrics* *Half-day Workshop* *Venice May 17th, 2024Ca’ Foscari University, San Giobbe Campus, Meeting Room 1, Venezia* Program: - 9:30-10:15, *Ovielt Baltodano Lopez*, (Ca' Foscari University of Venice), Heterogeneous dynamic stochastic block models and an application to international trade - 10:15-11:00, *Alexander Simon Mayer* (Ca' Foscari University of Venice), Least squares estimation in nonstationary nonlinear cohort panels with learning from experience - 11:00-11:30, Break - 11:30-12.15, *Dario Palumbo* (Ca' Foscari University of Venice), A simple parsimonious framework for extracting and modelling the term structure of interest rates - 12:15-13:30, *Esther Ruiz* (University Carlos III of Madrid), Economic activity and climate change *Abstracts*: Ovielt Baltonado Lopez, Ca' Foscari University of Venice, Italy, https://www.unive.it/data/people/18754547 Heterogeneous dynamic stochastic block models and an application to international trade *The increasing complexity of the global economy represents a challenge for monitoring public debt risks. We propose a twofold framework by applying a Dynamic stochastic block model to a multi layer network composed of extracted debt relationships and trade ows for European countries. On the one hand, this approach allows for clusters of countries with di erent levels of debt synchronization that evolve over time and are subject to structural changes suggesting an increase in systemic risk. On the other hand, the layer dependence accounts for con icts in macroeconomic objectives. In particular, external balance and scal stability. In this sense, the network approach jointly considers interdependence between countries and the twin de cit phenomenon coherent with the composite nature of the risks in the nancial systems. We nd evidence of structural changes in the topology of the debt network during crisis, from an assortative behavior to a coreperiphery system with high interdependence among countries' debt. Moreover, the results suggest parameter heterogeneity. In stable periods unemployment (real GDP per capita) di erences lead to higher (lower) debt synchronization, while income inequality and nancial depth reduce the similarity in the debt evolution. There is no evidence of twinde cit phenomenon for the period 2003-2023.* Alexander Simon Mayer, Ca' Foscari University of Venice, Italy, https://www.unive.it/data/people/26394407 Least squares estimation in nonstationary nonlinear cohort panels with learning from experience *We discuss techniques of estimation and inference for nonstationary nonlinear cohort panels with learning from experience, showing, inter alia, the consistency and asymptotic normality of the nonlinear least squares estimator used in empirical practice. Potential pitfalls for hypothesis testing are identified and solutions proposed. Monte Carlo simulations verify the properties of the estimator and corresponding test statistics in finite samples, while an application to a panel of survey expectations demonstrates the usefulness of the theory developed.* Dario Palumbo, Ca' Foscari University of Venice, Italy, https://www.unive.it/data/people/22437798 A simple parsimonious framework for extracting and modelling the term structure of interest rates *This paper introduces a novel methodology for the extraction and modelling of the unobserved term structure of interest rates which incorporates in a single inferential framework both cross-sectional and time-series information from observed bond prices. In doing so, the paper introduces both a parametric and a semi-parametric dynamic model for the term structure which can be extended to capture also features such as heteroschedasticity in both the time and cross-section dimension, as well as the zero-lowerbound constraint. The models provide a coherent description of the term structure and outperforms current term structure extraction methods in fitting the observed bond prices surface. The models also outperform other existing dynamic term structure models in forecasting observed bond prices at one, six and twelve months horizons. Moreover, the study highlights a strong sensitivity of the forecasting errors of the existing dynamic models to the choice of the term structure extraction method used to construct the samples for the parameters’ estimation.* Prof. Esther Ruiz, University Carlos III of Madrid, Spain, https://researchportal.uc3m.es/display/inv16189 Economic activity and climate change -- Roberto Casarin, PhD Professor of Econometrics Ca' Foscari University of Venice San Giobbe 873/b - 30121 Venezia, Italy http://sites.google.com/view/robertocasarin/ https://www.unive.it/vera <https://www.unive.it/isba2024> https://www.unive.it/isba2024

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seminario di Brzeźniak a Pavia - 22 maggio ore 11
by Benedetta Ferrario 13 May '24

13 May '24

Mercoledì 22 maggio presso il Dipartimento di Scienze Economiche e Aziendali dell'Università di Pavia il professor Z. Brzezniak (Università di York) terrà un seminario alle ore 11 (precise) in aula 14. Title: Reflection of Stochastic Evolution Equations in Infinite Dimensional Domains Abstract: In this paper, we establish the existence and the uniqueness of solutions of stochastic evolution equations (SEEs) with reflection in an infinite dimensional ball. Our framework is sufficiently general to include e.g. the stochastic Navier-Stokes equations. Based on a joint work with Tusheng Zhang (Manchester and Hefei).

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Seminar Dario Trevisan at Tor Vergata 22.05
by Michele Salvi 13 May '24

13 May '24

Dear all, On Wednesday, May 22nd, at 14h30 in Aula Dal Passo of Tor Vergata Math Department, RoMaDS (https://www.mat.uniroma2.it/~rds/events.php) will host Dario Trevisan (Università di Pisa) with the seminar "Gaussian Approximation and Bayesian Posterior Distribution in Random Deep Neural Networks” Abstract: We establish novel rates for the Gaussian approximation of randomly initialized deep neural networks with Gaussian parameters and Lipschitz activation functions, in the so-called wide limit, i.e., where the sizes of all hidden layers become large. Using the Wasserstein metric and related functional analytic tools, we demonstrate the distribution of the output of a network and the corresponding Gaussian approximation are at a distance that scales inversely with the width of the network, surpassing previously established rates. Furthermore, we extend our findings to approximate the exact Bayesian posterior distribution of the network when the likelihood is a bounded Lipschitz function of the network output, on a finite training set. This includes common cases, such as the Gaussian likelihood, which is defined as the exponential of the negative mean squared error. Our inequalities thus shed light on the network's Gaussian behavior by quantitatively capturing the distributional convergence results in the wide limit. The exposition will aim to be self-contained, by introducing all the basic concepts related to artificial neural networks and Bayesian statistics to a mathematical audience. Based on arXiv:2203.07379 (joint with A. Basteri) and arXiv:2312.11737. We encourage in-person partecipation. Should you be unable to come, here is the link to the Teams streaming: https://teams.microsoft.com/l/meetup-join/19%3arfsL73KX-fw86y1YnXq2nk5VnZFw… https://teams.microsoft.com/l/meetup-join/19%3arfsL73KX-fw86y1YnXq2nk5VnZFw… https://teams.microsoft.com/l/meetup-join/19%3arfsL73KX-fw86y1YnXq2nk5VnZFw… https://teams.microsoft.com/l/meetup-join/19%3arfsL73KX-fw86y1YnXq2nk5VnZFw… https://teams.microsoft.com/l/meetup-join/19%3arfsL73KX-fw86y1YnXq2nk5VnZFw… The seminar is part of the Excellence Project MatMod@TOV.

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MSc scholarships at Université Paris-Est
by Tiziano De Angelis 13 May '24

13 May '24

Dear All, I am forwarding a message from Damien Lamberton concerning MSc scholarships for students interested in pursuing an MSc from the Université Paris-Est. The full advert is below. Please notice the tight deadline on 20 May. Best wishes Tiziano ---------- Forwarded message --------- > Da: Damien Lamberton <damien.lamberton(a)univ-eiffel.fr> > Date: mar 7 mag 2024 alle ore 17:04 > Subject: Fwd: [umr8050] Candidatures au M2 Bézout > To: Tiziano De Angelis <tiziano.deangelis(a)unito.it> > > > > > Dear Tiziano, > > I am forwarding some advertisement about our master's scholarships, in > case some of your students could be interested.. > > All the best, > > Damien > > > > ———————————————————————————————————————————————————————— > > > > Dear colleague, > > The 2024-2025 hiring campaign for international Bézout master's > scholarships is open from March 20 to May 20 at midnight. We will be able > to accept 10 applications. The Bézout scholarship program is directed > towards excellent students in mathematics, computer science or both, from > foreign institutions willing to pursue their studies in Université > Paris-Est at the master level. The laureates will receive about 1300 € per > month over 11 months and will be proposed a room on the campus. The best > students will then be invited to join the PhD program of the Doctoral > School MSTIC (Mathematics, Sciences and Information and Communication > Technology). A joint supervision with the student's national doctoral > framework, leading to both PhD grades, is possible. > > The details of the program can be found here: > https://labex-bezout.fr/masters-scholarships/ . From the same webpage, a > link to the application form will be available soon. > > A description of the activities of the Bézout Labex can be found in the > attached leaflet. One can also send you a few printed leaflets at your > postal address if you wish. > > Contact: Raphaël Danchin <danchin(a)u-pec.fr> > > > >

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Special Day on "Matrix models for quantum systems" - Friday June 7th at IHES
by Matteo D'Achille 13 May '24

13 May '24

Dear colleagues, I would like to draw your attention to the upcoming conference Matrix models for quantum systems, to be held on June 7th at the IHES in Bures-sur-Yvette. This conference is organized by the Seed Seminar of Mathematics and Physics <https://seedseminar.apps.math.cnrs.fr/>. The aim of the conference, and of the seminar in general, is to foster interactions between the mathematics and theoretical physics communities on topics of common interest. We will have the pleasure to listen to the following speakers: Guillaume Aubrun (Institut Camille Jordan, Lyon) Philippe Biane (Laboratoire d'Informatique Gaspard Monge, Marne-la-Vallée) Bertrand Eynard (Institut de Physique Théorique, CEA Saclay) Vladimir Kazakov (Laboratoire de Physique de l'École Normale Supérieure, Paris) The talks will be from 10:00 to 16:30, with a welcome coffee from 9:30. Both in-person and online participation are free but limited. Please register at https://indico.math.cnrs.fr/event/12052 if you are planning to participate in either capacity. Thank you for your attention and kind regards. Matteo D’Achille, for the organizing committee ---------------------------------- Matteo D’Achille, PhD Laboratoire de Mathématiques d’Orsay - LMO (UMR 8628 CNRS) Équipe Probabilités et Statistiques Bâtiment 307, rue Michel Magat, Faculté des Sciences d’Orsay, Université Paris-Saclay, F-91405 Orsay Cedex Office 3I20 (+33) 01 69 15 68 38 https://www.imo.universite-paris-saclay.fr/~matteo.dachille/

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(PMS)^2 talk - J. Janák - may 16 at 11:15
by Carlo Orrieri 13 May '24

13 May '24

Dear colleagues, we are happy to announce the following talk Josef Janák (Università di Pavia) Parameter estimation for the stochastic heat equation with multiplicative noise from local measurements Abstract: We propose the stochastic heat equation driven by the multiplicative space-time white noise and we introduce several estimators to the diffusivity parameter that are inspired by the maximum likelihood estimator. Since our observation scheme relies on local measurements, the asymptotics of the estimators is pursued with a fixed time horizon and with the spatial resolution of the observations tending to zero. A stable central limit theorem shows that our proposed estimators are strictly consistent and asymptotically mixed normal. The performance of the estimators is demonstrated in numerical simulations. This is a joint work with Professor Markus Reiß. Date and time: Thursday May 16, 11:15-12:15 (Rome time zone) Place: Aula Beltrami, Dip. Matematica, Univ. Di Pavia. Zoom meeting link: https://zoom.us/j/95472715600?pwd=bG1lYVNFMXp5ZGxBcTFoNXNxbE1UZz09 <https://zoom.us/j/95472715600?pwd=bG1lYVNFMXp5ZGxBcTFoNXNxbE1UZz09> ID riunione: 954 7271 5600 Codice d’accesso: 043885 These talks are part of the (PMS)^2: Pavia-Milano Seminar series on Probability and Mathematical Statistics organized jointly by the universities Milano-Bicocca, Pavia and Milano-Politecnico. Participation is free and welcome! Best regards The organizers (Carlo Orrieri, Maurizia Rossi, Margherita Zanella)

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Seminario ALOS - May 17th
by Alessandro Ramponi 13 May '24

13 May '24

Dear All, on May 17th, at 15:00, in classroom A (Building B), Department of Economics and Finance, University of Roma Tor Vergata, the following seminar will take place: Speaker: Elisa Alos (Dpt. Economia i Empresa, UPF, Barcelona) Title: On the Skew and Curvature of the Implied and Local Volatilities Abstract: In this talk, we study the relationship between the short-end of the local and the implied volatility surfaces. Our results, based on Malliavin calculus techniques, recover the recent 1/(H+3/2) rule (where H denotes the Hurst parameter of the volatility process) for rough volatilities (see F. Bourgey, S. De Marco, P. Friz, and P. Pigato, 2022), that states that the short-time skew slope of the at-the-money implied volatility is 1/(H+3/2) of the corresponding slope for local volatilities. Moreover, we see that the at-the-money short-end curvature of the implied volatility can be written in terms of the short-end skew and curvature of the local volatility and vice-versa. Additionally, this relationship depends on H.

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Padova Seminars in Probability and Finance - Domenico Marinucci - 14:30, May 17th
by Alberto Chiarini 13 May '24

13 May '24

Dear all, It is our pleasure to invite you all to the Padova Seminars in Probability and Finance on May, 17th at 14:30, at the department of Mathematics in Padova for the seminar by: Domenico Marinucci (University of Rome "Tor Vergata") Title: Geometry and Topology of Spin Random Fields Date: May 17, 2024, at 14:30, 2AB45 Abstract: Spin random fields are very important in many physical applications; they can be viewed as random sections of the s-th complex tensor power of the tangent bundle of the 2-sphere. In this talk, we discuss how to characterize their expected geometry and topology. In particular, we investigate the asymptotic behaviour, under scaling assumptions, of general classes of geometric and topological functionals for (properly defined) excursion sets; we cover both the cases of fixed and diverging spin parameters s. In the special case of monochromatic fields (i.e., spin random eigenfunctions), we show how their asymptotic behaviour is non-universal; we can obtain complex versions of Berry's random waves and of Bargmann-Fock's model as subcases of a new general class, depending on the rate of divergence of the spin parameter. We shall also discuss how these random fields can be reparametrised into complex-valued random functions on the group of rotations SO(3), and we discuss the expected values of the same geometric functionals in this new framework. Based on joint works with Javier Carròn Duque, Antonio Lerario, Maurizia Rossi and Michele Stecconi. Best wishes, Alberto and Alekos

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SPASS Seminar: Yassine Tahraoui
by Francesco Grotto 13 May '24

13 May '24

Dear Colleagues, We would like to invite you to the following SPASS seminar, jointly organized by UniPi, SNS, UniFi and UniSi: *Stochastic obstacle problems: variational & non variational settings* by Yassine Tahraoui (Scuola Normale Superiore) The seminar will take place tomorrow TUE, 14.05.2024 at 14:00 CET in Aula Seminari, Dipartimento di Matematica, UNIPI and streamed online at the link below. The organizers, A. Agazzi, G. Bet, A. Caraceni, F. Grotto, G. Zanco https://sites.google.com/unipi.it/spass *---------------------------------------------------------* *Abstract: Obstacle problems are free boundary type problems, well known in the literature of applied mathematics and lead to numerous applications. My aim is to present some results about the well-posedness and the regularity of the solution to a "parabolic or hyperbolic" obstacle problem in the presence of multiplicative noise, studied in [1, 2]. After showing the well-posedness of such problems, we prove Lewy-Stampacchia's inequalities, which gives an estimate of the reflected measure generated by the singularities caused by the obstacle near the free boundary.* *[1]I. H. Biswas, Y. Tahraoui and G. Vallet: Obstacle problem for a stochastic conservation law and Lewy-Stampacchia inequality. Journal of Mathematical Analysis and Applications, 527 (1) 127356 (2023)* *[2]Y. Tahraoui and G.Vallet: Lewy-Stampacchia's inequality for a stochastic T-monotone obstacle problem. Stochastic Partial Differential Equations: Analysis and Computations 10, 90-125 (2022).*

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Seminar in Statistics - ALEX MUNK
by Pierpaolo De Blasi 13 May '24

13 May '24

SEMINARS IN STATISTICS @ COLLEGIO CARLO ALBERTO <https://www.carloalberto.org/events/category/seminars/seminars-in-statistic…> Venerdi 17 Maggio 2024, alle ore 12.00, presso il Collegio Carlo Alberto, in Piazza Arbarello 8, Torino, si terrà il seguente seminario: ------------------------------------------------ Speaker: Alex Munk (Georg August Universitat Gottingen) Title: *Optimal Transport Dependency* Abstract: Finding meaningful ways to determine the dependency between two random variables 𝜉 and 𝜁 is a timeless statistical endeavor with vast practical relevance. In recent years, several concepts that aim to extend classical means (such as the Pearson correlation or rank-based coefficients like Spearman’s 𝜌) to more general spaces have been introduced and popularized, a well-known example being the distance correlation. In this talk, we propose and study an alternative framework for measuring statistical dependency, the transport dependency 𝜏 ≥ 0 (TD), which relies on the notion of optimal transport and is applicable in general Polish spaces. It can be estimated via the corresponding empirical measure, is versatile and adaptable to various scenarios by proper choices of the cost function. It intrinsically respects metric and geometric properties of the ground spaces. Notably, statistical independence is characterized by 𝜏 = 0, while large values of 𝜏 indicate highly regular relations between 𝜉 and 𝜁 . Based on sharp upper bounds, we exploit three distinct dependency coefficients with values in [0, 1], each of which emphasizes different functional relations: These transport correlations attain the value 1 if and only if 𝜁 = 𝜑(𝜉), where 𝜑 is a) a Lipschitz function, b) a measurable function, c) a multiple of an isometry. Besides a conceptual discussion of transport dependency, we address numerical issues and its ability to adapt automatically to the potentially low intrinsic dimension of the ground space. Monte Carlo results suggest that TD is a robust quantity that efficiently discerns dependency structure from noise for data sets with complex internal metric geometry. The use of TD for inferential tasks is illustrated for independence testing on a data set of trees from cancer genetics. Joint work with Giacomo Nies and Thomas Staudt. ------------------------------------------------ Sarà possibile seguire il seminario anche in streaming: Join Zoom Meeting <https://us02web.zoom.us/j/81354066852?pwd=a2hEZTFHMDRuZHVYQ1RGSmd0Wi82QT09> Il seminario è organizzato dalla "de Castro" Statistics Initiative www.carloalberto.org/stats -- Pierpaolo De Blasi University of Torino & Collegio Carlo Alberto carloalberto.org/pdeblasi <https://sites.google.com/a/carloalberto.org/pdeblasi/>

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Seminario Karel Hron presso Politecnico di Milano
by Laura Maria Sangalli 12 May '24

12 May '24

Si avvisa che in data 15-05-2024, alle ore 11:00 precise al Politecnico di Milano, in aula Saleri (sesto piano Dipartimento di Matematica - edificio 14), si svolgerà il seguente seminario Karel Hron, University Olomouc Titolo: Analysing multivariate densities in Bayes spaces with implications for functional data analysis Abstract: Probability density functions can be embedded in the geometric framework of Bayes spaces which respect their relative nature and enable further modeling and analysis. Specifically, the Hilbert space structure of Bayes spaces (whereof compositional data are one specific instance) has several important implications for classical and Bayesian inference, as well as functional data analysis. In this contribution, an orthogonal decomposition of multivariate densities in Bayes spaces using a distributional analog of the Hoeffding-Sobol identity is constructed. The decomposition is based on a reformulation of the standard (arithmetic) margins into so-called geometric margins. These are orthogonal projections into one-dimensional space of information contained in multivariate densities and coincide with the arithmetic margins in case of independence. More generally, the decomposition contains an independent part and all possible interaction terms. The orthogonality of the decomposition results in an analog of Pythagoras' Theorem for squared norms of the decomposed densities and margin-free property of the interaction terms. Because the squared norms from the Pythagoras' decomposition are essentially compositional in nature, all tools of the log-ratio methodology can be used for their statistical processing. Theoretical results will be illustrated with empirical geochemical data. This talk is based on joint work with Christian Genest and Johanna Nešlehová from McGill University, Montréal, Canada. Il link per seguire il seminario online sarà reso disponibile pochi minuti prima dell’avvio del seminario al seguente link https://mox.polimi.it/mox-colloquia-seminars-list/mox-seminars/?id_evento=2… Tutti gli interessati sono cordialmente invitati a partecipare, Laura Sangalli —— Laura Maria Sangalli MOX - Dipartimento di Matematica Politecnico di Milano Piazza Leonardo da Vinci 32 20133 Milano - Italy (+39) 02 2399 4554 laura.sangalli(a)polimi.it<mailto:laura.sangalli@polimi.it> https://sangalli.faculty.polimi.it

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International Conference in Venice - CALL FOR PAPERS
by Monica Billio 12 May '24

12 May '24

23nd INTERNATIONAL CONFERENCE CREDIT 2024 *The frontiers of new risks: AI, digital and sustainability transitions * Venice, Italy 3 – 4 October 2024 * * *GRETA Associati* (Venice, Italy),*CRIF* (Bologna, Italy), *European Datawarehouse *(Frankfurt am Main, Germany), *European Investment Fund* (Luxembourg), *Intesa Sanpaolo* (Milan, Italy) and *Modefinance* (Trieste, Italy) are partners in organising a Conference to be held in Venice on October 3-4, 2024. * * The CREDIT 2024 conference will bring together academics, practitioners and PhD students working in various areas of financial and socio-economic risk with the aim of creating a unique opportunity for participants to discuss research progress and policy as well as industry-relevant insights and directions for future research. CREDIT 2024 is the *twenty-third* in a series of events dedicated to various aspects of credit risk and organised under the auspices of: the *Department of Economics *and*VERA - Venice centre in Economic and Risk Analytics for public policies* - of the *Ca’ Foscari University of Venice*,*Joint Research Center European Commission*, *ABI - Italian Banking Association*, *AIAF - Associazione Italiana per l'Analisi Finanziaria*, *AIFIRM - Associazione Italiana Financial Industry Risk Managers*. Sustainability necessarily involves the adaptation of today’s business model to the dynamic nature of the current digitalised environments. Corporations need to make sure that resources, especially technology, are being used responsibly and efficiently to improve the lives of the present generations and future generations as well as strengthen their relationships with the environment as to solve sustainability-related problems such as poverty, environmental degradation, pollution and inequality. Artificial Intelligence (AI) has the potential to address these societal problems including sustainability. The climate crisis and the degradation of the physical environment are complex problems that require the most innovative and advanced solutions. The real value of AI hence lies in its ability to facilitate and foster environmental and social governance, rather just as a tool to reduce pollution, poverty and resource depletion. In the age of AI, societies depend on big data, social media, knowledge management and data science to survive and achieve these sustainability goals. AI has the potential to reshape not only finance and industry but also the whole society. There is need to understand opportunities and challenges as to properly manage all relevant risks. The organisers encourage submissions on any topic within the overall theme of the conference, with attention to *the use of AI to assess the sustainability impact of finance *(i.e. exploiting AI techniques or Big Data to bridge primary information gaps and proxy the sustainability impact) and *on how climate and digital risks may interact* (i.e. climate denial, social media and social media strategies including deepfakes). The final program will include both submitted and invited papers. Acceptances received so far from invited speakers include *Patrick Bolton *(Imperial College London), and *Roberto Rigobon* (MIT Sloan School of Management). The Conference will also include panel discussions on the major issues at stake with the views of researchers', practitioners' and policy makers. The SCIENTIFIC COMMITTEE for the Conference consists of: *Marcin Kacperczyk *(Imperial College London, Programme Chair) *Monica Billio* (Ca’ Foscari University of Venice & GRETA) *Marie Brière* (AMUNDI & Université Libre de Bruxelles) *Lucia Alessi* (Joint Research Center, European Commission) *Leonardo Gambacorta *(Bank For International Settlements) *Mila Getmansky* (Isenberg School of Management, UMass Amherst) *Christian Gollier* (Toulouse School of Economics) *Helmut Kraemer-Eis *(European Investment Fund) *Jan Pieter Krahnen *(Leibniz Institute for Financial Research SAFE & Goethe University) *Steven Ongena* (University of Zurich, Swiss Finance Institute, KU Leuven, NTNU Business School & CEPR) *Roberto Rigobon *(MIT Sloan School of Management) *Stephen Schaefer* (London Business School) *Marti Subrahmanyam *(NYU Stern Business School) CALL FOR PAPERS Those wishing to present a paper at the Conference should submit by *June 10, 2024 *to the address given below (preferably in electronic format). Please indicate to whom correspondence should be addressed. Decisions regarding acceptance will be made by July 10, 2024. The final version of accepted papers must be received by August 31, 2024. Please send papers to: GRETA Associati, Dorsoduro 3707 - 30123 Venice, ITALY Phone : +39 349 060 3656 - e-mail: credit(a)greta.it More detailed information on the Conference website: https://www.greta.it/index.php/it/credit-2024

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Seminar RUSSO
by Stefano Pagliarani 10 May '24

10 May '24

Dear all, On May 15th, at 11 am, in the classroom Aula Seminari VIII Piano, Department of Mathematics of the University of Bologna, Francesco RUSSO will give a seminar entitled WEAK DIRICHLET PROCESSES AND BSDE<https://www.dm.unibo.it/seminari/mat/seminars/2024/05/15/francesco-russo>s The abstract is available at https://www.dm.unibo.it/seminari/mat/seminars/2024/05/15/francesco-russo For any question, please contact the organizers: Cristina di Girolami and Stefano Pagliarani. Best regards, ------------------------------------------------------------------------------------------------------------------------ Stefano Pagliarani, Associate Professor Piazza di Porta S. Donato, 5 University of Bologna (Alma Mater) 40126 Bologna (BO), Italy Department of Mathematics Cell. Phone +39 366 5013755 Email: stepagliara1(a)gmail.com<mailto:stepagliara1@gmail.com>, <mailto:stefano.pagliarani9@unibo.it> stefano.pagliarani9(a)unibo.it<mailto:stefano.pagliarani9@unibo.it> Zoom: https://unibo.zoom.us/j/3755841669 -----------------------------------------------------------------------------------------------------------------------

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Fwd: Summer School Ischia ESI
by Roy Cerqueti 09 May '24

09 May '24

Dear all, please, find the flyer of this Summer School, that can be of interest to some young scholars. Thank you. Yours sincerely, Roy Cerqueti -- *Fai crescere le giovani ricercatrici e i giovani ricercatori*** *con il 5 per mille alla Sapienza* Scrivi il codice fiscale dell'Università *80209930587 **Cinque per mille <https://www.uniroma1.it/it/node/23149>*

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Fwd: Next LTI@Unito Seminar: Stéphane Villeneuve | May 13 @ 12:00 - 13:00
by Luca Regis 08 May '24

08 May '24

Dear colleagues, please find below the announcement of the seminar by Stephane Villeneuve (TSE) organized by LTI@UniTO and Collegio Carlo Alberto. The seminar can be attended via zoom clicking on the button below. Best regards, Luca Regis ---------------------------------------- Associate Professor ESOMAS Department, University of Torino Affiliate, Collegio Carlo Alberto sites.google.com/view/lucaregis Office: +39 011 670 6065 www.carloalberto.org/lti Next LTI@Unito Seminar: Stéphane Villeneuve | May 13 @ 12:00 - 13:00 <https://4z5y5.r.sp1-brevo.net/mk/cl/f/sh/SMK1E8tHeFuBop7S3TtlKvKzHBSs/4oJ_v…> LTI@UniTO and Fondazione Collegio Carlo Alberto are pleased to invite you to the following seminar: *May 13, 2024 | 12:00 - 13:00* *Dynamic contracting with many agents* *Stéphane Villeneuve (Toulouse School of Economics)* *Abstract: *We analyze dynamic capital allocation and risk sharing between a principal and many agents, who privately observe their output. The state variables of the mechanism design problem are aggregate capital and the distribution of continuation utilities across agents. This gives rise to a Bellman equation in an infinite dimensional space, which we solve with mean-field techniques. We fully characterize the optimal mechanism and show that the level of risk agents must be exposed to for incentive reasons is decreasing in their initial outside utility. We extend classical welfare theorems by showing that any incentive-constrained optimal allocation can be implemented as an equilibrium allocation, with appropriate money issuance and wealth taxation by the principal. To attend online, join Zoom meeting <https://4z5y5.r.sp1-brevo.net/mk/cl/f/sh/SMK1E8tHeG13GxwPEe3FQkdjFU38/HGpf3…> *Fondazione Collegio Carlo Alberto* Piazza Arbarello 8 - 10122 Torino, Italy phone: +3901115630800 <tel:+3901115630800> segreteria(a)carloalberto.org - www.carloalberto.org <https://4z5y5.r.sp1-brevo.net/mk/mr/sh/SMJz09SDriOHWoY4zxneDRikeAJG/JT1digZ…> <https://4z5y5.r.sp1-brevo.net/mk/cl/f/sh/SMK1E8tHeG7uj6lMPoCjWZwTDmdO/xbd5a…> <https://4z5y5.r.sp1-brevo.net/mk/cl/f/sh/SMK1E8tHeGEmBFaJayMDcPFDC5De/7R5hd…> <https://4z5y5.r.sp1-brevo.net/mk/cl/f/sh/SMK1E8tHeGLddOPGm8VhiEXxANnu/KmFdZ…> <https://4z5y5.r.sp1-brevo.net/mk/cl/f/sh/SMK1E8tHeGSV5XEDxIfBo3qh8gOA/THQZY…> <https://4z5y5.r.sp1-brevo.net/mk/cl/f/sh/SMK1E8tHeGZMXg3B8Softt9R6yyQ/xDNI-…> <https://4z5y5.r.sp1-brevo.net/mk/cl/f/sh/SMK1E8tHeGgDzos8Jcy9ziSB5HYg/jDbOw…> *Founders* <https://4z5y5.r.sp1-brevo.net/mk/cl/f/sh/SMK1E8tHeGn5Rxh5Un7e5Xkv3a8w/r0Vb5…> <https://4z5y5.r.sp1-brevo.net/mk/cl/f/sh/SMK1E8tHeGtwu6W2fxH8BN3f1sjC/phw27…> *Sostieni il Collegio Carlo Alberto con il 5x1000 | c.f. 94049090015* *INFORMATION UNDER THE NEW GENERAL DATA PROTECTION REGULATION (GDPR)* Your personal information has been gathered for the exclusive purpose of informing you about the Collegio's initiatives, considering our and your legitimate interest or your consent. If you wish to have your personal data modified please contact Fondazione Collegio Carlo Alberto, piazza Arbarello 8, 1022 Torino, Italy - phone:+39011 15630 800 - privacy(a)carloalberto.org <https://4z5y5.r.sp1-brevo.net/mk/cl/f/sh/1t6Af4OiGsDhYHezxFlTns9XmrPqba/o-w…> To find out about the policies regarding the processing of personal data pursuant to articles 13-14 of EU Regulation 2016/679, consult the information at the following link _https://www.carloalberto.org/privacy/_ <https://4z5y5.r.sp1-brevo.net/mk/cl/f/sh/1t6Af4OiGsE9szrQLbrOy8DNAgOaJe/Drj…> *Unsubscribe* <https://4z5y5.r.sp1-brevo.net/mk/un/sh/SMJz09a0vkbXsu1klhxRMEbrtrvO/3tb3NOW…> *© 2022 Fondazione Collegio Carlo Alberto*

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STATISTICAL REFLECTIONS: Half-day Workshop on Statistical Methods - Ca’ Foscari University (Scientific Campus Venezia Mestre)
by Carlo Gaetan 08 May '24

08 May '24

Dear all, the STREAM group (https://www.unive.it/pag/16818/) of the Ca’ Foscari university invites to *STATISTICAL REFLECTIONS* *Half-day Workshop on Statistical Methods* *Venice May 22, 2024* Ca’ Foscari University Scientific Campus Aula Delta 1B Via Torino 155 Venezia Mestre Program: -14:00 David Firth (University of Warwick): Compositional quasi-likelihood and logit models -14:45 Ioannis Kosmidis (University of Warwick): Consistent, tuning-free model selection in regression problems -15:30 Omiros Papaspiliopoulos (Bocconi University): Functional estimation of the marginal likelihood Abstracts: Professor David Firth University of Warwick, UK https://warwick.ac.uk/dfirth Compositional quasi-likelihood and logit models A composition vector describes the relative sizes of parts of a thing. Some important modern application areas are microbiome analysis, time-use analysis and archaeometry (to name just three). We develop model-based analysis of composition, through the first two moments of measurements on their original scale. In current applied work the most-used route to compositional data analysis, following an approach introduced by the late John Aitchison in the 1980s, is based on contrasts among log-transformed measurements. The quasi-likelihood model framework developed here provides a general alternative with several advantages. These include robustness to secondary aspects of model specification, stability when there are zero-valued or near-zero measurements in the data, and more direct interpretation. Linear models for log-contrast transformed data are replaced by generalized linear models with logit link, and variance-covariance estimation is straightforward via suitably standardized residuals. Joint work with Fiona Sammut, University of Malta. Professor Ioannis Kosmidis University of Warwick, UK https://www.ikosmidis.com Consistent, tuning-free model selection in regression problems We present a family of consistent model selection procedures for regression problems, which appropriately threshold readily available statistics after estimating the model with all covariate information. The model selection procedures rely only on standard assumptions about information accumulation that guarantee the typically expected asymptotic properties of the estimators (e.g., consistency) and require neither the selection of tuning parameters nor the fitting of all possible models. We apply our thresholding methodology in widely used statistical models (e.g. generalized linear models and beta regression), demonstrate that it is easily implementable as part of the standard maximum likelihood output, and compare its performance to existing techniques, illustrating its effectiveness. Joint work with Patrick Zietkiewicz, University of Warwick. Professor Omiros Papaspiliopoulos Bocconi University, Italy https://dec.unibocconi.eu/people/omiros-papaspiliopoulos Functional estimation of the marginal likelihood We consider the problem of exploring the marginal likelihood of low-dimensional hyperparameters from high-dimensional Bayesian hierarchical models. We provide a unified framework that connects seemingly unconnected approaches to estimating normalizing constants, including the Vardi estimator, the umbrella sampling and the Gibbs sampler. The framework requires Monte Carlo sampling from the posteriors of the high-dimensional parameters for different values of the hyperparameters on a lattice. We establish a surprising reproducing property that leads to a functional estimator of the marginal likelihood and establish consistency both fixed-lattice and lattice-infill consistency. The resultant method is highly practical, black-box with theoretical guarantees. Best regards, Carlo Gaetan -- - Dipartimento di Scienze Ambientali, Informatica e Statistica - DAIS Università Ca' Foscari - Venezia Z.A12 - Edificio Zeta Via Torino, 155 I-30172 Mestre (VE) ITALY phone: ++39 041 234 8404 e-mail:[gaetan"at"unive"dot"it] web:[http://www.dais.unive.it/~gaetan] Please don't print this e-mail unless you really need to. Please avoid sending me Word, Excel or PowerPoint attachments. Seehttp://www.gnu.org/philosophy/no-word-attachments.html. Per favore non stampate questo messaggio se non è proprio necessario. Per favore non mandatemi allegati in Word, Excel o PowerPoint. Le ragioni sono spiegate quihttp://www.gnu.org/philosophy/no-word-attachments.it.html

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Kolmogorov meets Turing - May 23, 11am - 6pm, DIAG, Sapienza, Rome
by Marco Scarsini 07 May '24

07 May '24

Kolmogorov meets Turing *Workshop on probabilistic methods for the analysis of stochastic processes and randomized algorithms* This year's edition of the Kolmogorov meets Turing Workshop will take place on Thursday, May 23rd 2024, at DIAG <https://www.diag.uniroma1.it/>, via Ariosto 25, Aula Magna I floor. The purpose of KmT is to bring together researchers from Computer Science, Economics, Mathematics and related fields to present and discuss research on probabilistic methods for the analysis of games, distributed and stochastic processes, dynamic processes and randomized algorithms. When: Thursday May 23rd, 2024 Where: Dipartimento di Ingegneria Informatica, Automatica e Gestionale “A. Ruberti”, via Ariosto 25, Roma – Aula Magna, I floor Schedule Morning session 11.00 – 12.00. Nicolò Cesa-Bianchi (Università degli Studi di Milano): The mathematics of machine learning: between statistics and game theory 12.00 – 12.30. Xavier Mathieu Raymond Venel (Luiss University): Weighted average-convexity in Cooperative Games 12.30 – 13.00. Guido Schaefer (CWI, Netherlands): To Trust or Not to Trust: Assignment Mechanisms with Predictions 13.00 – 14.30: Lunch break Afternoon session 14.30 – 15.00. Pietro Caputo (University Roma Tre): Nonlinear Monte Carlo dynamics for the Ising model: some convergence results 15.00 – 15.30. Matteo Quattropani (Sapienza University of Rome): Mixing of the Averaging process on graphs and hypergraphs 15.30 – 16.00. Robin Vacus (Bocconi University): Minority Dynamics: the Short and Winding Road to Consensus 16.00 – 16.30: Coffee break 16.30 – 17.00. Maria Sofia Bucarelli (Sapienza University of Rome): On Generalization Bounds for Projective Clustering 17.00 – 17.30. Francesco D'Amore (Bocconi University): The Strong Lottery Ticket Hypothesis and the Random Subset Sum Problem 17.30 – 18.00. Federico Fusco (Sapienza University of Rome): The Role of Transparency in Repeated First-Price Auctions with Unknown Valuations _______________________________________________________ LIST OF ABSTRACTS Maria Sofia Bucarelli: On Generalization Bounds for Projective Clustering. Given a set of points, clustering consists of finding a partition of a point set into k clusters such that the center to which a point is assigned is as close as possible. Most commonly, centers are points themselves, which leads to the famous k-median and k-means objectives. One may also choose centers to be j dimensional subspaces, which gives rise to subspace clustering. In this paper, we consider learning bounds for these problems. That is, given a set of n samples P drawn independently from some unknown, but fixed distribution D, how quickly does a solution computed on P converge to the optimal clustering of D? We give several near p optimal results. In particular, 1) For center-based objectives, we show a convergence rate of O(√k/n). This matches the known optimal bounds of [Fefferman, Mitter, and Narayanan, Journal of the Mathematical Society 2016] and [Bartlett, Linder, and Lugosi, IEEE Trans. Inf. Theory 1998] for k-means and extends it to other important objectives such as k-median. 2) For subspace clustering with j-dimensional subspaces, we show a convergence rate of O(√kj2/n). These are the first provable bounds for most of these problems. For the specific case of projective clustering, which generalizes k-means, we show a converge rate of Ω(√kj/n) is necessary, thereby proving that the bounds from [Fefferman, Mitter, and Narayanan, Journal of the Mathematical Society 2016] are essentially optimal. Nicolò Cesa-Bianchi: The mathematics of machine learning: between statistics and game theory. Machine learning is the main driving force behind the current AI revolution. To provide a solid mathematical foundation to learning systems, we must formally characterize what a machine can learn and what is the minimal amount of training data needed to achieve a desired performance. In this talk, I will describe the two main approaches to algorithmic learnability, one rooted in statistics and one in game theory, and explore their connections. Pietro Caputo: Nonlinear Monte Carlo dynamics for the Ising model: some convergence results. We introduce and analyze a natural class of nonlinear Monte Carlo dynamics for spin systems such as the Ising model. The evolution is based on the framework of mass action kinetics, which models systems undergoing collisions, and captures a number of nonlinear models from various fields, including chemical reaction networks, Boltzmann’s model of an ideal gas, recombination in population genetics and genetic algorithms. In the context of spin systems, it is a nonlinear analog of the familiar Monte Carlo method based on Markov chains, such as Glauber dynamics and block dynamics, which are by now well understood. The nonlinearity makes the dynamics much harder to analyze, and even the most basic convergence issues are far from being settled. We discuss several open problems. The main result is an optimal estimate on the rate of convergence to stationarity in a regime of high temperature. Our analysis combines tools from percolation, branching and fragmentation processes. Based on joint work with Alistair Sinclair. Francesco D’Amore: The Strong Lottery Ticket Hypothesis and the Random Subset Sum Problem. The Strong Lottery Ticket Hypothesis (SLTH) posits that randomly-initialized neural networks contain subnetworks (strong lottery tickets) that achieve competitive accuracy when compared to sufficiently small target networks, even those that have been trained. Empirical evidence for this phenomenon was first observed by Ramanujan et al. in 2020, spurring a line of theoretical research: Malach et al. (ICML ’20), Pensia et al. (NeurIPS ’20), da Cunha et al. (ICLR ’20), and Burkholz (ICML & ICLR ’22) have analytically proved formulations of the SLTH in various neural network classes and under different hypotheses. In this presentation, we provide an overview of the state-of-the-art theoretical research on the SLTH and its connection with the Random Subset Sum (RSS) problem in theoretical computer science. While previous works on the SLTH ensure that the strong lottery ticket can be obtained via unstructured pruning, we demonstrate how recent advances in the multidimensional generalization of the RSS problem can be leveraged to obtain forms of structured pruning. Additionally, we highlight how refining the RSS results would yield tighter formulations of the SLTH. This presentation is based on a joint work with A. Da Cunha and E. Natale appeared at NeurIPS 2023. Federico Fusco: The Role of Transparency in Repeated First-Price Auctions with Unknown Valuations. We study the problem of regret minimization for a single bidder in a sequence of first-price auctions where the bidder discovers the item’s value only if the auction is won. Our main contribution is a complete characterization, up to logarithmic factors, of the minimax regret in terms of the auction’s transparency, which controls the amount of information on competing bids disclosed by the auctioneer at the end of each auction. Our results hold under different assumptions (stochastic, adversarial, and their smoothed variants) on the environment generating the bidder’s valuations and competing bids. These minimax rates reveal how the interplay between transparency and the nature of the environment affects how fast one can learn to bid optimally in first-price auctions. The talk is based on a joint work with Nicolò Cesa-Bianchi, Tommaso Cesari, Roberto Colomboni, and Stefano Leonardi, which will appear at STOC 2024. Matteo Quattropani: Mixing of the Averaging process on graphs and hypergraphs. The Averaging process is a mass redistribution process over the vertex set of a graph or, more generally, a hypergraph. Given a (hyper)graph G, the process starts with a non-negative mass associated with each vertex. At each discrete time step, one of the (hyper)edges of G is sampled at random and the total mass associated with the vertices of the chosen (hyper)edge is equally redistributed among its vertices. Clearly, as time grows to infinity, the state of the system will converge to a flat configuration in which all the vertices have the same mass. This very simple process appeared in different literatures under various names, and it was introduced to the probabilistic community by Aldous and Lanoue in 2012. However, until a few years ago, there were no sharp quantitative results on the time needed to reach equilibrium. Indeed, the analysis of this process requires different tools compared to the classical Markov chain framework, and even in the case of seemingly straightforward geometries—such as the complete graph or the cycle—it can be handled only by means of nontrivial probabilistic and functional analytic techniques. During the talk, I’ll give an overview of the problem and its difficulties, present the classes of examples that are currently settled, and mention some possible future directions of investigation. Based on joint work with Pietro Caputo and Federico Sau. Guido Schaefer: To Trust or Not to Trust: Assignment Mechanisms with Predictions. The realm of algorithms with predictions has led to the development of several new algorithms that leverage (potentially erroneous) predictions to enhance their performance guarantees. The challenge here is to devise algorithms that achieve optimal approximation guarantees as the prediction quality varies from perfect (consistency) to imperfect (robustness). This framework is particularly appealing in mechanism design contexts, where predictions might convey private information about the agents. In this talk, we present our recent results on the design of truthful mechanisms that leverage predictions to achieve improved approximation guarantees for several variants of the generalized assignment problem (GAP). We consider the private graph model introduced by Dughmi and Ghosh (2010), where the set of resources that an agent is compatible with is private information. We investigate GAP in the private graph model augmented with a prediction of the optimal assignment. We give a deterministic group-strategyproof mechanism that is (1 + 1/γ)-consistent and (1 + γ)-robust for the special case of bipartite matching, where γ ≥ 1 is some confidence parameter. We also prove that this is best possible. Remarkably, our mechanism draws inspiration from the renowned Gale-Shapley algorithm, incorporating predictions as a crucial element. For more general GAP variants, we introduce a unified greedy scheme and use randomization to derive universally group-strategyproof mechanisms that achieve improved consistency and robustness guarantees in expectation. Robin Vacus: Minority Dynamics: the Short and Winding Road to Consensus. The ”minority” rule is a peculiar opinion dynamics, which prompts agents to adopt the opinion least represented in a sample – in contrast to its far more famous and natural counterpart, the majority rule. Yet, as long as the sample size is large enough and communications happen in parallel, it proves to be an efficient way to reach agreement. Moreover, contrary to traditional consensus protocols, it demonstrates extreme sensitivity to even a small number of ”stubborn” individuals, enabling fast information propagation within the group. In this presentation, I will describe an analysis of convergence time, showcase simulation results, and discuss several open problems, shedding light on what is currently understood and what remains to be explored about this fascinating dynamic. This talk is based on a recent work with Luca Becchetti, Andrea Clementi, Francesco Pasquale, Luca Trevisan and Isabella Ziccardi, that was published in SODA 2024. Xavier Mathieu Raymond Venel: Weighted average-convexity in Cooperative Games. It is well known that the Shapley value of a convex game always belongs to the core. Looking for a weaker condition than convexity insuring that the Shapley value of a game lies in the core, Inarra and Usategui (1993) relaxed the convexity assumption by introducing the notion of average convexity. Assuming that weights are associated with the players, we generalize the notion of convexity and average-convexity for cooperative TU games to the notion of weighted average-convexity. We prove that if a game is weighted average-convex, then the corresponding weighted Shapley value is in the core. We then study the relations between weighted average-convexity, core-inclusion, and communication TU-games. We exhibit necessary and sufficient conditions on the underlying graph to preserve weighted average-convexity from any communication game to the associated Myerson restricted game, extending some previous results established in Slikker (1998). Joint work with Alexandre Skoda.

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Seminar Dr Frank Fu (MathWorks) - Roma Tre University
by Francesco Cesarone 07 May '24

07 May '24

Dear all, I am pleased to announce the upcoming seminar "MATLAB Applications in Finance<https://it.mathworks.com/company/events/seminars/matlab-applications-in-fin…>" held by Frank Fu, Academic Manager MathWorks, on May 17th, 2024. The seminar is part of a series (Friday Seminar Series) organized by the Research Group in Quantitative Finance, Department of Business Studies - Roma Tre University. It is aimed at students majoring in or interested in business, economics, and finance, lecturers, and professors who teach such subjects or do academic research in those areas. The seminar can be attended physically at the Computer Lab (small classroom) on the ground floor (Department of Business Studies - Roma Tre University, Via Silvio D'Amico, 77, 00145 Rome, Italy) or online via teams. Participation is free, but registration for the seminar is mandatory (link<https://it.mathworks.com/company/events/seminars/matlab-applications-in-fin…>). More information can be also found on the following webpage<https://www.francescocesarone.com/msc-in-finance/friday-seminar-series>. Best regards, Francesco Cesarone F Cesarone (2020), Computational Finance. MATLAB oriented modeling, Routledge-Giappichelli Studies in Business and Management, ISBN 978-0-367-49303-5<https://www.giappichelli.it/computational-finance> For more info: https://www.francescocesarone.com/books -- Francesco Cesarone - Ph.D. Associate Professor Department of Business Studies Roma Tre University Via Silvio D'Amico, 77 00145 - Roma, Italy tel: +39 06 57335744 Skype: francesco.cesarone email: francesco.cesarone(a)uniroma3.it<mailto:francesco.cesarone@uniroma3.it> Studio n. 20 piano V WWW: https://www.francescocesarone.com/

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Seminario di Federico Sau a Roma Tre il 14 maggio
by Pietro Caputo 07 May '24

07 May '24

Martedì* 14 Maggio* 2024 alle ore *14:30*, Federico Sau (Università degli Studi di Trieste) terrà il seminario di Probabilità dal titolo "*Scaling limits of the averaging process*". Abstract: The averaging process on a graph is a continuous-space Markov chain, which is commonly interpreted as an opinion dynamics, a distributed algorithm, or an interface moving through a randomized sequence of deterministic local updates. Its dynamics goes as follows. Attach i.i.d. Poisson clocks to edges, and assign real values to vertices; at the arrival times of these clocks, update the values with their average. As time runs, the averaging process converges to a flat configuration, and one major problem in the field is that of quantifying the speed of convergence to its degenerate equilibrium in terms of characteristic features of the underlying graph. In this talk, after reviewing some basic properties and recent results on mixing times for the averaging process on general graphs, we focus on the discrete $d$-dimensional torus, and on some finer properties of the process in this setting. We discuss some quantitative features (e.g., limit profile, early concentration and local smoothness), and look at nonequilibrium fluctuations, a particularly interesting problem in this degenerate context lacking a non-trivial notion of local equilibrium. If time permits, we will touch on the main ideas of the proof of such scaling limits, which combine tools from Malliavin calculus in Poisson space, their probabilistic dynamic interpretations, and some new discrete-gradient estimates. Talk based on the preprints arXiv.2311.14176, arXiv.2403.02032. Il seminario si svolgerà in presenza presso il Dipartimento di Matematica e Fisica - Lungotevere Dante 376 (Blocco Aule) - *Aula M2*

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RTT MAT/06 - Milano Statale
by Andrea Cosso 06 May '24

06 May '24

Buonasera, vi segnalo che è stato bandito un posto di ricercatore tenure-track (RTT) in MAT/06 presso il Dipartimento di Matematica dell’Università degli Studi di Milano. Il bando si trova al seguente link: https://www.unimi.it/it/ateneo/lavora-con-noi/reclutamento-ricercatori/sele… La scadenza per la presentazione delle domande è il 31 maggio 2024. Cordiali saluti, Andrea Cosso English version Dear colleagues, the Mathematics Department of the University of Milan has opened a position as tenure-track researcher (RTT) in the scientific sector MAT/06 (Probability and Mathematical Statistics): https://www.unimi.it/en/university/work-us/researcher-recruitment/researche… The deadline for applications is May 31, 2024. Best regards, Andrea Cosso

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