Influence of Risk Management Practices on the Financial Performance of Investment Firms Trading at the NSE
Bibliographic record
Abstract
This study aims to investigate the influence of risk management practices on the performance of investment firms in Kenya, specifically focusing on the role of risk management practices on the performance of investment firms trading at the Nairobi Securities Exchange. This study used a correlational research methodology and positivist philosophy to investigate how firm-specific characteristics affected the financial performance of 63 investment businesses listed between 2014 and 2023 on the Nairobi Securities Exchange (NSE). Using a census technique, data was gathered from secondary sources such as NSE, CBK, and KNBS. Statistical analysis methods such as SPSS were used to display the results.  The findings indicated that risk management strategies positively impact financial performance, with significant effects on ROA, ROE, and composite performance measures, highlighting the critical role of robust risk management in enhancing the economic performance of investment firms trading at NSE. Based on the study findings, investment firms should develop comprehensive risk management frameworks that effectively identify, assess and mitigate potential risks.
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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 | 0.001 | 0.001 |
| 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 | 0.000 |
| 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".