Montenegrin Stock Exchange Market on a Short-Term Perspective
Bibliographic record
Abstract
The objective of this study is to analyse the constitution of the emerging Montenegrin stock exchange. Four methodological time-series econometric steps are involved: the augmented Dickey–Fuller (ADF) test, run test, autocorrelation function (ACF) test, and Hurst test. The study utilises a daily data vector from 5 January 2004 to 20 June 2023, with a specific focus on the period encompassing the growth and peak of market stocks in 2007, followed by the significant 2008 financial crisis and subsequent developments thereafter. The analysis culminates on 28 May 2018, which is considered one of the lowest points in the Montenegrin stock exchange market in a comparative time-series assessment. The results of the tests conducted in this study do not provide empirical evidence supporting the random walk theory and its returns on aggregated shocks in the Montenegrin stock exchange market. By reviewing previous empirical studies and presenting new empirical findings, this study confirms the presence of stochastic trends in co-movements in finance, contributing to a deeper understanding of emerging stock exchange markets. Study implications support greater reliance on market efficiency, risk management, and portfolio diversification.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".