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<!DOCTYPE html>
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<title>MSGARCH | MSGARCH GSOC project</title>
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<a id="forkme_banner" href="/~https://github.com/keblu/MSGARCH">View on GitHub</a>
<h1 id="project_title">Markov-switching GARCH models in R</h1>
</header>
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<section id="main_content" class="inner">
<center>
<img src="/~https://github.com/keblu/MSGARCH/blob/master/hexmsgarch_large.png?raw=true" width="50%" height="50% align="middle" style="border:none;background:none;">
</center>
<p><a href="https://cran.r-project.org/package=MSGARCH"><img src="http://www.r-pkg.org/badges/version/MSGARCH" alt="CRAN" /></a> <a href="http://www.r-pkg.org/pkg/MSGARCH"><img src="http://cranlogs.r-pkg.org/badges/MSGARCH?color=brightgreen" alt="Downloads" /></a><a href="http://www.r-pkg.org/pkg/MSGARCH"><img src="http://cranlogs.r-pkg.org/badges/grand-total/MSGARCH?color=brightgreen" alt="Downloads" /></a>
<h2 id="introduction">Introduction</h2>
<p align="justify">Markov-switching GARCH models have become popular to account for regime changes
in the conditional variance dynamics of financial time series.
The R package <code class="highlighter-rouge">MSGARCH</code> (<a href="http://doi.org/10.18637/jss.v091.i04">Ardia et al., 2019</a>)
implements Markov-switching GARCH-type models very efficiently by using C++ object-oriented programming techniques.
It allows the user to perform simulations as well as Maximum Likelihood and MCMC/Bayesian estimations of a very large class of Markov-switching GARCH-type models. The package also provides methods to make single-step and multi-step ahead forecasts of the complete conditional density of the variable of interest. Risk management tools to estimate conditional volatility, Value-at-Risk and Expected Shortfall are also available.</p>
<div style="text-align:center">
<iframe width="560" height="315" src="https://www.youtube.com/embed/h2pCpMYBIZQ" frameborder="0" allow="autoplay; encrypted-media" allowfullscreen></iframe>
</div>
<h2 id="installation">Installation</h2>
<p>The latest stable version of <code class="highlighter-rouge">MSGARCH</code> is available on <a href=https://CRAN.R-project.org/package=MSGARCH>CRAN</a> and can be installed via:</p>
<div class="highlighter-rouge"><pre class="highlight"><code> R > install.packages("MSGARCH")
</code></pre>
</div>
<p>To install the latest development version of <code class="highlighter-rouge">MSGARCH</code> (which may contain bugs!) use these lines:</p>
<div class="highlighter-rouge"><pre class="highlight"><code> R > install.packages("devtools")
R > require("devtools")
R > devtools::install_github("keblu/MSGARCH", subdir="Package")
</code></pre>
</div>
<h2 id="references">References</h2>
<p>Please cite <code class="highlighter-rouge">MSGARCH</code> in publications:</p>
<p>Ardia, D., Bluteau, K., Boudt, K., Catania, L., Trottier, D.-A. (2019).<br />
<em>Markov-switching GARCH models in R: The MSGARCH package</em>.<br />
Journal of Statistical Software, Vol 91, Issue 4, pp. 1-38.<br />
<a href=http://doi.org/10.18637/jss.v091.i04>http://doi.org/10.18637/jss.v091.i04</a></p>
<p>Ardia, D., Bluteau, K., Boudt, K., Catania, L. (2018). <br />
<em>Forecasting risk with Markov-switching GARCH models: A large-scale performance study</em>. <br />
International Journal of Forecasting, Vol 34, Issue 4, pp. 733-747.<br />
<a href=https://doi.org/10.1016/j.ijforecast.2018.05.004>https://doi.org/10.1016/j.ijforecast.2018.05.004</a></p>
<p>Ardia, D., Bluteau, K., Ruede, M. (2019). <br />
<em>Regime changes in Bitcoin GARCH volatility dynamics</em>. <br />
Finance Research Letters, Vol 29, pp. 266-271. <br />
<a href=https://doi.org/10.1016/j.frl.2018.08.009>https://doi.org/10.1016/j.frl.2018.08.009</a></p> </p>
<h2 id="references">Core Team</h2>
<div style="clear: both">
<div>
<a href="https://www.hec.ca/profs/david.ardia.html">
<h4>David Ardia (HEC Montréal)</h4>
</a>
</div>
</div>
<div style="clear: both">
<div>
<a href="http://www.kevenbluteau.com">
<h4>Keven Bluteau (University of Neuchâtel)</h4>
</a>
</div>
</div>
<div style="clear: both">
<div>
<a href="https://www.linkedin.com/in/kris-boudt-44b20313/">
<h4>Kris Boudt (Ghent University, VUB, VUA)</h4>
</a>
</div>
</div>
<div style="clear: both">
<div>
<a href="https://www.linkedin.com/in/leopoldo-catania-1a515061/">
<h4>Leopoldo Catania (Aarhus University)</h4>
</a>
</div>
</div>
</section>
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<p class="copyright">MSGARCH maintained by <a href="/~https://github.com/keblu">Keven Bluteau</a></p>
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