A Generalized Heterogeneous Autoregressive Model using the Market Index

47 Pages Posted: 18 Dec 2019

See all articles by Rodrigo Hizmeri

Rodrigo Hizmeri

Lancaster University

Marwan Izzeldin

Lancaster University Management School

Ingmar Nolte

Lancaster University - Department of Accounting and Finance

Vasileios Pappas

University of Kent, Kent Business School

Date Written: December 2, 2019

Abstract

This paper shows that generalizing the heterogeneous autoregressive model (HAR) with realized (co)variances and semi-(co)variances from the index leads to more accurate volatility forecasts. To circumvent the effects of the market microstructure noise arising from using high sampling frequencies, we adopt noise-robust estimators for the realized (co)variances and develop novel noise-robust estimators for the semi-(co)variances. To explore the sampling frequency at which the forecasting gains are maximized, we adopt a mixed-sampling approach that iterates over several sampling frequencies of the stock and the index. Our analysis shows that gains are maximized at the combination of a low (high) frequency on the stock (index). We illustrate that the observed forecasting gains translates into economic gains such that a risk-averse investor is willing to pay up to 57 annual basis points by adopting a model specification that utilizes the index information.

Keywords: Realized Volatility, Micro-structure Noise, Pre-Averaged Estimators, Semi-variances, Semicovariances, Volatility Forecasting, Economic Value, Volatility-Timing Strategy

JEL Classification: C22, C51, C53, C58, G11, G14

Suggested Citation

Hizmeri, Rodrigo and Izzeldin, Marwan and Nolte, Ingmar and Pappas, Vasileios, A Generalized Heterogeneous Autoregressive Model using the Market Index (December 2, 2019). Available at SSRN: https://ssrn.com/abstract=3496804 or http://dx.doi.org/10.2139/ssrn.3496804

Rodrigo Hizmeri (Contact Author)

Lancaster University ( email )

Economics Department,
LUMS,
Bailrigg Lancaster, LA1 4YX
United Kingdom

Marwan Izzeldin

Lancaster University Management School ( email )

Lancaster, LA1 4YX
United Kingdom
01524 594674 (Phone)

HOME PAGE: http://www.lums.lancs.ac.uk/profiles/marwan-izzeldin/

Ingmar Nolte

Lancaster University - Department of Accounting and Finance ( email )

Lancaster, Lancashire LA1 4YX
United Kingdom

Vasileios Pappas

University of Kent, Kent Business School ( email )

Canterbury, Kent CT2 7PE
United Kingdom

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