Continuing the start of 2025 exploring one of what I describe as the competing “meta-narratives”, the idea of cycles, that there are limits to growth, “trees don’t grow to the sky”. Yesterday we talked about the business cycle in general, today we’ll dig into the “Credit Cycle” and the work of Hyman Minsky in his Financial Instability Hypothesis, something we touched on back in October when famed investor Paul Tudor Jones raised the idea of another “Minsky Moment”.
When I started this theme this week it was unbeknownst to me that the great Howard Marks was going to play right into my hands (or steal my thunder) with his first memo of 2025 “On Bubble Watch” in which he reflects on the 25th anniversary of the dot-com bubble. Marks is an ardent believer in impermanence, disruption, the inevitability of cycles, psychology and that overpaying is the greatest investment risk. He’s in the camp “trees don’t grow to the sky”. His memo feeds nicely into today’s topic on Minsky and tees up tomorrow’s discussion on CAPE., we both actually referenced Kindleberger (someone’s whose quotes I shared over the holiday)....great minds think alike I suppose.
While I discussed the basics of Minsky’s framework in that previous post, one of the striking features of his hypothesis is that a capitalist economy does not depend on an external shock (war, pandemic, etc.) to generate a business cycle (though it may help to start the process), we are more than capable of generating a business cycle all on our own and often amplified by interventions from policymakers.
Minsky has a specific description of credit cycles in his hypothesis, but more generically, a Credit or Debt Cycle is a way to describe the changing availability and pricing of credit in an economy. Credit takes on increased importance in the real economy as it’s generally a necessary ingredient for business and household investment, particularly big ticket items like real estate. In general when the economy is growing, credit increases and when the economy is contracting it decreases.
That all sounds pretty benign on its face, but these credit cycles have tended to produce long and deep business cycles both on the way up (expansion, mania) and the way down (recession, panic, crash). I state this somewhat definitively because there is empirical, historical evidence as well documented by the likes of Charles Kindleberger in his 1978 book, Manias, Panics, and Crashes. But why are credit cycles so important?
In building his financial instability hypothesis, Hyman Minsky, was influenced by earlier work of Keyne’s and Irving Fisher. From Keynes, Minsky took to ideas related to the role of capital development, how financing and creation of capital assets can drive fluctuations in economic growth and also Keyne’s “veil of money” which connects money to financing through the element of time, essentially that money flows to firms in expectation of future profits, while firms can only pay back that financing through realized profits. From Fisher, Minsky was influenced by Fisher’s classic “debt deflation” theory, whereby excessive debt can lead to falling asset prices, which leads to defaults, which leads to declining economic activity, which leads to further defaults and a self-reinforcing downward spiral (interest Nine Inch Nails album too). Inherent in the earlier work of Keynes and Fisher and other classical economists such as Adam Smith, Knut Wicksell and John Stuart Mill is a view that markets aren’t always self-correcting and can experience periods of disequilibrium and that expectations can change financial structures and contribute to instability. Minsky takes things a step further and emphasizes the fragility of the system and its propensity to have a disaster.
The basics of Minky’s model (as discussed by Kindleberger) are as follows:
“Displacement” - some shock comes along that alters the economic and profit outlook for at least one important sector of the economy and this attracts investment while pulling it away from other sectors. If this new opportunity dominates the old opportunities a boom is underway. This gets further fed by the expansion of bank credit and the formation of new credit instruments and even personal credit outside of banks.
“Euphoria” - the desire to speculate fueled by credit stimulus feeds into demand, prices increase, new profit opportunities emerge and a positive feedback loop ensues.
“Overtrading” - which could mean pure speculation that prices will increase further and the use of leverage, both of which can be accompanied by an overestimation of profits. When this speculation is taken on by a large number of firms and households we potentially lose rationality and it is termed a “mania”. All the while the credit system stretches further.
“Revulsion” - eventually something spurs the realization that the market can’t go higher forever, it might be a bank failure, an uncovered fraud, but people and firms begin to liquidate and there is a “revulsion” against lending against the collateral that were being speculated on.
“Panic” - which is really just the revulsion stage going to a point where people want to get through the door before it shuts and that last until…that’s for another time.
Or to summarize, as Morgan Housel describes Minsky, “calm plants the seeds of crazy”. Stability breeds instability by encouraging excessive risk taking which leads to booms and eventual busts.
To map this model to today we can look at AI as a possible example (to be clear I’m not saying AI is a “bubble” or anything of the sort). A new technology, AI, comes along creating new opportunities, it attracts a lot of capital (see AI chip spend and data center spend), encourages risk-taking, and generates a wave of optimism. As AI proves profitable, widespread optimism takes hold, credit is available for businesses associated with this trend and perhaps exuberance pushes asset prices higher, even exceeding their intrinsic value. At some stage a belief that the good times will keep rolling sets in and businesses and investors try to leverage their bets further, which further inflates asset prices, often moving to the “ponzi” stage of financing where rising asset prices are required to refinance assets as cash flows can’t even cover the interest. In the model this would sow the seeds of revulsion, where some event eventually causes investors and lenders to re-evaluate the landscape. In the AI example, this could be some revelation that obstacles to further scaling the models cannot be overcome. A sudden shift in sentiment could lead to selling and as a result the contraction of credit. Ultimately a panic could set in as liquidation of investment holdings creates a self-reinforcing cycle.
All of this is a story of a movement through the credit cycle from “Hedge Units” where there is sufficient cash flow generated to meet contractual liability obligations, to “Speculative Units” where cash flow is sufficient to cover interest but not repay the principal - meaning assets ultimately need to be sold or refinanced to meet the commitment, to “Ponzi Units” where the repayment of the debt is based solely on the ability to sell or refinance based on an asset that has increased in value.
That seems like enough foundational cycle related stuff, tomorrow we’ll get into a valuation metric based on the idea of cycles, specifically CAPE, the cyclically adjusted price-to-earnings ratio.
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https://x.com/ohcapideas/status/1871406046943891567?s=46&t=D2AESCsaw42dAEzgmjXHQA
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