Munich Personal RePEc Archive

Non-Stationary Stochastic Volatility Model for Dynamic Feedback and Skewness

Mukhoti, Sujay (2014): Non-Stationary Stochastic Volatility Model for Dynamic Feedback and Skewness.

[img]
Preview
PDF
MPRA_paper_62532.pdf

Download (622kB) | Preview

Abstract

In this paper I present a new single factor stochastic volatility model for asset return observed in discrete time and its latent volatility. This model unites the feedback effect and return skewness using a common factor for return and its volatility. Further, it generalizes the existing stochastic volatility framework with constant feedback to one with time varying feedback and as a consequence time varying skewness. However, presence of dynamic feedback effect violates the weak-stationarity assumption usually considered for the latent volatility process. The concept of bounded stationarity has been proposed in this paper to address the issue of non-stationarity. A characterization of the error distributions for returns and volatility is provided on the basis of existence of conditional moments. Finally, an application of the model has been explained using S&P100 daily returns under the assumption of Normal error and half Normal common factor distribution.

UB_LMU-Logo
MPRA is a RePEc service hosted by
the Munich University Library in Germany.