Talk Your Book: How to Eliminate Negative Alpha

Episode Summary

Executive Summary: Cole Wilcox of Longboard Asset Management argues that trend-following works best as a disciplined, rules-based way to capture market winners and avoid losers, especially in U.S. small- and mid-cap stocks where the power-law distribution is strongest. The conversation covers why systematic investing reduces emotional mistakes, how their strategy adapts to volatility, when it de-risks to Treasury bills, and how advisors can use the fund as a diversified alternative sleeve.

Main Topics: Why trend-following is systematic, not predictive: Wilcox explains that trend-following does not forecast winners; it removes emotion and uses rules to hold winners and cut losers as trends unfold. Power-law returns and stock market dispersion: The discussion centers on the idea that a small minority of stocks drive most market gains, making disciplined winner selection and loser avoidance crucial. Longboard’s stock-level implementation: Unlike multi-asset managed futures, Longboard applies trend-following to individual U.S. stocks, primarily within the Russell 2500 universe. Volatility management and drawdowns: Wilcox describes how the strategy gives winners room to run, adapts stop levels to volatility, and can shift heavily into Treasury bills during crises. Positioning within alternative investments: The fund is framed as part of an alternative sleeve for advisors, aiming to improve diversification without sacrificing all equity upside. Limits of managed futures marketing: Wilcox says managed futures are often oversold as a crisis hedge, arguing they are better understood as a low-correlation diversifier than a reliable short-term hedge. Benchmarking and investor expectations: He says the appropriate benchmark is the Russell universe, not the S&P 500, and that the strategy should be judged on return, volatility, and correlation together.

Key Arguments: Trend-following works because it uses a systematic process to stay with winners and exit losers, reducing behavioral mistakes rather than predicting the future. Market returns are power-law distributed: a small fraction of stocks create most of the gains, so avoiding weak names is as important as finding strong ones. Longboard’s approach is differentiated by applying trend-following to the full Russell 2500 stock universe instead of futures, asset-allocation switches, or a handful of names. Small- and mid-cap stocks are the most fertile ground for multi-baggers, so the strategy focuses there while still owning some large caps. The biggest source of alpha is eliminating losers and performance drag from low-quality stocks. Big winning stocks can suffer very large drawdowns, so the system must be patient and use volatility-adjusted exits rather than rigid sell rules. During crises, the strategy seeks stability in short-term Treasury bills rather than gold or other supposedly uncorrelated assets. There has been no observed deterioration in stock-level trend-following efficacy, though managed futures faced a difficult 2010s due to macro conditions and central-bank intervention. The strategy should be measured against the Russell, where it has aimed to match or exceed returns with lower volatility, lower beta, and lower correlation. Managed futures are better described as a low-correlation strategy than a dependable hedge; expectations should match that reality.

Data Points: Years in business: 25 years - Wilcox says Longboard has been doing this work for a quarter century. Internal strategy research began: 2005 - He said their in-house strategy development started in 2005. Pioneering research publication window: 2005 to 2007 - Wilcox referenced the period when they published early research. Stock universe: Russell 2500 - Their strategy analyzes the entire Russell 2500 index of U.S. companies. Alternative sleeve focus: Third leg of the portfolio - He defined alts as something beyond stocks and bonds used to diversify portfolios. Large-cap allocation: About 10% - Wilcox said roughly 90% of the portfolio is small- and mid-cap exposure and 10% is large cap. Beta to market: About 0.45 - He described the strategy’s long-term beta versus the S&P 500. Correlation to market: About 0.5 to 0.55 - He gave an average long-term correlation range versus the S&P 500. Current portfolio cash: About 25% cash / 75% invested - Wilcox mentioned the portfolio composition at the time of the interview. Current portfolio holdings: About 700 positions - He cited the approximate number of positions held currently. Average hold time: Multiple years - Highly profitable positions are typically held for years. Largest winning-stock drawdown cited: About 50% - He referenced research on the average drawdown suffered by the biggest winners over the prior decade. Worst-quarter example period: First quarter of 2020 - He noted that the Russell 2000 had a very severe decline during COVID. Maximum cash/T-bill holding in 2022: About 50% - He said the strategy got to roughly half cash/T-bills at the peak risk-off point in 2022. Crisis de-risking examples: 2008, 1987 - He said those events would have triggered full or near-full de-risking. Top-20 alt funds ranking: Third highest nominal rate of return - Wilcox said the fund ranks near the top of alt peers on nominal return.

Pivotal Quotes: "Trend following doesn't have a predictive advantage. It doesn't know which companies are going to be winners and losers, but it does have the advantage of a systematic process of holding your winners and folding your losers as markets kind of evolve and play out." — Cole Wilcox: Explaining the core edge of trend-following and why it works despite not forecasting outcomes. "The biggest source of alpha is taking out, you know, the losers." — Cole Wilcox: Discussing why avoiding weak stocks matters as much as capturing strong ones. "We want our cake and eat it too" — Cole Wilcox: Describing the goal of downside protection without sacrificing full upside participation in bull markets.

Implications: For investors and advisors, the message is to judge trend-following as a disciplined diversification tool, not a magic hedge. The best use case is as part of an alternatives sleeve, with realistic expectations about drawdowns, correlation, and benchmark choice.