The Investor Behaviour, Risk Perception and Expectations on Cryptocurrency Markets
Bibliographic record
Abstract
The financial sector, which has sparked increasing organizational and scientific interest in recent years, plays a vital role in the Turkish economy. After enduring multiple economic downturns, consumers have become more cautious when considering financial investments, making it challenging for financial institutions to formulate effective marketing strategies. This study aims to shed light on investor behavior in Tukish markets. The results of two surveys are examined: the first conducted in the final quarter of 2022, and the second in the first quarter of 2023. This article delves into various variables, including stress levels, portfolio holding times, investment choices, and attention to cryptocurrency markets. The methodology employs the Mann-Whitney U test, Cronbach's Alpha, Kolmogorov-Smirnov, and Shapiro-Wilk normality tests. The findings from the two surveys are compared. Based on the analysis results, it can be inferred that respondents' investment preferences and risk tolerance have evolved over time. The results demonstrate a spectrum of portfolio diversification tendencies.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".