Signal Model for Prediction of Exchange Rates
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Date
2017-05
Authors
Agwuegbo, S.O.N.
Onugha, E.E.
Akintunde, A.A.
Adewole, A.P.
Journal Title
Journal ISSN
Volume Title
Publisher
Journal of the Nigerian Association of Mathematical Physics
Abstract
The appropriate prediction of exchange rates is an area of financiaL forecasting which attracts a great deal of attention. For many years, the volatile nature of exchange rates has been the focus of Many researchers. Many researchers attribute interest in exchange rate volatility to the fact that it is empirically difficult to predict future exchange rate values. Foreign exchange market generally produces observable outputs which can be characterised as signals. III this study we investigated the monthly average exchange rates of usDollars to the Nigerian Naira using signal modelling approach, Front the study, there is a convincing statistical evidence to believe that exchange rates can be better modelled by a Markov process as the output of a first order discrete autoregressive process. The result demonstrated that a Markov process is sometimes called a first order autoregressive process.
Description
Staff publications
Keywords
Dynamics , Stationary process , Gaussian , Markov process , Martingale , Research Subject Categories::TECHNOLOGY::Information technology::Computer science
Citation
Agwuegbo, S.O.N, Onugha, E.E, Akintunde A.A. and Adewole, A.P. (2017). Signal Model for Prediction of Exchange Rates. Journal of the Nigerian Association of Mathematical Physics, Vol.41: 261-268pp.