Partial GARCH Models for Forecasting Volatility

Partial GARCH Models for Forecasting Volatility
Author(s):
Dr. Ashwini Kumari
Keywords:
ARCH, GARCH, Partial linear models,Volatility.
Abstract
This paper deals with the forecasting of volatility using the partial GARCH model. Volatility is also influenced by some exogenous factors such as climate, scientific development, growth rate of population, political situation of a country, demonetisation etc. The influences of exogenous factors are considered in partial GARCH model. In this paper we modify the GARCH model by incorporating the influence of exogenous factors for improving accuracy in forecasting volatility. To study the impact of exogenous factor in volatility, we introduce the nonparametric component in the GARCH model. An improved forecasting model for Volatility is developed by combining GARCH with Nonparametric functional estimate. The performance of the proposed estimator is compared with GARCH estimator through a simulation study. Simulation study reveals that proposed model shows minimum mean square forecasting error compare to the existing model.
Article Details
Unique Paper ID: 153121 Publication Volume & Issue: Volume 8, Issue 5 Page(s): 608 - 614
Article Preview & Download

Share This Article

NCSST-2021

AICTE Sponsored National Conference on Smart Systems and Technologies

Last Date: 25th November 2021

LATEST INNOVATION’S AND FUTURE TRENDS IN MANAGEMENT

Last Date: 7th November 2021

IJIRT.org enables door in research by providing high quality research articles in open access market.

Send us any query related to your research on editor@ijirt.org