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One of the books I enjoyed this year, Thinking In Bets, by Annie Duke, encourages being process-oriented in your decision-making and evaluation of those decisions.
Yet most investors care only about their outcomes — their returns — and little else.
“Resulters blame execution and bad decisions for why certain strategies don’t pan out. They fail to recognize that their evaluation is based on outcomes. The execution was good if the sales person made the sale; the decision to play the hand was bad if the player lost the hand.”
(Not you guys, of course, that’s why you’re here.)
Outcomes are the product of the quality of your decisions and luck. Luck is high variance and uncontrollable. You can control the quality of your decisions, however, by focusing on your objectivity, open-mindedness, and accuracy.
That’s one reason I enjoyed this quick piece from Ben Carlson, Mindless Resolutions.
“Thinking in terms of systems, not goals; process, not outcomes; and philosophy, not tactics is how you can see lasting change in your habits, and hopefully your life.”
It also resonates with what I wrote about in the last Nugget Fest, about how value investors generally, and Buffet in particular, have evolved their process of understanding and valuing companies.
Having a process and continually refining it is also your best source of opportunity. In a video interview with Michael Mauboussin, “Five Common Mistakes Investors Make,” he says that having an informational or analytical edge in today’s market is very hard, so avoiding behavioral mistakes may be a real source of alpha. Having an objective process that minimizes your biases, avoids narratives not supported by facts, etc., may make all the difference.
This week, we’re going to focus on the part of your process where you’re analyzing a company. So, let’s tee up this week’s Nugget Fest with this:
In this episode, Steve says the lifecycle of a company is as short as it’s ever been, and it’s getting shorter. Companies are being disrupted and getting put out to pasture faster. So, for him, it’s very important to understand the business (and industry) first.
FPA’s Crescent Fund has two main categories they look for: 1) Compounders, which are high-quality, growing businesses where they are confident earnings will be higher in a decade; and 2) Commerical, which are “traditional value” stocks but where they believe there is a 3-to-1 upside potential (3x upside to the downside). One example that hits both right now for him is MSFT.
But how do you figure out if earnings will be higher in a decade, or if the upside is significant compared to the downside?
Andreessen-Horowitz had a couple posts in December about Network Effects, and analyzing companies through this lens.
“Instead of winner-take-all markets where early movers may have once had a seemingly lasting advantage, network effects change more quickly than ever. Especially where specific factors — an asymptotic value proposition, network overlap, increasing number of contaminants, etc. — can lower the platform’s ability to generate a sustainable network effect in the future.”
Another way to look at this is through Ben Thompson’s “Aggregation Theory“. Simply stated: modern marketplaces get their power from aggregating the demand side, and is a much better position than the old way of trying to own the supply side.
Two recent posts on this are worth reading:
“In short, if somebody successfully inserts themselves between you and your customer, they can exercise tremendous control over you, including taking a big chunk of your profits or outright killing you.”
“More generally, that virtuous cycle characteristic of Aggregators, where more users attract more suppliers which attract more users, is likely most important in terms of the breadth with which a job is done. By doing more of a job, an Aggregator attracts more marginal users, which attract more suppliers on the edges of a space, which expands what jobs can be done for what users. In concrete terms, Amazon started by selling things to book buyers, then expanded to selling things to CD buyers, until it now sells everything to everyone; the job-to-be-done, though, was only ever selling things…
“This helps explain why it is there are a few large companies that dominate their space: Aggregators don’t simply get better at what they were already good at, they expand their purview into the broadest possible definition of their job.”
As an aside, if you’re into investing in tech companies, reading everything from Stratechery is absolutely required, in my opinion.
As part of my process, I like to see how other people think about moats and apply their thinking to real companies. This presentation analyzes AMZN, FB, and TSLA. I personally find the analysis much less nuanced than what you get if you read the a16z and Stratechery pieces for AMZN and FB, but I think analyzing another person’s thought process can help improve your own.
A must-read for seeing how other, in this case successful, investors approach security analysis. (Note that I don’t always look for how successful investors do things. You need to see how unsuccessful investors do it, too, so you can ensure you’re not selecting on the dependent variable. The key is to find what differentiates the two groups, ideally in a predictive way.)
Understanding companies and their industry dynamics is often not enough. You should generally also understand the markets and economies they are playing in.
If you haven’t read all of Ray Dalio’s economic principles yet, this was a great post that summarized a lot of what he’s written.
Another excellent article came from Steve Romick, on Meb Faber’s podcast linked to above. I highly recommend this one, even more than the Dalio post, to help piece together your perspective on either where the next downturn could come from or what might happen when it does come.
“We believe that sovereign and US municipal governments and corporates are more the problem now and that their excessive leverage will either catalyze or magnify the next downturn. The current debt trajectory, in terms of levels and quality of credit, is unsustainable and will inevitably end. Understanding this today will hopefully protect the capital of our investors in the future.”
I have also been thinking about what it means that so much of the equity market has become passive. But in this FPA article, there is a clear articulation of what it might mean in the bond market:
“To date, the increase in supply of corporate bonds has partially been soaked up by the increase in corporate bond exchange traded funds (ETFs). Such passive funds have grown from an immaterial amount in 2008 to $600 billion today.
“A relevant trait of most such funds is that they transact indiscriminately with frequent, ratable purchases and sales – a function of ETF inflows or outflows, respectively – that can drive bond prices to both new highs and new lows. In a downturn, passive investment vehicles could be forced to indiscriminately sell those investment grade bonds that the ratings agencies have downgraded to junk. Given the huge size of the BBB market, downgrades could incite a large volume of selling that could then infiltrate the rest of the market and quite possibly exacerbate the negative price action…
“More corporate bonds, more corporate bonds in passive hands, and less help from trading desks to smooth buying and selling of corporate bonds could well lead to price declines larger than one might otherwise suspect.”
Really nice presentation of the current state of all kinds of market and economic data.
This is also a good time to remember the incentives of most market prognosticators. Don’t let the noise into your process!
“Those recession probabilities from an economist at a sell-side shop or standalone research house… is anyone dropping those assumptions into asset allocation models? The predictions on year-end S&P 500 and 10-year levels? Odds on this outcome or that from the China trade war negotiations? Who is making adjustments to model portfolios or strategic asset allocation plans for new clients going into 2019 based on all these brilliant research pieces?
“…That’s not what these are really about. At every level, the Prediction Polka is a sales tool and nothing else.”
Druckenmiller on Economy, Stocks, Bonds, Trump, Fed: Full Interview – Bloomberg Markets and Finance (YouTube)
Great interview covering a wide range of subjects that may impact your macro analysis. Also, around 34 minutes, he talks about his view on cloud businesses. “In a period of slow, muted growth, if you can find a 20-30% grower…” Microsoft, Service Now, Workday, and Salesforce are ones he mentions.
These didn’t fit into my overall story for the week, but are still worth reading.
“Exposure to small caps likely explains private equity returns. Liquid alternatives to private equity can be created simply by buying small, cheap, and levered stocks.
“Some have reached similar conclusions and proposed that the nature of locked-up capital is what makes private equity so advantageous. It keeps investors from redeeming their funds at market lows and helps private equity firms weather storms like the global financial crisis. But the same fund structure can be replicated through public equities at a fraction of private equity fees.
“Furthermore, with $1.8 trillion sitting on the sidelines, too much money may end up chasing too few deals, creating high acquisition multiples that don’t augur well for expected returns.
“Of course, high valuations are now the rule in both private and public markets. And corporate debt levels are at all-time highs.
“Neither of these developments bode well for expected returns. So investors might be wise to reconsider direct private equity allocations and their liquid alternatives altogether.”
Research paper (not new, but I hadn’t read it till this week) reiterating that most of those factor strategies you’ve heard of probably don’t work.
“The anomalies literature is infested with widespread p-hacking. We replicate this literature by compiling a large data library with 447 anomalies. With microcaps alleviated via NYSE breakpoints and value-weighted returns, 286 anomalies (64%) including 95 out of 102 liquidity variables (93%) are insignificant at the 5% level. Imposing the t-cutoff of three raises the number of insignificance to 380 (85%). Even for the 161 significant anomalies, their magnitudes are often much lower than originally reported. Among the 161, the q-factor model leaves 115 alphas insignificant (150 with t < 3). In all, capital markets are more efficient than previously recognized.”
“Considering that the dividend yield on the S&P 500 recently crossed over 2%, yield-hungry investors are going to be pouring back into the stock market in the New Year. Remember, most dividends are tax-advantaged and taxed at a maximum federal rate of 23.8%. So, the S&P 500 actually yields more than a 10-year Treasury bond that is taxed at a maximum federal rate of 40.8%.”
“Mistakes in pricing are not spread uniformly across all areas of the capital markets. The market is more prone to error in areas where fewer security analysts are scrutinizing corporate financial statements. Analysts cannot afford to spend time on smaller companies in which their clients cannot invest significant sums of money. This institutional constraint means that large cap stocks tend to be priced more efficiently— 4 closer to intrinsic value—and that most bargains or mispricings are found in the small, micro and nano capitalization sectors of the market.”
Thanks for reading!
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