Neuro quantum-inspired decision-making for investor perception in green and conventional bond investments

Aigerim Birzhanova, A. Nurgaliyeva, A. Nurmagambetova, H. Di̇nçer, Serhat Yüksel
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Abstract

The purpose of this study is to make a comprehensive analysis of investor perceptions in the context of green and conventional bond investments. For this purpose, a new model is presented by considering two steps. First, a criteria set is generated by considering balanced scorecard perspectives that are finance, customer, organizational effectiveness and learning and growth. After that, the neuro Quantum fuzzy M-SWARA method is considered to weight these criteria. Secondly, seven critical determinants for bond investments are identified that are coupon rates, volume, maturity, riskiness, liquidity, volatility, and tax considerations. Neuro Quantum fuzzy TOPSIS approach is employed to rank these factors. The main contribution of the study is that by combining the balanced scorecard framework and quantum-inspired decision-making techniques, this paper offers a novel and sophisticated decision-making model to understanding investor behavior. Similarly, in the proposed model, a new methodology is generated by the name of M-SWARA. In this framework, some enhancements are adopted to the SWARA technique. The weighting results indicate that meeting customer expectations is the most critical factor that affects the investor perception to make investments to the bonds. Moreover, according to the ranking results, it is concluded that coupon rates are the most important item for both conventional and green bond investors. On the other hand, with respect to the conventional bond investor, tax is the second most essential factor. However, regarding the green bond investors, volatility plays a critical role. AcknowledgmentThis research has been/was/is funded by the Science Committee of the Ministry of Science and Higher Education of the Republic of Kazakhstan (№ AP 19679105 “Transformation of ESG financial instruments in the context of the development of the green economy of the Republic of Kazakhstan”).
投资者对绿色债券和传统债券投资认知的神经量子启发决策
本研究的目的是全面分析投资者对绿色债券和传统债券投资的看法。为此,我们通过两个步骤提出了一个新模型。首先,从平衡计分卡的角度,即财务、客户、组织效率和学习与成长的角度,生成一套标准。然后,考虑使用神经量子模糊 M-SWARA 方法对这些标准进行加权。其次,确定了债券投资的七个关键决定因素,即票面利率、数量、期限、风险性、流动性、波动性和税收因素。采用神经量子模糊 TOPSIS 方法对这些因素进行排序。本研究的主要贡献在于,通过将平衡计分卡框架与量子启发决策技术相结合,本文提供了一个新颖而复杂的决策模型来理解投资者行为。同样,在所提出的模型中,产生了一种名为 M-SWARA 的新方法。在这个框架中,对 SWARA 技术进行了一些改进。加权结果表明,满足客户期望是影响投资者对债券投资认知的最关键因素。此外,根据排序结果,票面利率对于传统债券和绿色债券投资者来说都是最重要的因素。另一方面,对于传统债券投资者来说,税收是第二重要的因素。本研究得到了哈萨克斯坦共和国科学和高等教育部科学委员会(№AP 19679105《哈萨克斯坦共和国绿色经济发展背景下的ESG金融工具转型》)的资助。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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