Predicting exchange rates using Taylor rule fundamentals: evidence from a portfolio optimisation framework
Date
2017
Authors
Jobo, Mathe Naleli
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Abstract
The paper studies exchange rate predictability using Taylor rule fundamentals in
an optimal portfolio framework.The study seeks to link exchange rate dynamics with
capital flows. Profit-seeking economic agents are assumed to repatriate funds across
borders in response to differentials in rates of return from risky assets of portfolios held.
We develop a uncovered portfolio return parity (UPRP) based exchange rate model
in which changes in the short-term nominal exchange rate depend on the difference of
optimal portfolio returns between two economies. In a two country economy where USA
is taken as the foreign country we test the model in 5 countries namely South Africa,
South Korea, Brazil, Mexico and Poland. The model is benchmarked against a UIP
model and a Random walk model in order to establish whether the study’s extension
enriches exchange rate prediction literature. We find that the main UPRP model
outperforms the Random walk model in the 12 month horizon for 4 out of 5 countries
using CW statistics. For the 1-month horizon the main model is outperformed by the
Random walk model in 4 out 5 countries and for the 2-month and 3-month horizons
the main model beats the Random walk using CW statistics. Theil’s U statistics also
show that with the exception of South Korea, the main model beats the Random walk
across all countries in the 3 and 12-month horizons. We conclude that out-of-sample
exchange rate forecasting based on an optimal framework and Taylor rule fundamentals
produces better nominal exchange rate forecasts relative to the Random walk model
and UIP model
Description
Thesis submitted in fulfillment of the requirements of the degree of
Master of Management in Finance and Investment
at
Wits Business School (WBS)
Faculty of Commerce, Law and Management
University of the Witwatersrand
Johannesburg
2017
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Citation
Jobo, Mathe Naleli (2017) Predicting exchange rates using Taylor rule fundamentals :evidence from a portfolio optimisation framework, University of the Witwatersrand, Johannesburg, <http://hdl.handle.net/10539/26200>