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good summary but i want to comment on the accounting part. generally accountants aim to create financial statements that are useful to most readers under normal circumstances. fuzzy concepts like "useful", "readers" and "normal" mean this goal is complicated and involves trade offs. accountants recognize these trade offs and financial statements include notes to try and explain how they were created and include numbers that help users create different statements for different circumstances. a few related points:

- there are several financial statements that are interconnected. changing the balance sheet automatically changes the income statement and the cash flow statement. making the balance sheet "more useful" can have the unwanted effect of making the income statement and cash flow statement "less useful"
- for example, "mark to market" on the balance sheet means creating "unrealized gains and losses" on the other statements. most users (and accountants) refer to these as "fake gains and loses" and hate them. most of the time they are not useful, but once in a while they become very important
- creating financial statements that are "more useful" during rare events like a bank run could mean having "less useful" financial statements the rest of the time

accounting rules evolve over time mostly in response to changes in what readers think is useful. bank runs are not a new phenomenon so i'd be surprised if it suddenly becomes more useful to show mark to market assets on the balance sheet. accounting rules can also be changed by regulation, but this is mostly bad, since it means implementing rules that are not useful. i think fears that accountants create rules to favor specific industries or companies at the expense of readers is unfounded. however, it's true that most readers of financial statements are in the financial industry, and it's plausible that "normal people" would prefer different rules (if they ever read financial statements).

i'm not sure if you're disagreeing with me, i too would like technology to be defined properly. i think the common understanding of technology would be confined to things like gadgets, software, automation. economists seem to use more of a civ version of the word, which includes things like writing, buddhism, plastic. if technology is not framed as "everything else", i'd be curious to know what kinds of things are used in the production function but don't fall in one of the three buckets. however, i'm more curious to know which bucket ai ends up in. i think most people would call it a technology, but i could be persuaded to stick it in capital (tool) or labor (brain).  

this is an interesting topic, thanks for the great post. i find it frustrating that economists use some non-standard definitions for common words (i'm not looking for precise definitions but consistent definitons would be helpful). in the context of the solow-swan model, i think the definitions/buckets would be something like:

input: raw materials, energy, time
capital: tools, infrastructure, liquid assets
labor: people, effort, skills
technology: everything else (including things like research, entrepreneurship, political institutions)
output: consumption goods, services

is this right? i think "technology" is the term that's farthest from its common usage.

I'll add that for competitive games, you want to encourage your opponent to use more luck and less skill, for example by praising his superior dice rolling abilities, and reframe your skillful moves as totally lucky, no way that could happen again!

In poker, you'll sometimes see a player get upset and criticize his opponent if he loses a hand because the opponent made a lucky draw or call (how could you call that, only one card could help you!) Rational players understand that having the opponent call with a bad hand is the only way they make money, so they'll praise the lucky draw (great call, I just can't seem to beat you!)

Answer by Clownfish30

If I can summarize your question as something like "can I beat the returns on an index fund by only investing in companies with new/useful technologies", I think you'll find this question is similar to "which version of the EMH is true", and you'll also find a lot of good discussions about this, for example here:

For the two stories presented, I would say Story 1 is trivially true and Story 2 is probably false, although it's not phrased super well (for example, is "advances in technology" company specific or general economic growth?). Trying to read between the lines, it seems like you're wondering something like "if my choice to invest is between two companies, and Company 1 has current cash flow of $1-million and future cash flow of $1-million (no growth), and Company 2 has current cash flow of zero but future cash flow of $1-trillion (lots of growth), should I always invest in Company 2?" And my answer is "no, unless you think weak EMH is true and there's a specific inefficiency that you can uncover through your research" ( and even then, your research might determine you should sell rather than buy Company 2).

To improve the framework, I suggest the following distinctions/assumptions:

  • Some form of EMH (weak, semi strong, strong) is true (I tend to agree with Sumner that anti-EMH models are not useful).
  • Value vs Price: Value is determined by things like future cash flows, risks, discounts and opportunity costs. Price is determined by supply and demand. I recommend Damodaran for discussions on this distinction, for example
  • There's a positive link/correlation between stock price and stock value in the long term. (In the short term price and value might diverge.)
  • Real vs Nominal: Real value/price is determined by things like goods produced, services provided, technology/productivity growth. Nominal value/price is determined by the above but also the supply and demand of money, inflation, exchange rates. I recommend Sumner for discussions on this distinction, he blogs at Econlog and TheMoneyIllusion.
  • Also, note that "technology" has a non-colloquial meaning under most economic models. For example, the Solow-Swan growth model says something like long term growth is determined by growth in the labor force and growth in "technology", where "technology" is basically anything that's not labor force and includes things like human capital/knowledge accumulation/diffusion and social/political institutions.

Using this framework, you could change your question to something like "assuming weak EMH is true, what sorts of public information about a company's new/useful technologies would allow me to value a company more accurately than the average investor". Then you could search for studies that try to answer this question or something similar.

Thanks, I loved this post. Its obviously hard to distinguish luck from skill when it comes to investment returns, I don't think focusing on money and track record would be enough to convince me of skill. I think I would need to also rationally evaluate the investment strategy to determine if it can be reasonably expected to beat the market. Common strategies like "we do what everyone else does but better", or "we invest in value/growth" would probably not convince me (risk premiums, liquidity premiums, animal spirits probably affect market prices but probably not in a way that can only be reliably predicted by a "chosen one"). Strategies like "we have a data connection that's 1 millisecond faster" or "we hide microphones in every lawyer's office" seem like they have a chance to beat the market, but they're hard/expensive to pull off. With respect to covid, it wouldn't be enough to say "I knew stock prices would go down" without explaining how you knew, what your confidence was, how you determined your confidence and your prediction accuracy/confidence calibration (the lack of confidence estimates on predictions is a huge red flag for me). My sense is that when someone says "my intuition tells me stock prices will go down due to covid", what they mean is something like "the market price currently implies the risk of a global pandemic is 20%, but my intuition tells me it's closer to 50%, therefore stock prices should go down half the time and my returns should be positive after 2 or 3 global pandemics". However, even with hindsight, it seems hard to determine if the actual risk of a global covid pandemic in Feb 2020 was 20% or 50% or some other amount, so focusing on outcomes doesn't look reliable. It seems like evaluating the prediction process rather than the outcome would be an easier approach ("we hide microphones in all WHO offices" seems like it would work).

Answer by Clownfish10

Have a look at, it sounds like what you're looking for, there's a website and a phone app. "Founded in 2012 by four friends, Blinkist now connects 6-million readers worldwide to the biggest ideas from bestselling nonfiction via 15-minute audio and text."

Also, this Atlantic article had a good comparison of Blinkist vs Wikipedia vs Reading The Book: