Double Down on Bottom Up

I find top-down, blanket statements entertaining. But it stops at that - entertainment. If someone tells me, “I think European or Japanese stocks are undervalued now…”, I’ll certainly read their thesis, but I’ll take it with a (large) grain of salt.

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That’s because – implicitly or in spirit – most, if not all, top-down calls are bottom-up averages or medians of the constituents of the basket of stocks. That’s probably not how they’re constructed, but that’s the implication. But they often ignore the variety or dispersion of potential outcomes among the constituents. Well, I’ll be blunt: Most ETF forecasts are punts.

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This is important in a super-charged, Bogle-ized Passive Investing world. Top-down blanket statements get a lot of eyeballs and clicks. Recommending or buying Market or Sector or Style ETFs has become the MO of many Financial Advisors, Finfluencers, and regular folks like us. Most of their reasons are generally solid, the main one being: Why pay high “active” management fees when evidence says that it doesn’t usually result in higher returns?

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Fair enough. But a purely top-down punt has its problems.

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For starters, Passive Management is not Passive . But that’s a different debate. For today, let’s assume that we’re all Bogleheads – we’re all in the Passive Investing camp. No problem. Within this camp, when I peel the layers, I see 3 other pervasive problems. I’d urge you to watch out for these:

1. Most ETF conversations don’t start with a specific return objective.
2. Mean Reversion is often used as an investment thesis. Oh boy, this topic deserves a separate note. Most meaningful metrics with any predictive value in investing are not mean reverting.
3. Fund level, rolled-up valuation metrics are usually backward-looking with little-to-no predictive value.

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On the issue of rolled-up valuation metrics, they’re generally historical stats that don’t say a whole lot about the future. This used to be less of an issue 20 or 30 years ago. But in today’s fast-changing world, a historical P/E average doesn’t tell us much; neither does a forward-looking P/E ratio. One can argue that return-on-capital metrics have predictive value – in terms of probability of generating higher returns or beating the market. I don’t know how reliable this is. If you know of a study that proves this let me know – we’ll all merrily scoop up ETFs with top-quartile ROEs and retire on an island!

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Take SPY vs. QQQ – two of the most popular Index ETFs. Look at the range in Forward 1 year P/E Ratios since 2014. Which one is mean reverting? Which one has predictive value in terms of generating high returns?

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The point is that it’s hard to rely on valuation metrics when selecting ETFs. They can’t be the only sanity check, especially when they’re backward-looking.

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In an ideal world we’d like to analyze ETFs (Index or Active) in a way that has 3 main characteristics:

1. It’s a bottom-up, rolled-up analysis, stock by stock.
2. The analysis is forward-looking.
3. The analysis is long-term oriented.

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This is difficult to execute. The main roadblock, especially for individual investors, is the depth and breadth of our analytical systems – both in terms of coverage of stocks and in terms of the “satisficing” question, “how much analysis is enough?”

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I’ve taken a crack at the Satisficing problem before , but here’s the gist: I’m borrowing Uncle Warren’s simple approach to investing…

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“Take the probability of loss times the amount of possible loss from the probability of gain times the amount of possible gain. That is what we’re trying to do,” says Buffett. “It’s imperfect but that’s what it is all about.” – The Warren Buffett Way by Robert Hagstrom

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Buffett was talking about analyzing individual companies and their stocks. But the statement can easily be applied to Indices and ETFs. So, there are 4 variables that we need to estimate:

1. Probability of Potential Gain
2. Magnitude of Potential Gain
3. Probability of Potential Loss
4. Magnitude of Potential Loss

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The rest of the distribution has an expected value of 0%. I’m not sure if Buffett implied that, but remember that we’re all about Satisficing. We’re all time-strapped, so to narrow our scope, we’ll make that assumption.

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In attempt to have a satisficing approach, I’ve found that Michael Mauboussin’s concept of Expectations Investing makes my life a helluva lot easier. Here’s how:

1. Probability of Gain: Unknown
2. Magnitude of Gain: This is my desired/required return from the stock. So, it’s known.
3. Probability of Loss: Unknown
4. Magnitude of loss: Can be estimated using conservative assumptions of revenue growth, cost structures, and FCF exit multiples.

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So, here’s the slight bummer: The probabilities of gain or loss are mostly subjective. I do quantify them to an extent, but the final assessment is subjective.

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In The Buycaster , I quantify them as Sanity and Safety Scores – that signify the sanity and safety level of the stock delivering a specified target return. The average of the Sanity and Safety scores is the Rationality Score. Here’s how they look for JNJ, for example:

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The Fundcaster then takes these bottom-up insights from The Buycaster and rolls them up at the fund/ETF level. Here’s how it looks for the XLV SPDR Healthcare ETF (Disclaimer: I hold this ETF in one of my portfolios):

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?How should we read this 6.4 number? How does that compare to the market?

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?Explanation from The Fundcaster:

?XLV's Rationality Rating is HIGH because of its OK Sanity Rating and HIGH Safety Rating. But that's just mechanics. The real takeaway is that if our target is 80% cumulative return in 5 years (12.5% CAGR), we would rather bet on XLV than SPY to get us there. However, regardless of its relative score vs. SPY, the absolute score is somewhat low, and therefore betting on XLV to deliver 80% cumulative return in 5 years (12.5% CAGR) is still an overoptimistic bet. It’s possible, but that would involve some luck.

?Note: We've also rolled up each holding's average Wall Street Analysts' Ratings (provided by various financial data providers) to the fund level. We've scaled up their rating to a max of 10 for easy comparison.

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This approach is in line with the main principles of Expectations Investing. It’s concise. It’s actionable. But it’s not perfect. The main drawback is that these quantifications don’t (can’t) truly capture the probabilities of gain or loss. Even AI won’t be able do that – not yet anyway. Despite its imperfections, the approach is:

1. Bottom-up
2. Forward-looking
3. Long-term

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Look, I built The Fundcaster because I needed a robust ETF analysis tool with those 3 characteristics. Maybe you do too. Maybe there are others out there that do it better, but I’m not aware of any. Whatever system you have, I just wanted to remind you to not punt on ETFs. I’ve been guilty of it too in the past and I’ve learned my lesson. I never want to overpay for an ETF ever again.

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If you don’t have a system to analyze ETFs, try this:

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For a market-cap weighted ETF (most of them are), analyze the top 10 holdings (by weight). That’s it. Analyze those stocks in a way that’s forward-looking and long-term. Of course, I’d say that using The Buycaster is the best way to do it (but I’m biased). But use whatever system you use now for analyzing stocks. It doesn’t have to be complicated.

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Here’s a start if you don’t have a system for analyzing ETFs:

1. Decide your desired return and timeframe. It could be something like mine: 80% cumulative in 5 years (12.5% CAGR). Be specific.
2. Now think about the probability of each of those 10 stocks delivering your desired return.

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To subjectively assess the probability of those 10 stocks to get you your desired return, use the Fab 4 that I always use:

1. Does the company have a long-term thematic tailwind ?
2. Does the company have a distinct competitive advantage?
3. How durable is this competitive advantage (economic moat)?
4. Is the management team’s growth strategy credible?

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My main message is this: Every Index or ETF is a portfolio, maybe it’s a systematic one, but it is still a portfolio with deliberate market-cap or sector or style bets. Try to answer the question, “what is the likelihood of this not-so-passive portfolio getting me my desired return?”

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This is obviously a heavy topic (that too for a Friday) which can’t be completely covered in a Newsletter. If you have any questions, please drop them in the comments. I’ll be happy to continue the discussion there!

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Have a great weekend!

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Many Happy Returns,

Saurav

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