What does “excess liquidity sloshing around the financial system” mean?

In the recent Odd Lots AMA episode, financial journalist Tracy Alloway said

…I coined the term ‘ China’s Great Ball of Money.’ This idea that you just have a bunch of  extra money that’s in a closed financial system and it’s just rolling from thing to thing. So it’ll go into housing and then it’ll go into stocks and then it’ll move back somewhere else. But if you expand that, you know, China’s an extreme example of that, but if you expand that to the whole world, I don’t think it’s a massive stretch to say that there is a lot of excess liquidity sloshing around the financial system and it needs to find a home somewhere.

This is one instantiation of an idea that was omnipresent in 2021-2022—that much of the weirdness in financial markets, from GameStop to crypto to stock market volatitlity, was driven by an excess of liquidity. This idea made a certain amount of inarticulable, pre-intuitive sense, but that sensibility does not a gears-level understanding make.

What are we going to do with this pre-intuition? The same thing we do with every pre-intuition: try to build a toy model! Imagine a market in a single asset, a claim on a fixed future cash flow. New claims can always be created for some fixed price; existing claims trade at some variable discount to that price. Claims are bought and sold by savers, who want to get some rate of return on their investment greater than their discount rate. Basically if the price is bigger than the net present value of the claim, savers are going to be unhappy.

(The obvious example of this kind of asset is a perpetuity, like the UK consols that were, and if you squint a little long-term bonds also fit. But I find more helpful to think about real-estate or widgetmaking. In real estate, if people are looking for a place to park capital they can invest in building new apartment buildings, which indefinitely throw off some amount of rent, net of maintenance etc. In manufacturing, a widgetmaker can sell new shares; the it uses the new capital to buy a new widget-making machine, which makes every year some number of widgets that the widget maker can sell for some profit that it passes on to investors.)

In this toy model, the market changes behavior when the rate of return generated by buying and holding crosses the participants’ discount rate. When the rate of return is high, savers can achieve their goals by buying, holding, and harvesting the resulting cash flow. When it is low, they must turn to other strategies: leverage, arbitrage, momentum trading, more sophisticated quant trading, and “beauty contest trading“: betting on what others will find popular, for (arguably) extra-economic reasons.

This toy market provides a nice story about retail investor behavior in 2020-2021. A bunch of people had cash burning holes in their pockets, due to shutdowns and stimulus. They weren’t satisfied by the general rate of return on, I don’t know, savings accounts or treasury notes or blue-chip stocks or the S&P500—viz., that return was below their discount rate. So they (we) turned to more exciting places: Gamestop, crypto, various stocks trading according the Elon markets hypothesis.

Yes, the resulting prices were disconnected from underlying economic reality, but that’s the whole point. In that same Odd Lots AMA episode, Joe Weisenthal said

Well, you know, look. I’m a markets reporter. I always have been. And people ask me what’s [a market]? And I always say completely unironically, it’s a line that goes up and down. If there’s a line on a screen that goes up and down, it’s probably a market story. And crypto is like the ultimate line that goes up and down.

When (1) you have excess savings and (2) you don’t see any assets whose net present value is worth the price, one natural place to turn is betting on whether the line is going to go up or down.

This toy market also provides a nice story about why there was so much large-scale, more or less blind investment in private companies in 2020-2022. I periodically read about Tiger Global more or less spraying pre-IPO tech companies with pension fund money. Why would they do this?

Say you’re a pension fund: you have cash now and liabilities in the future, so you’re trying to achieve some rate of return that will let you meet your liabilities. In my single-asset toy market, this is hard to achieve. One option is to turn to “a market is a line that goes up and down” strategies, like the retail investors I discuss above. But you’ve also got another option: you can go find another asset representing a (story about) a claim on a growing future cash flow, i.e. an early-stage tech company. If the growth rate is bigger than your discount rate, the net present value is (arguably) unbounded, or bounded only by considerations like the total addressable market! You, the pension fund, are a hero! You have snatched the victory of portfolio growth from the jaws of unfunded-liability defeat!

This story about growing future cash flow doesn’t actually have to be true—you just have to persuade yourself that it’s true, or let somebody else persuade you. After all, what else are you going to do? You have this huge amount of money to invest and nowhere (satisfactory) to put it, and Chase Coleman comes into your office and hands you a great place to put it. What are you going to do, say no? So you maybe don’t look quite as skeptically at the opportunity as you would if you had better options, and you invest in Tiger Global, and Tiger Global invests in lots of startups, and valuations go up and everybody is very happy, for at least a little while.

(A similar effect is probably at play when retail investors buy crypto or Tesla. We don’t have access to, idk, oxide.computer , so we have to tell ourselves stories about how a token for SBF’s famous box or a share in Tesla represents a claim on an unbounded, growing future cash stream. This reasoning may be most important insofar as it provides top cover for “line that goes up and down” investing.)

This is all a nice story, but how can we tell if it’s true? The obvious thing to do is model our toy market, and see if there are signatures in price or flow data. This would require specifying the toy market a great deal more precisely: value investing is maybe not so hard to specify, but what exactly should we have in mind when we talk about “line that goes up and down” strategies?

from Hacker News https://ift.tt/mOJ8fck