Perseid Macro - Understanding Global Liquidity, Part 1: Credit Conditions Matrix

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Understanding Global Liquidity, Part 1: Credit Conditions Matrix

As Stanley Druckenmiller said, “Earnings don’t move the overall market;…It’s liquidity that moves markets.Liquidity drives assets prices.” When he said it, he meant liquidity created by the Fed. In our new global world, we have to take a wider view. Excess liquidity created anywhere (Japan, Germany, Switzerland, China) will flow across borders looking for the highest returns, with the potential to drive up asset prices in surprising places (and crash those prices when the liquidity is removed).

Liquidity is impacted by the Fed, the ECB, the BOJ, and many other global actors all at once. Today, global liquidity is the single most important factor in understanding the current investment environment.

In this series, I’ll be trying to understand today’s global liquidity environment and how we got here. This is an on-going process for me—I’m far from a scholar, having just started my exploration of these factors 10 months ago.

I have to thank Alex at Macro Ops, Jeffrey P. Snider at Alhambra Partners, Luke Gromen at The Forest for the Trees, and Darth Macro for providing so much great information about this topic. Their writing has been critical in helping me ramp up on my understanding of this topic. However, these guys are all so smart and so expert in their understanding of the global financial systems, it has taken me a lot of work to be able to create a useful mental model of what they’re talking about.

This series has grown out of my attempts to understand these diverse, informative viewpoints and create my own personal framework for understand global liquidity. Hopefully, it’ll help other people make sense of these viewpoints—I’m sure it’ll help me clarify my thinking to write it.

On to Part 1!

Credit Drivers

Understanding liquidity means understanding credit. There are $4T actual dollars in the US economy, which support something like $60T in US-based credit. No one really knows, though, because credit can be created by any two parties willing to engage in a credit transaction.

The global balance of “money” vs credit is just as skewed—meaning that changes in credit are the determining factor in rising or falling liquidity.

So far, so good. What drives credit?

Interest Rates as a Driver of Credit Supply

The classic model of credit is that interest rates drive credit—especially short term interest rates, set by the Fed, which impact the cost of capital to banks. The banks then respond to changes in their cost of capital to increase or decrease their lending activity. In this way, the Fed has a throttle on credit creation and liquidity conditions.

Notice that the classic model focuses entirely on the Fed. As viewed through the core-periphery model, the US is at the absolute center of the global financial system because it controls the global reserve currency (the currency used in international transactions).

In this model, the Fed indirectly controls global liquidity, because all other players must react to Fed actions. If the Fed raises rates, all other countries must raise rates or see capital flow out of their countries into USD assets—causing (usually) undesirable economic knock-on effects.

And, as far as it goes, this model is true. If all other things are equal, then higher interest rates = tighter credit and lower interest rates = looser credit.

Interest rates are the price of credit. Since the price of things is generally set by supply and demand, the logic goes:

  1. If prices are low, there must be ample supply compared to demand (so credit is freely available, i.e. loose)
  2. If prices are high, there must be a large demand for credit compared to supply (so tight credit)

This logic is an extension of commodity pricing models, where it makes obvious sense and has been quite successful in predicting future outcomes. The thinking is that money is just another commodity.

Through some lenses, that may be true, but the market has shown that, if money is a commodity, the drivers of this market are different than for other commodities. This is a one-dimension view of credit—and the reality is that there is another critical factor driving credit: risk-tolerance.

Risk Tolerance as a Driver of Credit Supply

Over the past centuries, a number of economic thinkers have put forward the interest rate fallacy:

The interest rate fallacy says that low interest rates are not the cause of loose credit, but rather the effect of tight credit. The idea that interest rates drive credit tightness is a degenerate case that only holds true when certain, more dominant, environment factors are absent.

One of those dominant factors is risk tolerance on the part of creditors. What if creditors suddenly feel that the risks of lending are no longer worth the rewards? Credit would be hugely impacted, but not uniformly impacted. The process would look something like this:

  1. There is a healthy debt market where loans are being made between large pools of capital and would-be borrowers
  2. The fear of increased risk dramatically increases the bar of credit worthiness that would-be borrowers must meet to get a loan
  3. This instantly and severely decreases the pool of qualified borrowers
  4. Yet, the amount of capital seeking to earn a yield through debt instruments remains unchanged
  5. For those who meet the new ultra-high bar for credit worthiness, there is an almost unlimited supply of cheap credit. The only borrowers who meet the new lending criteria are governments and the largest corporations.
  6. Borrowers who don’t meet the bar are left unable to get credit
  7. Interest rates are determined by the clearing price for credit. They are set by the transactions between the now-outsized pool of lenders and the now-tiny pool of qualified borrowers. Therefore, they’re super low.
  8. For the borrowers who can no longer get credit, the lack of credit cuts off productive investment. Overall economy growth grinds to a crawl.
  9. Slow economic growth shows up as lack of inflation, justifying lenders’ propensity to lend money at really low interest rates to those who qualify.

That’s how a sudden risk aversion can cause both low interest rates and low growth. What might cause this risk aversion? Primarily, it’s caused by the fear that borrowers will default on the loans and the lender will lose not only interest but principal.

The 2008 financial crisis clearly gave plenty of people a reason to fear that—and it was followed by the 2011 banking crisis (and sovereign debt crisis) in Europe and the sell off in junk bonds in 2014. Given our recent history, who wouldn’t be afraid of losing their principal when making loans?

In order to get out of this slump, somebody needs to go first. Someone has to take the risk of lending to people who will productively use the debt. Their profits will slowly shift the risk tolerance of all other creditors.

Growth Expectation as a Driver of Credit Demand

On the opposite side of the market, there’s credit demand. There are any number of things that can kill credit demand:

  • An impulse event that disqualifies many borrowers for a time (for example, post-real estate bubble bankruptcies in the US)
  • A deeply ingrained aversion to credit (as displayed by the survivors of the Great Depression)
  • A fear of deflation (which I’d expect to be an important factor in Japan, with 25 years of stagnant growth after their bubble popped)
  • A lack of consumption (people might try to launch new businesses, but they’d find it impossible to generate the initial revenues that would cause follow-on borrowing for expansion)
  • Overbearing regulations (much of the borrowing is by small players who would not find new ventures profitable after sky-high compliance costs)
  • Anti-competitive environment (if large companies have too much market power or if they engage in anti-competitive practices like frivolous IP lawsuits, small companies get crushed before they can grow)

What happens when credit demand falls off? You also get low growth and low interest rates. But this problem is much harder to solve—there are likely deeply ingrained psychological fears or structural issues that need to be overcome to spur demand. Those fixes might also be slow acting, and we’ve seen how lacking the attention-span of modern democracies can be.

A 2D Model of Credit

Adding a view of risk tolerance, we can create a 2-dimensional Credit Conditions Matrix:

Credit Conditions Matrix

In our matrix terms, credit “tightness” references the difficulty or ease of qualifying to borrow, as separate from the price of borrowing. After all, what difference does all-time-low mortgage rates make to you, if no one will approve your loan?

With this view, we can see that, in 2017, we find ourselves in the bottom left corner of the matrix—not a great place to be. We got here because we spent 2002 - 2007 in the top left corner of the matrix—which felt nice at the time, but lead to a hell of a hangover. The 1980’s had the magic mix of high interest rates and loose credit that allows a lot of real growth while holding malinvestment in check.

Also note, the traditional, one-dimensional view of credit “tightness” makes perfect sense as long as we’re in the top-right corner of the matrix. When credit is highly available and interest rates are high, the credit qualification process still serves as a selection-factor, but one that’s not very constricting (leaving a large pool of qualified borrowers demanding credit). The high interest rates then set the bar for the IRR required to get the loan. When the interest rates are lowered, the IRR hurdle rate is lowered, more projects clear the bar, more credit is issued, and economic activity accelerates. When interest rates are raised, the IRR hurdle rate is raised, fewer projects clear the bar, less credit is issued, and economic activity slows. When we’re in this quadrant, interest rates function as a throttle on credit supply and economic activity as described the classic model—but only when we’re in this quadrant.

There is one exception to the matrix structure: low credit demand. The matrix assumes a constant, large demand for credit to pursue positive-IRR projects. If, for whatever reason, we find ourselves in a society where potential borrowers have been conditioned to avoid credit at all costs, then the picture can look quite different. Any time we also have low credit demand, the contents of that box would be:

  • Causes
    • Systemic fear of borrowing
  • Effects
    • Low velocity of money
    • Low economic activity
    • Deflation
    • Excessive saving

The biggest difference will be when we’re in the top-left corner (Loose Credit and Low Interest Rates). While there may also be impacts to the other matrix boxes, the top left box represents the loosest possible credit supply conditions—and thus the largest potential impact of low credit demand.

Next Up

In Part 1 here, I’ve tried to create a common foundation of understanding the drivers of credit, in abstract. Using the Credit Conditions Matrix, we can hopefully get a much better understanding why the economy is doing what it’s doing, if we understood how tight or loose the credit qualification process was.

Part 2: Eurdollars will begin the investigation into the the real world machinery underlying the credit creation process.

DISCLAIMER: None of this intended as investment advice. This is a place for me to put down my ideas and share them with others, whom I fully expect will tear these ideas apart. I have no professional training or certifications, and I've probably already changed my mind on whatever you just read.