  This paper uses the concepts of entropy to study the regularity/irregularity
of the returns from the Indian Foreign exchange (forex) markets. The
Approximate Entropy and Sample Entropy statistics which measure the level of
repeatability in the data are used to quantify the randomness in the forex
returns from the time period 2006 to 2021. The main objective of the research
is to see how the randomness of the foreign exchange returns evolve over the
given time period particularly during periods of high financial instability or
turbulence in the global financial market. With this objective we look at 2
major financial upheavals, the subprime crisis also known as the Global
Financial Crisis (GFC) during 2006-2007 and the recent Covid-19 pandemic during
2020-2021. Our empirical results overwhelmingly confirm our working hypothesis
that regularity in the returns of the major Indian foreign exchange rates
increases during times of financial crisis. This is evidenced by a decrease in
the values of the sample entropy and approximate entropy before and
after/during the financial crisis period for the majority of the exchange
rates. Our empirical results also show that Sample Entropy is a better measure
of regularity than Approximate Entropy for the Indian forex rates which is in
agreement with the theoretical predictions.
