df_financial

A dataset containing the S&amp;P 500 stock returns and the NFCI

datasets

Estimating GARCH-MIDAS (MIxed-DAta-Sampling) models (Engle, Ghysels, Sohn, 2013, <doi:10.1162/REST_a_00300>) and related statistical inference, accompanying the paper "Two are better than one: Volatility forecasting using multiplicative component GARCH models" by Conrad and Kleen (2020, <doi:10.1002/jae.2742>). The GARCH-MIDAS model decomposes the conditional variance of (daily) stock returns into a short- and long-term component, where the latter may depend on an exogenous covariate sampled at a lower frequency.

Onno Kleen

mfGARCH

Mixed-Frequency GARCH Models

df_financial function

A data frame with 11,306 rows and 5 variables:<dl class="dl-horizontal">
 <dt>date</dt><dd>date</dd>
 <dt>return</dt><dd>daily S&amp;P 500 log returns times 100</dd>
 <dt>rv</dt><dd>5-minute realized variances</dd>
 <dt>week</dt><dd>a dummy for each year/week combination</dd>
 <dt>nfci</dt><dd>National Financial Conditions Index</dd>
</dl>

Format

Stock returns and financial conditions. — df_financial

A data frame with 11,306 rows and 5 variables:<dl class='dl-horizontal'>
 <dt>date</dt><dd>date</dd>
 <dt>return</dt><dd>daily S&amp;P 500 log returns times 100</dd>
 <dt>rv</dt><dd>5-minute realized variances</dd>
 <dt>week</dt><dd>a dummy for each year/week combination</dd>
 <dt>nfci</dt><dd>National Financial Conditions Index</dd>
</dl>

df_financial: Stock returns and financial conditions.

Description

Usage

Arguments

Format