Quant Radio: Smarter Equal Weighting Strategies

When investors think about a simple, effective way to diversify, the equal-weighted portfolio often comes to mind. It's the strategy of giving every stock the same level of investment—easy to understand, easy to implement, and surprisingly, often outperforming more complex methods like market cap weighting. But in this episode, we ask a bold question: can we make it even better?

Join us as we explore groundbreaking research from Saru and Walker that suggests we can improve on equal weighting—with just a few smart, straightforward tweaks. We'll dive into two practical enhancements: one that filters out recent underperformers (momentum-based) and another that removes stocks with poor long-term risk-adjusted returns (Sharpe ratio-based). Both strategies are built on simple rules, but deliver surprisingly strong historical results across global markets.

We’ll unpack how these enhancements work, the theoretical foundation behind them, and what the data shows in terms of return, volatility, and drawdown. But we don’t stop there. We also look at the real-world trade-offs—like increased turnover, tax implications, and the limitations of backtested results. You’ll walk away with a clearer understanding of how these modest changes to a classic portfolio strategy could yield meaningful improvements without resorting to overly complex solutions.

If you've ever wondered whether simplicity can still leave room for innovation, or if there's a smarter way to build on a solid foundation like equal weighting, this episode is for you. Discover how rethinking the basics might just unlock better performance.

Find the full research paper here: https://community.quantopian.com/c/community-forums/outperforming-equal-weighting-quantpedia

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Quant Radio is an AI-generated podcast, intended to help people develop their knowledge and skills in Quant finance. This podcast is not intended to provide investment advice.