Yearly data cannot be converted to quarterly data.

Yeah, it can be done in eviwes

There are unsmoothing techniques that are used to re-noise financial time series data that fill in historical returns. Perhaps, begin your search with ARIMA model applications?

Yes there are methods to convert yearly data to quarterly data provided you have a related quarterly series. A typical old example was GDP for which value added tax (VAT) could be used. I entered your request in Google Scholar and found lots of papers. I will just mention Ginsburgh, Victor A. (1973), A Further Note on the Derivation of Quarterly Figures Consistent with Annual Data, Journal of the Royal Statistical Society. Series C (Applied Statistics) , Vol. 22, No. 3 (1973), pp. 368-374. Looking at papers citing it you will find more recent papers. Now, don't expect too much from this. I know that nowadays VAR models are built routinely with a mixture of quarterly, monthly, and even daily data. Good luck

Thank you Professor Guy Melard.

Thank you Professor Marc Faria.

While looking at something else, I felt on a working paper that refers to a paper by Anderson BD, Deistler M, Felsenstein E, Koelbl L. (2016). The structure of multivariate AR and ARMA systems: regular and singular systems; the single and the mixed frequency, Journal of Econometrics 192:366-373. It should be useful to you but I did not read it.

Hi Mohammad Mazibar, there several univariate methods to do that, as Prof. Melard mentions. There are also a few multivariate methods available (linked to the VAR methodology), such as the one a colleague of mine and I describe in the paper entitled "Temporal and Contemporaneous disaggregation of Multiple Economic Time Series" that you may find in the enclosed file.

Good luck and regards

Intead of looking for how you can convert your yearly data to quarterly data, it will be appropriate to use quaterly data set for your study.

Hi, i have a simple question can we transform this multivariate VAR into functional time series., if yes then how can apply VAR on order more than one in the functional version for forecasting of the multivariate time series data.