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Record W1983814398 · doi:10.6000/1929-7092.2015.04.02

Turnover Premium, Foreign Institutional Ownership, and Time-Varying Risk Premium in Taiwan Equity Markets

2015· article· en· W1983814398 on OpenAlexvenueno aff
Ying‐Jen Chen, Jen-Sin Lee

Bibliographic record

VenueJournal of Reviews on Global Economics · 2015
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicFinancial Markets and Investment Strategies
Canadian institutionsnot available
Fundersnot available
KeywordsEquity (law)Equity premium puzzleRisk premiumBusinessForeign ownershipMonetary economicsInstitutional investorEconomicsFinanceCorporate governanceForeign direct investment

Abstract

fetched live from OpenAlex

The low turnover premium found in U.S. equity markets is also found in Taiwan market, unlike the mixed evidence for other stylized effects such as size, book-to-market ratio and momentum. Consistent with investor overconfidence hypothesis proposed by Odean (1998, 1999), the percentage of foreign institutional shareholdings in a stock is found to vary inversely with turnover premium. This inverse relation is robust to the influence of other forces that may interact with turnover rate, such as market capitalization, book-to-market ratio and 6-month past returns, respectively. Time-varying risk premium, particularly in low turnover-low foreign institutional shareholdings percentage portfolio, provides partial explanation for the phenomenon, but the inverse relation persists after risk adjustment by models such as unconditional CAPM, Fama-French three factor model and conditional CAPM.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.062
GPT teacher head0.265
Teacher spread0.204 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2015
Admission routes1
Has abstractyes

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