Borrowing it
Nothing to install: this file belongs to ericxuzhesheng/Convertible-Bond-Pricing-Research. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/ericxuzhesheng/Convertible-Bond-Pricing-Research/main/AGENTS.mdgit clone --depth 1 https://github.com/ericxuzhesheng/Convertible-Bond-Pricing-ResearchWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/instructions/ericxuzhesheng/convertible-bond-pricing-research/agents-md)<a href="https://agentmods.dev/instructions/ericxuzhesheng/convertible-bond-pricing-research/agents-md"><img src="https://agentmods.dev/badge/instructions/ericxuzhesheng/convertible-bond-pricing-research/agents-md/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/instructions/ericxuzhesheng/convertible-bond-pricing-research/agents-md"><img src="https://agentmods.dev/badge/instructions/ericxuzhesheng/convertible-bond-pricing-research/agents-md.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.03439 | $0.03439 |
| Opus 5 | $0.01720 | $0.01720 |
| Sonnet 5 | $0.00688 | $0.00688 |
| Haiku 4.5 | $0.00344 | $0.00344 |
Grade A, and why
Convertible-Bond-Pricing-Research AGENTS.md 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 11d 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.
How it starts
The opening of the file, as written. The whole thing — 287 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md — Agent Instructions for Convertible Bond Pricing Research
This file tells Codex how to navigate and work with this codebase.
Project Purpose
Absolute pricing research for Chinese A-share convertible bonds using three models:
- Black-Scholes (BS): closed-form, offensive anchor (equity/vol driven)
- Zheng-Lin (ZL): Monte Carlo optimal stopping, defensive anchor (clause-aware)
- Least-Squares Monte Carlo (LSM): vectorized continuation-value regression and voluntary early conversion
The pipeline goes: raw data → pricing → mispricing signal → long-short strategy.
Current published vintage: 2026-08-28. Routine weekly work is strictly incremental; do not run a full-history rebuild unless a maintainer explicitly requests one.
Repository Layout
Convertible-Bond-Pricing-Research/
├── AGENTS.md ← you are here
├── README.md ← bilingual overview
├── backtest/ ← PRIMARY working directory
│ ├── data_pipeline.py ← Tushare data ingestion (run first)
│ ├── B-S_backtest.py ← BS model pricing + output
│ ├── Z-L_backtest_GPU_prod.py ← shared ZL driver (CUDA/CPU)
│ ├── Z-L_backtest_CPU_prod.py ← GitHub CPU incremental entrypoint
│ ├── LSM_backtest.py ← vectorized strict-incremental LSM driver
│ ├── lsm_backend.py ← batched quadratic Longstaff-Schwartz engine
│ ├── Z-L_backtest_GPU.py ← disabled legacy entrypoint
│ ├── full_history_rebuild.py ← fail-closed full-history rebuild
│ ├── regenerate_plots.py ← 一键重生成 README 图表（无需重跑模型）
│ ├── weekly_update.bat ← 周更新主入口（数据→模型→图表→Git推送）
│ ├── setup_weekly_task.ps1 ← 一次性注册 Windows 任务计划程序
│ ├── logs/ ← weekly_update.bat 日志
│ ├── cb_*.csv ← wide-format data caches (rows=date, cols=bond)
│ ├── rf_yield_cache.csv ← risk-free yield curve (tenor format, not wide)
│ ├── bs_volatility_cache.csv ← 250-day rolling vol for BS
│ ├── BS_Model_*.csv / .xlsx ← BS model outputs
│ ├── ZL_Model_*.csv / .xlsx ← ZL model outputs
│ └── LSM_Model_*.csv / .xlsx ← LSM outputs + independent manifest
├── long-short strategy/
│ └── BS_ZL_LSM_strategy.py ← three-model monthly rebalancing backtest
├── mispricing factor/
│ ├── B-S_mispricing_factor.py ← 6-factor BS composite
│ ├── Z-L_mispricing_factor.py ← 6-factor ZL composite
│ └── LSM_mispricing_factor.py ← 6-factor LSM composite
├── summary/
│ └── key_findings.md ← executive summary
└── report/ ← full research PDF
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.
- 11d ago First seen · 287 lines · 3,439 tokens per session scan A bb5d4af823f8
Convertible-Bond-Pricing-Research AGENTS.md is an instructions file published in the GitHub repository ericxuzhesheng/Convertible-Bond-Pricing-Research (7 stars, last pushed 11d ago), licensed MIT. It adds 3,439 tokens to every session, about $0.0172 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 2026-08-31.
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