Among many factors, market price trends are affected by broad shifts in economic conditions. One might say the economic input accounts for a percentage of the pricing function, particularly at the index level.

Hence, when expectations about economic data points shift, the market shifts as well, often powerfully. At times, however, those expectations shift excessively and unjustifiably. We believe that, in theory, this can sometimes happen as simply a function of the force of a powerful socio-cultural tide of mood. In the end, even economists are people. And people tend to get swept up in that tide, often in its final stages.

Market analysts who employ investor and trader sentiment data have long known this. And there are many quality indices of such data that often provide important indications that markets are overshooting the mark in one direction or the other. Our goal here is to attempt to develop a measure for when economic forecasting might be suffering from similar "tails" of subjective exuberance or panic.

Of course, sometimes economic activity is ruled by such tides as well, and economic data forecasting benefits from being in sync with that momentum. But other times, more importantly, the data show a different picture from the tide of sentiment. It is precisely at such times that market participants can most benefit from noticing the disparity.

Our plan is to begin tracking this regularly and highlighting any instances as they come about when we see particularly notable trends of deviation between the tide of expectations and reality.

The Federal Reserve Bank of Chicago created an index in 2001 that evaluates current economic conditions in the U.S. The purpose was to develop a real-time index that could track business cycle expansions and contractions.

The Chicago Fed National Activity Index (CFNAI) utilizes 85 different monthly indicators that are drawn from four categories of data:

1) production and income (23 series) 2) employment, unemployment, and hours (24 series) 3) personal consumption and housing (15 series) 4) sales, orders, and inventories (23 series).

Each series is individually weighted so that the index tracks the co-movement of all of the economic indicators. The weights are rebalanced each month, but the revisions tend to be small and have little effect on the overall time series. Furthermore, each data series is standardized so that each has a mean of 0 and a standard deviation of 1. The purpose of the standardization is to show that when the index is above 0 the economy is expanding at a faster rate than its average growth rate. If the index is equal to 1, the economy is moving one standard deviation faster than its average growth rate. The opposite is also true.

We have found that the CFNAI is the best indicator for showing if the economy is currently in a recession. Going back to 1970, the index has never falsely predicted that the economy had entered a recession. Only twice, in 1970 and 1974, did the indicator not predict the start or end of a recession within two months of the actual business cycle date.

The CFNAI does not include any inflation indicators. The Chicago Fed reasoned that when economic growth was moving above trend, the economy would already suffer from high inflationary pressures. Adding specific inflation data series into the model would then double count the effect of inflation on the business cycle.

To see how economists view the economy, we first created an economic activities index that matched the accuracy of the CFNAI in predicting business cycles, but utilized the available data that economists forecast. Next, using the same data series, we created an index consisting of Briefing.com consensus forecasts to determine real-time economic sentiment.

In order to develop these indices, we adjusted some of the properties of the CFNAI to meet our data requirements.

First, the economists in the consensus only forecasts 50 economic variables each month and some of them, like retail sales and retail sales excluding transportation, are redundant.

To compensate for the difference in the number of data series, our Briefing Research Economic Activity Index (BREAI) utilizes the same four broad categories of economic data described by the CFNAI, but we aggregated the 85 individual variables into 16 forecasted series. We then adjusted the 16 series so that the weights of the broad categories in the BREAI and CFNAI exactly matched. The series and weights are shown below.

Further, instead of a monthly index, which would lag movements in the S&P 500, we calculated the BREAI on a daily basis. As soon as a new economic release is issued, the old data utilized in the index is replaced by the new data. Any shock to economic output, good or bad, would show up immediately in the data. This way, shifts in the BREAI are synchronous with related market reactions.

Finally, the market reacts mostly to the new incoming data. Any prior revisions tend to be discounted. To account for this, the BREAI only utilizes the initial released data points. None of the revisions are used.

Using the original CFNAI releases (excluding all revisions to the data) shows the BREAI and the CFNAI follow each other with a correlation of 78.7%. With such a high correlation, the BREAI is nearly as accurate as the CFNAI in predicting the business cycle.

We developed a Consensus Economic Indicator (CEI) by using the Briefing.com consensus forecasts for each data series in the BREAI. Our consensus forecasts only go back to 2000, which prevents us from developing the index prior to that date.

The CEI tells us how the consensus views the economy at any given point. When the consensus is bullish, the indicator will rise above 0. Like the BREAI, if the CEI is at 1, then the consensus believes economic growth is tracking one standard deviation above the mean.

Interestingly, the data show the consensus underestimated the troughs of the recessions and overestimated the recovery periods. In other words, economists' expectations were by and large too bearish in recessions and too bullish in recoveries.

The simple difference between the BREAI and the CEI is the Briefing Research Economic Surprise Index (BRESI). At its lowest point, in 2009, the consensus was almost 2 standard deviations more bearish than the actual data.

As noted in the introduction, our theory for developing the BRESI is that the "overshooting" phenomenon described above is a function of the same dynamic responsible for similar trends found in investor sentiment data: individual expectations are subject to group-level tides of opinion during particularly powerful trends of change.

This is easily seen in the strong correlation between the American Association of Individual Investors' (AAII) Bull Ratio (bullish sentiment as a percentage of total sentiment in the AAII survey), the Put/Call Ratio and the BRESI.

We do not have enough historical data at this stage to systematize a set of clear guidelines, but there are some interesting "moments" to appreciate in the data we do have.

First, as noted above, the period of March thru May 2009 stands out as a critical moment of deviation between expectations and reality, as economist expectations were still diving while the actual data coming in were saying something entirely different.

We can also see that both the market highs in 2000 and 2007 were marked by clear excesses in bullish economic expectations.

But there are also clearly false signals that must be taken into consideration. Those were situations when expectations ran way ahead of reality, but no serious market top was anywhere in sight. 2004 provides a good example of this. Late 2009 and mid-2010 provide additional, similar examples.

One must recall, however, that the cycle of monetary stimulus and policy management is important to include in how we view these moments. In each case, the respective recoveries were in their adolescence. At such times, economic data that come in below expectations may not be a bear item as it can mean that more easy money is on the way. In fact, during much of 2009 and 2010, the phrase "bad is good" actually became popular in the financial media.

In the end, we believe that to maintain an effective perspective on market and economic data, one must be acutely aware of the tendency for tides of opinion to sweep up and carry individual expectations beyond the reach of real shifts during forceful trends.

Our current data set suggests that key moments in the market and business cycles are marked by clear divergences, though there is also a lot of noise, and this is far from a self-contained market timing system. It is not meant to be. It is simply an input that can offer additional perspective.

Right now, we are in a period where economists are viewing the economy in a more bullish light, but the BRESI has not reached a level where sentiment is clearly diverging from economic realities. As such, the index currently does not decisively point toward a change in our expectations of market performance.

However, given how the BRESI conformed to past market movements, especially in March thru May 2009, it is best to keep an eye on its performance, and revisit it when important deviations and trends in expectations present themselves.

--Jeffrey S. Rosen, Ph.D., Economist

--Brett Manning, Senior Market Analyst