Here we model
the evolution of Textron Inc. (NYSE: TXT) stock price. TXT is a company from industrial
goods sector which “operates
in the aircraft, defense, industrial, and finance businesses worldwide”. The model has been obtained using our concept of stock
pricing as a decomposition of a share price into a weighted sum of two consumer
price indices (CPIs). The background idea is a simplistic one: there is a
potential trade-off between a given share price and goods and services the
company produces and/or provides. For example, the energy consumer price does
influence the price of energy
companies. It should be taken into account that one defining consumer price (or
relevant CPI) has to be related to the share and the other CPI should be an independent
one as representing a dynamic reference, i.e. the changing price environment. Both
defining CPIs may lead the price of lag behind by a few months.
We
have borrowed the time series of monthly closing prices of TXT from Yahoo.com and the relevant (seasonally
not adjusted) CPI estimates through February 2014 are published by the BLS. We have found
that the evolution of TXT share price is defined by the consumer price index
of transportation services (TS) and the index of pets, pet products and
services (PETS) from recreation CPI category. We assume that the index of
transport services is the price driver, i.e. the consumer prices of
transportation services. It is instructive that Textron Inc. operates Cessna, Bell, and
Textron Systems, i.e. TXT is directly related to transportation systems. The
defining time lags are as follows: the TS index leads the share price by 5
months and the PETS index has a 3 months lead. The relevant
best-fit model for TXT(t) is as
follows:
TXT(t) = -2.78PETS(t-3) – 2.86TS(t-5) + 33.02(t-2000) + 832.91, February 2014
where TXT(t) is the TXT share price in U.S.
dollars, t is calendar time. Figure 1 displays the evolution of both
defining indices since 2002. Figure 2
depicts the high and low monthly prices for TXT share together with the
predicted and measured monthly closing prices (adjusted for dividends and
splits). It is worth noting that the predicted curve actually leads the
observed one by 3 months, i.e. the model sees three months ahead.
The
model is stable over time. Table 1 lists the best fit models, i.e.
coefficients, b1 and b2, defining CPIs, time lags, the slope
of time trend, c, and the free term, d, for select models for the period
between November 2009 and February 2014. These models all have the same
defining CPIs, similar coefficients and time lags – they are practically
identical. Therefore, the estimated TXT model is highly reliable over time and predicts
at a three month horizon. The model residual error is shown in Figure 3. The
standard deviation between July 2003 and February 2014 is $4.20.
The
model predicts TXT price to rise to $45 in May 2014.
Table
1. Selected best fit models for the period between November 2009 and February
2014
|
Month
|
b1
|
CPI1
|
lag1
|
b2
|
CPI2
|
lag2
|
c
|
d
|
|
Feb-14
|
-2.780
|
PETS
|
3
|
-2.860
|
TS
|
5
|
33.018
|
832.907
|
|
Jan
|
-2.795
|
PETS
|
3
|
-2.861
|
TS
|
5
|
33.122
|
834.553
|
|
Dec-13
|
-2.822
|
PETS
|
3
|
-2.859
|
TS
|
5
|
33.272
|
836.397
|
|
Nov
|
-2.807
|
PETS
|
3
|
-2.854
|
TS
|
5
|
33.156
|
834.278
|
|
Oct
|
-2.814
|
PETS
|
3
|
-2.849
|
TS
|
5
|
33.169
|
833.976
|
|
Sep
|
-2.836
|
PETS
|
3
|
-2.839
|
TS
|
5
|
33.243
|
834.010
|
|
Aug
|
-2.865
|
PETS
|
3
|
-2.826
|
TS
|
5
|
33.341
|
833.989
|
|
Jul
|
-2.877
|
PETS
|
3
|
-2.813
|
TS
|
5
|
33.333
|
832.626
|
|
Mar-12
|
-3.168
|
PETS
|
3
|
-2.929
|
TS
|
7
|
35.877
|
880.991
|
|
Feb
|
-3.125
|
PETS
|
3
|
-2.750
|
TS
|
7
|
34.582
|
842.784
|
|
Jan
|
-3.216
|
PETS
|
3
|
-2.890
|
TS
|
7
|
35.957
|
877.784
|
|
Dec-11
|
-3.240
|
PETS
|
3
|
-2.884
|
TS
|
7
|
36.091
|
878.639
|
|
Nov
|
-3.256
|
PETS
|
3
|
-2.877
|
TS
|
7
|
36.159
|
878.507
|
|
Oct
|
-3.274
|
PETS
|
3
|
-2.873
|
TS
|
7
|
36.268
|
879.271
|
|
Sep
|
-3.282
|
PETS
|
3
|
-2.869
|
TS
|
7
|
36.297
|
879.203
|
|
Aug
|
-3.282
|
PETS
|
3
|
-2.869
|
TS
|
7
|
36.297
|
879.214
|
|
Sep-10
|
-3.165
|
PETS
|
3
|
-3.089
|
TS
|
6
|
36.755
|
543.958
|
|
Aug
|
-3.247
|
PETS
|
3
|
-2.970
|
TS
|
6
|
36.663
|
525.980
|
|
Jul
|
-3.287
|
PETS
|
3
|
-2.909
|
TS
|
6
|
36.603
|
515.177
|
|
Jun
|
-3.307
|
PETS
|
3
|
-2.865
|
TS
|
6
|
36.506
|
506.284
|
|
May
|
-3.273
|
PETS
|
3
|
-2.927
|
TS
|
6
|
36.621
|
511.072
|
|
Apr
|
-3.231
|
PETS
|
3
|
-3.017
|
TS
|
6
|
36.818
|
519.723
|
|
Mar
|
-3.254
|
PETS
|
3
|
-2.972
|
TS
|
6
|
36.728
|
510.921
|
|
Feb
|
-3.280
|
PETS
|
3
|
-2.918
|
TS
|
6
|
36.634
|
500.730
|
|
Jan
|
-3.299
|
PETS
|
3
|
-2.878
|
TS
|
6
|
36.560
|
492.144
|
|
Dec-09
|
-3.299
|
PETS
|
3
|
-2.845
|
TS
|
6
|
36.421
|
484.038
|
|
Nov
|
-3.299
|
PETS
|
3
|
-2.841
|
TS
|
6
|
36.391
|
480.557
|
Figure
1. The evolution of PETS and TS indices
Figure 2.
Observed and predicted TXT share prices.
Figure 3.
The model residual error: stdev=$4.20.
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