Wednesday Nov 13, 2024
Strategic Asset Allocation: The Long Game vs. The AI Advantage
Overview
Welcome to the latest episode, where we dive into "Strategic Asset Allocation". In this briefing, we’ll explore insights from two influential sources that reshape how we think about portfolio construction. First, we look at William J. Bernstein's "The Intelligent Asset Allocator," which critiques the widely cited "Brinson 93.6% Effect" and questions the real role of active management over time. Bernstein emphasizes the power of long-term asset allocation, showing that in the long haul, setting an equity exposure is key, while the search for market-timing alpha may often boil down to luck.
In contrast, Algo-Chain's "Algo-Driven ETF Portfolios" white paper presents a tech-forward approach, leveraging AI to dynamically adjust allocations in response to economic cycles. By blending AI with evidence-based investing, Algo-Chain’s strategy highlights the potential of ETFs and data-driven adjustments to navigate today’s fast-paced market landscape.
Whether you're dedicated to long-term strategy or intrigued by the possibilities of AI-driven allocation, this episode provides a valuable overview of asset allocation’s evolution and the exciting intersection of technology and investing. Tune in for a fresh perspective on building resilient portfolios in the modern era.
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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