Quantifying Risk in Investment Decision-Making
Bibliographic record
Abstract
In the wake of inflation, investors engage in identifying inflation hedging instruments. Most importantly, investors attempt to minimize risk and maximize returns to safeguard against inflation. Risk plays an important role in this process. The objective of this research is to examine the relationship between risk factors and investor behavior, particularly in the Indian context. Based on the theory of planned behavior (TPB), we built a conceptual model investigating the intricate relationship between risk factors, investment priority, investment strategy and investment decision-making. We collected data from 537 respondents in the southern region of India and analyzed the data using Partial Least Squares Structural Equation Modeling (PLS-SEM). The result indicate: (i) risk factors (risk capacity, risk tolerance, and risk propensity) are positively related to investment priority and investment strategy, (ii) investment priority is positively related to investment decision-making, (iii) conscientiousness moderates the relationship between investment priority and investment decision-making, (iv) investment strategy is positively related to investment decision-making. Finally, the practical and theoretical implications for research are discussed.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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 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".