05 January 2021
Congratulations! If you are reading this newsletter, you’ve successfully lived through 2020 and made it to 2021. 2020 has shown me how fragile our life is and how much more science has to develop in the years to come.
I’ve a lot more in store coming up at DASAR and super excited to bring it to you and hear from you. From next week, we will be moving from this website to www.dasar.in Make sure you bookmark it!
What we fear doing most is usually what we most need to do.
~ Ralph Waldo Emerson
Morgan Housel does what he does best – explain a complex topic in a simple way. Here’s an absolute classic on lessons from important events in our history.
There are two kinds of history to learn from. History is full of specific lessons that aren’t relevant to most people, and not fully applicable to future events because things rarely repeat exactly as they did in the past. The second kind of history to learn from are the broad behaviors that show up again and again, in multiple fields and different eras.
How do people think about risk? How do they react to surprise? What motivates them, and causes them to be overconfident, or too pessimistic? Those broad lessons are important because we know they’ll be relevant in the future.
Covid-19 is the biggest event of the last decade, maybe the last generation.
Lesson #1: Calm plants the seeds of crazy. It’s hard to convince someone that they’re in danger of a risk they assume had been defeated. Carl Jung had a theory called Enantiodromia. It’s the idea that an excess of something gives rise to its opposite.
Lesson #2: Progress requires optimism and pessimism to coexist. The best financial plan – and I think this extends beyond finance – is to save like a pessimist and invest like an optimist. The trick is being able to survive the short-run problems so you can stick around long enough to enjoy the long-term growth.
Lesson #3: People believe what they want to believe, see what they want to see, and hear what they want to hear. One is that everyone has a model in their head of how they think the world works, and that model is built mostly from what you’ve experienced and what people you trust have told you. But since everyone has different experiences and trust a different set of people, the models of how we think things work vary wildly from person to person.
Incentives are expert storytellers, able to convince you that nonsense is real, harm isn’t happening, value is being created, and that whatever you’re doing is just fine.
Lesson #4: Important things rarely have one cause. The world is stable enough that one person, company, or event almost never moves the needle much on their own. But the needle still moves all the time, because unrelated things often collide and morph into something important.
Covid-19 is similar. A virus transferred from animal to humans (has happened forever) and those humans socialized with other people (of course). It was a mystery for a while (small sample size) and then bad news was then likely suppressed (hoping it would soon end). Other countries thought it would be contained (standard denial) and didn’t act fast enough (bureaucracy, lack of leadership). We weren’t prepared (over-optimism) and could only respond with blunt-force lockdowns (do what you gotta do) and panic (calm plants the seeds of crazy).
The other reason big events rarely have one cause is that all important events have ancestors – siblings, parents, grandparents, cousins – that have to be understood and recognized to understand how an event happened. It’s not until you study an event’s long roots that you recognize the chain of events that leads to something meaningful happening.
Lesson #5: Risk is what you don’t see. Two things happen when you’re caught off guard. One is that you’re vulnerable, with no protection against what you hadn’t considered. The other is that surprise shakes your beliefs in a way that leaves you paranoid and pessimistic.
David Beckham, known for his free-kicks, is considered one of the most iconic athletes in the world of football. But in this Twitter thread, Joe Pompliano shares how David Beckham signed one of the most lucrative sports contracts with LA Galaxy at MLS (USA).
At age 31 in 2007, DB7 signed a 5-year contract worth $32.5 Mn + percentage of team revenue + the right to purchase a future MLS expansion team at a fixed price!
In those 5 years, David earned over $250 Mn through revenue share.
David established Inter Miami CF with a group of investors in 2014 that is expected to be worth over $500Mn. Equity is the key.
From the ‘Class of ‘92’ at Manchester United to owning a series of brands, Golden Balls DB7 has taken his game to an incredible level. So how are you going to bend it like Beckham?
Li Jin deep dives into the creator economy and its current concentration at the top. She even provides details on who’s making how much on various creator platforms.
The current creator landscape more closely resembles an economy in which wealth is concentrated at the top. Just last year, YouTube creator David Dobrik’s monthly AdSense checks from the platform were $275,000 for an average of 60 million views. On Substack, the top 10 creators are collectively bringing in more than $7 million. Charli D’Amelio—who recently became the first TikTok creator to surpass 100 million followers—is estimated to be worth $4 million at age 16. She started on TikTok just 1.5 years ago.
Rosen argued that in markets with heterogeneous providers, like most creator economies, success accrues disproportionately to those on top: “lesser talent often is a poor substitute for greater talent […] hearing a succession of mediocre singers does not add up to a single outstanding performance.” This phenomenon is further exacerbated by technology which lowers distribution costs: the best performers in a given field are freed from physical constraints like the size of concert halls—and can address an unlimited market and reap a greater share of the revenue.
Creator platforms flourish when they provide an opportunity for anyone to grow and succeed. Some inequality is inherent in the nature of the passion economy: supply is heterogeneous and non-substitutable, and the trust and affinity that creators build with their audiences should be celebrated.
Some platform design decisions that can help make success attainable by many.
Focus on content types with lower replay value. Podcast vs music and game platforms.
Serve heterogeneity in user preferences & empower niche. Some content categories have more definitive, universal quality standards than others.
When algorithms do the searching for users, there are more opportunities for niches to thrive. A dose of randomness that enables normal creators without pre-existing large audiences to get exposure helps aid anyone in becoming successful on the platform, rather than creating a hardened social hierarchy in which “the rich get richer.”
Provide capital investment to up-and-coming creators.
The “radical egalitarianism” of the Creator Fund stems from rewarding creators that generate the highest engagement, rather than those that generate the highest spend.
Allow creators to capitalize on superfans. Subscription fan communities, paid access to creators (e.g. on Cameo, Looped, OnlyFans), and sales of high-value products such as courses and e-books can help creators with modest audiences to thrive.
Providing creators with a basic income may be a wise strategy to incentivize more creators to devote more time to content creation.
I’ve got some good compounders in my portfolio and I’ve sold some that I should’ve held on to longer. Marcellus helps understand how DCF is unable to compute longevity of a business due to its rigid approach.
An investor looking to buy and hold stocks over a long time period, needs to be able to differentiate between businesses which can deliver longevity of consistently healthy free cashflows and those that run a high degree of uncertainty in their fundamental prospects. This differentiation is essential.
The valuation approach (and hence annual insurance premium payment of a person) is easy to estimate because of the tangible evidence available regarding the human body’s longevity and hence mortality risk, based on the current age of an individual. However, when it comes to drawing parallels with a business, its longevity and the corresponding impact on valuations, the conventional approach to DCF (and hence P/E multiples) fails to adopt this differentiation.
Since typically a quick look at most companies (basis a meeting with the management team or some other short-cut towards understanding the company’s financials) points towards earnings growth at a rate somewhere between 10% CAGR and 25% CAGR, the band of P/E multiples which becomes psychologically acceptable for the fair value of a firm is 8x-24x typically.
The biggest challenge with the DCF approach is the rigidity of duration of Stage 1 (5 years). This rigidity works both towards massive over-valuation as well as towards under-valuation.
This over-estimation is because the conventional approach towards conducting research on a firm (management meeting, reading a couple of years of annual reports, reading a few broker notes, press articles and doing some ground level channel checks) isn’t enough to forecast a bleak outlook over the short term for any business.
There have been some businesses historically which have not seen a ‘fade period’ (i.e. no end to the Stage 1 of the DCF) in their business growth prospects for several decades on end. In effect, they have delivered the ‘Stage 1 of the DCF’ for time periods lasting several decades in a highly consistent manner. Two of the best examples of such longevity have been Asian Paints and HDFC Bank.
We believe it is impossible to accurately forecast the future of any business.
Here are some of the tools that can be used to add at least 8-10 years or reduce 2-3 years from the conventional 5-years’ time period of Stage 1 of the firm’s DCF by using a deep-dive research approach:
Evidence of accounting fraud.
Understanding of the DNA of the organization (predominantly based on historical evidence around the softer aspects of the business).
Deep understanding of ‘sustainability’ of the moats of an organization.
These tools can certainly be used to add a decade (or two) to an investor’s conviction on longevity assumptions of a consistent compounder. An investor might make a premature exit from their investment in a great quality franchise due to concerns around expensive valuations, and the investor might also get attracted towards inferior quality franchises just because they are trading at apparently cheap valuations.
Given today’s stock market scenario, I thought this Twitter thread by Corry Wang was on point. A gentle reminder that you never truly know and ‘time’ the market.
Investors were comparing the internet sector to tulip mania as early as mid-98. Bernstein held an entire conference on it in June 99!
In truth, the hard part about the tech bubble wasn’t noticing it. The hard part was timing it.
Nobody knew the bubble popped until months after it did. We found over the past 25 & 50-year periods the odds of being a 20% grower for 10-15 years was about 1 in 14.
“Tech” bubble was a misnomer… it was really a large cap growth bubble. Microsoft traded at 70x earnings. But Coca Cola was 43x. Pfizer was 92x. Every stock here was a disaster over the next 10 years.