The business cycle is a combination of multiple cycles consisting together in a push-pull relationshipa.
Current methods for forecasting based on extrapolation has historically been wrong, and the ongoing use of the process will continue to output unreliable forecasts.
We choose to use a different method in our analysis, leading indicators. Using indicators to find turning points in the economy is a better alternative than extrapolations.
“Investing is a matter of preparing for the financial future. It’s simple to define the task: we assemble portfolios today that we hope will benefit from the events that will unfold.”
Cycles Within Cycles
The business cycle represented by the fluctuation of Gross Domestic Product (GDP) above or below the potential aggregate output of an economy follows a natural path of contraction and expansion. It is common knowledge that the events regularly support each other in a usual sequence: upswings followed by downswings, and eventually by new accelerations.
But to have a full understanding of cycles, that is not enough. The events in the business cycle shouldn’t be viewed merely as each being followed by the next, but, much more importantly, as each is causing the next. Understanding the causality of the business cycle will give a practitioner and advantage to anticipate the next phase beyond what an observer can quantify.
The most crucial aspect of causality in the business cycle is an understanding that a business cycle does not operate in a vacuum. Just because expansion takes place above the pace of the potential output does not alone cause a recession. Other factors influence the path of the business cycle; this is where my theory of “cycles within cycles” begins.
There are several primary cycles to consider; the profit cycle, monetary policy cycle, growth rate cycle, interest rate cycle, inflation cycle, and so on. Some sequences are sector-specific, like a cycle in durable goods, housing, and industrial production. Some cycles are independent of each other but are often influenced by each other. Some affect different sequences more than others, while others extend further away from there anchor than expected (bubbles). When we study the business cycle, we focus on all of the primary cycles in our rubicon, and they all influence each other.
As I see it, the problem with current forecasts of the business cycle fails to consider the independent periods that drive each other. Most forecasters probably use some statistical model designed with machine learning or regression analysis to extrapolate into the future. They might be putting in all of the usual suspects and figured out correlations and then extrapolating and making forecasts for growth or inflation or jobs or whatnot and saying, okay, here is where we are in the cycle. The worst of the models are ones that estimate based on the period lasted x years; so we are early or late based on that time.
We don’t use models for forecasting. Models are useful for identifying correlations and relationships between the different cycles, but often fail to predict anything. If you look at the research– and there’s quite a bit of research on this– systematically, the most significant errors in forecasting– kind of like small-cap prediction or something like that– will occur around turning points in growth and inflation and jobs, turning points and pretty much anything simply because the models like to extrapolate. And they miss the turn. And they only see it in the rearview mirror. And that’s why you get these surprises.
We Are Different
One of my significant influencers Geoffery Moore, as the father of leading indicators, created the first index for the United States some 60, 70 years ago. His mentor, Wesley Mitchell, actually defined what a cycle was back in– 100 years ago. And these leading indicators are designed to turn ahead of the target.
So, for example, let’s say I am trying to predict a turning point in production. Well, in theory, new orders could be a leading indicator of production, and it makes sense. You don’t have to be a rocket scientist to figure that out. So basically, we have both short and long leading indicators designed to react before a coincident indicator does. If the short leading indicator confirms the long leading indicators, we then look for a confirmation in the coincident indicator before making a call on a direction. Lagging indicators used to confirm the decision we already made.
Our theory is not new; past Fed chairman has used such methods. Former Fed chairman Allan Greenspan was a student of Geoffery Moore and was able to avoid the Fed heating up the economy in the mid ’90s by use of leading indicators. Today, Moore’s legacy can found in firms such as ECRI and NBER, the group that defines and identify recessions.
Monitoring each smaller cycle is just as important as tracking the entirety of the business cycle. Thus, our approach to the financial markets is an understanding that financial markets, sectors, domestic economy, and foreign economies all follow a rhythm, while not always the same, they do follow a pattern influenced by other cycles. By segregating the business cycle into smaller, more managed components, we can have a clearer perspective of the aggregate.
Furthermore, we do not extrapolate to predict the flow of these cycles, which inherently causes missed turning points. Instead, we use leading indicators confirmed by coincident indicators to identify turning points. Each cycle influences assets in different ways, and these factors diligently drive the performance of asset classes through various stages of the business cycle. Risks change as our position in the cycles change.
“The odds change as our position in the cycles changes. If we don’t change our investment stance as these things change, we’re being passive regarding cycles; in other words, we’re ignoring the chance to tilt the odds in our favor. But if we apply some insight regarding cycles, we can increase our bets and place them on more aggressive investments when the odds are in our favor, and we can take money off the table and increase our defensiveness when the odds are against us.”
Identifying where we are at in the primary economic cycles provides us with insight that will help guide our investment decisions. After all, we believe that the world can be explained by math; our process is designed to seek understanding of the forever changing financial markets. Our goal is to use this knowledge to manage our client’s wealth around the macroeconomic environment in attempts to provide the best odds of higher returns and lower risk.
Learn more by talking to your financial advisor, if you don’t have a financial advisor, we would love to hear from you.