EViews.com

The code you gave is for an EViews program. You'll need to run it in a program. Click on File->New->Program, then type it in there, and hit the run button.

Thank you so much Gareth, you are a lifesaver! I have been able to successfully run the program :)

Hi again,

I have further question regrding my forecasting using GARCH models.
I want to try to forecast over different time horizons (eg.1, 5, 21 and 252 days ahead). In order to do this I am using the program I specified in my previous post.
However, when using a rolling window of 1, I do not get the same results as I do when I am using the drop down menues. I am staring to wonder if I have completely misunderstood what I am doing :?

Do you mind explaining to me what eviews actualy does when I use the drop down menues (choosing static forecast), or how I should go about forecasting different time horizons?

I have attached the program I am using, when trying to forecast over 5 days.
As usally all help is much appreciated! :)

'set window size'
!window=4070
'get size of workfile'
!lenght=@obsrange
'declare equation for estimation'
equation eq01
'set step size'
!step=1
'calculate number of rolls'
!nrolls=@floor((!lenght-!window)/!step)

'matrix to store coefficient estimates'
Matrix(5,!nrolls)coefmat 'where 5 is the number of coefficients
'series to store forecast estimates
series fcast
series fcastse
series fcastvar

'catching start and end points
%start= "@first"
%end= "@last"
'variable keeping track of how many rolls we've done
!j=0
'move sample !step obs at a time
for !i=1 to !lenght-!window+1-!step step !step
!j=!j+1
'set sample for estimation period
%first=@otod(@dtoo(%start)+!i-1)
%last=@otod(@dtoo(%start)+!i+!window-2)
smpl {%first} {%last}
'store coefficients
colplace(coefmat,eq01.@coefs,!j)

'1-period-ahead forecast
%5pers=@otod(@dtoo(%start)+!i+!window-1)
%5pere=@otod(@dtoo(%start)+!i+!window+4)

'set smpl for forecasting period
smpl {%5pers} {%5pere}

' forecast with command *fit*
eq01.fit(f=na) g_f1 g_se g_var

' store forecasts
fcast=g_f1
fcastse=g_se
fcastvar=g_var

'calculate RMSE
scalar rmse=@rmse(returns, fcast)

‘calculate MAE
Scalar mae=@mae(returns, fcast)

next

I'm not sure I understand what you're asking.

Sorry for not being clear enough. Basically, I thought that when I was doing a static forecast from the drop down menu I was forecasting 1-step ahead, meaning that as I am using daily data I would be forecasting 1 day ahead..

However, when I tried to adjust the program I attached to my previous post for it to become a 1 day rolling window, my outcomes are completely different. Have I misunderstood what Eviews is doing in the drop down menu or is my program not doing what I want it to do (forecast over different horizons)?

If I then open up eq01, hit the forecast button and select "static" as the forecast type, then open up the series returnsf and fcast, they're identical.

I am sorry for being so slow, but I still don't get it right...
I still do not get the same results by trying the two methods and my RMSE and MAE end up being the exact same number when I am trying to use the commands.

create u 4966 (this number is the total number of observations)

series returns=nrnd
series x1=nrnd
equation eq01.arch returns c x1

'set window size'
!window=4070 (this is my in-sample period)
'get size of workfile'
!lenght=@obsrange
'declare equation for estimation'
equation eq01
'set step size'
!step=1
'calculate number of rolls'
!nrolls=@floor((!lenght-!window)/!step)

'matrix to store coefficient estimates'
Matrix(5,!nrolls)coefmat 'where 5 is the number of coefficients
'series to store forecast estimates
series fcast
series fcastse
series fcastvar

'catching start and end points
%start= "@first"
%end= "@last"
'variable keeping track of how many rolls we've done
!j=0
'move sample !step obs at a time
for !i=1 to !lenght-!window+1-!step step !step
!j=!j+1
'set sample for estimation period
%first=@otod(@dtoo(%start)+!i-1)
%last=@otod(@dtoo(%start)+!i+!window-2)
smpl {%first} {%last}
'store coefficients
colplace(coefmat,eq01.@coefs,!j)

'1-period-ahead forecast
%1pers=@otod(@dtoo(%start)+!i+!window-1) (%1pers because I am trying a 1-day ahead forecast)
%1pere=@otod(@dtoo(%start)+!i+!window+0)

'set smpl for forecasting period
smpl {%1pers} {%1pere}

' forecast with command *fit*
eq01.fit(f=na) g_f1 g_se g_var

' store forecasts
fcast=g_f1
fcastse=g_se
fcastvar=g_var

'calculate RMSE
scalar rmse=@rmse(returns, fcast)

‘calculate MAE
Scalar mae=@mae(returns, fcast)

next

smpl 4070 @last

I get the same results.

The same results by trying to use both methods (using my code)?
When doing it from the drop down menu I get RMSE=0.993259, MAE=0.797992
When I use the code RMSE=MAE=0.895579

Is there something wrng with my code? :?

Hi Gareth,

I am sorry to bother you, but I am really struggling to figure out what I am doing wrong.
For some reason my RMSE and MAE come out identical and both inconsistent with the results I get when using the drop down menu.
When I try the example you posted I seem to get it right, but when trying to apply it to my workfile it doesn't work :(

Could you please have a look at my code as I am unable to figure out what I am doing wrong?

Let's ignore the RMSE and MAE for the moment. You said that the actual forecast series are different. Is that true?

That is correct. Can this be caused by me using the rolling window?
I have attached a screen shot of my forecasts using the two approaches. ReturnsF is the one when I used the drop down menu, while Fcast is the one where I used the program.

Post the exact program you are using. Give precise details on exactly what you are doing when you generate the forecast.

When using the dropdown menu I estimate the simple GARCH(1.1) model by including "returns c returns(-1)" in the mean equation and nothing in the variance equation. I estimate my in-sample for 2/1/1995 12/30/2009, which equals 4070 observations. Then I press forecast - static - forecast sample "12/31/2009-6/13/2014"-deselect the "insert actuals for out of sample".

When trying to conduct a 1-step ahead forecast (1 day as I am using daily data) I use the following program:

'set window size' (my in-sample window)
!window=4070
'get size of workfile'
!lenght=@obsrange
'declare equation for estimation' (this is a standard GARCH(1.1) with a constant and a lagged value in the mean equation, which i have named eq01)
equation eq01
'set step size'
!step=1
'calculate number of rolls'
!nrolls=@floor((!lenght-!window)/!step)

'matrix to store coefficient estimates'
Matrix(5,!nrolls)coefmat 'where 5 is the number of coefficients
'series to store forecast estimates
series fcast
series fcastse
series fcastvar

'catching start and end points
%start= "@first"
%end= "@last"
'variable keeping track of how many rolls we've done
!j=0
'move sample !step obs at a time
for !i=1 to !lenght-!window+1-!step step !step
!j=!j+1
'set sample for estimation period
%first=@otod(@dtoo(%start)+!i-1)
%last=@otod(@dtoo(%start)+!i+!window-2)
smpl {%first} {%last}
'store coefficients
colplace(coefmat,eq01.@coefs,!j)

'1-period-ahead forecast (%1 because i want to forecast one day ahead)
%1pers=@otod(@dtoo(%start)+!i+!window-1)
%1pere=@otod(@dtoo(%start)+!i+!window+0)

'set smpl for forecasting period
smpl {%1pers} {%1pere}

' forecast with command *fit*
eq01.fit(f=na) g_f1 g_se g_var

' store forecasts
fcast=g_f1
fcastse=g_se
fcastvar=g_var

'calculate RMSE
scalar rmse=@rmse(returns, fcast)

'calculate MAE
Scalar mae=@mae(returns, fcast)

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