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Call for abstracts: "Statistical mechanics approaches to earth system dynamics'' EGU Session
by Giulia Carigi 13 Dec '21

13 Dec '21

Dear Colleagues, with apologies for cross-posting, we would like to draw your attention to the session NP1.1 ``Statistical mechanics approaches to earth system dynamics: invariant measures, response, and large deviations'' to be held as part of the upcoming General Assembly of the European Geosciences Union (Vienna, Austria, 3rd to 8th of April 2022). A short description of the session can be found here https://meetingorganizer.copernicus.org/EGU22/session/42646 or at the end of this email. We would be very happy if you could consider submitting an abstract to this session. IMPORTANT: deadline for abstract submission is 12 January 2022, 13:00 CET For further info on abstract submission see here: https://egu22.eu/abstracts_and_programme/how_to_submit_an_abstract.html EGU2022 will be a hybrid conference – more information at https://egu22.eu/about/provisional_meeting_format.html Best wishes, Jochen Broecker (Convener), Vera Melinda Galfi, Giulia Carigi, Georgios Margazoglou, Jeroen Wouters (Co-Conveners) SESSION DESCRIPTION: The equations governing the dynamics of the atmosphere and the ocean provide us with an enormously powerful tool to understand and predict the future evolution of these dynamics. By integrating these equations forward in time from a given initial condition, we are able to produce highly realistic trajectories of the earth system's temporal evolution. A number of scientific questions however consider the statistical behaviour of solution ensembles, with the heterogeneity coming from different (yet ``typical'') initial conditions or random external forces. Examples are questions related to the global mean temperature or rainfall, the frequency of extreme events, but also questions regarding the average predictability of the system or its susceptibility to external perturbations. Statistical mechanics provides a framework in which such questions can be addressed. Rather than considering individual solutions, randomness and uncertainty are introduced to describe the ensemble of solutions in a probabilistic manner. This statistical mechanics approach to earth system dynamics will be the theme of this session. Contributions will cover a broad range of aspects from theory to applications and from mathematics to climate science. Topics include: * Novel mathematical techniques from the theory of stochastic processes and PDE's * Examples of ideas and methods from statistical mechanics being applied to the earth system (including, but not limited to, linear response, model reduction, large deviations and related algorithms) * Potential future applications, for instance in downscaling, data assimilation and parametrisations ----------------------------------------------------------------- Giulia Carigi, Postdoctoral Research Fellow Department of Mathematics and Statistics University of Reading, UK

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Seminar by A. Picarelli in Padova (this Friday)!
by Giorgia Callegaro 13 Dec '21

13 Dec '21

Dear all, it is a pleasure to announce the forthcoming seminar by *Athena Picarelli* (Università di Verona), which will be held *in person* room 2BC30 of the Mathematics Department (Torre Archimede) of the University of Padova and online, via Zoom, this Friday. Here are the details: * Date and time: 17 December, 14.30 pm * Title: *Optimal management of pumped hydroelectric production with state constrained optimal control* * Abstract: We present a novel technique to solve the problem of managing optimally a pumped hydroelectric storage system. This technique relies on representing the system as a stochastic optimal control problem with state constraints, these latter corresponding to the finite volume of the reservoirs. Following the recent level-set approach presented in O. Bokanowski, A. Picarelli, H. Zidani, State-constrained stochastic optimal control problems via reachability approach, SIAM J. Control and Optim. 54 (5) (2016), we transform the original constrained problem in an auxiliary unconstrained one in augmented state and control spaces, obtained by introducing an exact penalization of the original state constraints. The latter problem is fully treatable by classical dynamic programming arguments. * Zoom link: please visit the webpage https://www.math.unipd.it/~bianchi/seminari/ Thanks for your attention and see you soon in Padova, Giorgia Callegaro -- Giorgia Callegaro Associate Professor Department of Mathematics - University of Padova Via Trieste 63 , I-35121 Padova - ITALY Tel: +39-0498271481 Fax: +39-0498271499 E-Mail: gcallega(a)math.unipd.it <https://webmail.math.unipd.it/horde3/imp/message.php?mailbox=Sent&index=598#> Personal web-page: https://sites.google.com/site/giogiocallegaro/Home

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Scouting Internazionale presso la Scuola IMT, Lucca
by Irene Crimaldi 13 Dec '21

13 Dec '21

Carissimi, scrivo per portare alla vostra attenzione lo scouting internazionale avviato dalla Scuola IMT nelle aree di Statistica, Econometria e Machine Learning. Vi prego di diffondere la notizia. Grazie. Cordiali saluti, Irene Crimaldi Statistica, Econometria, Machine Learning *Scadenza per la presentazione della manifestazione di interesse: 31 marzo 2022 ore 23:59 (ora italiana)* Candidature ideali sono quelle di studiosi con un solido background di ricerca a livello internazionale su temi di statistica, econometria o machine learning. La Scuola IMT è interessata a candidate/i con una eccellente produzione scientifica e una solida esperienza nello sviluppo di metodi statistici applicati all'analisi dei sistemi economici. La posizione fa parte di una serie di iniziative promosse dalla Scuola IMT per lo sviluppo strategico delle attività di data science con applicazioni in diversi domini e con il contributo di diversi ambiti disciplinari. Le candidate / i candidati devono possedere una consolidata esperienza nella conduzione di gruppi di ricerca, specifiche esperienze di insegnamento e supervisione studenti a livello dottorale, un'ampia produzione scientifica con chiara evidenza dei risultati sinora conseguiti e delle future prospettive. Tutte le attività della Scuola IMT, incluse le attività didattiche, sono condotte in lingua inglese. I potenziali candidati sono invitati a compilare il modulo on-line allegando: 1. un curriculum vitae con la lista delle pubblicazioni 2. una lettera di motivazione 3. tre nomi di esperti ai quali chiedere lettere di referenze.

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Seminar in Statistics LORENZO MASOERO
by Pierpaolo De Blasi 10 Dec '21

10 Dec '21

SEMINARS IN STATISTICS @ COLLEGIO CARLO ALBERTO <https://www.carloalberto.org/events/category/seminars/seminars-in-statistic…> Venerdi 17 Dicembre 2021, alle ore 12.00, presso il Collegio Carlo Alberto, in Piazza Arbarello 8, Torino, si terrà il seguente seminario: ------------------------------------------------ Speaker: *Lorenzo Masoero *(Amazon) Title: *Improved prediction and optimal sequencing strategies for genomic variant discovery via Bayesian nonparametrics* Abstract:Despite the advent of Big Data, data-gathering in many domains can still be an expensive process that necessitates careful planning when operating under a fixed, limited budget. For instance, sequencing new genomic data is a complex procedure that requires careful tuning: researchers can spend resources to sequence a greater number of genomes (quantity), or spend resources to sequence genomes with increased accuracy (quality). In this talk, I consider the common setting in which scientists have already conducted a pilot study to reveal variants in a genome and are contemplating a follow-up study. Spending additional resources has the potential to reveal new variations in the genome, and thereby new genetic insights. Therefore, practitioners are interested in (i) predicting how many new discoveries they will make under different experimental design choices. In turn, they can leverage these predictions to optimally allocate available resources in the design of a future experiment, e.g. (ii) to maximize the number of future discoveries or (iii) to optimize the usefulness of a future experiment for the task at hand, e.g. the power of an associated statistical test. I discuss novel methodologies to solve the problems mentioned above. Our approach relies on a Bayesian nonparametric formulation that facilitates (i) prediction for the number of new variants in the follow-up study based on the pilot study. We show empirically that, when experimental conditions are kept constant between the pilot and follow-up, our method's prediction is competitive with the best existing methods. Unlike current methods, though, our new method allows practitioners to change experimental conditions between the pilot and the follow-up. We demonstrate how this distinction allows our method to be used for more realistic predictions and for optimal allocation of a fixed budget between quality and quantity. In particular, we first show how, under a fixed budget, my predictions can be used to maximize (ii) the number of new genomic variants discovered in a follow-up study. Last, we show how our framework can guide practitioners in other experimental design problems, and specifically how to achieve (iii) the highest possible power in statistical tests in the context of rare variants association studies. ------------------------------------------------ In ottemperanza alle norme anti Covid, per partecipare in presenza è necessario prenotarsi tramite il seguente form online: https://forms.gle/jVPLoDCQ1ANSB5dg8 Sarà possibile seguire il seminario anche in streaming: Join Zoom Meeting <https://us02web.zoom.us/j/88971670320?pwd=VXFseHNlYm5EKzFmZ25oTGdlRWw4QT09> Meeting ID: 889 7167 0320 Passcode: 362208 Il seminario è organizzato dalla "de Castro" Statistics Initiative www.carloalberto.org/stats Cordiali saluti, Pierpaolo De Blasi --- University of Torino & Collegio Carlo Alberto carloalberto.org/pdeblasi <https://sites.google.com/a/carloalberto.org/pdeblasi/>

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(PMS)^2 online talk: Martin Huesmann (Dec 13, 5:30pm)
by Mario Maurelli 08 Dec '21

08 Dec '21

Dear colleagues, We are happy to announce the following online talk: Speaker: *Martin Huesmann* (Universität Münster) *Title*: A fluctuation result for the optimal matching problem *Abstract*: The optimal matching problem is one of the classical random optimization problems. While the asymptotic behavior of the expected cost is well understood only little is known for the asymptotic behavior of the optimal couplings - the solutions to the optimal matching problem. In this talk we show that at all mesoscopic scales the displacement under the optimal coupling converges in suitable Sobolev spaces to a Gaussian field which can be identified as the curl-free part of a vector Gaussian free field. Based on joint work with Michael Goldman. Date and time: *Monday December 13, 17:30-18:30* (Rome time zone) *Zoom link*: https://us02web.zoom.us/j/8342220461 This is a talk of the *(PMS)^2: Pavia-Milano Seminar series on Probability and Mathematical Statistics* organized jointly by the universities Milano-Bicocca, Pavia, Milano-Politecnico and Milano-Statale. For more information see the dedicated webpage: https://paviamilanoseminars.wordpress.com/ Participation is free and welcome! Best regards The organizers (Mario Maurelli, Carlo Orrieri, Maurizia Rossi, Margherita Zanella)

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4 Assistant Professorships + 1 Harrison position in Statistics @Warwick
by Massimiliano ... 08 Dec '21

08 Dec '21

Dear all, 4 assistant professorships (permanent with a 5 year probation) and 1 Harrison position(until October 2024) are available at the Department of Statistics, University of Warwick, seewww.warwick.ac.uk/statjob<http://www.warwick.ac.uk/statjobs>for more details. All applications close on January 9. For the Assistant professorships, we are particularly keen in making appointment in the following areas: * Applied Statistics * Data Science * Stochastic Finance but welcome applications across the spectrum of Probability and Statistics, broadly interpreted, seehttps://atsv7.wcn.co.uk/search_engine/jobs.cgi?owner=5062452&ownertype=fair&jcode=1880930&vt_template=1457&adminview=1 I'd appreciate if you could circulate this information around your networks, and encourage applications from talented early career researchers you are aware of. Feel free to get back to me if you have any questions. Best wishes, Massimiliano ------ Dr. Massimiliano Tamborrino Assistant Professor Department of Statistics University of Warwick https://warwick.ac.uk/tamborrino

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Reminder -- Online Quantitative Finance Seminars @SNS, December 10, 2021
by Giulia Livieri 07 Dec '21

07 Dec '21

Dear all, We would like to announce the following two Online Seminars @SNS: *December 10, 2021 at 3PM (CEST)* *Speaker: *Prof. Agostino Capponi (Columbia University) *Title: * The Adoption of Blockchain-based Decentralized Exchanges (joint work with Dr. Ruizhe Jia) *Abstract: *We show that the blockchain order execution mechanism and liquidity pooling create arbitrage rents in decentralized exchanges. The arbitrage rent raises the cost of liquidity provision and imposes negative externalities on users of the underlying blockchain. In equilibrium, automated market makers (AMMs) are adopted by liquidity providers only if exchange rates of token pairs are sufficiently stable. A pricing curve with higher curvature reduces arbitrage rents, but also decreases trading activities. We provide statistical support for our main model implications using transaction-level data of AMMs. *Link: * https://teams.microsoft.com/l/meetup-join/19%3ameeting_NjAyODk0YzQtNmVmYS00… We are looking forward to seeing you at the seminars! Best regards, Giulia

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Seminario Online :: Panaretos@DSS-Sapienza
by Pierpaolo Brutti 07 Dec '21

07 Dec '21

...ricevo e inoltro... --P ----------------------------------------------------------------------------- A v v i s o d i S e m i n a r i o O n l i n e ----------------------------------------------------------------------------- Venerdì 10 Dicembre, ore 12:00 ----------------------------------------------------------------------------- Zoom: [Link <https://uniroma1.zoom.us/j/86881977368?pwd=SWRFcVFjMDZTa0lXZk05TE1zNm5adz09>] [code: 432940] ----------------------------------------------------------------------------- VICTOR PANARETOS <http://smat-files.epfl.ch/victor/> (Ecole Polytecnique Federale de Lausanne) terrà un seminario dal titolo: TESTING FOR THE RANK OF A COVARIANCE KERNEL ----------------------------------------------------------------------------- Summary How can we discern whether the covariance of a stochastic process is of reduced rank, and if so, what its precise rank is? And how can we do so at a given level of confidence? This question is central to a great deal of methods for functional data, which require low-dimensional representations whether by functional PCA or other methods. The difficulty is that the determination is to be made on the basis of i.i.d. replications of the process observed discretely and with measurement error contamination. This adds a ridge to the empirical covariance, obfuscating the underlying dimension. We describe a matrix-completion inspired test statistic that circumvents this issue by measuring the best possible least square fit of the empirical covariance's off-diagonal elements, optimised over covariances of given finite rank. For a fixed grid of sufficiently large size, we determine the statistic's asymptotic null distribution as the number of replications grows. We then use it to construct a bootstrap implementation of a stepwise testing procedure controlling the family-wise error rate corresponding to the collection of hypotheses formalising the question at hand. Under minimal regularity assumptions we prove that the procedure is consistent and that its bootstrap implementation is valid. The procedure circumvents smoothing and associated smoothing parameters, is indifferent to measurement error heteroskedasticity, and does not assume a low-noise regime. Based on joint work with Anirvan Chakraborty. -----------------------------------------------------------------------------

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[MLfF] Program: 3rd One-Day International Workshop on MACHINE LEARNING FOR FINANCE
by Marco Corazza 06 Dec '21

06 Dec '21

Kind All, I'm glad to send you the program of the Remote *3rd One-Day International Workshop onMACHINE LEARNING FOR FINANCE* (*https://www.unive.it/data/agenda/3/55613 <https://www.unive.it/data/agenda/3/55613>*). For receiving the *Zoom address*, *ID* and *passcode*, it is necessary to communicate the email address of the attendee to corazza(a)unive.it. I hope to see you at the workshop! The warmest regards, Marco Corazza ***** ***** ***** MORNING ***** ***** ***** 08:50-09:00 - Openings 09:00-09:30 - He X., Cong L. W., Feng G., He J.: "Asset pricing with Panel Trees under global split criteria" 09:30-10:00 - Barbopoulos L. G., Dai R., Putniņš T., Saunders J. A.: "Market Efficiency in the age of Machine Learning" 10:00-10:30 - Caliciotti A., Corazza M., Fasano G.: "Regression models and Machine Learning approaches for Bitcoin price forecast" 10:30-11:00 - Kumar P.: "Deep Hawkes process for high-frequency market making" 11:00-11:15 - Break 11:15-11:45 - Al-Ameer A., Alshehri K.: "Conditional Value-at-Risk for quantitative trading: A Direct Reinforcement Learning approach" 11:45-12:15 - Carrillo Menéndez S., Hassani B.: "Expected Shortfall reliability – Added value of traditional statistics and advanced Artificial Intelligence for market risk measurement purposes" 12:15-12:45 - Daluiso R., Nastasi E., Pallavicini A., Polo S.: "Reinforcement Learning for options on target volatility funds" 12:45-13:15 - Dell’Era M.: "Local volatility and Hopfield Neural Network" 13:15-13:45 - Break ***** ***** ***** AFTERNOON ***** ***** ***** 13:45-14:15 - Goudenège L., Molent A., Zanette A.: "Moving average options: Machine Learning and Gauss-Hermite quadrature for a double non-Markovian problem" 14:15-14:45 - Jaydip S., Dutta A., Mehtab S.: "Portfolio optimization using Deep Learning models - A comparative study of risk-based portfolio design approaches" 14:45-15:15 - Lillo F., Livieri G., Marmi S., Solomko A., Vaienti S.: "Analysis of bank leverage via dynamical systems and deep neural networks" 15:15-15:45 - Scholz M.: "Forecast combinations for benchmarks of long-term stock returns using Machine Learning methods" 15:45-16:00 - Break 16:00-16:30 - Ameridad B., Cattaneo M., Luciano E., Kenett R.: "AI and Adversarial AI in insurance: Background, examples and future implications" 16:30-17:00 - Gnoatto A., Picarelli A., Reisinger C.: "Deep XVA Solver - A Neural Network based counterparty Credit Risk management framework" 17:00-17:30 - Mansouri S., Momtaz P. P.: "Financing sustainable entrepreneurship: ESG measurement, valuation, and performance in token offerings" 17:30-18:00 - Modina M., Zedda S.: "A quantitative identification and description of the default syndromes affecting the Italian SMEs" 18:00-18:10 - Closings -- Marco Corazza, Ph.D. Department of Economics - Ca' Foscari University of Venice San Giobbe, Cannaregio 873 - 30121 Venezia, Italy Mobile: (+39) 366 602-9134 Phone: (+39) 041 234-6921 Fax: (+39) 041 234-7444 E-mail: corazza(a)unive.it Editor-in-Chief: Mathematical Methods in Economics and Finance - www.unive.it/m2ef --

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Posizione da Assistant Professor in Statistics alla Luiss
by Marco Perone Pacifico 03 Dec '21

03 Dec '21

Care colleghe e colleghi, la Luiss ha pubblicato una "call for expression of interest" per una posizione da Assistant Professor in Statistics and Data Science (tutti i dettagli a questo link<https://www.luiss.edu/call-expression-interest-2021/assistant-professorship…>). La call rimarrà aperta fino a metà febbraio, ma le selezioni inizieranno a gennaio. Per chi fosse interessato, il consiglio è di inviare la domanda entro il 31 dicembre 2021. Un saluto, Marco Perone Pacifico Marco Perone Pacifico Professor of Statistics Department of Economics and Finance LUISS University Viale Romania 32 00197 Roma, ITALY La presente e-mail proviene da Luiss Guido Carli e s'intende inviata per scopi lavorativi. Tutte le informazioni ivi contenute, compresi eventuali allegati, sono da ritenersi esclusivamente confidenziali e riservati secondo i termini del vigente D.Lgs. 196/2003 in materia di privacy e del Regolamento europeo 679/2016 - GDPR. È vietato qualsiasi ulteriore utilizzo non autorizzato. Qualora la stessa Le fosse pervenuta per errore, La preghiamo di eliminarla immediatamente e di darcene tempestiva comunicazione. Grazie. This e-mail message is sent by Luiss Guido Carli for business purposes. All informations contained therein, including any attachments, are for the sole use of the intended recipient and may contain confidential and privileged information pursuant to Legislative Decree 196/2003 and the European General Data Protection Regulation 679/2016 - GDPR -. Any unauthorized review, use, disclosure or distribution is prohibited. If you are not the intended recipient, please contact the sender by soon reply this e-mail and destroy all copies of the original message. Thanks

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