Category Archives: Fundamentals

Non Farm Payrolls time again…

It is NFP time again, sweepstakes must be rife on trading floors around the world…..So it is time to use my NFP forecasting model which leverages on both an ARIMA forecast and a simple linear regression using the ADP as the independent variable to generate a mixed forecast of the NFP.

Not surprisingly the ADP and the NFP data releases are positively correlated, thoug this has been significantly time varying. Also the NFP tend to be generally twice as volatile than the ADP numbers, highlighting their challenging nature for a forecaster.

plot of chunk chartsplot of chunk charts

##       ADP               NFP         
##  Min.   :-845.95   Min.   :-823.00  
##  1st Qu.:  23.17   1st Qu.:  20.75  
##  Median : 144.57   Median : 138.50  
##  Mean   :  83.18   Mean   :  85.72  
##  3rd Qu.: 212.27   3rd Qu.: 230.50  
##  Max.   : 383.98   Max.   : 524.00

In the below chart I use a 24-month rolling Granger Causality test to investigate the causality at a lag of one between ADP and NFP releases. The chart shows the P-values of the test which indicate in which way the causality,if any, flows. Clearly sometime the ADP has been a leading indicator, other times not.

plot of chunk causality

In the below I use an optimising algorithm to find the best ARIMA over the entire sample so as to generate a trend forecast of the NFP. The wide confidence intervals clearly highlight that those forecasts are associated with a high degree of of uncertainty.

plot of chunk arimachart

Finally I use a mixed model to generate an estimate of what the next NFP release will be. The forecast is derived both from a linear regression model forecast with the ADP as the independent variable and also from the forecast generated by the previously fitted ARIMA model.

The LM model forecasts an NFP release of : 253,618 whilts the ARIMA calls for a release of: 178,689 . This contributes to a mixed model forecast of : 218,792

Snap Election…Snap Stats – Update

OK it is election time again here in the UK and the Conservatives have the upper according to many polls and surveys monitoring the voting intention of UK voters. Though there are many surveys and polls the data available is quite noisy and also inconveniently irregularly spaced. This makes it difficult to detect trends and evaluate possible scenarios. In an attempt to bring some clarity I use UK polls survey results since the May 2010 sourced from the UK Polling Report website. They provide the results of 2172 polls made since may 2010. I First aggregate the data by calculating the weekly means of all the surveys, generating a sample of 344 weekly estimates. As shown in the below charts this greatly reduces the noise in the data .

plot of chunk charts

As of the week ending 2017-04-24 the average percentage of intention to vote was standing at 49.11 % for the Conservatives, 27.44 % for Labour, 11.81 % for the LDEM, 8.53 % for UKIP and 3.11 % for the Green party.

plot of chunk monthtodate

The following charts show for each party the historical distribution of the percentage of vote intention (since 05/2010 for Conservatives, Labour and LDEM; 04/2012 for UKIP and 07/2012 for the Green party), the current level at which it stands (vertical green line) and its mean over the whole sample (blue line).

plot of chunk distribution

Finally the below provides an arima forecast of the percentage of vote intention by party and the 95% confidence intervals based on the previous 52 weeks of data. Each forecast is based on the best fitted ARIMA over the history used.

plot of chunk arimaforecast

Already Non Farm Payrolls time again…

It is NFP time again, sweepstakes must be rife on trading floors around the world…..So it is time to use my NFP forecasting model which leverages on both an ARIMA forecast and a simple linear regression using the ADP as the independent variable to generate a mixed forecast of the NFP.

Not surprisingly the ADP and the NFP data releases are positively correlated, thoug this has been significantly time varying. Also the NFP tend to be generally twice as volatile than the ADP numbers, highlighting their challenging nature for a forecaster.

plot of chunk chartsplot of chunk charts

##       ADP                 NFP           
##  "Min.   :-881.19  " "Min.   :-823.00  "
##  "1st Qu.: -31.53  " "1st Qu.: -30.75  "
##  "Median : 142.53  " "Median : 124.50  "
##  "Mean   :  57.12  " "Mean   :  64.31  "
##  "3rd Qu.: 196.57  " "3rd Qu.: 218.00  "
##  "Max.   : 356.56  " "Max.   : 522.00  "

In the below chart I use a 24-month rolling Granger Causality test to investigate the causality at a lag of one between ADP and NFP releases. The chart shows the P-values of the test which indicate in which way the causality,if any, flows. Clearly sometime the ADP has been a leading indicator, other times not.

plot of chunk causality

In the below I use an optimising algorithm to find the best ARIMA over the entire sample so as to generate a trend forecast of the NFP. The wide confidence intervals clearly highlight that those forecasts are associated with a high degree of of uncertainty.

plot of chunk arimachart

Finally I use a mixed model to generate an estimate of what the next NFP release will be. The forecast is derived both from a linear regression model forecast with the ADP as the independent variable and also from the forecast generated by the previously fitted ARIMA model.

The LM model forecasts an NFP release of : 181,026 whilts the ARIMA calls for a release of: 196,490 . This contributes to a mixed model forecast of : 188,190

Non Farm Payrolls time again…

It is NFP time again, sweepstakes are rife on trading floors around the world so I could not let my friend Chris down…..So it is time to use my NFP forecasting model which leverages on both an ARIMA forecast and a simple linear regression using the ADP as the independent variable to generate a mixed forecast of the NFP.

Not surprisingly the ADP and the NFP data releases are positively correlated, thoug this has been significantly time varying. Also the NFP tend to be generally twice as volatile than the ADP numbers, highlighting their challenging nature for a forecaster.

plot of chunk chartsplot of chunk charts

##       ADP                 NFP           
##  "Min.   :-881.19  " "Min.   :-823.00  "
##  "1st Qu.: -32.09  " "1st Qu.: -33.25  "
##  "Median : 140.99  " "Median : 124.50  "
##  "Mean   :  55.87  " "Mean   :  63.58  "
##  "3rd Qu.: 196.90  " "3rd Qu.: 218.00  "
##  "Max.   : 356.56  " "Max.   : 522.00  "

In the below chart I use a 24-month rolling Granger Causality test to investigate the causality at a lag of one between ADP and NFP releases. The chart shows the P-values of the test which indicate in which way the causality,if any, flows. Clearly sometime the ADP has been a leading indicator, other times not.

plot of chunk causality

In the below I use an optimising algorithm to find the best ARIMA over the entire sample so as to generate a trend forecast of the NFP. The wide confidence intervals clearly highlight that those forecasts are associated with a high degree of of uncertainty.

plot of chunk arimachart

Finally I use a mixed model to generate an estimate of what the next NFP release will be. The forecast is derived both from a linear regression model forecast with the ADP as the independent variable and also from the forecast generated by the previously fitted ARIMA model.

The LM model forecasts an NFP release of : 176,474 whilts the ARIMA calls for a release of: 183,545 . This contributes to a mixed model forecast of : 179,756

Non Farm Payrolls time again…

It is NFP time again, sweepstakes must be rife on trading floors around the world…..So it is time to use my NFP forecasting model which leverages on both an ARIMA forecast and a simple linear regression using the ADP as the independent variable to generate a mixed forecast of the NFP.

Not surprisingly the ADP and the NFP data releases are positively correlated, thoug this has been significantly time varying. Also the NFP tend to be generally twice as volatile than the ADP numbers, highlighting their challenging nature for a forecaster.

plot of chunk chartsplot of chunk charts

##       ADP                 NFP           
##  "Min.   :-881.19  " "Min.   :-823.00  "
##  "1st Qu.: -32.15  " "1st Qu.: -33.75  "
##  "Median : 140.44  " "Median : 122.50  "
##  "Mean   :  54.42  " "Mean   :  62.30  "
##  "3rd Qu.: 196.57  " "3rd Qu.: 218.00  "
##  "Max.   : 356.56  " "Max.   : 522.00  "

In the below chart I use a 24-month rolling Granger Causality test to investigate the causality at a lag of one between ADP and NFP releases. The chart shows the P-values of the test which indicate in which way the causality,if any, flows. Clearly sometime the ADP has been a leading indicator, other times not.

plot of chunk causality

In the below I use an optimising algorithm to find the best ARIMA over the entire sample so as to generate a trend forecast of the NFP. The wide confidence intervals clearly highlight that those forecasts are associated with a high degree of of uncertainty.

plot of chunk arimachart

Finally I use a mixed model to generate an estimate of what the next NFP release will be. The forecast is derived both from a linear regression model forecast with the ADP as the independent variable and also from the forecast generated by the previously fitted ARIMA model.

The LM model forecasts an NFP release of : 202,487 whilts the ARIMA calls for a release of: 229,596 . This contributes to a mixed model forecast of : 215,070

Non Farm Payrolls time again…

It is NFP time again, sweepstakes must be rife on trading floors around the world…..So it is time to use my NFP forecasting model which leverages on both an ARIMA forecast and a simple linear regression using the ADP as the independent variable to generate a mixed forecast of the NFP.

Not surprisingly the ADP and the NFP data releases are positively correlated, thoug this has been significantly time varying. Also the NFP tend to be generally twice as volatile than the ADP numbers, highlighting their challenging nature for a forecaster.

plot of chunk chartsplot of chunk charts

##       ADP                 NFP           
##  "Min.   :-881.19  " "Min.   :-823.00  "
##  "1st Qu.: -32.17  " "1st Qu.: -34.00  "
##  "Median : 140.08  " "Median : 122.00  "
##  "Mean   :  53.57  " "Mean   :  61.11  "
##  "3rd Qu.: 195.86  " "3rd Qu.: 218.00  "
##  "Max.   : 356.56  " "Max.   : 522.00  "

In the below chart I use a 24-month rolling Granger Causality test to investigate the causality at a lag of one between ADP and NFP releases. The chart shows the P-values of the test which indicate in which way the causality,if any, flows. Clearly sometime the ADP has been a leading indicator, other times not.

plot of chunk causality

In the below I use an optimising algorithm to find the best ARIMA over the entire sample so as to generate a trend forecast of the NFP. The wide confidence intervals clearly highlight that those forecasts are associated with a high degree of of uncertainty.

plot of chunk arimachart

Finally I use a mixed model to generate an estimate of what the next NFP release will be. The forecast is derived both from a linear regression model forecast with the ADP as the independent variable and also from the forecast generated by the previously fitted ARIMA model.

The LM model forecasts an NFP release of : 215,121 whilts the ARIMA calls for a release of: 199,018 . This contributes to a mixed model forecast of : 207,650