Literature Survey and Research Agenda of Risk Determinants in Indian Equities and Machine Learning

Main Article Content

Pradeep Kumar Rangi
P. S. Aithal

Abstract

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.

Article Details

How to Cite
Pradeep Kumar Rangi, & P. S. Aithal. (2021). Literature Survey and Research Agenda of Risk Determinants in Indian Equities and Machine Learning. International Journal of Management, Technology and Social Sciences (IJMTS), 6(1), 83–109. https://doi.org/10.47992/IJMTS.2581.6012.0131
Section
Articles

Most read articles by the same author(s)

<< < 5 6 7 8 9 10 11 > >>