• India and USA’s data for last 36 years analyzed and ascertained impact of 7 important variables on exchange rate.
• New idea, thinking approach, analytical method for evaluating & studying the impact of these variables on exchange rate.
• A mathematical, exponential smoothing and moving average models and their regressions exhibiting the relationship and correlation with theexchange rate.
• All models are tested on the past data and it gives over 90% dependencies.
• Forecasting of Exchange Rates based on tested models mathematically and statistically.
• Giving effect of non-quantifying variables, reasonable estimations can be made.
• Help in formulating hedging strategy for exporter and importer.
• Explained various foreign exchange hedging techniques.
• Planning for long term/ short term foreign loan/ borrowing strategy.

The book demystifies the inscrutable process of determination of exchange rate with the help of regression. It offers an insightful and impressive analysis, and understanding of the concept over the past decade. It clearly states the assumptions made by the author. If anyone wishes to change the assumptions based on economic conditions, then certainly the result will vary.

The book will be of great help for the investors, bankers, fund managers etc. to assess the possible future movement of the rupee vis-à-vis the US dollar since a reasonable prediction can be made based on this model.

Vinay has the capabilities to further test the same kind of model with the different currencies.In future, he will definitely come up with other financial models too.

Dated: 28th february2015

I have gone through the models designed by Mr. Vinay Kshirsagar & Mr. Omkar Kshirsagar. The Models have been built by taking into consideration of the data on various Economic parameters for India and USA of last 36 years from 1980 to 2016.

The said input data used for these models is not tested for or validated by me on the assumption that the data taken is correct, unbiased and satisfies the condition of uniformity. The models have been worked out by using Mathematical method, Exponential smoothing average method and Moving Average method. For exponential smoothing method the value of smoothing constant is taken as 0.7 for this value logical explanation is given. Even in Moving average method weights are 0.55, 0.3, 0.1 and 0.05 which represent the proportion of the impact.

All the 3 models are tested for goodness of fit. The method used is regression analysis. This confirms the applicability of the model. The results show- Multiple correlation over 90%, dependency over 85%, significantly lower standard error, residual graph having random pattern, Significant F value ( P-value of overall model is less than 0.05 ). This shows all values are well within the acceptable limits which confirm the overall work-ability of the models to forecast the exchange rate.

Although some coefficients individually doesn't properly indicate the changes in exchange rate however all the coefficients together greatly influences the movement of exchange rate with very high degree of accuracy.

Also considering that the future prediction can never be 100% accurate however this Model is tested with past data for its fitness. The actual results are compared for the Financial years 2016 and 2017. Only the time will confirm its accuracy in the years to come.

I understand from authors that major Economic variables which impact the exchange rate are considered in building the model.

Further when asked about the removal of variables having insignificant impact on the model on the principle of p value and multicollinearity, it has been clarified that the author has done extensive research and evolve this model which has high degree of correlation and dependency. If one of the variables is removed in long runs it impacts. The final combination of these 7 variables gives the best results.

We wish authors all the very best in their future endeavours.

Mrs. Milan Gholba
Retd. Associate Professor,
Department of Statistics,
VPM’s B. N. Bandodkar College of Science, Thane

Dated: 28th September 2017

Initially we tried to work out mathematically; the exchange rate based on the resultant impact of the seven variables and plotted it against the actual exchange rate. Then we built the regression model from 1980 to 2016 and tested for long term but it did not work (because Indian economy was regulated and closed prior to 1991 and in 1991, it transformed into an open economy, thus there were many changes which happened in the last 30 years). But for short term, i.e., for a period of 15 years it worked, and if we plot results versus actual then it is seen that regression results are close to actual same as like we calculated in mathematical model.

For forecast, we have assumed the factors such as lending rate, inflation and growth rate, and other variables that have been projected on the basis of long- or short-term trend based on the earlier year figures. Then, we worked out the forecast based on the mathematical model as well as by regression. Then, we attempted to estimate the forecast of exchange rate in the next two years with the help of both models.

We further tested the conformity of the model through exponential smoothing and moving averages method and worked out regression on those two methods as well. All the 3 results give us the conclusion that numbers are closer and we have reason to believe that the result may be possible in the future. We also tested the biasness of the model and found that model is neither biased upwards nor biased downwards which shows great signs and increases the trust of the results derived by the model.