Modeling Stock Market Volatility Using GARCH Models Case Study of Dar es Salaam Stock Exchange (DSE)

This study was carried out to model volatility of stock returns at Dar es Salaam Stock Exchange (DSE) using daily closing stock price indices from 2nd January 2012 to 22nd November 2018. Modeling was done using both symmetrical and asymmetrical generalized auto regressive Heteroskedastic model (GARC...

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Bibliographic Details
Published in:Review of Integrative Business and Economics Research 2020-01, Vol.9 (2), p.138-150
Main Authors: Marobhe, Mutaju, Pastory, Dickson
Format: Article
Language:English
Subjects:
Automation
Capital markets
Institutional investments
New stock market listings
Rates of return
Securities markets
Securities prices
Stochastic models
Stock exchanges
Stock market indexes
Stock prices
Studies
Volatility
Withholding taxes
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Summary:This study was carried out to model volatility of stock returns at Dar es Salaam Stock Exchange (DSE) using daily closing stock price indices from 2nd January 2012 to 22nd November 2018. Modeling was done using both symmetrical and asymmetrical generalized auto regressive Heteroskedastic model (GARCH) models; these were GARCH (1,1), E-GARCH (1,1) and P-GARCH (1,1). The findings showed that all three (3) models were significant to forecast stock returns volatility at DSE. GARCH (1,1) and P-GARCH (1,1) both revealed that the magnitude of shocks in volatility is higher with good news as opposed to bad news. E-GARCH model (1,1) showed the evidence of leverage effect associated with the stock returns which can be detrimental to the trading companies' capital structures. P-GARCH (1,1) was found to be more accurate to in predicting stock returns based on both the Root Mean Squares Error (RMSE) and Theil Inequality Coefficient (TIC).
ISSN:2414-6722
2304-1013