Overview

Ever wonder how data science can help streamline and optimize your investment portfolio? In this episode, we’re diving into the world of clustering algorithms and how they can transform Model Portfolio management. We break down key concepts from a fascinating presentation on machine learning and financial engineering—making them accessible for Wealth Managers

You’ll discover:

• Clustering techniques that group similar investments, helping to identify trends and manage risk.
• The role of dissimilarity measures in understanding which investments go well together—and which don’t.
• A rundown of popular algorithms like K-means, hierarchical clustering, and mixture models, and how they can enhance portfolio diversification.

We even touch on multidimensional scaling, a cool visualization tool that makes complex data a bit easier to digest.

If you are curious about data-driven finance, this episode will open up new perspectives on portfolio management. Don’t miss it—tune in now and take a step toward a smarter, more optimized investment strategy!

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This podcast has been provided as part of Algo-Chain's Model Portfolio Masterclass Series.

Presented over a number of weeks by the co-founders of Algo-Chain, Allan Lane, Ph.D & Irene Bauer, Ph.D, this series aims to share their many years of hands-on experience with Wealth Managers & Financial Advisors who are looking to offer their own suite of Model Portfolios.

Covering everything from portfolio construction using ETFs, to the more ambitious goal of actively managing an optimized portfolio using trading signals.

Our goal is to help you deliver top quartile performance.

Access Algo-Chain's landing page to learn more about our we are using AI assisted ETF search to deliver top quartile returns.

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