Perception of Investors towards the Investment Pattern on Different Investment Avenues - A Review
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
In India, usually all investment avenues professed risky by the investors. The main features of investments are security of principal amount, liquidity, income stability, approval and easy transferability. Investment avenues are available such as shares, bank, companies, gold and silver, real estate, life insurance, postal savings and so on. The required level of returns and the risk tolerance decided the choice of the investor. The investment may be differ choices from national savings certificates, provident fund, mutual fund schemes, insurance schemes, chit funds, bank fixed deposits, and company fixed deposits, company shares, bonds /debentures, government securities, postal savings schemes and real estate. It would be concluded that in this fast affecting world, we save get extra money. Added risk directs to more profit. For the example total liquidity, income stability a variety as shares, bank companies, gold and silver, real estate, life insurance postal etc., but, most of the people preferred bank deposit by the cause of more respondents invested for purchasing home and long-term growth but, most of the investors could not aware to investing their money in mutual funds and shares. More of debate and confusions in the investment pattern, investment avenues. Therefore, in this paper, the researcher wants to check the earlier research work based on investors among the investment avenues to get an idea about the investment pattern.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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