Episode Summary
Executive Summary: Meb Faber and co-host Jeff discuss why popular investing styles cycle in and out of favor, arguing that value, smart beta, momentum, commodities, and passive/active debates are best viewed through long-term history, behavioral biases, and implementation discipline rather than recent performance. They stress common-sense backtesting, avoiding performance chasing, and recognizing that real wealth is usually built through concentrated ownership or entrepreneurship, while diversified portfolios mainly preserve wealth over time.
Main Topics: Style Cycles, Value Investing, and Mean Reversion: They debate claims that value investing is "dead," arguing that style underperformance is normal and often temporary. The discussion emphasizes factor rotations, crowding, and the possibility that value can recover even after long periods of lagging the market. Passive vs Active and Smart Beta: They react to Burton Malkiel's shift toward acknowledging active inefficiency exploitation and discuss smart beta, robo-advisors, and the tension between market-cap indexing and factor-based alternatives. The hosts are skeptical of marketing pivots but supportive of evidence-based improvements. Backtesting, Data Integrity, and Common Sense: A major theme is how to interpret backtests responsibly: historical context matters, survivorship bias and overfitting invalidate weak research, and large drawdowns are often larger than modeled. Backtests should inform judgment, not replace it. Momentum, Trend Following, and Behavioral Biases: They distinguish performance chasing from rules-based momentum/trend following, arguing that disciplined entry/exit rules and overlays can help exploit investor behavior. They also discuss parameter stability and why blended trend signals can be more robust than a single moving average. Commodities, Gold, and Inflation Hedges: The conversation covers why commodities can be useful diversifiers despite long-term drag, especially in inflationary or negative real-rate environments. They note that modern commodity index design can improve roll yield and that commodity fundamentals are hard to forecast. Wealth Building vs Wealth Preservation: The hosts contrast diversified, long-term investing with the faster wealth creation often found in entrepreneurship, private companies, and concentrated bets. They argue that building wealth usually requires ownership concentration, while asset allocation is more about staying rich.
Key Arguments: Value underperformance is part of normal style rotation; weak recent performance does not prove a strategy is broken. Market-cap weighting is acceptable but not optimal because it has no valuation tether and tends to overweight expensive winners. Many smart beta and quantitative strategies fail when they are based on limited history, overfitting, or poor data hygiene such as survivorship bias. Backtests are most useful when they teach history and risk awareness rather than promising precise future returns. Performance chasing differs from momentum because momentum has explicit buy/sell rules, while chasing often lacks an exit process. Trend following can be layered on top of many asset classes and factors, and blending multiple signals may reduce whipsaw risk. Commodities remain a reasonable portfolio diversifier, especially when inflation surprises or real rates are negative, but implementation matters because futures roll yield can help or hurt returns. True outperformance often comes from concentration, business ownership, private deals, or entrepreneurial effort, not from broad diversification alone.
Data Points: Value investing cumulative loss: 15% over the past decade - Referenced from a Bloomberg article claiming value has lagged badly versus the S&P 500. S&P 500 relative performance: Nearly double over the same period - Used to frame the gap between value strategies and cap-weighted equities. High dividend yield valuation: 50% valuation discount in 1999; now a premium over the past few years - Example used to illustrate factor timing and crowding. Vanguard robo-advisory assets: $65 billion - Mentioned as the largest robo platform, larger than the next three combined. General robo assets ranking: Top four platforms discussed - Vanguard, Schwab, Betterment, and Wealthfront were cited as major players. Top stocks in S&P 500 weight: Near all-time lows - Used to argue that market-cap distortions ebb and flow over time. 4% rule: Historical threshold where a U.S. company entering the top weight often gets hit hard - A rule-of-thumb cited to show how hard it is to stay dominant in the index. Largest drawdown: Always in the future - Used to caution that backtested risk estimates are often too low. Commodity portfolio example: 20% allocation in broad commodity index - Referenced via the Ivy portfolio question. Gold allocation example: 15% in gold - Attributed to Ray Dalio's style of portfolio thinking. Trend following sample history: 200-day moving average looked strong since 1999 - Used as an example of how a short backtest window can mislead. Harvard endowment drawdown: About 50% - Illustrated how a globally diversified portfolio can suffer much deeper losses than expected in crises. Business concentration example: Net worth 90% dominated by Cambria - Meb used himself as an example of concentrated wealth creation through a business. Amazon drawdowns: Multiple 50% drawdowns; about 90% in the tech bubble - Used to show that even the best stocks can be extremely volatile. Potential retirement longevity: Possibly 80, 100, or 120 years - Discussed in the context of planning for longer retirements and glide paths.
Pivotal Quotes: "The largest drawdown is always in the future." — Meb Faber: Used to warn against overconfidence in backtests and to emphasize hidden tail risk. "Performance chasing has no rules-based approach." — Meb Faber: He contrasted undisciplined hot-idea buying with systematic momentum and trend-following strategies. "If you don’t own gold, you understand neither history nor economics." — Ray Dalio (quoted by Meb): Cited during the commodities discussion to support gold as a strategic hedge.
Implications: Listeners should focus less on recent winners and more on process, diversification, valuation, and behavioral discipline. For the industry, the episode reinforces that product design, factor crowding, and data quality will matter more as quantitative strategies proliferate.
From the Episode
Your largest, and it's factual, the largest drawdown is always in the future. And this is why a lot of people are surprised about 2008. You know, a lot of the endowment-style models, a lot of people had a buy-and-hold model that was globally diversified. And the largest drawdown going into that was probably 20%-ish, and it doubled. You know, an endowment-style portfolio probably had a drawdown of 50%. You know, Harvard endowment, if it was market-to-market on a monthly basis, would have lost half. You know, having a healthy respect. For history, but also understand that things can go wrong and do, and that there's worse cases, and understanding why your back test may be overstated or may not work as well in the future. I mean, look at price to book as an example, as a factor, the most famous, probably value factor that's been around for decades. And then it's had countless funds and strategies that have been based on price to book. You know, DFA, original pioneer, and then.
I think there's a pretty key difference, and that is performance chasing has no rules-based approach. So, usually, people's performance chasing they find a hot sector, they buy it. So, they have one, usually, no buy methodology other than their neighbor or what they read in the newspaper. But, more importantly, way more importantly, is they have no sell methodology. So, usually they sell it when it goes down by 50% or something, right? So, momentum, at least you have buy and sell rules. That doesn't mean it always works. But you have rules to take advantage of when do I get in, when do I get out? Same with trend following. Entry is one of the least, usually least helpful, but novice traders most interested in entry. I want to pick the top, I want to buy the bottom, but then they have no exit. They don't have a process for selling. And that's way more important. I mean, I've seen research that shows you can build profitable trading systems with random entries because you.
Flat approach is also fine. I think, you know, Ray Dalio, largest hedgehog in the world, often says, we talked about a prior episode: if you don't own gold, you understand neither history nor economics. And I think in his allocation, he proposed owning like 15% in gold or something. Anyway, so implementation is: well, there were the first-generation commodity indices which weren't necessarily optimal. So they didn't take into account role yield and all these other things. So Most commodity investments happen through futures. So, listeners, you can think about you buy a commodity contract, futures contracts that say expire quarterly out into the future. And depending on demand, you could have a situation where they're either in backwardation, which is the future commodity prices are lower than the current contract, or contango, which is they're higher. And so, if you buy them in certain ways, that roll yield is either positive or negative in your favor. And historically,
About The Meb Faber Show
Ready to grow your wealth through smarter investing decisions? With The Meb Faber Show, bestselling author, entrepreneur, and investment fund manager, Meb Faber, brings you insights on today’s markets and the art of investing. Featuring some of the top investment professionals in the world as his guests, Meb will help you interpret global equity, bond, and commodity markets just like the pros. Whether it’s smart beta, trend following, value investing, or any other timely market topic, each week you’ll hear real market wisdom from the smartest minds in investing today. Better investing starts here. For more information on Meb, please visit MebFaber.com. For more on Cambria Investment Management, visit CambriaInvestments.com.