Quantitative Finance Stack Exchange is a question and answer site for finance professionals and academics. Join them; it only takes a minute:

Sign up
Here's how it works:
  1. Anybody can ask a question
  2. Anybody can answer
  3. The best answers are voted up and rise to the top

I am working with data for an exotic currency, that has been re-denominated a couple of times during the twenty years of data that I have.

What is the best way of 'normalising' the data, so that I can work with the data, although it contains two 'switch over' dates on which the currency was re-denominated?

share|improve this question
Belarusian ruble ? :)) – IharS Aug 22 '14 at 12:48
up vote 3 down vote accepted

How is this different than a reverse stock split? If you just want the same scale for all the data, you'd just have to update the historic data using the reverse split ratio.

share|improve this answer
This is the approach that first occurred to me, but I was waiting to see if someone (possibly, more experienced) would suggest this too. – Homunculus Reticulli Sep 13 '14 at 20:15

why not run the same time series 3 times, once for each data set?

share|improve this answer

You are working with a time series $x(t)$ which has been re-denominated at times $t_1$ and $t_2$. You want to rescale the time series for all times $t < t_2$.

First, do you know what the rescaling factors ($k$) should be (e.g. did 1000 units turn into one unit)? If not, I would set $k_2:= t_2^+ / t_2^-$, where $t_2^-$ is the last currency rate before the last rescale, and $t_2^+$ is the first data point after the rescale. For all $t < t_2$, multiply all $x(t)$ by $k_2$. Do the same thing around $t_1$: set $k_1:= t_1^+ / t_1^-$ (if you have no other information on $k_1$) and then for all $t < t_1$, multiply all $x(t)$ by $k_1$.

Good luck!

share|improve this answer

Your Answer


By posting your answer, you agree to the privacy policy and terms of service.

Not the answer you're looking for? Browse other questions tagged or ask your own question.