Factors like 'value' don't get arbitraged away, despite being public knowledge, because of human behavior. These strategies can underperform for a decade or more, causing immense career risk and psychological pain. This difficulty in execution, not lack of knowledge, is why the edge persists.
Backtests and research from asset management firms that sell the related product are inherently biased. Similar to drug studies sponsored by pharmaceutical companies, the incentive is to create a favorable outcome. Investors should heavily discount such research and seek less biased evidence from sources like academic journals.
For most investors, alpha isn't about generating hedge-fund-level excess returns. Instead, it's about accessing unique strategies via ETFs that shape a portfolio beyond standard market-cap-weighted beta. This 'alpha for the rest of us' focuses on diversification and unique outcomes, not just beating the market.
When evaluating a backtest, investors should distrust any model that shows impressive returns without also revealing why the strategy is incredibly difficult to implement. A believable backtest must demonstrate the associated pain, such as long periods of underperformance or high career risk, which explains why the potential for future returns exists.
Many factor ETFs are 'closet indexers' that only slightly tilt a benchmark. A purer, academic approach builds concentrated portfolios (e.g., top 10% on momentum), creating high active share and true differentiation. This method risks severe, prolonged deviation from benchmarks, making it suitable only for investors with very long time horizons.