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Record W2912458412

Estimating Exchange Rate Exposures: Some

2000· article· en· W2912458412 on OpenAlexaff
Gordon M. Bodnar, M.H. Franco Wong

Bibliographic record

VenueSSRN Electronic Journal · 2000
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicRisk Management in Financial Firms
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsEconometricsCash flowEquity (law)PortfolioEconomicsMarket portfolioMonetary economicsFinancial economics
DOInot available

Abstract

fetched live from OpenAlex

From a sample of 910 U.S. firms over the period 1977 1996, we find that structure of the empirical model has significant impacts on resulting estimates of exchange rate exposures from equity returns. While lengthening the return horizon has minimal impact on exposure estimates, the inclusion of a market portfolio in the specification results in significant changes to the exposure estimates. We further demonstrate that different definitions of the market portfolio result in important differences in the overall distribution of exposure estimates and the interpretations of the sign, size, and significance of many firms' exposures. The source of the exposure differences across market portfolios is due to a strong size-exposure relation for U.S. firms. Surprisingly, this size-exposure relation does not appear to be driven by an underlying correlation between size and foreign cash flow position of the firms. An alternative model specification using matched CRSP capital-based size portfolios as controls for market movements in the exposure model produces firm-level exposures with a stronger relation to foreign cash flows and less of a correlation with firm size.

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)0.004
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.009
GPT teacher head0.215
Teacher spread0.206 · 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 designTheoretical or conceptual
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

Citations19
Published2000
Admission routes1
Has abstractyes

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