Can recessions be predicted?

Thoughts on Vega's Macroeconomic Algorithm

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From: Scott Shuttleworth

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Can recessions be predicted? The results may surprise you.


Recall that the definition of a recession is where GDP falls for at least 2 successive quarters.

GDP is the dollar value of goods produced domestically by a country. Naturally, someone has produced the GDP (i.e. production) and another has consumed it (i.e. consumption). More consumption begets more production unless we finance the difference with debt (and another nation provides the goods and services).

Hence by looking at variables which influence consumption and production significantly, we can get a rough idea about where GDP is headed. The variables Vega uses are systemic liquidity, employment levels, interest rate stress finally market momentum and I'll explain how these work in today's blog.

In the below table (please allow images if viewing in your email inbox), I’ve demonstrated the effectiveness of our algorithm over the top five worst recessions for markets over the past 50 years. Note that recessions are usually identified retrospectively by economists so these results are very strong.

And now onto the variables.


Systemic liquidity

The sheer volume of capital floating around the financial system is an important consideration in macroeconomics for two reasons.

  1. As capital becomes scarcer, less financing is able to take place which impairs the ability of consumers and businesses to spend and invest which puts downward pressure on GDP growth. The scarce capital available will usually command a higher price which also means fewer deals get financed.
  2. Economics 101 will tell you that when one commodity becomes scarcer relative to another, its price must rise (all else equal). Hence as money becomes scarce, the price of other assets should fall on a relative basis to restore some equilibrium.


Employment levels

As an individual becomes employed they gain spending power. Their spending becomes someone else’s income (either a business or individual) which can be used to hire others or spend which begets more hiring and spending. Hence as individuals become employed, the economy grows, others become employed and the cycle continues.

This is fine until some individuals become unemployed. Then they stop spending, which begins to break the cycle.

When a lot of citizens become unemployed at once (for one or many reasons), it creates downward pressure on GDP growth.


Interest rate stress

As interest rates rise, heavily indebted companies begin to struggle due to debt service burdens. Naturally, the failure of these businesses reduces employment and consumption.

Hence we want to identify points at which high-interest rates will cause problems in the economy.


Market momentum

You may have heard of the term ‘Don’t catch falling knives’ when looking to buy falling stocks? The same goes for when we’re trying to short – the algorithm tends to do better by letting some of the bubbliness fizz out of the market before shorting.

There is a slight amount of wealth effect noted here, but it’s not the primary purpose of this variable.


To sum it up

2019 is looking to be an interesting year in terms of the business cycle. As we go further through I'll provide updates on what our algorithms are seeing - but as far, the risks continue to build.

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