Impact of Demographics and Perceptions of Investors on Investment Avenues
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The primary purpose of this study is to investigate how investment choice gets affected by the demographics and perceptions of the investor. Investor’s behavior is influenced by many factors at the time of investment decision making. Demographic profile and perceptions play an important role to select a particular choice of investment. This paper helps to enhance the knowledge on different investment avenues like bank deposits, life insurance policies, mutual funds and equity which in turn will be highly useful to the financial advisors as it will help them advise their clients regarding these avenues with respect to their demographic profiles. The study also highlights the evidences that the investment choice depends on and is affected by the demographic variables and perceptions. However, the results of this research shows that the most investors have little knowledge on the investment avenues for their investments. Mann Whiteny ‘U’ test, Kruskal- Wallis has been conducted to test the hypotheses with the help of SPSS. Logistic regression results of this study proves that investors’ age, gender, education and occupation significantly influences the selection of investment avenues. Wealth Management professionals emphasizes that customer behavior and psychology play a vital role in successfully building and sustaining a wealth management relationship. Behavioral finance is new emerging science which focuses on understanding the psychology effects on investment decision.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| 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 it