From rof-skills
Audits finance empirical/theoretical analysis for Review of Finance standards: sample construction, identification, asset-pricing tests, corporate-finance variables, robustness, and code reproducibility.
How this skill is triggered — by the user, by Claude, or both
Slash command
/rof-skills:rof-data-analysisThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
Use this when the finance result is not yet credible enough for RoF. Reopen the current
Use this when the finance result is not yet credible enough for RoF. Reopen the current author guidelines and code-sharing policy before final submission.
For each headline result, record:
Result | Economic magnitude | Identification/model threat | Benchmark | Replication file
Then ask whether the claim would survive a top-three-finance referee:
If the answer is weak, repair the analysis before rewriting the introduction.
RoF's EFA readership expects cross-market evidence handled with the same care US-only papers give CRSP. Known traps an RoF referee will catch:
| Setting | Expected default | Objection if absent |
|---|---|---|
| Firm/bank panel | firm + time FE; cluster by firm, two-way when shocks are common | "standard errors understated" |
| Fama–MacBeth | Newey–West lags matched to horizon; Shanken correction | errors-in-variables attack |
| Portfolio sorts | value-weighted headline plus equal-weighted check; microcap screen | "driven by tiny illiquid stocks" |
| Staggered adoption | heterogeneity-robust DID alongside TWFE | negative-weights critique |
| Cross-country panel | country-by-year FE or equivalent; cluster at country | "one country's shock in disguise" |
| Anomaly/factor claim | multiple-testing discipline; international or out-of-sample split | data-snooping objection |
Put one defining specification in the body and route the grid of variants to the internet appendix — RoF editors prize clean identification and economic magnitudes over kitchen-sink regressions.
Illustrative numbers only. The headline: after the 2014 negative-policy-rate cut, high-deposit banks lowered lending margins 28 bp more than low-deposit banks; sample of 412 euro-area banks from Bankscope, 2010–2019.
rof-replication-and-data-policy).One reproducible path, because RoF can hold publication until programs arrive:
raw/ immutable vendor pulls (Datastream, Bankscope, CRSP), dated
build/ cleaning scripts: screens, delisting merges, winsorize 1/99
analysis/ one numbered script per manuscript table or figure
out/ exhibits regenerated end-to-end by run_all; diffs reviewed
[Analysis readiness] strong / adequate / weak
[Claim -> evidence] <claim: table, figure, model, or robustness>
[Top-three-standard gap] <one issue>
[Replication blocker] <data, code, pseudo-data, or logs>
[Next analysis] <single task>
npx claudepluginhub brycewang-stanford/awesome-journal-skills --plugin rof-skillsBuilds or audits empirical data and estimation pipelines for Journal of Banking & Finance manuscripts: financial datasets, bank panels, winsorization, fixed effects, robustness checks, and reproducible scripts.
Runs and documents empirical finance analysis for JFQA papers: data construction (CRSP/Compustat/TAQ/IBES), winsorizing, fixed effects, clustered/Newey-West standard errors, robustness, and reproducibility.
Builds the multi-test and out-of-sample robustness battery expected by RFS referees for empirical finance manuscripts.