A Simple Approximate Long Memory Model of Realized Volatility
The paper proposes an additive cascade model of volatility components defined over different time periods. This volatility cascade leads to a simple AR type model in the realized volatility with the feature of considering different volatility components realized over different time horizons and thus termed Heterogeneous Autoregressive model of Realized Volatility (HAR RV) In spite of the simplicity of its structure and the absence of true long memory properties, simulation results show that the HAR RV model successfully achieves the purpose of reproducing the main empirical features of financial returns (long memory, fat tails, and self similarity) in a very tractable and parsimonious way. Moreover, empirical results show remarkably good forecasting performance. Copyright The Author 2009. Published by Oxford University Press. All rights reserved. For Permissions, please e mail: journals.permissions@oupjournals.org, Oxford University Press.