Abstract
This study sought to model the stock market return volatility at the Nairobi Securities Exchange (NSE) in the presence of structural breaks. Using daily NSE 20 share index for the period 04/01/2010 to 29/12/2017, the market return volatility was modeled using different GARCH type models and taking into account four endogenously identified structural breaks. The market exhibited a non-normal distribution that was leptokurtic and negatively skewed and also showed evidence for ARCH effects, volatility clustering, and volatility persistence. We found that by considering structural breaks, volatility persistence was reduced, while leverage effects were found to lead to explosive volatility. In addition, investors were not rewarded for taking up additional risk since the risk premium was insignificant for the full period. However, during explosive volatility, investors were rewarded for taking up more risk. Moreover, we found that risk premium, leverage effects, and volatility persistence were significantly correlated. The GARCH (1,1) and TGARCH(1,1) models were found to be the best fit models to test for symmetric and asymmetric effects respectively. While the GARCH models were able to provide evidence for the stylized facts in the NSE, we conclude that the presence or absence of these features is period specific. This especially relates to volatility persistence, leverage effects, and risk premium effects. Caution should, therefore, be taken in using a specific GARCH model to forecast market return volatility in Kenya. It is thus imperative to pretest the data before any return volatility forecasting is done.
Highlights
In the wake of various global financial crises, the analysis of stock market return volatility has for a long time attracted the attention of academicians and practitioners
Presence of leverage effects increased the volatility persistence and the EGARCH model was prevalent at exhibiting explosive volatility for all periods unlike the other models in the study due to its exponential growth on the conditional variance
We found that leverage effect, volatility persistence and risk premium were correlated
Summary
In the wake of various global financial crises, the analysis of stock market return volatility has for a long time attracted the attention of academicians and practitioners. This is due to the role it plays in the stock market trading system. An unstable stock market will impact on the stability of the financial sector of any economy(Sinha, 2012 ). Stock market return volatility may create an efficient and liquid market and it is not always destructive. Excess market return volatility may cause financial market crisis and crashes which affects both developed and emerging markets ( Huwart and Verdier,2013 )
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