- Lyall Taylor's Why I Worry More About A Melt-Up Than A Melt-Down
- Chris Meredith, Jesse Livermore, Patrick O’Shaughnessy's Factors From Scratch (Link)
Minsky Moments in Venture Capital by Abraham Thomas
Paradox of high prices is they imply low risk which further attracts more inflows.
The key idea of Minsky cycles isn't that rising prices attract capital; that's just standard trend dynamics. The key Minsky idea is that increasing capital inflows reduce perceived risk.
This is the Minsky boom. Money entering a market boosts returns and reduces volatility, leading to very strong (realized) performance. This attracts more money, which improves performance even more. A positive feedback loop ensues.
And this is perfectly legit! Economies can and do reallocate resources all the time. This is how it works; this is how it’s expected to work.
The problem with feedback loops is that they tend to overshoot.
True Risk vs Measured Risk
One way to understand Minsky cycles is that they’re driven by the gap between ‘measured risk’ and ‘true risk’.
When you lend money, the ‘true risk’ you take is that the borrower defaults3. But you can’t know this directly; instead you measure it by proxy, using credit spreads. Credit spreads reflect default probabilities, but they also reflect investor demand for credit products. A subprime credit trading at a tight spread doesn’t necessarily imply that subprime loans have become less risky (though that could be true); the tight spread may also be driven by demand for subprime loans. Measured risk has deviated from true risk.
Similarly, when you invest in a startup, the ‘true risk’ that you take is that the startup fails. But you can’t know this directly; instead you measure it by proxy, using markups. Markups reflect inverse failure probabilities (the higher and faster the markup, the more successful the company, and hence the less likely it is to fail — at least, so one hopes). But markups also reflect investor demand for startup equity. Once again, measured risk has deviated from true risk.
During Minsky booms, measured risks decline. During Minsky busts, measured risks increase. The flip from boom to bust occurs when the market realizes that true risks haven’t gone away.
So now let’s rephrase the question. Has the true risk of venture investments changed? More rigorously:
Does the compression of timelines in venture change the distribution of terminal outcomes for venture-backed companies?
On that question, the jury is still out. It’s not obvious to me that accelerated markups change the power-law dynamics of venture portfolios. Markups change the journey of a business, but do they change the destination?
If the answer is yes, then there’s no Minsky dynamic at play; what we’re seeing is a rational evolution of the venture industry. Maybe startups are truly less risky now; maybe the market truly has matured. More capital, lower returns, safer investments4.
If the answer is no, then venture is very possibly in a Minsky boom, and we’re just waiting for the moment when it turns into a Minsky bust.
“Incentives to produce” are incentives to rig the game by Interfluidity
This essay contends that the cost of mitigating inequality is likely small compared to its benefit. Rent-seeking behavior is inevitable but incentive to capture rents or grift is stronger if the potential prize is bigger (I'm not so sure that any reasonably capitalistic society would escape this problem at any level of naturally occurring inequality — something we must live with anyway as a consequence of humans’ endemic differences which we happily agree to entertain when we reject communism)
- Starts with allusion to the ever present efficiency vs equity tradeoff: Reducing rewards to those at the top of the wealth/income distribution might blunt their incentives to produce. But the cost of that might be offset by utilitarian benefits of transfers to the less well off...But at current margins, I suspect there is no tradeoff. There might be a tradeoff in measured GDP, but GDP happily tallies economic coercion and rent-capture along with genuinely productive activity...Causing a disease and then expensively treating it does not in fact make the world richer. But it may well inspire economic activity — the mass production of a new drug, visits to doctors, extra hours people choose to work in order to afford the treatment, etc. In aggregate, we work harder just to stay in place. But the distributional effects of the operation are very real.
- Rent capture increases as a natural defense to technology’s unseating effects: We should expect the prevalence of rent capture (or worse) as a source of economic profit to increase with technological progress. Why? Because, absent chicanery, technology increases the ease of production and the efficiency of distribution. As Schumpeter pointed out, the source of profit in real-life capitalism is the fact that monopoly power is ubiquitous because of natural barriers to competition...Technological progress renders moats that derive from nature harder to come by. Instead, successful businesses — and successful people (since under capitalism, a human is just a small business) — must rely increasingly on moats that result from social and political arrangements....The distribution of profits is determined by social choices rather than by natural scarcities.
- This is not necessarily wrong but if you care about social cohesion it's problematic because it creates incentives to side with the winners....But the distribution of affluence is less and less a matter of direct attachment to production, and more and more a function of winning social games and political contests that determine to whom the fruits of production will be allocated. There’s no conspiracy in that. Nor is it an answer to say “capital” now determines who enjoys wealth. As technology improves, capital goods become mere commodities like everything else. Financial capital, whatever it is, is not an input into any material production process. It is a construct and artifact of a huge and ever-changing array of social and legal institutions. “Human capital”, “social capital”, and “organizational capital” are things we impute ex-post to winners of distributional contests as explanations of observed returns. They do not straightforwardly exist in the world...high dispersion of outcome creates a strong incentives to be on the side of winners.
- This incentive creates inefficiency: a well ordered society depends upon people sometimes making choices opposed to their material interests on ethical or other grounds. Then it is obvious how inequality might be costly. Instead of talking about “incentives to” (produce, extract rents, whatever), we might describe outcome dispersion as a tax on refraining from mercenary behavior. If the difference between economic winners and losers is modest, people of ordinary virtue might refrain from participating in activities they consider corrupt, might even be willing to “blow the whistle”, because the cost of doing so is outweighed by their preference for behaving well. But as outcome dispersion grows, absenting oneself from or even opposing activities that would be personally remunerative but socially undesirable becomes too costly.
- Moloch equilibrium: Wouldn’t it be odd to live in a country where, say, bankers individually acknowledge that their industry often behaves destructively, where insiders perceptively describe the conditions that create incentives for people to take bad risks or fleece “muppets“, but continue to work in those places and do nothing about it? Wouldn’t it be odd to live in a country where doctors privately apologize for the way their services are “priced“, but nevertheless take home their paychecks and pay AMA dues? Or in a country where economics instructors teach agency costs using textbook pricing as a case study, during a course for which students are required to purchase a $180 textbook?... In all of these cases, there really isn’t anything any one individual can do to remedy the bad practices. Making a big issue of them would lead to useless excommunication. Instead we shrug ironically. In our society, an ironic attitude is a token of sophistication (a telling word, which once meant corruption but now implies competence). An ironic attitude towards collective ethics is adaptive. It helps basically decent individuals participate in coalitions that ruthlessly contend for rents. But perhaps we’d have a better society if, rather than turning our ethical discomfort into an object of aesthetic consideration, lots of us worked straightforwardly to remedy it. And perhaps more of us would do so if the risk of losing our place were not so terrible. Ethical behavior is endogenous. “Inequality” renders it costly.
On the Floor Laughing: Traders Are Having a New Kind of Fun by James Somers
- The upshot is that there is a lot of energy on a trading floor. Go to a law firm, Silicon Valley startup, magazine, or corporate headquarters. Even if what they do there shakes the world, even if the staff practically sneezes vibrant creativity, still you can't escape that Office-y undercurrent, the unmistakable intimation of malaise you find wherever adults are stuck inside doing their homework. This place, on the other hand, feels like something closer to an active battleship.
- The more I watch, the more I think I understand the peculiar grip this place has on him -- and, for that matter, the peculiar grip it seems to have on me. From the minute I walked in here I've been sort of dazzled. I've felt almost exactly like I did when I was first invited as a nine or ten year-old into the cockpit of a commercial airliner. There is just something undeniably cool and complicated and a little bit spectacular about both places, each in its own way the frenetic nexus of an intricate machine. It looks fun, basically -- in the one case because you get to fly a plane, and in the other because people take you seriously and pay you lots of money and yet what you do all day is qualitatively equivalent to playing a video game. If that sounds a bit silly, consider for a moment what makes a game a game. The trick seems to be that games are constrained in a way that the real world isn't: there is a board, field, pitch, court, area, table, ring or other enclosure that bounds the action in space; clocks that bound it in time; and rules that restrict the space of allowable moves. In some ways those constraints are what make games mentally satisfying, because they relieve us of what existentialists called "the anxiety of freedom." By giving us obvious, well-defined goals, they save us from having to define success; and with points, leaderboards, heads-up displays, indicators, badges, etc., they tell us exactly when we've achieved it. Humans crave that kind of structure, probably because we get so little of it in real life. It's a lot harder to say whether you "have a healthy romantic relationship" or "are making a lasting contribution to something bigger than yourself" than that you've "lined up the yellow gemstones," "scored more points than the other team in twenty minutes," or "collected forty pounds of silver."
The Origin Of Wealth Book Summary by Taylor Pearson
Traditional neoclassical economics tends to use tools that require it to look at the economy as a static, equilibrium-seeking thing – something akin to a factory or machine. Complexity economics, an outgrowth of complexity science, instead tends to view the economy more like a biological system.
In The Origin of Wealth, Eric Beinhocker introduces complexity economics and argues that “wealth creation is the product of a simple, but profoundly powerful, three-step formula—differentiate, select, and amplify—the formula of evolution”
and “the same process that led to an explosion of species diversity in the Cambrian period led to an explosion in SKU diversity during the Industrial Revolution.”
Evolution is an algorithm for innovation searching the “fitness landscape” of a given system. This could be an ecosystem as in biological evolution or the economy. The environment creates a design space and then selection (natural or otherwise) tests all the configurations in that design space over time and evolves with it.
- Peak California by Byrne Hobart
- Power Laws in Venture by Jerry Neumann
- Dennis Rodman and The Art Of Portfolio Optimization by Chris Cole
- Even God Would Get Fired as an Active Investor by Wes Gray
- Warren Buffett is Wrong About Options (Except) by Jon Seed
- What Explains The Rise Of AMMs by Haseeb Qureshi
- Salary Negotiation: Make More Money, Be More Valued by Patrick McKenzie
- Hitting the High Notes by Joel Spolsky
- My Top 10 Peeves by Cliff Asness
- The Commoditization of Information by Geoff Yamane
- CEOs Don’t Steer by Venkatesh Rao
- William Baumol and the Cost Disease by Alex Tabarrok
- Art Of Gig II: Talking About Money by Venkatesh Rao
- Risk and Returns Before and After The Fact by Byrne Hobart
- 15 Ideas, Frameworks, and Lessons from 15 Years by Corey Hoffstein
Proprietary Trading: Truth and Fiction by Peter Muller
- But the most important risk is the possibility of our models not working correctly. To minimize that risk, we set loss targets for strategies — if we lose more money than the pre-specified target then the strategy is re-evaluated and shut down for a while (perhaps forever). This is not that different from the old school of proprietary trader management: ‘Go ahead and trade, don’t do anything too risky, and if you lose more than $x we’re going to shut you down. ’Our strategies are evaluated by looking at reward/risk measures. For symmetric, market-neutral strategies without significant tail events, the Sharpe Ratio (SR) is probably the best ex-ante measure. SR is defined as the portfolio annual excess return divided by the annualized standard deviation of that return. Our benchmark is cash, hence measuring excess returns is appropriate for our portfolio. For long-only managers, the Information Ratio—which measures excess returns relative to a benchmark—is more appropriate. When we evaluate past performance, we also look at peak-to-trough drawdowns (a measure of the maximum drop between consecutive maximum and minimum values of return over the life of the strategy) as an additional risk variable. This can help pick up serial correlation in portfolio returns that the Sharpe Ratio doesn’t capture. Also of interest is the fraction of expected gross profits consumed by expected transaction costs. The higher this number, the more money we expect to lose if our model stops working. At least some of our edge comes from opportunities that are created in the market by institutional managers who trade too much. Their trading is usually based on either an exaggerated view of how well they can predict investment returns or a misunderstanding of how trading costs increase with size. The strategies of institutional managers can still be perfectly rational despite providing us with opportunities through over-trading, simply because of the huge agency issues in portfolio management.
- In Grinold and Kahn’s book on Active Portfolio Management, the authors describe the ‘FundamentalLaw of Active Management’: a strategy’s Sharpe Ratio is proportional to the number of independent bets taken by the strategy multiplied by the correlation of those bets with their outcome. To get a higher SR, you need to increase the number of your bets or increase the strength of your forecasts. In my opinion, it is far better to refine an individual strategy by increasing both the number of bets within the strategy and the strength of the forecasts made in the strategy, than to attempt to put together lots of weaker strategies. Depth is more important than breadth for investment strategies…I would much rather have a single strategy with an expected Sharpe Ratio of 2 than a strategy that has an expected Sharpe Ratio of 2.5 formed by putting together five supposedly uncorrelated strategies each with an expected Sharpe Ratio of 1. In the latter case, you’re faced with the risk that the strategies are more correlated than you realize (think Long Term Capital). There is also the increased effort of ascertaining whether each individual strategy really has a Sharpe Ratio of 1.
- An important choice for many proprietary traders is whether to focus on shorter or longer-horizon strategies. Typically, shorter horizon strategies get their edge from providing temporal liquidity to a marketplace or predicting short-term trends that arise from efficient trading. Longer-term models focus on asset pricing inefficiencies. How does the implementation of these strategies compare? Shorter-horizon investment strategies are desirable because they tend to create higher Sharpe ratios. If your average holding period is a day or a month, you have the opportunity to place many more bets than if you hold positions for three months to a year or longer. On the flip side, shorter horizon strategies tend to have capacity issues (it’s easy to make a small amount of money with them, but harder to make a lot of money). Shorter horizon strategies also require serious investments in trading infrastructure, since quick and inexpensive execution is much more important than for longer horizon strategies. Risk management for shorter-horizon strategies tends to occur through position trading rather than portfolio construction. Assets are not held for long periods of time and portfolio characteristics change quickly. The biggest risk for shorter horizon strategies model risk, or the risk that the trading strategy deployed has stopped working. Since even the best trading strategies experience periodic drawdowns, the hardest challenge for the short-term model-based trader is to figure out whether his model is going through a regular drawdown or has stopped working altogether. Longer-horizon model-driven investment strategies have different issues. Since assets are held for longer periods of time, execution costs (although still important) are not the primary focus. Statistical inference becomes more difficult and the danger of overfitting or mining data becomes larger. Risk management for longer-term strategies happens in portfolio construction: since rebalancing occurs less frequently, more care needs to be taken to ensure the portfolio is not exposed to unintended sources of risk. Because they tend to have lower Sharpe ratios, longer horizon strategies have a different kind of capacity issue—the capacity for pain. However, there is one advantage: because trading occurs less frequently it’s possible to lead a much better lifestyle than if you’re running shorter horizon strategies!
Letter to a friend who just made a lot of money by Graham Duncan
- One of the best things I've read on delegation To allocate decision space they used a basic formula: credibility = proven competence plus relationships plus integrity
Identify what you’re good at and how you’re going to use that strength
Our founding client, the CEO of a large home builder, is fond of saying that it’s common for people to make money like professionals and then invest it like amateurs. Warren Buffett says that if you don’t know who the dumb money at the poker table is, you’re the dumb money. In order to avoid being the amateur or the dumb money, I would first try to establish what you and people who know you well believe you have a lot of credibility in doing.
Delegating “decision space”
General Stan McChrystal, who together with his chief of staff, Chris Fussell, led the U.S. military’s Joint Special Operations Command, observed that their job in running all of the special forces units in Afghanistan was to assess the various team captains’ credibility and then give them the appropriate amount of “decision space” based on that assessment. To allocate decision space they used a basic formula: credibility = proven competence plus relationships plus integrity.
I see the task of managing a pool of one family’s or foundation’s capital as essentially that same exercise — assess people’s credibility on a given activity, and then give them the appropriate amount of decision space based on that assessment.
What you need to do is assess your own credibility and that of potential partners, and then decide how to divide up the decision space over your capital. It’s important to take your own ego out of it and assess your own comparative advantage with clear eyes. Warren Buffett gave his entire savings to the Bill and Melinda Gates Foundation to manage his charitable giving; he had a quiet ego and saw that they could do it better than he could ever realistically do himself. Bill Gates owns a ton of Berkshire Hathaway because he knows that Buffett is much more credible on making investments than Gates will ever be himself.
The bottom line is that giving your team captains both autonomy and accountability is critical.
The no-man’s land, which we see people fall into all the time, is where the capital owner wants to have one foot on the playing field and one foot off, suggesting ideas to the manager of the capital without having to execute them. That puts the manager in a uniquely bad position: if they pursue the investment and it doesn’t work, they get the blame; if it does work, the owner gets the credit. Several prominent family offices have gone through way too many CIOs to count because of this dynamic; now no one credible will ever again take the job because they correctly realize that it’s a “tails you win, heads I lose” proposition.
Figure out how you’re going to build trust with your manager
Assessing credibility and building trust is a skill, and it’s learnable.
I have a question I ask candidates when I’m hiring them for a skill set I don’t have: “if you were going to hire someone to do this, what criteria would you use?” The answer is often wildly different for apparently similar people with similar backgrounds and reveals what they believe to be critical based on their experience.
When it comes to a CIO to manage your capital, I would answer that question with the following criteria:
A) Someone who can provide evidence that they have good “taste” in people; has an ability to assess other people’s credibility and give them the appropriate amount of decision space; and attracts the top talent by exuding an attitude of abundance about fees and opportunities, an implicit message of “let’s compound our capital together”
B) Someone with a “quiet” ego who is pragmatically focused on making money for you (and themselves, assuming they have incentive compensation), not on scoring style or status points or constantly proving to you how smart they are — as Taleb puts it, deep down they want to win, not win an argument
C) Someone who is conservative by nature; hates losing money with a passion but, paradoxically, can still take “good” risks; and has that unusual mix of aggression and paranoia
- I’ll close with Taleb’s observation that the stoic Seneca understood that success has the potential to make you fragile:
When you become rich, the pain of losing your fortune exceeds the emotional gain of getting additional wealth, so you start living under continuous emotional threat. A rich person becomes trapped by belongings that take control of him, degrading his sleep at night, raising the serum concentration of his stress hormones, diminishing his sense of humor, perhaps even causing hair to grow on the tip of his nose and similar ailments. Seneca fathomed that possessions make us worry about downside, thus acting as a punishment as we depend on them. Even more: dependence on circumstances — rather, the emotions that arise from circumstances — induces a form of slavery.
I meet a lot of rich people and many of them are what Taleb and Seneca might describe as surprisingly fragile — the events of fate pose more downside than upside for them. Don’t let your new fortune make you fragile!