Stock price index analysis of four OPEC members: a Bayesian approach

IF 6.9 1区 经济学 Q1 BUSINESS, FINANCE Financial Innovation Pub Date : 2024-05-29 DOI:10.1186/s40854-024-00651-1
Saman Hatamerad, Hossain Asgharpur, Bahram Adrangi, Jafar Haghighat
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Abstract

This study examines the relationship between macroeconomic variables and stock price indices of four prominent OPEC oil-exporting members. Bayesian model averaging (BMA) and regularized linear regression (RLR) are employed to address uncertainties arising from different estimation models and variable selection. Jointness is utilized to determine the nature of relationships among variable pairs. The case study spans macroeconomic variables and stock prices from 1996 to 2018. BMA findings reveal a strong positive association between stock price indices and both consumer price index (CPI) and broad money growth in each analyzed OPEC country. Additionally, the study suggests a weak negative correlation between OPEC oil prices and the stock price index. RLR results align with BMA analysis, offering insights valuable for policymakers and international wealth managers.
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欧佩克四个成员国的股票价格指数分析:贝叶斯方法
本研究探讨了欧佩克四个主要石油出口国的宏观经济变量与股票价格指数之间的关系。采用贝叶斯模型平均法(BMA)和正则化线性回归法(RLR)来解决不同估计模型和变量选择带来的不确定性。联合性用于确定变量对之间关系的性质。案例研究横跨 1996 年至 2018 年的宏观经济变量和股票价格。BMA 的研究结果表明,在所分析的每个欧佩克国家中,股票价格指数与消费者价格指数(CPI)和广义货币增长之间都存在很强的正相关关系。此外,研究还表明欧佩克石油价格与股票价格指数之间存在微弱的负相关性。RLR 的结果与 BMA 的分析一致,为政策制定者和国际财富管理者提供了有价值的见解。
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来源期刊
Financial Innovation
Financial Innovation Economics, Econometrics and Finance-Finance
CiteScore
11.40
自引率
11.90%
发文量
95
审稿时长
5 weeks
期刊介绍: Financial Innovation (FIN), a Springer OA journal sponsored by Southwestern University of Finance and Economics, serves as a global academic platform for sharing research findings in all aspects of financial innovation during the electronic business era. It facilitates interactions among researchers, policymakers, and practitioners, focusing on new financial instruments, technologies, markets, and institutions. Emphasizing emerging financial products enabled by disruptive technologies, FIN publishes high-quality academic and practical papers. The journal is peer-reviewed, indexed in SSCI, Scopus, Google Scholar, CNKI, CQVIP, and more.
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