Contoh Praktis Menggunakan EVIEWS

7/26/2019 Contoh Praktis Menggunakan EVIEWS

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Presented by

2013/10/24

Practical Examples using Eviews


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P.40-P.43File: SandPedge.xls


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Estimati!n !" an !ptimal edge rati!#is secti!n s!ws !w t! run a $ivariate regressi!n usin

g Eviews.%e "!cus !n te relati!nsip $etween S and F'#'(E

S:

1. )evel regressi!n *l!ng run relati!nsip+

2. (eturn regressi!n *s!rt run relati!nsip+

.

#e appr!priate edge rati! will $e te sl!pe estimate, , in a regressi!n were te dependent varia$le is te sp!t returns and te independent varia$le is te "utures return.

.#est weter !r n!t, we can iew !e"". #ests !e"". (estricti!ns. #/pe *+12.


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nput 5ata


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5escriptive Statistics

6enr t/pe r"utures12007dl!g*"utures+ rsp!t12007dl!g*sp!t+5! n!t "!rget t! Save te w!r8"ile.


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(un (egressi!n" /!u want t! save te summar/ statistics, /!u

must name tem $/ clic8ing 9ame and ten c!!se a name, e.g.

5escstats

.%e can n!w pr!ceed t! estimate te regressi!n.


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9ame returnreg

n te same wa/, we als! !$tain levelreg


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#est !e""icients !" (egressi!nSupp!se n!w tat we wanted t! test te null /p

!tesis tat rater tan .


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P.-P.;0File: capm.xls


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Example "!r


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6enerate 9ew aria$les

(S3=?2

E(S


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3=


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P.AA-P.204File: macr!.xls

Peri!d: 2A;B?03C00?04


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Press 6enr6enr din"lati!n 1 d*in"lati!n+

6enr must$3m 1 ust$3m?2

6enr rterm 1 d*term+

6enr erms!"t 1 rms!"t must$3m

6enr ersandp 1 rsandp must$3m

'se )east S@uares !ver te w!le sample peri!d.

*erms!"t c ersandp dpr!d dcredit din"lati!n dm!ne/dspread rterm+


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Stepwise regressi!n


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P.23B-P.23AFile: macr!.w"l

Peri!d: 2A;B?03C00?04


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#esting "!r eter!scedasticit/" te residuals !" te regressi!n ave s/stematic

all/ canging varia$ilit/ !ver te sample, tat is asign !" eter!scedasticit/.

t is ard t! see an/ clear pattern, s! we need t!run te "!rmal statistical test. *%ites test+

-60

-50

-40

-30

-20

-10

0

10

20

30

86 88 90 92 94 96 98 00 02 04 06

ERMSOFT Residuals


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#! test "!r eter!scedasticit/ using %ites test.VV ambiguous!!X


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'sing %ites m!di"ied standard err!r estimates in Eiews

The heteroscedasticity-consistent s.d. errors are smaller than "

#urbin-$atson %#$& is a test 'or (rst orderautocorrelation.


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5etecting aut!c!rrelati!n>reusc-6!d"re/ test:


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#esting "!r n!n-n!rmalit/#e >era-Gar@ue n!rmalit/ tests

iew (esidual #ests Hist!gram 9!rm

alit/ #est


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=ultic!llinearit/

Iuic8?6r!up Statistics?!rrelati!ns

n te dial!g $!x tat appears:

Ersandp dpr!d dcredit din"lati!n dm!ne/ dspread

rterm


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(ESE# tests *p.2+

iew Sta$ilit/ tests (amse/ (ESE# test


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)t *ould be concluded thatthe linear model 'or the +icroso't returnsis a,,ro,riate.


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Sta$ilit/ tests *p.2;;+

iew Sta$ilit/ #ests !w >rea8p!int #e

st


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P.34-P.3;File: 'JHP.w"l

Peri!d: 2AA2?03C00?0K


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5!u$le clic8 5H iew?!rrelati!n )ag 2&J

Estimating te aut!c!rrelati!n c!e""icients "!r up t! 2 lags


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'sing in"!rmati!n criteria t! decide !nm!del !rders

Iuic8 Estimate E@uati!n


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#is speci"/ an


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&ne m!re example: Ldp c ar*2+ ar*+ ar*3+ ar*4+ar*K+ ma*2+ ma*+ ma*3+ ma*4+ ma*K+M

'sing


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F!recasting using


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F!recast d/namic?static


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Simultane!us e@uati!ns m!delling using Eiews

%at is te relati!nsip $etween in"lati!n and st!c8 returnsN

n Eiews, t! d! tis we need t! speci"/ a list !" instruments, wic w!uld $e all !" te varia$les "r!m te re

duced "!rm e@uati!n. #e reduced "!rm e@uati!ns:

Iuic8 Estimati!n E@uati!n


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#e c!e""icients are all n!t signi"icant.#e "itted relati!nsip $etween te st!c8 returns

and in"lati!n series is p!sitive *al$eit n!t signi"icantl/ s!+.

#e adOusted is negative.


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P.30;File: currencies.w"l

Peri!d: 2AA2?03C00?0K


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ect!r aut!regressive m!dels#e simplest case:

&pen Lcurrencies.w"lM

Iuic8 Estimate


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H!w t! decide te lengt !" lagged termN

iew )ag Structure )ag )engt riteria

20

!nclusi!n: c!!se

Contoh Praktis Menggunakan EVIEWS

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