<?xml version="1.0" encoding="UTF-8"?><oembed><type>video</type><version>1.0</version><html>&lt;iframe src=&quot;https://www.loom.com/embed/ab5f2688955a4b8e8b04945c45aa1bf3&quot; frameborder=&quot;0&quot; width=&quot;1670&quot; height=&quot;1252&quot; webkitallowfullscreen mozallowfullscreen allowfullscreen&gt;&lt;/iframe&gt;</html><height>1252</height><width>1670</width><provider_name>Loom</provider_name><provider_url>https://www.loom.com</provider_url><thumbnail_height>1252</thumbnail_height><thumbnail_width>1670</thumbnail_width><thumbnail_url>https://cdn.loom.com/sessions/thumbnails/ab5f2688955a4b8e8b04945c45aa1bf3-766cdde3536ae102.gif</thumbnail_url><duration>1910.18</duration><title>Convexity and uniqueness of optimizers (ECON2125/6012 week 8)</title><description>In this video, I delve into the concepts of convexity and concavity in mathematical functions, explaining their significance in optimization problems. I provide examples to illustrate these concepts, including the properties of convex sets and the implications for functions. I also touch on the importance of first and second order conditions in determining local maxima and minima. Please take a moment to review the examples and let me know if you have any questions!</description></oembed>