This Posting has expired.
See www.inomics.com for latest entries.

Bayesian Modelling for Multivariate (Large) Time Series Analysis

Date of Appearance: 
Mar 13, 2017
Duration of the course: 
May 29, 2017 to Jun 1, 2017
Application Deadline: 
Apr 18, 2017

Bayesian Modelling for Multivariate (Large) Time Series Analysis

Date of Appearance: 
Mar 13, 2017
Duration of the course: 
May 29, 2017 to Jun 1, 2017
Application Deadline: 
Apr 18, 2017
Center for Operations Research and Econometrics (CORE), Université catholique de Louvain
0
0 Reviews

Course Details

Summer Schools
Credits or certification after course completion: 
3 ECTS
Study Options: 
Full-Time

Course Fees

Regular Fee: 
€500,00
International Student Fee: 
€200,00

Location of Course

Location: 
1348 Louvain-la-Neuve
Belgium

CEMS PhD course on Bayesian Dynamic Modelling for Multivariate Time Series Analysis

By Prof. Mike West (Duke University)
May 29th-June 1st , 2017 at UCLouvain Louvain-La Neuve

Abstract

This short-course covers principles and methodology of Bayesian dynamic modelling, with a main focus on methodology for multivariate time series analysis and forecasting. Following introductory conceptual and perspective development in univariate settings, the course works through a series of contexts of multivariate dynamic modelling for multiple time series. Key model developments and examples involve analysis, inference and forecasting in financial and econometric contexts, including Bayesian decision analysis overlaying modelling and computational methodology. Several examples are drawn from these areas, while others exemplify use of this range of models in other fields. The course includes recent modelling and methodological developments in multivariate time series and forecasting, and contacts current research frontiers.

Topics

  1. Brief Overview of Bayesian Dynamic Modelling and Forecasting
  2. Multivariate Time Series: Common Components, Multivariate Volatility
  3. Dynamic Latent Factor Models
  4. Dynamic Graphical Models
  5. Simultaneous Dynamic Graphical Models
  6. Dynamic sparsity via latent thresholding– in economic and financial forecasting and decisions

More info on the content here. 

Registration is mandatory / by May the 1st 2017

  • Members of the organizing institutions : free
  • Academics & PhD students : 200 Euro
  • Other : 500 Euro
  • Please transfer the money to: Banque Belfius - 44, Boulevard Pachéco - B 1000 Bruxelles, Account number: 091-0015728-43, 
    Account holder: UCLouvain, IBAN : BE66.0910.0157.2843, BIC (SWIFT) : GKCCBEBB. With communication: 41.11000.031 + "Mike West"

Registration includes access to course, course material, coffee breaks and lunches

 

Course Instructors/Professors:

  • Mike West (Duke University)

More information

Follow us

Become an INOMICS Fan on Facebook  Follow inomics on Twitter  LinkedIn  googlePlus  Stay Informed Email List

Copyright © 1998-2017 INOMICS. All rights reserved.

Login

or
×

Switch on your career radar!

Get started for free.

or
Sign Up with e-mail

×

×