<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Volatility on Viet Hung Vu</title><link>https://viethungvu1998.github.io/tags/volatility/</link><description>Recent content in Volatility on Viet Hung Vu</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Sun, 31 May 2026 09:00:00 +1000</lastBuildDate><atom:link href="https://viethungvu1998.github.io/tags/volatility/index.xml" rel="self" type="application/rss+xml"/><item><title>Volatility and Risk Notes</title><link>https://viethungvu1998.github.io/posts/volatility-risk-notes/</link><pubDate>Sun, 31 May 2026 09:00:00 +1000</pubDate><guid>https://viethungvu1998.github.io/posts/volatility-risk-notes/</guid><description>&lt;p&gt;Volatility is both a modeling target and a practical risk signal.&lt;/p&gt;
&lt;p&gt;In a research workflow, I care less about finding a single perfect volatility model and more about comparing forecasts under consistent assumptions. Realized volatility, historical volatility, GARCH-style models, and machine learning forecasts should be evaluated on the same data splits and loss functions.&lt;/p&gt;</description></item></channel></rss>