Binary Logistic Regression Modeling in Predicting Consumer Behavior towards Mutual Fund Investment
DOI:
https://doi.org/10.51983/ajms-2019.8.1.1446Keywords:
Predictive Modeling, Binary Logistic Regression, Investor Behavior, Mutual FundAbstract
Mutual fund, as a financial investment option, has gained reasonable acceptance in India since its inception. While traditional forms of investment have its own merits, the sheen of mutual fund has also been realized by Indian investors. A huge investor class have scored mutual fund higher than its counterparts on many counts. While the popularity of this new age investment option is on a rise, however, a mixed view is also experienced. The present study explores the behaviour of investors’ towards mutual fund. The study is based on the premise of regression analysis and binary logistic regression has been used to develop a model that best represents the consumer behaviour. The best model selection is based on the information criteria of Akike. Also, from the model, the researchers have evaluated the probability of mutual fund purchase by consumers. Finally, the research work shows computation of odds ratio that signifies the extent to which the probability of purchasing mutual fund would change with unit change in the levels of the covariates. This study is descriptive in nature and is based on primary survey with a sample size of 376. The results reveal that high returns are the most preferred determinant of investment behavior followed by the liquidity which is also evident from the odds ratio computation.
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