Non-Farm Payroll (NFP) Forecast – December 2013

This article presents the Trader Edge aggregate neural network model forecast for the December 2013 non-farm payroll data, which is scheduled to be released tomorrow morning at 8:30 AM EST.

Non-Farm Payroll (NFP) Model Forecast - December 2013

The Trader Edge aggregate NFP model represents the average of three neural network forecasting models, each of which employs a different neural network architecture.  Unlike expert systems, neural networks use algorithms to identify and quantify complex relationships between variables based on historical data.  All three models derive their forecasts from seven explanatory variables and the changes in those variables over time.

The table in Figure 1 below includes the monthly non-farm payroll data for two months: November and December 2013.  The November data was released last month and the non-farm payroll data for December 2013 will be released tomorrow morning at 8:30 AM EST.

The model forecasts are in the third data row of the table (in blue).  Note that past and current forecasts reflect the latest values of the independent variables, which means that forecasts will change when revisions are made to the historical economic data.

The monthly standard error of the model is approximately 78,600 jobs.  The first and last data rows of the table report the forecast plus 0.5 standard errors (in green) and the forecast minus 0.5 standard errors (in red), respectively.  All values are rounded to the nearest thousand.  If the model errors were normally distributed, roughly 31% of the observations would fall below -0.5 standard errors and another 31% of the observations would exceed +0.5 standard errors.

The actual non-farm payroll release for November 2013 is in the second data row of the table (in purple).  The consensus estimate (reported by Briefing.com) for December 2013 is also in the second data row of the table (in purple).  The reported and consensus NFP values also include the deviation from the forecast NFP (as a multiple of the standard error of the estimate).  Finally, the last column of the table includes the estimated changes from November to December 2013.

Figure 1: Non-Farm Payroll Table December 2013

Figure 1: Non-Farm Payroll Table December 2013

Model Commentary

The aggregate model forecast for December is 270,000, which is up 55,000 jobs from last month's revised forecast of 215,000.  The Briefing.com consensus estimate for December is only 197,000, which is 6,000 lower than the November NFP release.  The actual November data was slightly below the revised November forecast (-0.15 S.E.) and the consensus estimate for December is significantly below the model forecast (-0.93 S.E.).

The model sees compelling evidence of increasing strength in the labor market from November to December, demonstrated by a forecast increase of 55,000 jobs. This is in sharp contrast to the consensus estimate, which reflects a 6,000 decline in  jobs from November to December.  This degree of disparity is unusual and increases the probability of an upside surprise in the December NFP data released tomorrow.

Except for an unusually low observation in the actual NFP data in August of 2013 (which was reversed the following month), the actual NFP data has been steadily increasing since the spring of 2013 (see Figure 2 below).  The model forecasts have less variability than the actual NFP data and definitely show a positive trend in the strength of the labor market over the same period.

One caveat: the model forecasts have exceeded the actual/consensus data in six out of the last seven months.  Keep this in mind when evaluating the probability of an upside surprise tomorrow.  The good news for the market is that the underlying data and model forecasts demonstrate increased strength in the labor market and I would argue that the underlying data is a more reliable economic indicator than the actual month-to-month NFP data.

Figure 2: Non-Farm Payroll Graph December 2013

Figure 2: Non-Farm Payroll Graph December 2013

Summary

Basic forecasting tools can help you identify unusual consensus economic estimates, which often lead to substantial surprises and market movements.  Identifying such environments in advance may help you protect your portfolio from these corrections and help you determine the optimal entry and exit points for your strategies.

In the case of the NFP data, the monthly report is notoriously unreliable and prone to substantial revisions.  As a result, having an independent and unbiased indicator of the health of the U.S. job market is especially important.

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Brian Johnson

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About Brian Johnson

I have been an investment professional for over 30 years. I worked as a fixed income portfolio manager, personally managing over $13 billion in assets for institutional clients. I was also the President of a financial consulting and software development firm, developing artificial intelligence based forecasting and risk management systems for institutional investment managers. I am now a full-time proprietary trader in options, futures, stocks, and ETFs using both algorithmic and discretionary trading strategies. In addition to my professional investment experience, I designed and taught courses in financial derivatives for both MBA and undergraduate business programs on a part-time basis for a number of years.
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