This article presents the Trader Edge aggregate neural network model forecast for the March 2013 non-farm payroll data, which will be released tomorrow morning.
Non-Farm Payroll (NFP) Model Forecast - March 2013
The table in Figure 1 below includes the monthly non-farm payroll data for two months: February and March 2013. The February data was released last month and the non-farm payroll data for March 2013 will be released tomorrow morning at 8:30 AM EDT.
The model forecasts are in the third data row of the table (in black). 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 78,900 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. Assuming the model errors are 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 February 2013 is in the second data row of the table (in purple). The consensus estimate (reported by Briefing.com) for March 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 February to March 2013.
The model forecast for March is 159,000, which is almost unchanged from last month's revised forecast of 158,000. The Briefing.com consensus estimate for March is 192,000, which is 0.42 standard errors above the model forecast. The actual NFP observation in February was significantly higher than the revised model forecast. In fact, the actual NFP data in February was almost a full standard error above the estimate, which is unusual. In the past, unusually high or low reported values (relative to the model forecasts) have frequently been offset in subsequent months. This potentially explains why the March Briefing consensus estimate is 44,000 below the reported February data.
As you can see from the graph in Figure 2 below, actual NFP releases above the green dashed line (+0.50 SE), have typically led to significant reversals in subsequent months. This implies the Briefing consensus forecast of +192,000 could be overstated as well. Given the recent spate of weaker than expected economic data, an anemic NFP report for March would put additional pressure on the equity markets.
Basic forecasting tools can help you identify unusual consensus economic estimates, which often lead to substantial surprises and market movements. Identifying such environments may help you protect your portfolio from these corrections and help you determine the optimal entry and exit points for your strategies. In addition, significant deviations from the new model's forecasts may foretell subsequent moves in the equity markets and the economy.
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I think you’re right. Note the 10-year performance over the last few days. People are anticipating a pretty bad number tomorrow.
Great to hear from you. It is interesting that you mentioned the performance of the 10-year Treasury note. Inter-market analysis is one of the most powerful and reliable tools for identifying trend changes, often before they show up in prices. John Murphy has several excellent books on the topic. My proprietary inter-market equity trend indicator is based on six different symbol pairs. It turned negative (bearish) on a both a weekly and a daily basis in mid-March.
Given that the equity market is significantly overbought and a number of sentiment indicators are at bullish extremes, a correction looks increasingly likely. Additional evidence of economic weakness could increase the severity of the pullback.
It will be interesting to see how the NFP number affects the market.