Hi

This is the right forum to ask this, not sure though it is the right form
;-) You are asking here many questions, some of which cannot be answered
without reproducible code. So let me just answer 1.1 and 2:

1.1: Not the seasonal components refer to deterministic seasonality, not
stochastic. So this is nto the same as ARIMA vs SARIMA, since SARIMA
concerns stochastic seasonality. There have been some papers on seasonal
cointegration (what corresponds to SARIMA), but not very popular, and not
implemented in R afaik.
1.2/1.3: not clear or no code to answer

2: yes, you are right, ecdet="const", restricts the constant to enter the
coint relationship.

Best

Matthieu


2013/6/3 gunjan narulkar <gunjan_narulkar@yahoo.com>

> Hi,
>
> I'm trying to learn about cointegration, specifically about how to use "
> ca.jo" for finding the cointegration basis. The data is that of FX rates
> and M1 supply difference. I need help understanding the below two points:
>
> 1. Seasonal variables:
>
> -> What is the importance of season parameter apart from seemingly obvious
> explanation in the documentation; in other words, should it be understood
> as equivalent of Seasonal ARIMA vs ARIMA where we take care of the seasonal
> unit roots?
>
> -> Should the parameter be set to the value at which the Y_t under
> question is sampled? Or should it be based on some common frequency derived
> from individual Y_t component series's periodicity as found from their
> periodogram (spectrum command in R)?
>
> -> Should the season paramater must be greater then 2? As by spectrum of
> M1 and FX rate series, I was getting the prominent frequencies for both
> variables as 2 and its multiples, but got below error, which got resolved
> as soon as I used anything >2:
>
> "Error in while (nrow(dums) < N) { : argument is of length zero"
>
> Background: I tried checking for cointegration between two monthly series,
> taking the "season" parameter as 12 (as I had monthly data) first time and
> without having any season parameter the second. The order of cointegration
> in both the cases was 1. But further, when I tried fitting VECM and using
> vec2var created 6 months ahead forecasts and calculated MAPE (Mean Absolute
> Percentage Error), the MAPE for ca.jo output without season parm
> specified was better then with season parameter - which lead me to the
> above confusions.
>
>
> 2. ecdet paramter:
> The awesome book as well as documentation describe this parameter nicely.
> But when I use it, the message that comes in the output is a bit confusing:
>
> > cv1.m1.bop = ca.jo
> (cor2,type="trace",ecdet="const",K=2,season=12,dumvar=bop)
> > summary(cv1.m1.bop)
>
>
> ######################
> # Johansen-Procedure #
> ######################
>
> Test type: trace statistic , without linear trend and constant in
> cointegration
> .
> .
> .
>
> The confusion is that I'm interested in finding out presence of
> "restricted constant", so I used "ecdet='const'". Am I correct in doing so?
>
> Apologies if this is not the right forum for asking these questions and
> also for the long mail.
>
> Thanks & Regards,
>
> Gunjan Narulkar,
> Ist Year M. Mgmt., DOMS,
> Indian Institute of Science
> Contact: +91-99007-40404
> LinkedIn: in.linkedin.com/pub/gunjan-narulkar/19/a3b/521
>
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