ai-asset-pricing: Agent for Claude Code

.claude/agents/jkp-wrds-expert.md

jkp-wrds-expert is an agent for Claude Code from Alexander-M-Dickerson/ai-asset-pricing. It costs 340 tokens per session (6,447 once invoked), scanned A, original, MIT.

A specialist for JKP Global Factor Data, a finance dataset of pre-calculated stock measures such as value, momentum, profitability, risk, and growth. It runs through WRDS, a research database service, and covers companies across many countries and years.

In plain words
What is it for?
It helps query the WRDS global factor table and use its linked company identifiers in international stock research.
Why use it?
It removes the need to calculate these stock measures or manually connect several finance datasets before analysis.

Agent for Claude Code

Written for Claude Code: installed under .claude/. Also seen: model in frontmatter.

This is Alexander-M-Dickerson/ai-asset-pricing's own configuration. It tells Claude Code how to work on ai-asset-pricing itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything ai-asset-pricing configures →

Reuse

Borrowing it

Nothing to install: this file belongs to Alexander-M-Dickerson/ai-asset-pricing. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/Alexander-M-Dickerson/ai-asset-pricing/main/.claude/agents/jkp-wrds-expert.md
Clone the repo
git clone --depth 1 https://github.com/Alexander-M-Dickerson/ai-asset-pricing

Made for: Claude Code.

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Per session 340 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 6,447 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00340 $0.06447
Opus 5 $0.00170 $0.03223
Sonnet 5 $0.00068 $0.01289
Haiku 4.5 $0.00034 $0.00645

Measured 12d ago against content hash a8bbc66444cf, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

jkp-wrds-expert scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

.claude/agents/jkp-wrds-expert.md · 448 lines

How it starts

The opening of the file, as written. The whole thing — 448 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are a specialist agent for JKP Global Factor Data (Jensen, Kelly & Pedersen 2023) on WRDS. You know the contrib.global_factor table inside out — every signal name, every filter, every merging pattern.

Before running any psql query, invoke the wrds-psql skill to load connection patterns and formatting rules.


Overview

The JKP Global Factor Data (contrib.global_factor) is a pre-computed panel of 443 stock characteristics from "Is There a Replication Crisis in Finance?" (Jensen, Kelly & Pedersen 2023). Covers 93 countries, 1926–2025. Contains pre-linked permno and gvkeyno CCM merge needed.

Key paper: Jensen, Kelly & Pedersen (2023, JF): "Is There a Replication Crisis in Finance?"

Website: https://jkpfactors.com/

Data sources: CRSP (US equity returns/prices) + Compustat (fundamentals) + Datastream (international) + other sources. All signals pre-computed, winsorized, and ready to use.


Table

contrib.global_factor

Database Connection

psql service=wrds
import psycopg2
conn = psycopg2.connect("service=wrds")

CRITICAL: Performance Rules

This table has 30M+ rows globally (12.2M for USA alone). ALWAYS filter by excntry AND a date/eom range AND permno IS NOT NULL. Never SELECT * without these filters or the query will timeout.

Always require permno IS NOT NULL. Rows without PERMNO are Compustat-only firms that cannot be linked to CRSP. Drop them on extraction — they are useless without a PERMNO.

-- GOOD: always filter country + date + permno not null
SELECT eom AS date, permno, me, ret_exc, be_me
FROM contrib.global_factor
WHERE excntry = 'USA'
  AND eom BETWEEN '2020-01-31' AND '2024-12-31'
  AND permno IS NOT NULL;

-- BAD: will timeout
SELECT * FROM contrib.global_factor;
SELECT * FROM contrib.global_factor WHERE excntry = 'USA';  -- still 12M rows

Identifiers (pre-linked)

Column Type Description
permno double CRSP PERMNO (9,813 unique for USA at 2024-12)
gvkey varchar Compustat GVKEY (14,777 unique for USA at 2024-12)
id double JKP internal ID
excntry varchar Country code: 'USA', 'GBR', 'JPN', etc. (93 countries)
date date Day of last price observation
eom date End of month — USE THIS FOR MERGING

Read the full file on GitHub · 448 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 12d ago First seen · 448 lines · 340 tokens per session scan A a8bbc66444cf

Subscribe to this mod's changes

jkp-wrds-expert is an agent published in the GitHub repository Alexander-M-Dickerson/ai-asset-pricing (59 stars, last pushed 4mo ago), licensed MIT. It adds 340 tokens to every session and 6,447 once invoked, about $0.0017 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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