corrected : new update on ppi model for inflation book dear all ,
i followed up on the suggestions at the conference call as follows : -
1 ) use less data
unfortunately , kicking out only 1990 makes the overall equation a lot less
robust , in fact dramatically so , and so eliminates the possibility of using
less data . the model tested was the rpi ( month + 15 ) ppi pre - empts the moves in rpi by about 8 months . the
magnitude of the oscillations is also reduced . this shows that if we had
more detail in our rpi forward curve , then the ppi model would reflect those
peaks and humps adequately .
conclusion
i therefore propose that we use the model that incorporates rpi , rpi [ t + 15 ]
and deviations of brent crude from long - term average . the new model is
plotted below in burgundy and can be compared to the old ppi which is
depicted in blue .
the new model achieves the two main objectives of the ppi curve : it is
significantly more robust and stable than the existing one , and it is
considerably less sensitive to the input coefficients , which results in us
having more confidence in our monthly p it was found that deviations of dated brent crude from the
long - term average of $ 18 . 80 was the best form of the variable to use ( for
predictions the brent forward curve produced by the global products group is
used ) . the three new equations developed were : -
pllu ( t ) = a . rpi ( t ) + b . rpi ( t + n ) + c . ( datedbrentcrude - 18 . 8 ) + constant ,
where n is 14 , 15 or 16
[ reddish curves ]
r - squared approx 0 . 49
f - stat approx 32
the chart below shows what our projected pllu curve would be given this
equation , and also the three best relations from before which were based upon
current and future rpi :
pllu ( t ) = a . rpi ( t ) + b . rpi ( t + n ) + constant , where n is 14 , 15 or 16
[ greenish curves ]
r - squared approx 0 . 47
f - stat approx 45
comparison of models
as you can see , the two equations differ in the very short - term and very
long - term ; the inclusion of deviations of brent crude leads to short - term
predictions of 3 . 0 % to 3 . 2 % over the next six months . the greenish curves
predict pllu in the range of 2 . 5 % to 2 . 8 % over the next six months .
the curves are then very similar until 2009 , when the models including crude
break - away to the upside , relative to the falling rpi curve . the model based
purely on rpi hugs the rpi curve much more closely in the longer term . this
is only important to the extent that we have large positions beyond 2009
( which we don ' t ) .
suggestion
what could be useful now is a differently - specified model designed to
forecast only the next 3 months , using auto - regressive or auto - regressive
error terms . this model would be far more accurate in the near - term , and we
could include this information onto the front of this long - term model . this
may be useful , despite the fact that most of our exposure is in future time
buckets .
back - testing
all the models give similar visual and statistical performance over the data
sample used ( based mainly on 1990 s " new paradigm " economy ) .
hopefully we can discuss these and other points later in the tele - conference ;
your ideas on this would be appreciated .
regards ,
anjam
x 35383
corrected : new update on ppi model for inflation book
dear all ,
i followed up on the suggestions at the conference call as follows : -
1 ) use less data
unfortunately , kicking out only 1990 makes the overall equation a lot less
robust , in fact dramatically so , and so eliminates the possibility of using
less data . the model tested was the rpi ( month + 15 ) ppi pre - empts the moves in rpi by about 8 months . the
magnitude of the oscillations is also reduced . this shows that if we had
more detail in our rpi forward curve , then the ppi model would reflect those
peaks and humps adequately .
conclusion
i therefore propose that we use the model that incorporates rpi , rpi [ t + 15 ]
and deviations of brent crude from long - term average . the new model is
plotted below in burgundy and can be compared to the old ppi which is
depicted in blue .
the new model achieves the two main objectives of the ppi curve : it is
significantly more robust and stable than the existing one , and it is
considerably less sensitive to the input coefficients , which results in us
having more confidence in our monthly p it was found that deviations of dated brent crude from the
long - term average of $ 18 . 80 was the best form of the variable to use ( for
predictions the brent forward curve produced by the global products group is
used ) . the three new equations developed were : -
pllu ( t ) = a . rpi ( t ) + b . rpi ( t + n ) + c . ( datedbrentcrude - 18 . 8 ) + constant ,
where n is 14 , 15 or 16
[ reddish curves ]
r - squared approx 0 . 49
f - stat approx 32
the chart below shows what our projected pllu curve would be given this
equation , and also the three best relations from before which were based upon
current and future rpi :
pllu ( t ) = a . rpi ( t ) + b . rpi ( t + n ) + constant , where n is 14 , 15 or 16
[ greenish curves ]
r - squared approx 0 . 47
f - stat approx 45
comparison of models
as you can see , the two equations differ in the very short - term and very
long - term ; the inclusion of deviations of brent crude leads to short - term
predictions of 3 . 0 % to 3 . 2 % over the next six months . the greenish curves
predict pllu in the range of 2 . 5 % to 2 . 8 % over the next six months .
the curves are then very similar until 2009 , when the models including crude
break - away to the upside , relative to the falling rpi curve . the model based
purely on rpi hugs the rpi curve much more closely in the longer term . this
is only important to the extent that we have large positions beyond 2009
( which we don ' t ) .
suggestion
what could be useful now is a differently - specified model designed to
forecast only the next 3 months , using auto - regressive or auto - regressive
error terms . this model would be far more accurate in the near - term , and we
could include this information onto the front of this long - term model . this
may be useful , despite the fact that most of our exposure is in future time
buckets .
back - testing
all the models give similar visual and statistical performance over the data
sample used ( based mainly on 1990 s " new paradigm " economy ) .
hopefully we can discuss these and other points later in the tele - conference ;
your ideas on this would be appreciated .
regards ,
anjam
x 35383