Backward prediction stock time series

Hello Everyone,

Im currently writing my thesis and need to backward predict the values of a stock price time series.

I have data of a stock from 2018-2020, but i want to predict the values for 2016-2017 in order to have

a full time series from 2016-2020.

Could you help me with the coding or advice on how to do this? I the data of one of the stocks.

Appreciate you time guys!

Answer 1

[Sulaymon Eshkabilov]

In this case, you'd need to perform the followings in order to extrapolate backward:

(1) Import data, e.g.:

D = readtable('https://www.mathworks.com/matlabcentral/answers/uploaded_files/717269/PR1C_dailyvalues.xlsx')

(2) Select rows where nans are not present:

IDX = isnan(D.PR1C);

(3) Convert the dates to numbers:

F1 = D(IDX==1,1).Date; F1D = datenum(F1); F1D=F1D-F1D(1)+1;
F2 = D(IDX==0,1).Date; F2D = datenum(F2); F2D=F2D-F2D(1)+1;
Data = D(IDX==0,2).PR1C;

(4) Find a fit model:

FM = fit(F2D,Data,'poly3'); % Cubic polynomial

(5) Compute the extrapolation values:

FIT_Data = polyval(FM, F1D);
% etc.

[ingCr]

Thanks! that helped me a lot. The only thing is that I stil cant make the backward prediction. Keeps telling me that there is a problem with the data structure.

Do you happen to know who to do the same but with a time-series model?

Appreciate your time!