The first point to observe is whether the curve is generally elevated — say, around 5% — or low — say, about 1%. A lofty yield curve can be a good sign since a growing economy involves competition for funds and can lead to higher interest rates. It can also be a bad sign if the high rates are a product of inflation. In that situation, the analyst subtracts inflation from nominal rates to arrive at the real rate of interest, which can be much lower than the nominal rate shown on the curve.

A low-rate yield curve can also be good or bad. It’s good if the low rates indicate steady growth with no inflation. It’s bad if the low rates indicate weak growth and low velocity (turnover) of money. And bear in mind that in a world of zero inflation, low nominal rates can still be high real rates, even at the 2% level.

The predictive power of the yield curve is that it tends to get there first. This means that when conditions change for better or worse, the change in the shape of the yield curve is often the first signal. Other market signals (stocks, inflation, growth) catch up later.

This is what gives the yield curve its predictive power. If the yield curve told you what you already know, it would be an interesting confirmation but not highly predictive. It’s when the yield curve indicates something that the rest of the market doesn’t know that you should read the clues and position accordingly before the rest of the market catches up.

We also look at the steepness of the yield curve. If one-year bill rates are 2% and 10-year note rates are 2.7% (both about where they are today), that’s notably flat. It tells us that the market expects somewhat high rates in the short run (because of Fed tightening) but doesn’t expect high rates in the long run (because of recession risks).

The Fed part of that forecast is headline news, but the recession part of that forecast is less publicised and argued about by economists. Still, the yield curve is signalling a recession with negative implications for stock prices. That’s a powerful signal you shouldn’t ignore.

**The future is here (if you know where to look)**

One of the best tools is Bayes’ theorem. The way to use Bayes’ theorem is to begin with a hypothesis about where markets are going. You make an estimate using the best information available. If you have no information, you just assume a 50% probability.

For example, today, I assign an 80% probability of a 0.5% increase in the policy rate at the next Fed meeting on 15 June 2022. That’s not much of a guess because the Fed has already told us what to expect.

[**Note:** This article was adapted from an early June 2022 edition of *Strategic Intelligence Australia*. Therefore, some dates mentioned may have already occurred.]

Then you begin a process of updating the figures using new information. Each speech or public testimony of every Fed official is examined to see whether it confirms or refutes the hypothesis. Assuming Fed officials are consistent in suggesting a 0.5% rate hike and there are no dissenting voices, then I might gradually dial my probability up from 80% to 85% and maybe even 90% on the day of the Fed meeting. (You never set the odds at 100%; there should always be some allowance for the unexpected.) It’s simply a matter of starting with a good estimate and then dialling the odds up (or down) based on new information as and when it appears.

A more difficult analysis might involve predicting whether the stock market will be higher or lower at year-end. This is more difficult because there’s no policy board like the Fed telling us what the target is, there’s a longer time horizon, and there are far more variables in the mix, including bond markets, commodity prices, supply chain breakdowns, consumer demand, and the war in Ukraine, among others. Based on the best information available today, I might set the odds of the stock market being lower by year-end at 65%.

As each day goes by, one would look at a long list of indicators, including GDP updates, retail sales, real wages, corporate earnings, interest rates, commodity prices, foreign exchange rates, labour force participation, and more. Based on this new information, one would continually update the 65% probability up or down depending on the substance of the news. By next September, I might have moved the probability to 80% or perhaps lowered it to 40% if a wave of good news emerges. The Bayes process (which is mathematically based) results in extremely accurate forecasts over time.

Of course, Wall Street looks at the same variables we use. The difference is that Wall Street uses regressions and correlations to make forecasts on the assumption that the future will resemble the past. Our team uses Bayesian mathematics on the assumption that the future is path-dependent, and by following the path (data updates), we can see the destination before we arrive.

**A forecaster would rather be approximately right than exactly wrong**

In addition to fractal mathematics and Bayes’ theorem, we have other advanced tools in our toolkit that aren’t well understood on Wall Street. These include complexity theory, behavioural psychology, history, natural language processing, and a new branch of applied mathematics called fuzzy cognition.

Don’t be put off by the word fuzzy. It’s just a recognition that a forecaster would rather be approximately right than exactly wrong. We don’t have time to explore all these concepts in this article except to say that it’s a full toolkit, and all these tools help us to discern the future. Again, the future is not entirely in the future. A lot of it is present today if you know where to look.

With that as a background, we turn to one of the best places to look for clues about the future of markets. That place is the yield curve. Almost everyone on Wall Street knows what a yield curve is, but very few know how to read them correctly for powerful indicators of the future of the economy. For that matter, there are many different yield curves that convey information in different ways — some more powerfully than others.

In this series of articles, we examine some of the most important yield curves and explain what they’re telling us about the future of the economy and markets.

We’ll begin with an explanation of what yield curves are, explore the variety of yield curves, and then finally do a deep dive into the single most powerful indicator coming from one of the least-understood yield curves of all.

Don’t worry. We can put all of this into plain English, and no maths is required beyond the fifth-grade level. The hard part isn’t the maths — it’s knowing how to interpret the signs.

Keep an eye out for the next instalment of this four-part series in the New Year, where Jim delves into yield curves and their impact on interpreting figures in the market.

**All the best,**

**Jim Rickards, Strategist, The Daily Reckoning Australia**

This content was originally published by *Strategic Intelligence Australia*, a financial advisory newsletter designed to help you protect your wealth and potentially profit from unseen world events. Learn more here.

The post Keeping Ahead of the Power Curve — Part Two appeared first on Daily Reckoning Australia.