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Publication Type : Conference Paper
Publisher : 2017 International Conference on Data Management, Analytics and Innovation (ICDMAI)
Source : 2017 International Conference on Data Management, Analytics and Innovation (ICDMAI), p. 326-329 (2017)
Keywords : behavioral finance, behavioural sciences, cognition, Cognitive biases, cognitive traits, Demographic Variables, demographical profile, Finance, financial information, financial management, Frequency measurement, Herding, herding behavior, Indian stock investors, investment, investment behavior, mouth, Qualifications, stock investment decisions, stock markets
Campus : Coimbatore, Kochi
School : School of Business
Department : Business
Year : 2017
Abstract : Behavioral finance proposes that cognitive traits of investors impact their investment decisions which are not always rational, in contradiction to traditional finance. These cognitive traits of stock investors are influenced by their demographical profile and the financial information that they receive from various sources which in turn influences their stock investment decisions. Investors with similar demographic profile tend to follow a similar pattern with regard to their investment behavior biases. The main objective of this study is to analyze the impact of Indian stock investors' demographics and various sources of financial information on their cognitive biases. Various behavioral biases like herding, loss aversion, regret aversion, market information; mental accounting, price change, and price anchoring were studied but herding behavior has been taken into consideration for analysis in this study. A questionnaire was floated by using quota sampling. Stata software was used for analysis, by using ordered logistic regression on the conceived model. Gender, age, marital status and word of mouth are found to have significant impact on the herding behavior of stock investors.
Cite this Research Publication : M. A. Nair, Dr. P. Balasubramanian, and Yermal, L., “Factors Influencing Herding Behavior among Indian Stock Investors”, in 2017 International Conference on Data Management, Analytics and Innovation (ICDMAI), 2017, pp. 326-329.