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Tag Archives: monthly emplyoment report
Non-Farm Payroll (NFP) Forecast: March 2013
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) Forecast: February 2013
This article presents the Trader Edge aggregate neural network model forecast for the February 2013 non-farm payroll data, which will be released tomorrow morning.
Non-Farm Payroll (NFP) Forecast: January 2013
I introduced a simple non-farm payroll forecasting model a few months ago. Over the past month, I have developed a much more sophisticated model that aggregates the forecasts for three neural network models, each with a unique architecture. The aggregate … Continue reading
No Non-Farm Payroll Forecast for December
For the past few months I have used a systematic model to forecast an estimate of the monthly non-farm payroll data, which is one of the most influential economic data releases. Unfortunately, the Briefing.com current week’s economic data and consensus … Continue reading
Non-Farm Payroll (NFP) Model Forecast – October 2012
I introduced a simple non-farm payroll forecasting model last month. Since then, I have revised the model, which improved the fit and reduced the standard error. This article explains the current forecast for the October non-farm payroll data, which will … Continue reading
Anomalies in Recent Employment Data
There have been some strange and contradictory economic data released recently. The following post examines some of these anomalies and discusses the implications for the market.
Non-Farm Payroll (NFP) Model Forecast – October 2012
The monthly non-farm payroll or employment report is arguably one of the most influential economic releases in the US. While it may not be the best leading economic indicator, it does move the market. I have been surprised by the … Continue reading
Non-Farm Payroll (NFP) Forecast – November 2012
I introduced a simple non-farm payroll forecasting model a few months ago and revised the model last month. The revisions improved the fit and reduced the standard error. Going forward, I may also attempt to build a neural network model … Continue reading →