A mediocre product with a great distribution beats a great product with mediocre distribution.1
The most recent example of this is Slack vs. Teams. Teams had a late start with a broken product. But Microsoft bundled it with Office and Windows and forced a shotgun marriage on Slack.
Slack had around 4 million users in 2016 and that number would increase to just 12 million four years later, while Microsoft — which added Teams to its 365 bundle without increasing the price — took Teams from zero to 115 million users.
Very few startups (Zoho, for example) have survived providing a wide range of mediocre products. Typically, the focus is on getting one thing right. From POC to MVP to scale, the one thing is the thing.
Best-of-breed companies, which do one thing extremely well, have clear priorities and their incremental edge creates value for customers on mission-critical uses and when customers use them intensely — particularly at large organizations. Bundles, however, drive value through integration and can take advantage of more efficient go-to-market sales, not to mention by offering customers the convenience of one-stop-shopping for both sales and support.
Even luxury brands have consolidated under large corporate umbrellas. As far back as 2001, HBR had run a piece on Bernard Arnault (LVMH).
While Arnault is obviously the GOAT, the rest of the industry is consolidated AF.
Having a decent product is table stakes. Distribution decides the winner.
Markets this Week
This week, the US Fed increased rates by 75bps to fight inflation while the RBI wrote a secret letter to the Finance Ministry as to why it is failing the fight against inflation.
Indian equities up, US equities down.
US mortgage rates now at the highest level in 22 years is bringing home buying/building activity to a standstill.
The pain beyond the frontline indices on Friday was excruciating. Most of the COVID era go-go stocks got obliterated.
King Dollar stuck again.
Links
Robert Wilson was one of the great stock investors of the past 50 years. He started with $15,000 and had a miserable rate of return in the early years. But from 1960 on, he turned $70,000 into $225 million over 26 years before retiring in 1986 at age 59. (gdoc)
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The dildo of the consequences of global capital flows rarely arrives lubed.
US net capital inflows drive the international synchronization of house price growth. An increase (decrease) in US net capital inflows improves (tightens) US dollar funding conditions for non-US global banks, leading them to increase (decrease) foreign lending to third-party borrowing countries. This induces a synchronization of lending across borrowing countries, which translates into an international synchronization of mortgage credit growth and, ultimately, house price growth. Importantly, this synchronization is driven by non-US global banks’ common but heterogenous exposure to US dollar funding conditions, not by the common exposure of borrowing countries to non-US global banks.
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Hope Zuckerberg proves his critics wrong. Went from darling to dud at breathtaking speed.
It is worth noting that in good times, when earnings are rising and stock prices are upward bound, investors do not seem to have much interest in corporate governance, and it is only when the numbers start to move against them, that they rediscover the importance of the topic.
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It seems the Twitter brass perfected not the production of cash for the owners but the production of shares for themselves.
Bloomstran on Twitter’s life in the public markets (Thread)
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It was the rate cycle all along.
We study the importance of the decline in interest rates in the discovery of asset pricing anomalies. We investigate 153 discovered anomalies as well as 1,395 potential undiscovered anomalies and find that absent the decline in interest rates, the asset pricing literature would likely entertain a different set of anomalies today.
The Factor Multiverse: The Role of Interest Rates in Factor Discovery
Speaking of factors…
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China is North Korea 2.0
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Stop trying to predict prices!
most AI/ML techniques were designed for stationary problems with high signal to noise ratios - eg image processing . there are analogous tasks in finance they can be great for; automating manual tasks like mapping identifiers of unknown format comes to mind but naive prediction of asset returns is not one of them.
Speaking of ML, here are some of the best and most recent machine learning courses available on YouTube.
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An Eurodollar market 101
The Eurodollar market is incredibly important and is how the rest of the world finances a lot of its economic activity, the global benchmark for bank financing, and a tradeable interest rate market for all purposes.
A Trend-following 101
The strategy has a few pretty well defined components -
1. Universe selection
2. Trend detection (aka signal)
3. Mapping from trend strength to desired position
4. Sector/asset class weights
5. Portfolio risk targeting
6. Trading rules
7. Execution
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Renting computers is (mostly) a bad deal for medium-sized companies like ours with stable growth. The savings promised in reduced complexity never materialized. So we're making our plans to leave.
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World's Wildest Police Videos no more?
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Buy clothes and wear them until they tear and then use them as a mop. That is the only way.
Some 59,000 tons of unwanted clothing arrive in Chile each year from places like Europe, Asia and the United States. But because it is illegal to dump them in landfills, they often end up in places like the Atacama Desert in the north of the country, where they harm the environment.
Fast fashion is causing an environmental disaster in Chile's Atacama Desert
Memes of the Week
I think it’s a Peter Thiel quote. If you know who said it, please comment below.