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Author Shi, Feng, active 2019, author

Title Learn about the generalized autoregressive conditional heteroskedasticity (GARCH) model in R with data from the DJIA 30 stock time series (2018) / Feng Shi
Published London : SAGE Publications Ltd., 2019
Online access available from:
Sage Research Methods Datasets    View Resource Record  


Description 1 online resource : illustrations
Summary This dataset is designed for teaching the generalized autoregressive conditional heteroskedasticity (GARCH) model for a univariate time series. The dataset is a subset of data derived from the 2018 DJIA 30 Stock Time Series dataset, and the example examines the time series of daily closing price of the stock MMM from 2006 to 2017. The dataset file is accompanied by a Teaching Guide, a Student Guide, and a How-to Guide for R
Notes Description based on XML content
Subject GARCH model -- Study and teaching
R (Computer program language)
Time-series analysis
R (Computer program language)
Time-series analysis.
Form Electronic book
ISBN 1526487659