{"id":{"repo_id":"zulu","oai_identifier":"oai:uzspace.unizulu.ac.za:10530/1643"},"canonical_url":"https://search.dev.ndltd.org/etd/zulu/oai:uzspace.unizulu.ac.za:10530/1643","repository":{"repo_id":"zulu","name":"University of Zululand","base_url":"https://uzspace.unizulu.ac.za/server/oai/request"},"display":{"title":"Predictability of the Dollar- Rand exchange rate using Taylor Rule fundamentals and commodity Prices.","abstract":"International trade is strongly hinged on the exchange rates of participating nations. The financial crisis of 2008/2009 amongst other things, brought to light the strong interdependence of nations and their currencies. It is therefore of paramount importance for South Africa to be able to effectively predict its long and short term exchange rates especially vis-à-vis its major trading currency, the US dollar. South Africa being a small open commodity exporting economy with inflation targeting as a monetary policy framework is quite vulnerable to international shocks. This paper is an attempt to forecast the US/ R exchange rate using time series data for the period 1980-2016. The paper estimated three forecasting models, namely, the augmented Taylor rule specification, a Johansen Vector Error Correction Model (VECM) and a Random walk approach. The results from the Root Mean Squared Error (RMSE) show that the Random walk model outperforms both the Taylor rule and VECM models. This brings us to the conclusion that although commodity prices and interest rates may influence short term international trade flows, they are not strong enough to influence exchange rate in the long term. Future researchers should attempt to use other variables, such as socio-political instability and downward economic ratings, in explaining exchange rate movements and forecasting using more sophisticated techniques like neural networks or dynamic stochastic general equilibrium modelling.","abstract_html":"International trade is strongly hinged on the exchange rates of participating nations. The financial crisis of 2008/2009 amongst other things, brought to light the strong interdependence of nations and their currencies. It is therefore of paramount importance for South Africa to be able to effectively predict its long and short term exchange rates especially vis-à-vis its major trading currency, the US dollar. South Africa being a small open commodity exporting economy with inflation targeting as a monetary policy framework is quite vulnerable to international shocks. This paper is an attempt to forecast the US/ R exchange rate using time series data for the period 1980-2016. The paper estimated three forecasting models, namely, the augmented Taylor rule specification, a Johansen Vector Error Correction Model (VECM) and a Random walk approach. The results from the Root Mean Squared Error (RMSE) show that the Random walk model outperforms both the Taylor rule and VECM models. This brings us to the conclusion that although commodity prices and interest rates may influence short term international trade flows, they are not strong enough to influence exchange rate in the long term. Future researchers should attempt to use other variables, such as socio-political instability and downward economic ratings, in explaining exchange rate movements and forecasting using more sophisticated techniques like neural networks or dynamic stochastic general equilibrium modelling.","abstract_has_math":false,"creators":["Olowe, Ayodele Rita"],"institution":"University of Zululand","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2018,"date_issued":"2018","date_published":"2018","updated_at":"2026-07-24T06:17:08Z","subjects":["exchange rate --forecasting --Taylor rule --commodity price --VAR/VECM --random walk model"],"languages":[],"rights":[],"rights_urls":["https://devspace.unizulu.ac.za/bitstreams/6fd44ae6-7cc6-4dc7-9ff1-196d24420472/download"],"identifier_entries":[]},"links":{"outbound_url":null,"outbound_label":null,"outbound_source":null},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:creator","label":"Author","values":["Olowe, Ayodele Rita"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.issued","label":"Date","values":["2018"]},{"key":"dc:publisher.institution","label":"Dc Publisher Institution","values":["University of Zululand"]},{"key":"dc:relation.isreferencedby","label":"Dc Relation Isreferencedby","values":["http://uzspace.unizulu.ac.za:8080/xmlui/handle/10530/1643"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["exchange rate --forecasting --Taylor rule --commodity price --VAR/VECM --random walk model"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:rights","label":"Dc Rights","values":["https://devspace.unizulu.ac.za/bitstreams/6fd44ae6-7cc6-4dc7-9ff1-196d24420472/download"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://devspace.unizulu.ac.za/bitstreams/9cb876af-2ef9-4e74-b54b-4742c3ded271/download"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["International trade is strongly hinged on the exchange rates of participating nations. The financial crisis of 2008/2009 amongst other things, brought to light the strong interdependence of nations and their currencies. It is therefore of paramount importance for South Africa to be able to effectively predict its long and short term exchange rates especially vis-à-vis its major trading currency, the US dollar. South Africa being a small open commodity exporting economy with inflation targeting as a monetary policy framework is quite vulnerable to international shocks. This paper is an attempt to forecast the US/ R exchange rate using time series data for the period 1980-2016. The paper estimated three forecasting models, namely, the augmented Taylor rule specification, a Johansen Vector Error Correction Model (VECM) and a Random walk approach. The results from the Root Mean Squared Error (RMSE) show that the Random walk model outperforms both the Taylor rule and VECM models. This brings us to the conclusion that although commodity prices and interest rates may influence short term international trade flows, they are not strong enough to influence exchange rate in the long term. Future researchers should attempt to use other variables, such as socio-political instability and downward economic ratings, in explaining exchange rate movements and forecasting using more sophisticated techniques like neural networks or dynamic stochastic general equilibrium modelling."]},{"key":"dc:format.checksum.md5","label":"Dc Format Checksum Md5","values":["3c534d9f632defd8fd54436506173290","8a4605be74aa9ea9d79846c1fba20a33","cc9889d1fb84c91605001074c1244b7a"]},{"key":"dc:title","label":"Title","values":["Predictability of the Dollar- Rand exchange rate using Taylor Rule fundamentals and commodity Prices."]}]}],"canonical_facts":{"dc:creator":["Olowe, Ayodele Rita"],"dc:date.issued":["2018"],"dc:description.abstract":["International trade is strongly hinged on the exchange rates of participating nations. The financial crisis of 2008/2009 amongst other things, brought to light the strong interdependence of nations and their currencies. 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