Mean Reversion and Momentum in Central and Eastern European Countries – A Case Study on Poland and Romania
Bibliographic record
Abstract
There is considerable evidence showing that both mean reversion and momentum exist in stock prices, especially in financially-developed countries. We analyze these phenomena for two Central and Eastern European countries with very different transitions from centrally-planned to market economies: Poland and Romania. Although Poland’s stock market cannot be considered well-developed, its capitalization increased from 3 percent of GDP in 1995 to about 30 percent in 2017, while Romania’s stayed under 6 percent of GDP in the 1990s and early 2000s, and only recently has increased to about 21 percent. Examining how mean reversion and momentum affect stock prices, we find very similar results for the two countries. The speed at which stocks converge back to their fundamentals (i.e., mean reversion) is much faster than that of the developed markets, with half-lives of just over 9 months for both countries (similar to the results obtained in the literature for the Chinese market, but much shorter than the 3-4 years for the well-developed markets). We also find that the momentum effect lasts less than in the developed countries. Therefore, in most cases, strategies combining mean reversion and momentum generate abnormal excess returns only for holding periods of less than 12 months.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".