Template-Type: ReDIF-Paper 1.0
Author-Name: McAleer, M.J.
Author-Name-Last: McAleer
Author-Name-First: Michael
Author-Person: pmc90
Author-Name: Medeiros, M.C.
Author-Name-Last: Medeiros
Author-Name-First: Marcelo
Title: Forecasting Realized Volatility with Linear and Nonlinear Models
Abstract: In this paper we consider a nonlinear model based on neural networks as well as linear models to forecast the daily volatility of the S&P 500 and FTSE 100 indexes. As a proxy for daily volatility, we consider a consistent and unbiased estimator of the integrated volatility that is computed from high frequency intra-day returns. We also consider a simple algorithm based on bagging (bootstrap aggregation) in order to specify the models analyzed in the paper.
Creation-Date: 2009-11-24
File-URL: https://repub.eur.nl/pub/17303/EI2009-37.pdf
File-Format: application/pdf
Series: RePEc:ems:eureir
Number: EI 2009-37
Classification-JEL: C22, C53, G12, G17
Keywords: bagging, financial econometrics, neural networks, nonlinear models, realized volatility, volatility forecasting
Handle: RePEc:ems:eureir:17303