Return volatility and equity pricing: a frontier market perspective
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Social science research network
Abstract
Using both monthly and weekly return series between 1999:01 and 2013:12, we investigate the dynamics of stock returns and volatility in a Kenya’s fledgling equity market – the Nairobi Securities Exchange. Both the GARCH-in-mean and E-GARCH models yield positive and significant conditional variance parameters. We also find that shocks to equity returns of conditional volatility are highly persistent. Our results also indicate that conditional variance is driven more by the past conditional variance than it is driven by new disturbances. Finally, we find evidence of volatility clustering in the stock markets around major world and domestic economic episodes. Results are consistent with the inference that investors require larger risk premia on equities if they anticipate greater price volatility in future.
Description
Journal article published in Social Science Research Network (SSRN) available at SSRN: http://ssrn.com/abstract=2520737 or http://dx.doi.org/10.2139/ssrn.2520737
Using both monthly and weekly return series between 1999:01 and 2013:12, we investigate the dynamics of stock returns and volatility in a Kenya’s fledgling equity market – the Nairobi Securities Exchange. Both the GARCH-in-mean and E-GARCH models yield positive and significant conditional variance parameters. We also find that shocks to equity returns of conditional volatility are highly persistent. Our results also indicate that conditional variance is driven more by the past conditional variance than it is driven by new disturbances. Finally, we find evidence of volatility clustering in the stock markets around major world and domestic economic episodes. Results are consistent with the inference that investors require larger risk premia on equities if they anticipate greater price volatility in future.
Using both monthly and weekly return series between 1999:01 and 2013:12, we investigate the dynamics of stock returns and volatility in a Kenya’s fledgling equity market – the Nairobi Securities Exchange. Both the GARCH-in-mean and E-GARCH models yield positive and significant conditional variance parameters. We also find that shocks to equity returns of conditional volatility are highly persistent. Our results also indicate that conditional variance is driven more by the past conditional variance than it is driven by new disturbances. Finally, we find evidence of volatility clustering in the stock markets around major world and domestic economic episodes. Results are consistent with the inference that investors require larger risk premia on equities if they anticipate greater price volatility in future.
Keywords
Volatility, equity returns, Nairobi Securities Exchange, GARCH