An analytical study on currency correlation and risk grading

The aim of this paper is to investigate the correlation among the major trading currencies and grading of those currencies based on the volatility. In order to realise the stated objectives the researchers have collected the data from 2010 to 2016 from various data sources of major trading currencies such as Indian Rupees (INR), US Dollar (US$), British Pound (GBP), Japanese Yen (JPY), Euro (EUR), Canadian Dollar (CA$), Swiss Franc (CHF), Singapore Dollar (SG$), Australian Dollar (AU$), New Zealand Dollar (NZ$), Hong Kong Dollar (HK$). In the very first phase the collected time series data has been tested for the stationarity by conducting ADF test. In the very first phase, the exchange rates of all the currencies on the basis of Indian Rupee are tabulated and correlation coefficients among each currency with each other have been calculated by taking reference of INR. In the next phase, the reference base has been changed to other strong and most traded among ten currencies and in the last phase, correlation among the cross currency exchange rates were tested for the significance by running student t test and risk grading has been assigned based on the volatility of each currency on the basis of standard deviation between base period and the current period. The study revealed that only US$ fall in the category of “B+” which means it has average transaction related risk. Euro, SNGD, Japan, Swiss Franc, Canadian dollar, Australian dollar, INR, Hong Kong dollar, New Zealand dollar currency has fallen in the category of “D” which means currency is highly volatile and risky compared to other currency like US dollar which is very stable. However, Pound Sterling which falls under category C.