Forecasting, Causality, the Black Swan, and Your Edge
In currency trading, we need only concentrate on two things: the consensus rational and the potential for surprise to the consensus rationale, asserts Jack Crooks of Black Swan Capital.
“Those who have knowledge, don’t predict. Those who predict, don’t have knowledge. “
—Lao Tzu, 6th Century BC
I shared this seemingly simple equation with you recently; and today I would like to add a few comments and delve deeper:
The currency equation of expected total return:
↑Expected Total Return = ↑Interest Yield + ↓Inflation + ↑Future Exchange Rate
This equation says the primary rationale for holding a particular currency is to maximize total return, and expected total return is a function of the real yield achieved (nominal interest rates minus the inflation rate) and the future exchange rate (that which we are trying to forecast).
Do rising real yields cause the exchange rate to rise? Or is it a rising exchange rate, impacting the fundamentals, which leads to rising yields?
In the real-world prices are driven by a tangled web of rationales which manifest into a complex array of feedback loops. I think this explains why it is so painfully difficult to determine which variables lead and which follow in a supposed correlation. The word “supposed” is used because correlation is not causality; and worst still, causality itself is suspect as Sir Karl Popper explains (below).
I could give you plenty of examples of when a currency’s relative yield dropped, yet the currency soared, and vice versa. It is rarely an A+B=C causation (though I plead guilty at times pretending it may be that simple).
In fact, if you were to stop and calculate the odds of forecasting correctly based on your inherent A+B=C causality mindset, you might start to question the efficacy of ever forecasting again.
“In chess, there are 400 different possible positions after the opening two moves.
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