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An Empirical Analysis of Kenyan Daily Returns Using EGARCH Models

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  • Georges Ogum
  • Francisca M Beer
  • Genevieve Nouyrigat

    (CERAG - Centre d'études et de recherches appliquées à la gestion - UGA - Université Grenoble Alpes)

Abstract

This paper offers a comprehensive view of four time properties that emerge from the empirical time series literature on asset returns. It examines: (1) the predictability of returns from past observations; (2) the auto-regressive behavior of conditional volatility; (3) the asymmetric response of conditional volatility to innovations; (4) and the conditional variance risk premium. One emerging market previously under-researched in this respect is considered: Kenya (NSE index). The paper employs exponential GARCH (EGARCH) framework for the analyses. The results indicate that asymmetric volatility found in the U.S. and other developed markets does not appear to be a universal phenomenon. In Kenya, the asymmetric volatility coefficient is significant positive, suggesting that positive shocks increase volatility more than negative shocks of an equal magnitude. NSE (Kenya) returns series report negative but insignificant risk-premium parameters. The results also show that expected returns are predictable, the auto-regressive return parameter (Ø1) is significant. Finally, the GARCH parameter ( ) is statistically significant indicating that volatility persistence is present in Kenya

Suggested Citation

  • Georges Ogum & Francisca M Beer & Genevieve Nouyrigat, 2004. "An Empirical Analysis of Kenyan Daily Returns Using EGARCH Models," Post-Print hal-04533532, HAL.
    • Handle: RePEc:hal:journl:hal-04533532
    Note: View the original document on HAL open archive server: https://hal.science/hal-04533532
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