<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:content="http://purl.org/rss/1.0/modules/content/"><channel><title>Heat-Equation on Inflection Quant Lab</title><link>https://inflection-quant.pages.dev/tags/heat-equation/</link><description>Recent content in Heat-Equation on Inflection Quant Lab</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Tue, 09 Jun 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://inflection-quant.pages.dev/tags/heat-equation/index.xml" rel="self" type="application/rss+xml"/><item><title>Finite Difference Methods: Marching Forward or Solving Together</title><link>https://inflection-quant.pages.dev/articles/quant-foundations/fdm/</link><pubDate>Tue, 09 Jun 2026 00:00:00 +0000</pubDate><guid>https://inflection-quant.pages.dev/articles/quant-foundations/fdm/</guid><description>&lt;h2 id="why-this-matters"&gt;Why This Matters&lt;/h2&gt;
&lt;p&gt;A derivative price can be computed two equivalent ways: as a risk-neutral expectation, or as the solution of a PDE. This is the &lt;a href="../../articles/quant-foundations/feynman_kac/"&gt;Feynman-Kac result&lt;/a&gt;, which I explored in the earlier article. Monte Carlo is the natural way to handle the expectation, and the &lt;a href="../../articles/quant-foundations/mc_variance_reduction/"&gt;previous article&lt;/a&gt; worked through techniques for making it more efficient. Here I want to look at the other side, where the price is the solution of a PDE and we solve it on a grid.&lt;/p&gt;</description></item></channel></rss>