MCFAM Seminar - Modeling heteroscedastic, skewed and leptokurtic returns in discrete time

Speaker: Joseph Ivivi Mwaniki, University of Nairobi

Abstract: Popular models of finance, fall short of  accounting  for  most empirically  found stylized features of financial time series data, such as volatility clustering, skewness  and leptokurtic nature of log returns. In this study we propose a general framework for modeling  asset  returns which  account for serial dependencies in higher  moments and  leptokurtic nature  of  scaled GARCH filtered residuals.  Such  residuals are calibrated to normal inverse Gaussian and hyperbolic  distribution. Dynamics of risky assets assumed  in  Black Scholes model, Duans(1995) GARCH model  and other benchmark models for option valuation, are shown to be  nested in the proposed framework. Different sets of data are  used to support  the proposed framework.

Start date
Friday, Nov. 19, 2021, Noon
End date
Friday, Nov. 19, 2021, 1 p.m.