印度股票和机器学习风险决定因素的文献调查和研究议程

Pradeep Kumar Rangi, P. Aithal
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引用次数: 14

摘要

尽管2020年期间金融放缓,冠状病毒大流行严重,但一些散户投资者直接进入二级股票市场,引发了巨额购买。对SEBI数据的审查表明,2020年4月至9月期间,超过600万个新的非物质化账户同比增长约125%。与此同时,AMFI报告的数据显示,散户投资者净流出股票基金。这些数据表明,散户投资者可能选择直接投资股票,而不是依靠股票共同基金经理进行投资。股权投资是一个动态的过程,在选择股票时需要考虑不同的变量,更重要的是要避免股票。创造财富的基石是以远低于其内在价值的价格投资商店。利用股票创造长期财富的基础是根深蒂固的。一种是以大大低于其内在价值的价格购买企业(内在价值指的是企业在估计了会计风险、宏观经济、管理和行为风险决定因素之后的未来现金流量)。因此,本文献综述将涵盖行为学、会计学、宏观经济、波动性和管理理论,以及预测和ML技术,用于聚类、预测和分类,以支持使用不同模型的风险决策,例如ARIMA、LSTM、VAR、Facebook Prophet、ARCH和GARCH家族模型等。文献综述还表明,风险的概念是高度主观的,不同的投资者对风险的感知也不同;它并不总是完全客观的,在做出投资决策之前需要仔细评估的信仰、认知和社会文化因素之外。然而,检查关键风险指标将使投资者做出更明智的决定。使用有价值的ABCD和SWOT管理框架定义和评估了研究差距和确定的进一步审查议程。因此,通过提供建议来分析文献调查结果,以便为印度股票市场的长期股票投资者创建一个全面的研究议程。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Literature Survey and Research Agenda of Risk Determinants in Indian Equities and Machine Learning
Notwithstanding the financial slowdown and severity of the Coronavirus pandemic during 2020, several retail investors ventures directly to the secondary equities market, setting off gigantic purchasing. A review of SEBI data indicates that over 6 million new dematerialization accounts between April and September 2020 are about 125 percent growth on year on year basis. At the same time, data reported by AMFI shows net outflows from equity funds by retail investors. These data points indicate that retail investors may have opted to invest using direct stock investments instead of relying on the equity mutual fund manager. Equity Investment is a dynamic process requiring and require considering different variables in selecting and, more importantly, avoiding stocks. The cornerstone of wealth creation is to invest in stores at a price considerably smaller than their intrinsic value. The very foundation of creating long-term wealth using equities is deeply embedded. One is buying businesses at a price substantially below its intrinsic value (intrinsic value indicates the entity's future cash flows after estimating the number of accounting risk, macro-economic, managerial, and behavioral risk determinants). This Literature review, therefore, is organized to cover Behavioral, Accounting, Macro-economic, Volatility, and Management theories and Forecasting and ML techniques for clustering, predictions, and classification to support risk decisions using different models, e.g., ARIMA, LSTM, VAR, Facebook Prophet, ARCH and GARCH family models, etc. The literature review also establishes that the concept of risk is highly subjective and is perceived by different investors differently; it is not always entirely objective and outside the beliefs, cognitive and socio-cultural considerations requiring careful assessment before making investment decisions. However, examining the critical risk indicators would allow investors to make a more informed decision. The research gap and identified agenda for further review were defined and assessed using valuable ABCD and SWOT management frameworks. Consequently, the literature investigation findings are analyzed by offering recommendations for creating a comprehensive research agenda pertinent to long-term equity investors in the Indian Equity market.
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