Non-Gaussian Distributions of Returns on S&P 500 Index

DOI

10.2991/ceed-18.2018.51How to use a DOI?

Keywords

GJR-GARCH; Fat-Tailed Distributions; Stable Paretian Distributions

Abstract

Distributions of returns on market index are always assumed to be normal. In fact, many researchers argue that the distributions have tails fatter than normal. GARCH models illustrate that this non-normality is because of volatility clustering. This paper investigates the distribution of returns on S&P 500 index between 2006 and 2007. It is found that the distribution is still fatter than normal even though the heteroskedasticity has been adjusted by GARCH models. Moreover, the stable GJR-GARCH model performs better than Gaussian GJR-GARCH model.

Copyright

© 2018, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - U Sio Chong
PY  - 2018/12
DA  - 2018/12
TI  - Non-Gaussian Distributions of Returns on S&P 500 Index
BT  - Proceedings of the 1st International Conference on Contemporary Education and Economic Development (CEED 2018)
PB  - Atlantis Press
SP  - 244
EP  - 247
SN  - 2352-5398
UR  - https://doi.org/10.2991/ceed-18.2018.51
DO  - 10.2991/ceed-18.2018.51
ID  - SioChong2018/12
ER  -