Proceedings of the 1st International Conference on Contemporary Education and Economic Development (CEED 2018)

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

Authors
U Sio Chong
Corresponding Author
U Sio Chong
Available Online December 2018.
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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Volume Title
Proceedings of the 1st International Conference on Contemporary Education and Economic Development (CEED 2018)
Series
Advances in Social Science, Education and Humanities Research
Publication Date
December 2018
ISBN
978-94-6252-631-0
ISSN
2352-5398
DOI
10.2991/ceed-18.2018.51How to use a DOI?
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/).

Cite this article

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  -