VOLATILITY ESTIMATION OF STOCK PRICES USING GARCH METHOD

Authors

  • Peter N Mwita Jomo Kenyatta University of Agriculture and Technology, Kenya
  • joel koima Kabarak University
  • Dankit K Nassiuma African International University, Kenya

Keywords:

GARCH, Stylized facts, Volatility clustering

Abstract

Economic decisions are modeled based on perceived distribution of the random variables in the future, assessment and measurement of the variance which has a significant impact on the future profit or losses of particular portfolio. The ability to accurately measure and predict the stock market volatility has a wide spread implications. Volatility plays a very significant role in many financial decisions.

The main purpose of this study is to examine the nature and the characteristics of stock market volatility of Kenyan stock markets and its stylized facts using GARCH models. Symmetric volatility model namly GARCH model was used to estimate volatility of stock returns. GARCH (1, 1) explains volatility of Kenyan stock markets and its stylized facts including volatility clustering, fat tails and mean reverting more satisfactorily.The results indicates the evidence of time varying stock return volatility over the sampled period of time.

In conclusion it follows that in a financial crisis; the negative returns shocks have higher volatility than positive returns shocks.

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Author Biography

Peter N Mwita, Jomo Kenyatta University of Agriculture and Technology, Kenya

Department of Statistics and Actuarial SciencesJomo Kenyatta University of Agriculture and Technology P.O Box 62000-00200, Nairobi, KENYA.Cell phone: 0721429770 Email: peter_mwita@yahoo.com or petermwita@fsc.jkuat.ac.ke Skype: peter.nyamuhanga

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Published

2015-03-04

How to Cite

Peter N Mwita, Joel Koima, & Dankit K Nassiuma. (2015). VOLATILITY ESTIMATION OF STOCK PRICES USING GARCH METHOD. Kabarak Journal of Research & Innovation, 3(1), 48–53. Retrieved from https://journals.kabarak.ac.ke/index.php/kjri/article/view/12