dcsimg
 

5 Critical Tools for Your Lean Deployment

As your customers demand more and organizations fight to stay competitive, the battle to create more value with fewer resources is ever present. How can you leverage Lean tools to thrive in your business?

Save Your Seat

How to Use Statistical Software to Predict the Exchange Rate

The Minitab Fan section of the Minitab blog is your chance to share with our readers! We always love to hear how you are using Minitab products for quality improvement projects, Lean Six Sigma initiatives, research and data analysis, and more. If our software has helped you, please share your Minitab story, too!

My LSS coach suggested that I regularly conduct data analysis to refresh my Minitab skills. I'm sure many of you have heard about the devaluation of Russian currency caused by European Union and United States sanctions, and dropping oil prices. 

I decided to check this situation with statistical analysis. The question I intended to answer was simple: is there any correlation between Brent oil price and the exchange rate between the Russian ruble and the U.S. dollar?

I found relevant data from 01-Jan-2014 through 18-Dec-2014 and used the regression tools in Minitab statistical software to interpret it.

First I looked at the model and saw the regression equation was:

RR/USD = 78,90 - 0,4071 USD/bbl (Brent), with R-Sq(adj) = 90,2%

This means that the model describe the behavior of RR/USD exchange rate on 90%, which is very good. Another 10% can be assigned to outside USD/bbl (Brent) factors, such as sanctions.
Then I paid attention to Residual Plots.


Ideally the residuals should be distributed randomly. In the real world we see that at the end of data observation the residuals are much higher than expected (see graphs in the right column).

This is very much correlated with recent news: many people in Russia are now buying foreign currency to avoid further devaluation. That kind of people behavior significantly increases the currency demand and exchange rate.

If we would build the graph when oil price was moving within $110 and $85 USD/bbl (Brent), then we expect that when the oil price was 60, the RR/USD exchange rate should be about 45-50 rubles per US dollar. But we actually see that it falls within 60-70, which may reflect panic on the Russian exchange market.

The conclusions I draw from my analysis:

1. There is a strong correlation between Brent oil price and the exchange rate between the Russian ruble and U.S. dollar. About 90% of the ruble's fall can be explained by the oil price.

2. Be careful when you build a regression model and do not “extend” it for the interval you have not tested it, as you may encounter with another significant factors which are beyond consideration.

You can see that now the ruble is cheaper that it is expected based on oil prices. So maybe it is a good time for you to visit Russia!

Alexander Drevalev
Consultant and Master Black Belt
Accenture
Moscow, Russia


 

Comments

blog comments powered by Disqus