Is the Warsaw Stock Exchange Mature Enough to Analyse the Returns by the Models Known on the Developed Markets?
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
Polish economy has been characterised by the dynamic development since political changes in 1989. Relatively fast economic development, privatisation program and financial sector reforms gave a fundamental background for creating capital market. For the last few years the Polish capital market has been growing rapidly. More and more financial instruments appear on the market. Also growing number of investors’ trade on the market. All decision-making processes have to include the risk related to the capital market. Consequently it is necessary to measure the level of the risk. Widely used measures of risk are standard deviation andbetaparameter (ß) known, for example, from models of returns from investments or CAPM model. Some of the models show which variables influence the returns of assets. One of these is an arbitrage pricing model (APT) developed by Ross (1976). First, the APT model was evaluated on the markets of the developed countries (such as Japan, Canada, UK, and USA) and later on developing markets. Many recently published papers describe the application of the model on South Asian markets, for example, on Korean, Malaysian and Taiwan markets (see Clare and Priestley 1998). An empirical analysis of the APT on both developed and developing markets suggests that the sources of systematic risk could be the following variables: unexpected inflation, changes in industrial production and changes in the structure of the interest rate.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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