Momentum profits and idiosyncratic volatility: the Korean evidence
Bibliographic record
Abstract
Purpose This study aims to focus on the profitability of momentum trading in the Korean stock market. More specifically, it aims to conduct an examination of the relationship between momentum returns and idiosyncratic volatility (IVol) to determine whether momentum profits can be explained by IVol. Design/methodology/approach Portfolios are formed based on their past performance and examine the momentum, or contrarian returns, as the difference between winning and losing portfolios. To confirm that the momentum strategy provides excess returns, the relationship between momentum returns and IVol is studied. The Fama and French three‐factor model is also examined to see whether systematic risk affects momentum profits. Firm size, stock price, and turnover are controlled to determine robustness. Finally, a time‐series relationship between aggregate IVol and momentum profits is investigated. Findings The paper illustrates that excess returns are obtained from a momentum strategy, not a contrarian strategy, in the Korean stock market. Momentum returns are higher among high IVol stocks, especially high IVol winners. Examining the Fama and French three‐factor model, it is found that momentum returns cannot be explained by systematic risk. The findings are robust after controlling for factors such as firm size, book‐to‐market ratio, and turnover. The paper confirms the effect of IVol on momentum returns by illustrating that a time‐series relationship between momentum returns and aggregate IVol is positive. Originality/value This paper is among the first, to the authors' knowledge, to examine the relationship between momentum profits and IVol in the Korean stock market, one of the mature financial markets. The findings in this study can be applied to better understand the sources of gains from the momentum strategy in international stock markets.
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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 | 0.000 |
| 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 | 0.000 | 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".