<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Alessio Di Paolo | Valerio Ficcadenti</title><link>https://valerioficcadenti.com/authors/alessio-di-paolo/</link><atom:link href="https://valerioficcadenti.com/authors/alessio-di-paolo/index.xml" rel="self" type="application/rss+xml"/><description>Alessio Di Paolo</description><generator>Hugo Blox Builder (https://hugoblox.com)</generator><language>en-us</language><image><url>https://valerioficcadenti.com/media/icon_huef8cf56cc73f48d41a5f1ecba5605ab4_269363_512x512_fill_lanczos_center_3.png</url><title>Alessio Di Paolo</title><link>https://valerioficcadenti.com/authors/alessio-di-paolo/</link></image><item><title>Rank-Size Analysis of Optimal Portfolio Weights Across Portfolio Optimization Models</title><link>https://valerioficcadenti.com/talks/euro_2025/</link><pubDate>Mon, 23 Jun 2025 00:00:00 +0000</pubDate><guid>https://valerioficcadenti.com/talks/euro_2025/</guid><description>&lt;p>&lt;strong>Event:&lt;/strong> &lt;a href="https://www.euro2025leeds.com/" target="_blank" rel="noopener">EURO 2025 - 32nd European Conference on Operational Research&lt;/a>&lt;br>
&lt;strong>Location:&lt;/strong> Leeds, United Kingdom&lt;br>
&lt;strong>Date:&lt;/strong> June 23-25, 2025&lt;/p>
&lt;hr>
&lt;p>This presentation introduces a novel rank-size analysis framework for comparing optimal portfolio weight distributions across different portfolio optimization models. The research provides innovative insights into portfolio concentration patterns and offers a systematic methodology for evaluating portfolio construction strategies.&lt;/p>
&lt;p>&lt;strong>Key Contributions:&lt;/strong>&lt;/p>
&lt;ul>
&lt;li>Novel rank-size analysis approach for portfolio optimization&lt;/li>
&lt;li>Comparative analysis of four portfolio strategies (Mean-Variance, CVaR, Most Diversified, Risk Parity)&lt;/li>
&lt;li>Stochastic dominance methodology for model selection&lt;/li>
&lt;li>Empirical analysis across major financial indices (2009-2023)&lt;/li>
&lt;/ul>
&lt;p>&lt;strong>Methodology:&lt;/strong>
The study employs various rank-size functions including the Exponential Law, Discrete Generalised Beta Distribution, and the Universal Law to model optimal weight distributions, with a robust selection methodology based on stochastic dominance applied to RMSE distributions.&lt;/p>
&lt;p>&lt;strong>Collaborative Research:&lt;/strong>
This work represents a collaborative effort with researchers from Roma Tre University (Italy) and other international institutions, showcasing the international scope of the research collaboration.&lt;/p>
&lt;p>&lt;strong>Presentation Materials:&lt;/strong>
Full presentation slides available for download (PDF format), including comprehensive data visualizations and empirical analysis results across multiple financial indices.&lt;/p></description></item><item><title>Alessio Di Paolo</title><link>https://valerioficcadenti.com/authors/alessio-di-paolo/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://valerioficcadenti.com/authors/alessio-di-paolo/</guid><description/></item></channel></rss>