A comparative study of time-series models for forecasting the indonesian gold price

M. Taufik, Ashri Shabrina Afrah, Endah Septa Sintiya, D. Hariyanto
{"title":"A comparative study of time-series models for forecasting the indonesian gold price","authors":"M. Taufik, Ashri Shabrina Afrah, Endah Septa Sintiya, D. Hariyanto","doi":"10.1145/3427423.3427438","DOIUrl":null,"url":null,"abstract":"Although the value improves from year to year, gold can also suffer from significant price drops sometimes. For example in 2013, due to a severe decline in inflation rate all around the world, the price of gold plummeted either in Indonesia or other countries. Therefore, to make an investment decision and minimize the risks, sufficient information about price fluctuation of gold is highly needed. One of the common approaches for predicting gold price is time-series analysis. The ultimate goal of this research is to determine the most appropriate model of time series to predict gold price in Indonesia. The time series forecasting methods which were compared through simulations are Brown's Double Exponential Smoothing, Holt's Double Exponential Smoothing, and Fuzzy Time Series Markov Chain. The data used in this paper is the daily gold price in Indonesia that was observed from May to July 2020. According to the examination carried out with the Durbin Watson test, it was revealed that the data was dependent on time thus the time series analysis was suitable to apply. The testing with standard and relative statistical measurement showed that the Fuzzy Time Series Markov Chain was the best compared to other tested models, with the value of RMSE= 3269.022 and MAPE= 0.3%.","PeriodicalId":120194,"journal":{"name":"Proceedings of the 5th International Conference on Sustainable Information Engineering and Technology","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2020-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 5th International Conference on Sustainable Information Engineering and Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3427423.3427438","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

Abstract

Although the value improves from year to year, gold can also suffer from significant price drops sometimes. For example in 2013, due to a severe decline in inflation rate all around the world, the price of gold plummeted either in Indonesia or other countries. Therefore, to make an investment decision and minimize the risks, sufficient information about price fluctuation of gold is highly needed. One of the common approaches for predicting gold price is time-series analysis. The ultimate goal of this research is to determine the most appropriate model of time series to predict gold price in Indonesia. The time series forecasting methods which were compared through simulations are Brown's Double Exponential Smoothing, Holt's Double Exponential Smoothing, and Fuzzy Time Series Markov Chain. The data used in this paper is the daily gold price in Indonesia that was observed from May to July 2020. According to the examination carried out with the Durbin Watson test, it was revealed that the data was dependent on time thus the time series analysis was suitable to apply. The testing with standard and relative statistical measurement showed that the Fuzzy Time Series Markov Chain was the best compared to other tested models, with the value of RMSE= 3269.022 and MAPE= 0.3%.
印尼黄金价格预测的时间序列模型比较研究
虽然黄金的价值每年都在上升,但有时也会遭受价格大幅下跌的影响。例如在2013年,由于全球通货膨胀率的严重下降,黄金价格在印度尼西亚或其他国家暴跌。因此,要做出投资决策,将风险降到最低,就需要有足够的黄金价格波动信息。预测黄金价格的常用方法之一是时间序列分析。本研究的最终目的是确定最合适的时间序列模型来预测印度尼西亚的黄金价格。通过仿真比较了Brown双指数平滑法、Holt双指数平滑法和模糊时间序列马尔可夫链三种时间序列预测方法。本文使用的数据是印度尼西亚2020年5月至7月观察到的每日黄金价格。通过Durbin Watson检验,发现数据具有时间依赖性,适合采用时间序列分析。标准检验和相关统计检验表明,模糊时间序列马尔可夫链与其他被检验模型相比效果最好,RMSE= 3269.022, MAPE= 0.3%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信