A Modified ARIMA Model Based on Extreme Value for Time Series Modelling

DOI

10.2991/meic-15.2015.272How to use a DOI?

Keywords

Time Series; modelling; ARIMA; extreme value;

Abstract

The ARIMA model is an important method and is widely used in time series modelling. The model relies heavily on autocorrelation patterns in the data, and doesn't consider other factors. However, in most cases, the extreme value of series has an influence on the subsequent behaviour of series. But this information isn't considered in the original ARIMA model. To solve this problem, We proposes a modified ARIMA model based on the past maximum and minimum value of series to solve the modelling tasks which includes the factor of past extreme value in the model. The modified model is tested on USD-EUR exchange rate time series. The experimental results show that it is possible to improve the performance by considering extreme value for time series modelling compared to the original ARIMA model.

Copyright

© 2015, 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  - Yaohui Bai
AU  - Xixia Zong
AU  - Benting Wan
AU  - Wenyuan Rao
PY  - 2015/04
DA  - 2015/04
TI  - A Modified ARIMA Model Based on Extreme Value for Time Series Modelling
BT  - Proceedings of the 2015 International Conference on Mechatronics, Electronic, Industrial and Control Engineering
PB  - Atlantis Press
SP  - 1197
EP  - 1200
SN  - 2352-5401
UR  - https://doi.org/10.2991/meic-15.2015.272
DO  - 10.2991/meic-15.2015.272
ID  - Bai2015/04
ER  -