Skip to main content

Research Repository

Advanced Search

Measure of volatility and its forecasting: evidence from Naira / Dollar exchange rate

Adedotun, A; Onasanya, O; Alfred, O; Agboola, O; Okagbue, H

Measure of volatility and its forecasting: evidence from Naira / Dollar exchange rate Thumbnail


Authors

A Adedotun

O Onasanya

O Alfred

O Agboola

H Okagbue



Abstract

In the last five decades, Box Jenkins methodology has been in existence to model univariate time series data but fails or has limitations on modeling volatility. Most financial time series data do exhibit heavy tail and thick distribution, to this effect various parametric and semi-parametric non –linear time series models have been proposed two or three decades ago to capture volatility. However, this research entails measuring volatility and its forecasting using time series exchange rate annual data over the period from 1981 to 2020 (wide periodicity). The exchange rate was transformed to return, and parametric non –linear time series was modeled on it. It was found out that GARCH (1,2) reveals continuous volatility for short while and was the best model to predict the exchange rate volatility based on the evidence from measurement volatility tool; RMSE, MAE, MAPE among other extensions of GARCH models; EGARCH and TGARCH. EGARCH (1, 4) captures the asymmetry effect revealing that negative shocks will persistently have an effect on the volatility of the naira/dollar exchange rate.

Citation

Adedotun, A., Onasanya, O., Alfred, O., Agboola, O., & Okagbue, H. (2022). Measure of volatility and its forecasting: evidence from Naira / Dollar exchange rate. Mathematical modelling and engineering problems (Online), 9(2), 498-506. https://doi.org/10.18280/mmep.090228

Journal Article Type Article
Acceptance Date Feb 19, 2022
Online Publication Date Apr 28, 2022
Publication Date Apr 28, 2022
Deposit Date Aug 30, 2022
Publicly Available Date Aug 30, 2022
Journal Mathematical Modelling of Engineering Problems
Print ISSN 2369-0739
Electronic ISSN 2369-0747
Volume 9
Issue 2
Pages 498-506
DOI https://doi.org/10.18280/mmep.090228
Publisher URL https://doi.org/10.18280/mmep.090228

Files




Downloadable Citations