Proceedings of the 2018 4th International Conference on Education Technology, Management and Humanities Science (ETMHS 2018)

Short-term Forecasting Of Gold Price Based On ARMA Model

Authors
WanLe Chi
Corresponding Author
WanLe Chi
Available Online April 2018.
DOI
10.2991/etmhs-18.2018.110How to use a DOI?
Keywords
Forecasting, Gold Price, ARMA, ADF.
Abstract

Gold price is complicated for containing many factors. So the evolution process in the gold price is important. In the paper the sequence of gold price is defined as a time series. The ARMA model is used to solve time series problems, especially in the field of finance. The ARMA model is a regression model developed by Box and Jenkins to identify, assess and diagnose dynamic time series model in which the time variable plays a key role . The paper collects the afternoon fixing price of London gold market the period of 1990-01-01 to 2018-01-12 (7315 working days) and uses ARMA model to solve the short-term forecast problem of gold price. The paper is helpful to gold investors to make more scientific decision-making.

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 2018 4th International Conference on Education Technology, Management and Humanities Science (ETMHS 2018)
Series
Advances in Social Science, Education and Humanities Research
Publication Date
April 2018
ISBN
10.2991/etmhs-18.2018.110
ISSN
2352-5398
DOI
10.2991/etmhs-18.2018.110How 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  - WanLe Chi
PY  - 2018/04
DA  - 2018/04
TI  - Short-term Forecasting Of Gold Price Based On ARMA Model
BT  - Proceedings of the 2018 4th International Conference on Education Technology, Management and Humanities Science (ETMHS 2018)
PB  - Atlantis Press
SP  - 521
EP  - 525
SN  - 2352-5398
UR  - https://doi.org/10.2991/etmhs-18.2018.110
DO  - 10.2991/etmhs-18.2018.110
ID  - Chi2018/04
ER  -