Turn-of-month effect in the Indian currency market

摘要

Purpose - The purpose of this paper is to examine the presence of the turn-of-month effect in the Indian currency market for selected currency pairs: USD-INR, EUR-INR, GBP-ESIR and JPY-INR, from January 1999 to April 2014. Design/methodology/approach - Ordinary least square regression analysis is used to examine the presence of the turn-of-month effect and to test the efficiency of the Indian currency market. The characteristics of the returns during the turn-of-month days are compared with that of the non-turn-of-month trading days. The sample period is later divided into two sub-periods, that is, pre- and post-2008 to capture the behavior of returns before and after the 2008 financial crisis. Findings - The results indicate the existence of pricing patterns which are unique to individual currencies. For the entire sample period, USD and JPY exhibit turn-of-month effect and the returns in turn-of-month trading days are significantly lower than the returns during non-turn-of-month trading days. For the sub-period before 2008, all the currencies exhibit significant turn-of-month effects and the returns in the turn-of-month trading days are significantly lower than those in the non-turn-of-month trading days. However, post-2008; this effect vanishes for all the currencies except for USD. Practical implications - The results have important implications for both traders and investors. The findings suggest that the investors might not be able to earn excess profits by timing their positions in some particular currencies taking the advantage of turn-of-month effect which in turn indicates that the currency markets have become more efficient with time. The results are in conformity with those reported for the developed markets. Originality/value - To the best of the author's knowledge, no study has yet examined these calendar anomalies in the currency markets using data which covers two important periods, pre-2008 and post-2008. Therefore, we provide a pioneer study in which we analyze the calendar anomalies in an emerging currency market (India) by segregating the data before and after 2008 financial crisis.