Re: st: Re: Currency_Time-series

["Rodrigo A. Alfaro" <raalfaroa@gmail.com>]

Assuming that we want to move from high to low frequency the "sophisticated" 
procedures availables in EViews are: (1) average, (2) sum, (3) first, (4) 
last, (5) maximum and (6) minimum (user guide downloaded from eviews.com). 
You can start with your daily data and create a monthly dataset 
using -collapse- for average, max and min and replacing for the case of 
first and last observation. You could follow the suggestions in the first 
section of Baum's paper http://fmwww.bc.edu/EC-P/WP598.pdf.


----- Original Message ----- 
From: "David Jacobs" <jacobs.184@sociology.osu.edu>
To: <statalist@hsphsun2.harvard.edu>
Sent: Tuesday, April 03, 2007 2:51 PM
Subject: Re: st: Re: Currency_Time-series



> The econometrics package named EViews offers sophisticated routines that 
> convert lower frequency data to data at higher frequencies.  Although it 
> contains many sophisticated procedures, this package is not difficult to 
> learn.
>
> Dave Jacobs
>
>
> At 02:31 PM 4/3/2007, you wrote:
>
> > Thanks, I guess if no one is able to provide direction on my initial 
> > query, worst case scenario will be converting daily frequencies into 
> > monthly data. I
> > may well apply what you have suggested, do you recall the source of where 
> > you
> > noted such information?
> >
> > Regards,
> > B
> > quoting "Rodrigo A. Alfaro" <raalfaroa@gmail.com>:
> >
> >
> > > Bilal
> > >
> > > I read some articles in applied finance that uses monthly data combinated 
> > > with daily frequency. In the bond markets, they used the last day of the 
> > > month data from the daily dataset. I think that you can do the same... 
> > > but I will be suspicious for the case of quarterly.
> > >
> > > R.
> > >
> > >
> > >
> > > ----- Original Message ----- From: "b.qureishi" <b.qureishi@ucl.ac.uk>
> > > To: <statalist@hsphsun2.harvard.edu>
> > > Cc: <bill138@gmail.com>
> > > Sent: Tuesday, April 03, 2007 12:51 PM
> > > Subject: st: Currency_Time-series
> > >
> > >
> > >
> > > > Dear All,
> > > >
> > > > My name is Bilal Qureishi. I am currently studying for a Masters In 
> > > > Comparative
> > > > Economics, at University College, London.
> > > >
> > > > I will be conducting an empirical study to asses the affects of "The 
> > > > release of
> > > > US Macro data on daily currency prices"- and whether or not such 
> > > > fundamental
> > > > releases start certain trends.
> > > > I have about 30 years of data for cable, eur/usd and usd/jpy.-dependant
> > > > variables.
> > > > My independent variables consist of GDP, PPI, CPI, INTEREST RATES and
> > > > UNEMPLOYMENT DATA.
> > > > The frequency of my independent variables in monthly, excluding GDP 
> > > > which is
> > > > quarterly, over 30 years.
> > > > The frequency of my dependant variables is daily over 30 years.
> > > >
> > > > In light of the above, my data is no-doubt time-series. My question is, 
> > > > how to I
> > > > get my independent variables to reconcile with my dependant variables? 
> > > > I.e how
> > > > can I get for example quarterly gdp figures to translate to a daily fx 
> > > > figure?-
> > > > my lecturer who is not a currency whiz suggests that I should convert my 
> > > > daily
> > > > rates into quarterly rates. I could do this, but believe that it will 
> > > > not
> > > > directly contribute to what I want to do.
> > > >
> > > > Your thoughts, suggestions and direction would be most appreciated.
> > > >
> > > > Regards,
> > > >
> > > > Bilal Al-Qureishi
> > > >
> > > >
> > > >
> > > >
> > > >
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