What’s driven the S&P 500 Index for that past eight years or so? It’s the Federal Reserve, says economist Brian Barnier, a principal at ValueBridge Advisors and founder of FedDashBoard.com.

Speaking recently on Yahoo Finance, Barnier explained what happened when he looked at the impact of four factors on public equities: future (or forward) GDP, monetary policy, open market paper (commercial debt) and household debt.

“If we filter through … things … from the 1970s … for powerful factors,” he said in a televised interview Friday, by “taking out the snippets that worked,” in other words applying regression and other analytical tools, the economist is able to zoom in on which of the four factors most influenced the performance of the S&P 500.

“We had our tech bubble, our credit bubble and then our Fed bubble,” Barnier said.

The Fed used several trillion dollars to buy bonds. That quantitative easing policy, he says, means the Fed was essentially responsible for more than 93% of the market’s movement. Plus, the Fed caused the entire market’s growth in the first six months of 2013.

“That’s the beauty of the visual analysis,” he said. “All we have to do is find straight, stable lines and we know we’ve got something good.”

From November 2008 to October 2014, the S&P 500 roughly doubled in value, thanks to QE.

“This is amazingly stable; it is the strongest factors going back to the history [since] World War II,” Barnier stated.

With QE coming to an end in 2014, it’s time for investors to pinpoint the next driver, he adds.

“Quantitative easing has stopped, but now we’re into the interest rate world,” he said. “That means for any investor trying to figure out what to do, step one is starting with a macro strategy.”

As for earlier periods, future GDP estimates explained 90% of the market movement through the mid-‘70s, his analysis shows.

Next, household debt expanded and is tied to 95% of market movement through the early ‘90s.

The tech bubble came next, with Barnier’s research finding that commercial paper increases explain as much as 97% of that development.

The housing bubble emerged shortly thereafter and contributed to 94% of the market’s move through around 2007-2008. 

Analyzing the Analysis

Investors and other readers posted more than 960 comments about Barnier’s conclusions, prompting the economist to post a response on FedDashBoard.com.

“Regarding the recent ‘Fed era,’ then-Chairman [Ben] Bernanke laid out the history and expectations nicely in his 2012 Jackson Hole speech,” the economist said.

As for future analysis, methods of prediction should be adjusted going forward, he says, for the following reasons:

  • Data have changed, such as in the credit distribution in households;
  • The Dodd-Frank Act has completely reshaped open market paper; and
  • The Federal Open Market Committee is “struggling with the clash between outdated theory and today’s economy being reshaped by technology and related forces (global capacity, sharing economy or online search for better products at better prices).”

Barnier admits that “there were other influences” beyond the Fed on the market since 2008. However, his analysis aims “only to show the power of a single factor.”

And, as all good statisticians know, correlation is not causation. “This is a big problem when commentators say ‘lockstep’ because of a loose visual association of two lines,” he added.

As for a commenter, “an apparent physicist who noted [that Barnier’s analysis] assumes that the relationship between the stock market and other factors is purely linear, but makes no attempt to justify that model,” the economist explains his methods as follows:

First, he “did not mean to give an impression of linear relationships at all stages of analysis, but rather that more explanatory power creates more stable, horizontal lines on a chart.

And, second, that the tools used for these conclusions are “not the same tools that failed to predict the housing bubble busting.” (See Treacherous Triangle.)

Barnier says the method he relies on “is just graphical econometrics, also used for some types of problems in operations research, quality management and such.”

The aim of the analysis is to help visual learners, and “it works for linear, curved functions and stochastic data. It’s especially satisfying for students as they can ‘see’ themselves solving the problem the closer the solution gets to a stable line with only true random variation,” he explained.

— Check out Warning: Don’t Party Over This Market Rally, BlackRock’s Koesterich Says on ThinkAdvisor.