A coupled component DCS-EGARCH model for intraday and overnight volatility.

Citation metadata

Authors: Oliver Linton and Jianbin Wu
Date: July 2020
From: Journal of Econometrics(Vol. 217, Issue 1)
Publisher: Elsevier Science Publishers
Document Type: Report; Brief article
Length: 229 words

Document controls

Main content

Abstract :

Keywords DCS; GAS; GARCH; Size-based portfolios; Testing Abstract We propose a semi-parametric coupled component exponential GARCH model for intraday and overnight returns that allows the two series to have different dynamical properties. We adopt a dynamic conditional score model with t-distributed innovations that captures the very heavy tails of overnight returns. We propose a several-step estimation procedure that captures the nonparametric slowly moving components by kernel estimation and the dynamic parameters by maximum likelihood. We establish the consistency, asymptotic normality, and semiparametric efficiency of our semiparametric estimation procedures. We extend the modelling to the multivariate case where we allow time varying correlation between stocks. We apply our model to the study of Dow Jones industrial average component stocks and CRSP size-based portfolios over the period 1993--2017. We show that the ratio of overnight to intraday volatility has actually increased in importance for Dow Jones stocks during the last two decades. This ratio has also increased for large stocks in the CRSP database, but decreased for small stocks in CRSP. Author Affiliation: (a) Faculty of Economics, University of Cambridge, Austin Robinson Building, Sidgwick Avenue, Cambridge, CB3 9DD, United Kingdom of Great Britain and Northern Ireland (b) School of Economics, Nanjing University, Nanjing, 210093, China * Corresponding author. Article History: Received 24 September 2018; Revised 20 September 2019; Accepted 29 December 2019 Byline: Oliver Linton [obl20@cam.ac.uk] (a), Jianbin Wu [wujianbin@nju.edu.cn] (b,*)

Source Citation

Source Citation   

Gale Document Number: GALE|A624915349