Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/10579
Title: Exchange Rate Behaviour in Ghana
Authors: Atepor, Loretta Aku Yayra
Keywords: Autoregressive fractionally integrated moving average
Denoising
Ensemble empirical mode decomposition
Exchange rate
Issue Date: Dec-2021
Publisher: University of Cape Coast
Abstract: ABSTRACT Exchange rate is a key economic variable all around the world due to its multi faceted nature and its effect on the lives of every individual in many ways. However, the non-linear and the non-stationary characteristics of exchange rates make them difficult to understand their dynamics as well as factors that drive exchange rates. Therefore, the behaviour of the GHS/USD exchange rate from 2000 to 2019 was examined in this research work. The study adopted the heterogeneous market hypothesis (HMH) to explain the intrinsic characteristics of the GHS/USD exchange rate. To achieve the objectives of the study, the ensemble empirical mode decomposition (EEMD) technique was employed to determine the factors influencing the GHS/USD exchange rate. Using the EEMD, the GHS/USD exchange rate was decomposed into intrinsic mode functions (IMFs) and a residue. Secondly, the IMFs and the residue were classified into high-frequency, medium-frequency, low frequency and trend components. These were then analysed and it was found that the macroeconomic fundamentals were the main drivers of GHS/USD exchange rates. Finally, the rescaled range analysis (R/S analysis) and the autoregressive fractionally integrated moving average (ARFIMA) were used to also investigate and analyse the existence of long memory in GHS/USD exchange rates. It was observed that the GHS/USD exchange rates possessed long memory characteristics. It is, therefore, recommended that policymakers, as well as investors, should closely monitor the movement of the exchange rates and macroeconomic fundamentals when formulating exchange rate policies and adopting investment strategies.
Description: ii,ill:92
URI: http://hdl.handle.net/123456789/10579
Appears in Collections:Department of Accounting & Finance

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