Jfqa Topic Selection

---
name: jfqa-topic-selection
description: "Use when judging whether a research question fits the Journal of Financial and Quantitative Analysis (JFQA) — empirical and quantitative financial economics (corporate finance, investments, capital and security markets, financial institutions, finance-relevant quantitative methods). Use before investing in a JFQA submission to test scope fit and the quantitative-evidence bar."
category: business-and-finance
source_repo: brycewang-stanford/Awesome-Journal-Skills
source_path: "Journal-of-Financial-and-Quantitative-Analysis-Skills/skills/jfqa-topic-selection/SKILL.md"
source_url: https://github.com/brycewang-stanford/Awesome-Journal-Skills/blob/HEAD/Journal-of-Financial-and-Quantitative-Analysis-Skills/skills/jfqa-topic-selection/SKILL.md
---


# JFQA Topic Selection (jfqa-topic-selection)

Use this skill to test whether a finance question belongs in the **Journal of Financial and Quantitative Analysis (JFQA)** before you build the paper and pay the **$350** submission fee (only **$275** refundable if it is not sent to a reviewer).

## What JFQA publishes

JFQA covers **theoretical and empirical** research in financial economics, with a quantitative core:

- **Corporate finance** — capital structure, payout, governance, M&A, investment.
- **Investments / asset pricing** — cross-section of returns, factors, anomalies, portfolio choice.
- **Capital and security markets** — market microstructure, liquidity, price discovery.
- **Financial institutions** — banks, intermediaries, regulation.
- **Quantitative methods** relevant to finance.

The name is load-bearing: the journal rewards **quantitative analysis** — disciplined data, models, and inference — over purely descriptive or institutional essays.

## Fit checklist

- [ ] Question sits squarely in financial economics, not adjacent (pure macro, accounting-only, generic econometrics).
- [ ] There is a **quantitative empirical or theoretical** answer — not just a narrative.
- [ ] The data/design can deliver a clean, defensible result (see jfqa-identification-strategy).
- [ ] The contribution is sharp enough to survive a journal that prints **< 9%** of 1,000+ annual submissions.
- [ ] If empirical, the data can be archived (raw or pseudo dataset) under the JFQA Code Sharing Policy.

## Anti-patterns

- A descriptive industry study with no quantitative test or model.
- A method paper with no genuine finance application (belongs in an econometrics outlet).
- An incremental anomaly with no economic mechanism or out-of-sample discipline.
- Excessive length that invites desk rejection (JFQA discourages over-long papers).

## Fit-scoring rubric (score before you build)

| Dimension | 0 points | 1 point | 2 points |
|---|---|---|---|
| Finance object | none identifiable | adjacent (accounting/macro proxy) | a return, spread, ratio, or institution JFQA readers own |
| Quantitative core | narrative only | descriptive statistics | estimation or a model with testable implications |
| Identification feasibility | pure correlation | plausible design, untested | a named shock, threshold, or restriction |
| Data archivability | data cannot be shared or simulated | pseudo data possible with effort | raw or pseudo data straightforward |
| Novelty at < 9% selectivity | replication-grade | extends a known result | changes a number or conclusion the field uses |
| Length discipline | sprawling multi-question paper | trimmable | one question, one design |

Read the total: 10-12, build for JFQA; 7-9, repair the weakest dimension before writing; 6 or below, retarget the venue or redesign the project.

## Two candidate questions scored (illustrative)

- Candidate A — "Does option-implied information subsume post-earnings-announcement drift?" Finance object 2, quantitative core 2 (options plus stock-return data), identification 1 (predictive design with multiple-testing exposure), archivability 2 (pseudo data is routine), novelty 1, length 2 → 10. Verdict: build it, but write the multiple-testing defense into the design before the first regression.
- Candidate B — "How do fintech lenders talk about their culture?" Scores roughly 3: no finance quantity is measured and nothing is estimated. Verdict: either redesign around measurable lending outcomes (rates, default, approval gaps) or send the descriptive version to a field outlet.

## Borderline calls from adjacent fields

- Accounting-flavored questions qualify when the outcome is a finance quantity (cost of capital, returns, spreads) rather than reporting quality for its own sake.
- A pure econometrics advance qualifies only if it changes a finance conclusion in a real application.
- Macro-finance fits when the asset-market or intermediary channel is the object, not the backdrop.
- Household finance fits when portfolio, credit, or pricing behavior is quantified at scale.

## Portfolio thinking under the fee structure

- Score every candidate project on the rubric before any is built; the journal's fee-and-refund design effectively prices a failed screen, so weak candidates should die at this stage, not at submission.
- A 7-9 project with a repairable dimension (usually identification or novelty) often beats starting a fresh 10 — the repair plan itself can become the paper's design section.
- Re-score after the first full results pass: projects drift, and a question that scored 11 as proposed can be an 8 as executed.

## Output format

```
【Scope fit】corporate finance / investments / markets / institutions / methods?
【Quantitative core】Y/N — what is measured/estimated
【Selectivity check】is the contribution sharp enough for <9%?
【Next step】jfqa-literature-positioning
```

---

**Source:** [`brycewang-stanford/Awesome-Journal-Skills`](https://github.com/brycewang-stanford/Awesome-Journal-Skills) → `Journal-of-Financial-and-Quantitative-Analysis-Skills/skills/jfqa-topic-selection/SKILL.md`