Hi
I am working with this data:
my data summary is:
> summary(spi)
open high low close volume
Min. :4315 Min. :4365 Min. :4301 Min. :4352 Min. :
0
1st Qu.:4480 1st Qu.:4497 1st Qu.:4458 1st Qu.:4475 1st
Qu.:11135
Median :4609 Median :4631 Median :4594 Median :4614 Median
:14439
Mean :4620 Mean :4640 Mean :4599 Mean :4620 Mean
:16590
3rd Qu.:4773 3rd Qu.:4796 3rd Qu.:4753 3rd Qu.:4766 3rd
Qu.:18294
Max. :4944 Max. :4954 Max. :4912 Max. :4937 Max.
:73559
openInterest direction volatility volumeXdirection
Min. : 0 Min. :-62.00000 Min. : 0.00 Min. :-2795242
1st Qu.:184685 1st Qu.:-19.25000 1st Qu.:30.00 1st Qu.: -248740
Median :193233 Median : -1.50000 Median :38.50 Median : -15905
Mean :188825 Mean : 0.01563 Mean :41.58 Mean : 6275
3rd Qu.:199800 3rd Qu.: 17.00000 3rd Qu.:50.00 3rd Qu.: 206325
Max. :236759 Max. : 74.00000 Max. :94.00 Max. : 2024470
volatilityXdirection upDown nextDay
Min. : 0 Min. :0.0000 Min. :0.0000
1st Qu.: 362816 1st Qu.:0.0000 1st Qu.:0.0000
Median : 540187 Median :0.0000 Median :0.0000
Mean : 731595 Mean :0.4844 Mean :0.4844
3rd Qu.: 996650 3rd Qu.:1.0000 3rd Qu.:1.0000
Max. :3604391 Max. :1.0000 Max. :1.0000
>
and trying to do a glm like this:
> logistic.model = glm(formula = as.factor(nextDay) ~ .,
family=binomial, data=spi[1:50,])
> summary(logistic.model)
Call:
glm(formula = as.factor(nextDay) ~ ., family = binomial, data =
spi[1:50,
])
Deviance Residuals:
Min 1Q Median 3Q Max
-1.9994 -0.8575 -0.0330 0.7961 1.8376
Coefficients: (2 not defined because of singularities)
Estimate Std. Error z value Pr(>|z|)
(Intercept) -3.016e+01 2.934e+01 -1.028 0.3040
open -2.514e-02 8.939e-02 -0.281 0.7785
high 7.598e-02 1.295e-01 0.587 0.5575
low -1.065e-01 1.176e-01 -0.905 0.3656
close 5.943e-02 7.995e-02 0.743 0.4573
volume 1.960e-04 1.977e-04 0.991 0.3215
openInterest 5.728e-05 5.266e-05 1.088 0.2767
direction NA NA NA NA
volatility NA NA NA NA
volumeXdirection 3.605e-06 3.765e-06 0.958 0.3383
volatilityXdirection -5.815e-06 5.708e-06 -1.019 0.3082
upDown -2.561e+00 1.259e+00 -2.034 0.0419 *
---
Signif. codes: 0 `***' 0.001 `**' 0.01 `*' 0.05 `.' 0.1 ` ' 1
(Dispersion parameter for binomial family taken to be 1)
Null deviance: 69.235 on 49 degrees of freedom
Residual deviance: 55.000 on 40 degrees of freedom
AIC: 75
Number of Fisher Scoring iterations: 7
>
I am getting NA for direction and volatility. I got it both before and
after casting them as.numeric.
Can anyone tell me what I am doing wrong?
Thanks
Stephen
--
20/02/2006
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