<div dir="ltr"><div class="gmail_quote"><div dir="ltr" class="gmail_attr"><b style="font-size:11pt;color:rgb(0,0,0);font-family:Calibri,sans-serif">From:</b><span style="font-size:11pt;color:rgb(0,0,0);font-family:Calibri,sans-serif"> Insper - Seminários Acadêmicos <</span><a href="mailto:seminariosacademicos@insper.edu.br" target="_blank" style="font-size:11pt;font-family:Calibri,sans-serif">seminariosacademicos@insper.edu.br</a><span style="font-size:11pt;color:rgb(0,0,0);font-family:Calibri,sans-serif">></span><br></div><div class="msg131380536250219562"><div dir="ltr"><div id="m_-4728177110973134979divRplyFwdMsg" dir="ltr"><font face="Calibri, sans-serif" style="font-size:11pt" color="#000000">
<b>Sent:</b> Tuesday, April 25, 2023 11:13 AM<br>
<b>To:</b> Insper - Seminários Acadêmicos <<a href="mailto:seminariosacademicos@insper.edu.br" target="_blank">seminariosacademicos@insper.edu.br</a>><br>
<b>Subject:</b> Academic Seminar of Data Science with Mariane Branco Alves of UFRJ - Online</font>
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<strong><span lang="EN-US" style="font-family:"Verdana",sans-serif;color:black">Title:</span></strong><b><span lang="EN-US" style="font-family:"Verdana",sans-serif;color:black"> </span></b><span lang="EN-US" style="font-family:"Verdana",sans-serif">Modelling
 stochastic volatilities via k-parametric Dynamic Generalized Linear Models: a sequential approach via Information Geometry</span></p>
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<span lang="EN-US">Joint work with Helio S. Migon, Silvaneo V. Santos Jr and Raíra Marotta.</span><b><span lang="EN-US" style="font-family:"Verdana",sans-serif;color:black"></span></b></p>
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<p style="line-height:18.0pt"><strong><span lang="EN-US" style="font-family:"Verdana",sans-serif;color:black">Speaker:</span></strong><span lang="EN-US" style="font-family:"Verdana",sans-serif;color:black"> <a href="http://www.im.ufrj.br/index.php/pt/ensino/pos-graduacao/pos-graduacao-do-im/cursos-lato-sensu/204-especializacao-em-ciencia-de-dados/corpo-docente/1585-mariane-branco-alves" target="_blank">
 Mariane Branco Alves</a></span></p>
<p style="line-height:18.0pt"><strong><span lang="EN-US" style="font-family:"Verdana",sans-serif;color:black">University:</span></strong><span lang="EN-US" style="font-family:"Verdana",sans-serif;color:black"> 
<a href="http://www.im.ufrj.br/index.php/pt/" target="_blank">UFRJ</a></span></p>
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<p style="text-align:justify;line-height:115%"><strong><span lang="EN-US" style="font-family:"Verdana",sans-serif">Abstract:</span></strong><span lang="EN-US" style="font-family:"Verdana",sans-serif;color:#414042"> </span><span lang="EN-US" style="font-family:"Verdana",sans-serif">
 Dynamic generalized linear models may be seen as an extension to dynamic linear models, accommodating non-Gaussian responses, and to generalized linear models, formally treating serial auto-correlation inherent to responses in the exponential family, observed
 through time. The Bayesian inference scheme does not have an analytical solution, and there are several numerical approximating proposals in the literature, many of them relying on Monte Carlo Markov Chain methods, with the burden of high computational cost
 and loss of temporal sequencing in the analysis. In this talk, a new approach based on information geometry, focusing on the k-parametric exponential family for uni or multivariate responses, will be presented. Among others, the proposed method accommodates
 multinomial responses on k=d+1 categories, gamma responses, univariate normal responses with dynamic predictive structure for the mean as well as for the precision parameter (k=2) and multivariate normal responses, which is a work in progress. One particular
 focus in this talk is the use of the dynamic gamma as well as uni and multivariate normal frameworks for marginal and joint modelling of returns, in the context of stochastic volatility models. As will be shown, the method preserves the sequential aspect of
 the Bayesian inferential procedure, producing real-time inference. Information geometry concepts such as the projection theorem and Kullback-Leibler divergence are used in the development of the method, placing it close to recent approaches of variational
 inference. The method is computationally efficient and flexible enough to quickly accommodate new patterns and information when strategically needed, favorably comparing to alternative approaches in the literature, preserving aspects of monitoring and intervention,
 which are usual in sequential analyzes.</span><span lang="EN-US"></span></p>
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<p><span style="font-size:10.5pt;font-family:"Verdana",sans-serif;color:black">May 4, 2023</span></p>
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<p><span style="font-size:10.5pt;font-family:"Verdana",sans-serif;color:black">12pm de São Paulo, Brasil (UTC/GMT -03:00)</span></p>
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<p><span lang="EN-US" style="font-size:10.5pt;font-family:"Verdana",sans-serif;color:black">The seminar will be streamed at
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<p><span style="font-size:8.5pt;font-family:"Verdana",sans-serif;color:#3a3a41">Rua Quatá, 300 - Vila Olímpia - São Paulo/SP - Brasil - CEP: 04546-042 | Tel: (11) 4504-2400</span><span></span></p>
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</div></div><br clear="all"><div><br></div><span class="gmail_signature_prefix">-- </span><br><div dir="ltr" class="gmail_signature" data-smartmail="gmail_signature"><div dir="ltr"><span style="color:rgb(0,0,0);font-family:Calibri,Arial,Helvetica,sans-serif,"Apple Color Emoji","Segoe UI Emoji",NotoColorEmoji,"Segoe UI Symbol","Android Emoji",EmojiSymbols;font-size:small">Hedibert Freitas Lopes, PhD</span><br style="color:rgb(0,0,0);font-family:Calibri,Arial,Helvetica,sans-serif,"Apple Color Emoji","Segoe UI Emoji",NotoColorEmoji,"Segoe UI Symbol","Android Emoji",EmojiSymbols;font-size:small"><span style="color:rgb(0,0,0);font-family:Calibri,Arial,Helvetica,sans-serif,"Apple Color Emoji","Segoe UI Emoji",NotoColorEmoji,"Segoe UI Symbol","Android Emoji",EmojiSymbols;font-size:small">Professor of Statistics and Econometrics</span><br style="color:rgb(0,0,0);font-family:Calibri,Arial,Helvetica,sans-serif,"Apple Color Emoji","Segoe UI Emoji",NotoColorEmoji,"Segoe UI Symbol","Android Emoji",EmojiSymbols;font-size:small"><span style="color:rgb(0,0,0);font-family:Calibri,Arial,Helvetica,sans-serif,"Apple Color Emoji","Segoe UI Emoji",NotoColorEmoji,"Segoe UI Symbol","Android Emoji",EmojiSymbols;font-size:small">INSPER - Institute of Education and Research</span><br style="color:rgb(0,0,0);font-family:Calibri,Arial,Helvetica,sans-serif,"Apple Color Emoji","Segoe UI Emoji",NotoColorEmoji,"Segoe UI Symbol","Android Emoji",EmojiSymbols;font-size:small"><span style="color:rgb(0,0,0);font-family:Calibri,Arial,Helvetica,sans-serif,"Apple Color Emoji","Segoe UI Emoji",NotoColorEmoji,"Segoe UI Symbol","Android Emoji",EmojiSymbols;font-size:small">Rua Quatá, 300 - São Paulo, SP 04546-042 Brazil</span><br style="color:rgb(0,0,0);font-family:Calibri,Arial,Helvetica,sans-serif,"Apple Color Emoji","Segoe UI Emoji",NotoColorEmoji,"Segoe UI Symbol","Android Emoji",EmojiSymbols;font-size:small"><span style="color:rgb(0,0,0);font-family:Calibri,Arial,Helvetica,sans-serif,"Apple Color Emoji","Segoe UI Emoji",NotoColorEmoji,"Segoe UI Symbol","Android Emoji",EmojiSymbols;font-size:small">Phone: +55 11 4504-2343</span><br style="color:rgb(0,0,0);font-family:Calibri,Arial,Helvetica,sans-serif,"Apple Color Emoji","Segoe UI Emoji",NotoColorEmoji,"Segoe UI Symbol","Android Emoji",EmojiSymbols;font-size:small"><span style="color:rgb(0,0,0);font-family:Calibri,Arial,Helvetica,sans-serif,"Apple Color Emoji","Segoe UI Emoji",NotoColorEmoji,"Segoe UI Symbol","Android Emoji",EmojiSymbols;font-size:small"><a href="http://www.hedibert.org" target="_blank">www.hedibert.org</a></span><br></div></div></div>