Testing For Long Memory In The South Asian Foreign Exchange Rates

Exchange rate movements have a great impact on the political and Economic stability of a country. Understanding the dynamic behavior of exchange is extremely important for decision makers such as legislators, investors and market participations in foreign exchange markets. The efficiency of the foreign exchange market is related to the long memory property of the exchange rate dynamics. The question of whether exchange rate markets are efficient or not, is directly related to the long memory in the exchange rate changes. Therefore, detecting long memory in an exchange rate dynamic is important to understand whether exchange rate markets of an economy are efficient or not. Long memory suggests very strong market inefficiency. However, South Asian exchange rates have not received much attention about long memory in the finance literature. This study intends to fill this gap in the finance literature by examining the long memory properties of the South Asian foreign exchange rates against to U.S. dollar, namely Sri Lankan Rupee (LKR/USD), Indian Rupee (INR/USD), Pakistan Rupee (PKR/USD), Bangladesh Taka (BDT/USD), Bhutanese Ngultrum (BTN/USD), Nepalese Rupee (NPR/USD), Maldivian Rufiyaa (MVR/USD) and the Afghan Afghani (AFN/USD). The study covers the period from January 1, 2007 to December 31, 2017 consisting 2870 daily observations per country. The growth rates of daily exchange rate are measured by the return series defined as log difference of exchange rate. These data were collected from the Central bank of Sri Lanka. To examine the random walk nature (issue of unit roots) of empirical exchange rate behavior, standard unit root tests; the ADF test (Dickey & Fuller, 1979, 1981) and the PP test (Phillips & Perron, 1988), and the KPSS test (Kwiatkowski-Phillips-Schmidt-Shin (1992)) are implemented on all exchange rate series. The ADF and PP tests are used to test the null hypothesis of the series are non-stationary I(1), against the alternative that they are stationary. The null hypothesis of KPSS test is: series is stationary against series are nonstationary. To achieve the main objective of the study, a battery of non-parametric (Rescaled Range Statistics (R/S)), Semi-parametric (Geweke and Porter-Hudak (GPH) and Local Whittle Estimator (LWE)), parametric (Fractionally Integrated Autoregressive Moving Average (ARFIMA)) tests are employed based on econophysics models. Tests show that exchange rate return series have long memory except Maldivian Rufiyaa (MVR/USD), Bangladesh Taka (BDT/USD) and Afghan Afghani (AFN/USD) and they are fractionally integrated. The fractional difference parameters are significant at 5 % level. Findings showed that south Asian foreign exchange rates except Afghanistan, Bangladesh and Maldives possess long memory. The findings of the study have policy implications for traders and investors in implementing trading strategies. The results indicate that an exchange rate market which has long memory is not efficient.