Cari colleghi,
vi segnalo che il Dipartimento di Matematica dell'Università di Padova
ha bandito un posto di ricercatore di tipo B nel settore MAT/06.
Il bando è disponibile alla pagina
http://www.math.unipd.it/it/news/?id=1898
La scadenza per la presentazione delle domande è il 25 agosto 2016.
Marco Ferrante
_First Call for Papers_
*Joint EUROPEAN CONFERENCE ON STOCHASTIC OPTIMIZATION and COMPUTATIONAL
MANAGEMENT SCIENCE Conference
*
*7-9 July 2021, Venice, Italy*
The organizers are delighted to invite you to ECSO – CMS 2021 that will
be held in Venice, Italy, 7-9 July 2021, at the Department of Economics
- Ca’ Foscari University of Venice, in the San Giobbe Economics Campus.
/This is the rescheduled event for the Conference ECSO – CMS 2020,
suspended due to the COVID -19 pandemic emergency. We are planning to
organize the conference in presence in 2021./
ECSO - CMS 2021 is jointly organized by the Department of Economics of
Ca’ Foscari University of Venice, the CMS Journal and the EURO Working
Group on Stochastic Optimization.
ECSO 2021 is the 3rd edition of a stream of conferences organized by the
EURO Working Group on Stochastic Optimization (EWGSO). The previous
editions were held in Paris (2014) and Rome (2017). The scope of the
conference is to bring together researchers and professionals in
Stochastic Optimization and its applications in different fields spacing
from economics and finance to supply chain, logistics, etc.
CMS 2021 is the 17th edition of an annual meeting associated with the
journal of Computational Management Science published by Springer. The
aim of the conference is to provide a forum for theoreticians and
practitioners from academia and industry to exchange knowledge, ideas
and results in a broad range of topics relevant to the theory and
practice of computational methods in management science.
This joint event will provide a forum for fruitful discussions and
interactions among researchers and professionals from industry and
institutional sectors on decision making under uncertainty in a complex
world.The conference will be within the scopes of both CMS and EWGSO
and, in particular, it will focus on models, methods and computational
tools in stochastic, robust and distributionally robust optimization and
on computational aspects of management science with emphasis on risk
management, valuation problems, measurement applications. Traditional
fields of application, such as finance, energy, water management,
logistics, supply chain management, and emerging ones, such as
healthcare, climate risk and sustainable development, will be included.
VENUE: Department of Economics, Ca’ Foscari University of Venice
San Giobbe Campus – Cannaregio 873, 30121 Venice, Italy
Webpage: www.unive.it/ecsocms2021 <http://www.unive.it/ecsocms2021>
Conference Secretariat: ecsocms2021(a)unive.it
Conference hashtag: #ecsocms2021
IMPORTANT DATES
Abstract submission: *March 31, 2021*
Notification of acceptance: *April 20, 2021*
Early registration: *April 30, 2021*
Conference: J*uly 7-9, 2021*
CONFIRMED INVITED SPEAKERS
DARINKA DENTCHEVA, Stevens Institute of Technology (USA)
DAVID MORTON, Northwestern University (USA)
GAH-YI BAN, University of Maryland (USA)
DANIEL KUHN, École polytechnique fédérale de Lausanne (CH)
GIORGIO CONSIGLI, Università di Bergamo (I)
A *prize for the student best paper* will be awarded. Papers should be
nominated via e-mail by the students’ supervisors
(ecsocms2021(a)unive.it). *Deadline for the submissions to the prize is
May 15.* The program will include a devoted session for presenting the
best papers to compete for the prize, such that the jury could make the
final choice. The paper does not have to be published. The papers should
be principally authored by the student, but co-authors are permitted as
long as their contributions are clarified. Only registered participants’
papers will be considered for the prize.
Jury for the Student Best Paper Prize: Stein-Erik Fleten (NTNU Norwegian
University of Science and Technology), Milos Kopa (Charles University of
Prague), Francesca Maggioni (University of Bergamo), Ruediger Schultz
(University Duisburg-Essen).
We are looking forward to seeing you in Venice.
Best Regards,
Diana Barro, Stein-Erik Fleten and Martina Nardon
Organizing and Program Committee Chairs
--------------------------------------
Dr. Martina Nardon
Dipartimento di Economia
Università Ca' Foscari Venezia
San Giobbe - Cannaregio, 873
30121 Venezia, Italy
tel. +39 041 234 7413
--------------------------------------
Dear all,
This is a reminder for the: STAR Online Seminars.
The seminar will be held Friday 13. November from 11:00-12:00 . You will recieve the link for the Zoom room by registering for the seminar with the link provided at the end of this mail. The lecture will last for 45 minutes + questions.
This week's speaker is Rama Cont - University of Oxford, with the seminar: Excursion risk
Abstract: A broad class of dynamic trading strategies may be characterized in terms of excursions of the market price of a portfolio away from a reference level. We propose a mathematical framework for the risk analysis of such strategies, based on a description in terms of price excursions, first in a pathwise setting, without probabilistic assumptions, then in a probabilistic setting, when the price is modelled as a Markov process. We introduce the notion of δ-excursion, defined as a path which deviates by δ from a reference level before returning to this level. We show that every continuous path has a unique decomposition into such δ-excursions, which turn out to be useful for the scenario analysis of dynamic trading strategies, leading to simple expressions for the number of trades, realized profit, maximum loss and drawdown. When the underlying asset follows a Markov process, we combine these results with Ito's excursion theory to obtain a tractable decomposition of the process as a concatenation of independent δ-excursions, whose distribution is described in terms of Ito's excursion measure. We provide analytical results for linear diffusions and give new examples of stochastic processes for flexible and tractable modeling of excursions. Finally, we describe a non-parametric scenario simulation method for generating paths whose excursions match those observed in a data set. This is joint work with: Anna Ananova and RenYuan Xu.
After the end of the seminar, you are invited to bring a cup of coffee/tea and have a chat in our Coffee in the Stars here you will have the chance to talk and interact with the other persons that attended the seminar, and have a digital "coffee break".
We are looking forward to see you, online!
Best regards,
We are looking forward to see you, online!
Best regards,
Michele Giordano
Doctoral research fellow
Department of Mathematics
University of Oslo, Norway
-------------------------------------------------------------------------
Register for the seminar: https://nettskjema.no/a/159180
Link for the seminar webpage: https://www.mn.uio.no/math/english/research/projects/storm/events/seminars/…
(aggiungo che il sito del master è https://md2sl.imtlucca.it/)
-------- Messaggio Inoltrato --------
Oggetto: Borse di studio per Master Data Science and Statistical
Learning (MD2SL)
Data: Thu, 24 Dec 2020 10:03:30 +0100
Mittente: datascience(a)unifi.it
Organizzazione: Universita' degli Studi di Firenze
A: datascience(a)unifi.it
Cari tutti,
vi segnaliamo che è stato pubblicato il bando di selezione per il
conferimento di *due Borse di Studio* finalizzate all'iscrizione al
*Master di II livello in Data Science and Statistical Learning (MD2SL)*,
promosso dal Florence Center for Data Science, attraverso il
Dipartimento di Statistica, Informatica, Applicazioni (DISIA) "G.
Parenti" dell'Università degli Studi di Firenze, e dalla Scuola IMT Alti
Studi Lucca.
Il bando e ulteriori dettagli sono disponibili al seguente link:
https://www.disia.unifi.it/upload/sub/didattica/master/disia_Bando_Borse_Ma…
<https://www.disia.unifi.it/upload/sub/didattica/master/disia_Bando_Borse_Ma…>,
e sul sito del Florence Center for Data Science, tra le News:
https://datascience.unifi.it/index.php/news/
<https://datascience.unifi.it/index.php/news/>.
Scadenza per la presentazione delle domande: 14/01/2021 ore 13.00.
Vi chiediamo gentilmente di diffondere l'annuncio tra i potenziali
interessati.
Grazie,
Cordiali Saluti,
Florence Center for Data Science
Inoltro a tutti gli interessati il seguente annuncio (la posizione è quella
attualmente occupata da Wolfgang Woess).
********************************************************************************
Full professor "Discrete Mathematics and Probability", TU Graz
TU Graz is looking to appoint a tenured full professor of Discrete
Mathematics and Probability, starting October 2022. We are looking for a
highly qualified individual of international standing who has an excellent
research profile and is committed to represent the intersection of
Discrete Mathematics and Probability in both teaching and research.
For more information please see the web apge
https://www.tugraz.at/go/professorships-vacancies. Applications must be
sent to the email address bewerbungen.mpug(a)tugraz.at no later than March
31, 2021.
---------------------------------------------------------------------
Johannes Wallner Tel (+43) 316 873 8440
Institut fuer Geometrie der TU Graz,
Kopernikusgasse 24, 8010 Graz.
j.wallner(a)tugraz.at http://www.geometrie.tugraz.at/wallner
--------------------------------- ------------------------------------
WEBINARS IN STATISTICS @ COLLEGIO CARLO ALBERTO
<https://www.carloalberto.org/events/category/seminars/seminars-in-statistic…>
Joint initiative with
MIDAS COMPLEX MODELING RESEARCH NETWORK <http://midas.mat.uc.cl/network>
Giovedi 17 Dicembre 2020, alle ore 17:00, si terrà il seguente webinar:
------------------------------------------------
Speaker: *David Rossell *(Universitat Pompeu Fabra, Barcelona, Spain)
Title: *Approximate Laplace approximation*
Zoom link:
https://us02web.zoom.us/j/84312531120?pwd=VVJraStLVkR2M0w0ZXZnU3M0MFp2UT09
<https://us02web.zoom.us/j/88252069649?pwd=V2Z3b1UrZVVWNWZ4OXhydUtIakxpUT09>
Meeting ID: 843 1253 1120
Passcode: 105560
Abstract:
Bayesian model selection requires an integration exercise in order to
assign posterior model probabilities to each candidate model. The
computation becomes cumbersome when the integral has no closed-form,
particularly when the sample size is large, or the number of models is
large. We present a simple yet powerful idea based on the Laplace
approximation (LA) to an integral. LA uses a quadratic Taylor expansion at
the mode of the integrand and is typically quite accurate, but requires
cumbersome likelihood evaluations (for large n) an optimization (for large
p). We propose the approximate Laplace approximation (ALA), which uses an
Taylor expansion at the null parameter value. ALA brings very significant
speed-ups by avoiding optimizations altogether, and evaluating likelihoods
via sufficient statistics. ALA is an approximate inference method equipped
with strong model selection properties in the family of non-linear GLMs,
attaining comparable rates to exact computation. When (inevitably) the
model is misspecified the ALA rates can actually be faster than for exact
computation, depending on the type of misspecification. We show examples in
non-linear Gaussian regression with non-local priors, for which no
closed-form integral exists, as well as non-linear logistic, Poisson and
survival regression.
------------------------------------------------
Il webinar è organizzato dalla "de Castro" Statistics Initiative
www.carloalberto.org/stats
in collaborazione con il Collegio Carlo Alberto e rientra nel Complex Data
Modeling Research Network
midas.mat.uc.cl/network
Cordiali saluti,
Pierpaolo De Blasi
---
University of Torino & Collegio Carlo Alberto
carloalberto.org/pdeblasi
<https://sites.google.com/a/carloalberto.org/pdeblasi/>