Proceedings of the 2017 International Conference on Economics, Finance and Statistics (ICEFS 2017)

A Simple Test for Causality in Volatility

Authors
Chia-Lin Chang, Michael McAleer
Corresponding Author
Chia-Lin Chang
Available Online January 2017.
DOI
https://doi.org/10.2991/icefs-17.2017.3How to use a DOI?
Keywords
Random coefficient stochastic process, Simple test, Granger non-causality, Regularity conditions, Asymptotic properties, Conditional volatility.
Abstract
An early development in testing for causality (technically, Granger non-causality) in the conditional variance (or volatility) associated with financial returns, was the portmanteau statistic for non-causality in variance of Cheng and Ng (1996). A subsequent development was the Lagrange Multiplier (LM) test of non-causality in the conditional variance by Hafner and Herwartz (2006), who provided simulations results to show that their LM test was more powerful than the portmanteau statistic. While the LM test for causality proposed by Hafner and Herwartz (2006) is an interesting and useful development, it is nonetheless arbitrary. In particular, the specification on which the LM test is based does not rely on an underlying stochastic process, so that the alternative hypothesis is also arbitrary, which can affect the power of the test. The purpose of the paper is to derive a simple test for causality in volatility that provides regularity conditions arising from the underlying stochastic process, namely a random coefficient autoregressive process, and for which the (quasi-) maximum likelihood estimates have valid asymptotic properties under the null hypothesis of non-causality. The simple test is intuitively appealing as it is based on an underlying stochastic process, is sympathetic to Granger's (1969, 1988) notion of time series predictability, is easy to implement, and has a regularity condition that is not available in the LM test.
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Proceedings
2017 International Conference on Economics, Finance and Statistics (ICEFS 2017)
Part of series
Advances in Economics, Business and Management Research
Publication Date
January 2017
ISBN
978-94-6252-311-1
ISSN
2352-5428
DOI
https://doi.org/10.2991/icefs-17.2017.3How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Chia-Lin Chang
AU  - Michael McAleer
PY  - 2017/01
DA  - 2017/01
TI  - A Simple Test for Causality in Volatility
BT  - 2017 International Conference on Economics, Finance and Statistics (ICEFS 2017)
PB  - Atlantis Press
SP  - 19
EP  - 23
SN  - 2352-5428
UR  - https://doi.org/10.2991/icefs-17.2017.3
DO  - https://doi.org/10.2991/icefs-17.2017.3
ID  - Chang2017/01
ER  -