Preprint Article Version 1 This version is not peer-reviewed

Modeling Volatility of Nigeria Stock Exchange Using Multivariate GARCH Models

Version 1 : Received: 2 February 2019 / Approved: 4 February 2019 / Online: 4 February 2019 (14:56:07 CET)

How to cite: Adenomon, M.O.; Mbuk, J.J.; Yahaya, H.U. Modeling Volatility of Nigeria Stock Exchange Using Multivariate GARCH Models. Preprints 2019, 2019020039 (doi: 10.20944/preprints201902.0039.v1). Adenomon, M.O.; Mbuk, J.J.; Yahaya, H.U. Modeling Volatility of Nigeria Stock Exchange Using Multivariate GARCH Models. Preprints 2019, 2019020039 (doi: 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.

Subject Areas

Volatility; Stocks; Persistence; Exchange Rate, Inflation Rate; Financial Time Series; Generalized Autoregressive Conditional Heteroscedasticity (GARCH); Multivariate GARCH (MGARCH)

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