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GARCH Models in R

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Course Report - GARCH Models in R

Course Report

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Course Features

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Duration

4 hours

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Delivery Method

Online

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Available on

Limited Access

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Accessibility

Mobile, Desktop, Laptop

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Language

English

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Subtitles

English

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Level

Intermediate

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Teaching Type

Self Paced

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Video Content

4 hours

Course Description

Are you curious about the heartbeat of financial markets? Do you want to know when a market goes down? This course will help you balance risk and reward in financial decisions. The course gradually moves from the GARCH(1) standard model to more advanced volatility model that includes a leverage effect and GARCH in–mean specification. It also uses the skewed student t distribution for asset returns modeling. Portfolio optimization, rolling sampling evaluation, value-at-risk forecasting and study of dynamic covariances all have applications to stock and exchange rates return models.

Course Overview

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Virtual Labs

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International Faculty

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Post Course Interactions

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Hands-On Training,Instructor-Moderated Discussions

Skills You Will Gain

Prerequisites/Requirements

Manipulating Time Series Data with xts and zoo in R

Time Series Analysis in R

What You Will Learn

Specify and fit GARCH models to forecast time-varying volatility and value-at-risk

Course Instructors

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Kris Boudt

Professor of Finance and Econometrics at VUB and VUA

Kris Boudt is professor of finance and econometrics at Ghent University, Vrije Universiteit Brussel and Amsterdam. He teaches the courses "GARCH models in R" and "Introduction to portfolio analysis i...
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