A Comparative study of exchange rate volatility in Sri Lanka and India

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2024

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Exchange rate is identified as one of the most discussed financial variables in finan- cial time series literature. Exchange rate can be recognized as the key driving factor in the global market as the exchange rate is the financial measurement of the value of one currency in terms of another currency. Therefore, exchange rate acts as the finan- cial medium between the countries that interact in the global market platform in the form of trade, investments etc. Exchange rate volatility can be described as the risk or the uncertainty in the exchange rate values. Anyone who is engaged in the activ- ities of the global market would benefit from information on the future behaviour of exchange rate volatility. Hence this research aims to forecast exchange rate volatility of the US dollar Sri Lankan rupee and the US dollar Indian rupee in a multivariate framework. The predictor variables are selected under three major categories; vari- ables representing the current account, variables representing the capital account and variables representing the volatility of the local market and foreign market. Data is collected for the period covering from December 2011 to April 2023 and according to the statistical test results, stationary behaviour, dynamic correlation behaviour and the presence of causality from each independent variable to dependent variables are exhibited in the data series. DCC-GARCH (1,1) model which captures the dynamic behaviour of the volatile time series variables is employed to forecast the exchange rate volatility of the US dollar Sri Lankan rupee and the US dollar Indian rupee. The resultsmodelresultshowedthatUSdollarSriLankanrupeeexchangeratevolatilityis more sensitive to the uncertainty of the own market, while US dollar Indian rupee ex- changeratevolatilityismoresensitivetothevariablesrepresentingthecurrentaccount of the country. Further, the economic uncertainty or the risk from the Western part of the world is more persistent on both of the exchange rate volatility. Model prediction accuracy results showed that the DCC-GARCH model provides more accurate results inpredictingUSdollarSriLankanrupeeexchangeratevolatilitywhereSriLankaisan Asian frontier market compared to the DCC-GARCH prediction of US dollar Indian rupee exchange rate volatility where India is an Asian emerging market.

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Kethmi, G.A.P (2024). Continuous [Master\'s theses, University of Moratuwa]. Institutional Repository University of Moratuwa. https://dl.lib.uom.lk/handle/123/23704

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