Company Stock Performance Analysis on IDX ESG Leaders Index Using the ARIMA-GARCH Model

Hazelino Rafi Pradaswara, D. Susanti, S. Sukono
{"title":"Company Stock Performance Analysis on IDX ESG Leaders Index Using the ARIMA-GARCH Model","authors":"Hazelino Rafi Pradaswara, D. Susanti, S. Sukono","doi":"10.46336/ijqrm.v3i3.347","DOIUrl":null,"url":null,"abstract":"Stocks are one of the most popular forms of investment. In investing stocks, it is necessary to know the movement of stock prices and the investment risks that may occur. The purpose of this study is to predict the level of risk, see the characteristics of stock returns, and whether the ESG Risk Rating makes the company's stock performance better. The models used to predict stock returns are Auto Regressive Integrated Moving Average (ARIMA) and Generalized Autoregressive Conditional Heteroscedasticty (GARCH), and Value at Risk (VaR) is used to predict risk. Based on the research, the potential loss for Bank BCA is IDR29.800.000,00 and Bank Mandiri is IDR33.600.000,00 with the assumption that an investor invests as much as IDR1.000.000.000,00. In addition, Bank BCA has a lower ESG Risk Rating than Bank Mandiri, but has a better performance.","PeriodicalId":14309,"journal":{"name":"International Journal of Quantitative Research and Modeling","volume":"19 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Quantitative Research and Modeling","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.46336/ijqrm.v3i3.347","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Stocks are one of the most popular forms of investment. In investing stocks, it is necessary to know the movement of stock prices and the investment risks that may occur. The purpose of this study is to predict the level of risk, see the characteristics of stock returns, and whether the ESG Risk Rating makes the company's stock performance better. The models used to predict stock returns are Auto Regressive Integrated Moving Average (ARIMA) and Generalized Autoregressive Conditional Heteroscedasticty (GARCH), and Value at Risk (VaR) is used to predict risk. Based on the research, the potential loss for Bank BCA is IDR29.800.000,00 and Bank Mandiri is IDR33.600.000,00 with the assumption that an investor invests as much as IDR1.000.000.000,00. In addition, Bank BCA has a lower ESG Risk Rating than Bank Mandiri, but has a better performance.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于ARIMA-GARCH模型的IDX ESG领导者指数公司股票绩效分析
股票是最受欢迎的投资形式之一。在投资股票时,必须了解股票价格的变动和可能发生的投资风险。本研究的目的是预测风险水平,看看股票收益的特征,以及ESG风险评级是否使公司的股票业绩更好。预测股票收益的模型有自回归综合移动平均(ARIMA)模型和广义自回归条件异方差(GARCH)模型,风险值(VaR)模型用于预测风险。根据研究,假设投资者投资高达1.000.000.00亿印尼盾,BCA银行的潜在损失为2980万印尼盾,Mandiri银行的潜在损失为3360万印尼盾。此外,BCA银行的ESG风险评级低于Mandiri银行,但绩效更好。
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 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Risk Measurement of Investment Portfolio Using Var and Cvar from The Top 10 Traded Stocks on the IDX Application of Structural Equations Modeling Partial Least Square at the Comparation of the Niveau of Responsibility From Cs and Digics Investment Portfolio Optimization In Infrastructure Stocks Using The Mean-VaR Risk Tolerance Model A Scoping Review of Green Supply Chain and Company Performance Application of Mathematical Model in Bioeconomic Analysis of Skipjack Fish in Pelabuhanratu, Sukabumi Regency, Jawa Barat
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1