how to treat the last observation? Forecasting??

Dear all,

I have the following cell matrix

A={

 '24/09/2000'                  [4.1583]
    '22/10/2000'              [3.9389]
   '19/11/2000'               [4.3944]
    '17/12/2000'              [3.9313]
   '14/01/2001'               [3.9313]
    '11/02/2001'               [3.9313]
    '11/03/2001'              [4.0339]}

I can easily convert the above data points to monthly averages; through the calculation of the weighted average between successive observations.

For instance for the first observation I have

24*4.1583+ 6*3.9389

where 24 is the 24 days from month Octomber and 6=(last date of the month-24=30-24) The only problem is how to treat the last observation:

11*4.0339+?

One way is to extrapolate but I do not consider this method reliable. The above values are prices. So could I apply some other way? Maybe forecasting taking into account seasonality?

Any help/code provided will greatly appreciated

thanks

[Oleg Komarov]

Why do you call them averages? You don't have multiple observations per month. Have you looked at interp1(), you can also extrapolate to the last day of March 2001.

[antonet]

HOw can I extrapolate to the last day of march 2001?

I tried but I do not know if I am correct

[Walter Roberson]

You do not have enough data to forecast with, not with any meaningful accuracy.

[antonet]

Hi Walter. I have. the above matrix is an example

Answer 1

[Oleg Komarov]

A ={'24/09/2000'    4.1583
    '22/10/2000'    3.9389
    '19/11/2000'    4.3944
    '17/12/2000'    3.9313
    '14/01/2001'    3.9313
    '11/02/2001'    3.9313
    '11/03/2001'    4.0339};

% Convert to tractable double matrix, i.e. use serial dates

A = [datenum(A(:,1),'dd/mm/yyyy') cat(1,A{:,2})];
A =
                    730753                    4.1583
                    730781                    3.9389
                    730809                    4.3944
                    730837                    3.9313
                    730865                    3.9313
                    730893                    3.9313
                    730921                    4.0339

% Create a list of end-of-month dates (using two tricks):

1. create first-day-of-next-month dates and subtract one
2. datenum() automatically adjusts the date in case one of the units exceeds the max accepted value

xi = datenum(2000,10:16,1)-1;

% Interpolate

B  = interp1(A(:,1),A(:,2), xi,'linear','extrap');

% Plot

plot(A(:,1),A(:,2),'-dr',xi,B,'-ob')
set(gca,'Xtick',sort([A(:,1); xi']),'xgrid','on')
datetick('x','dd/mm','keepticks')