The Determinants of Stock Returns in the Emerging Market of Kenya: An Empirical Evidence
Bibliographic record
Abstract
This study examined the sources of risk factors that determine stock returns in the emerging market of Kenya. The specific objectives were to determine the validity of the Capital Asset Pricing Model (CAPM) and then empirically test for factors that are priced in stock returns in Kenya.The factors examined are the excess market premium and selected macroeconomic factors including inflation, exchange rates, money supply and short term interest rates. The study utilizes monthly time series data for the period April 1996: December 2016. The CAPM, a multifactor approach and Fama and MacBeth (1973) two-step procedure are used for data analysis.The study finds that CAPM cannot be rejected and that the market premium is the most important factor in explaining stock return variability in Kenya. Therefore, the study concludes that unlike the recent evidence on the collapse of CAPM in advanced markets, the model can still be validly used for the Kenyan market.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".