Factors that affect mutual fund investment decision of Indian investors
Bibliographic record
Abstract
The paper seeks to extend the findings of Gill and Biger (2009) related to gender differences and factors that affect stock investment decision of Western Canadian investors by examining the affects of: 1) investors' investment expertise; 2) investors' knowledge of 'neutral information'; 3) investors' consultation with investment advisors on their decisions to invest in mutual funds. The present study is based on a sample of people living in Punjab and Delhi areas of India. Subjects were asked about their beliefs and feelings in relations to their investment decisions with particular reference to investments in mutual funds. We found that the degree of mutual fund investment decision is related to the degree of Indian investors' perceptions about their: 1) investment expertise; 2) general knowledge about the economy and the concept of mutual funds; 3) consultation with investment advisors. Family size also plays some role in the decision to invest in mutual funds. The valuable and useful recommendations for the investment managers and investment advisors have also been provided in the paper.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".