Adenomon, M.O.; Mbuk, J.J.; Yahaya, H.U. Modeling Volatility of Nigeria Stock Exchange Using Multivariate GARCH Models. Preprints2019, 2019020039. https://doi.org/10.20944/preprints201902.0039.v1
APA Style
Adenomon, M.O., Mbuk, J.J., & Yahaya, H.U. (2019). Modeling Volatility of Nigeria Stock Exchange Using Multivariate GARCH Models. Preprints. https://doi.org/10.20944/preprints201902.0039.v1
Chicago/Turabian Style
Adenomon, M.O., John Joseph Mbuk and Haruna Umar Yahaya. 2019 "Modeling Volatility of Nigeria Stock Exchange Using Multivariate GARCH Models" Preprints. https://doi.org/10.20944/preprints201902.0039.v1
Abstract
The aim of this research work was to provide model for predicting stock volatility in Nigeria Stock market. To achieve this, monthly data for Nigerian stock exchange, Exchange rate, Share index and inflation rate was collected for a period of January 1990 to December 2016.The descriptive statistics revealed these variables to exhibit volatility as a characteristics of financial time –varying series. DCC Model was fitted, were the coefficients for all the parameters and that of the correlation-Targeting (rho_21) are both negative and positive and tend very close to 1 and -1, indicating that high persistence in the conditional variances. The Model DCC, satisfied the properties of a good model of conditional mean and variance of the confidential Interval (C.I) of 1 and -1, that is, the conditional variances are finites and their series are strictly stationary. This therefore implies that the Nigerian Stock Exchange, Exchange rate, share index and Inflation rate will experience a non-steady shock in the Stock market. However Each of these variables have different length of recovery (volatility half- life) ranging from 1.5month, 6.5months, 6months to 2,4months for stock exchange, exchange rate, share index and inflation rate respectively. By implication, the volatility of these variables had a long memory, persistence and mean-reverting.
Computer Science and Mathematics, Probability and Statistics
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
