Agent skill

A-Share Convertible Bond Analysis

by HKUDS in HKUDS/Vibe-Trading

Analyzes Chinese A-share convertible bonds with a three-part valuation, clause game analysis, the double-low strategy and a rotation framework for choosing bonds; instructions are in Chinese.

MITAuto-check passedBusiness, Finance & HR

SKILL.md written in Chinese; this summary is our English description.

Install A-Share Convertible Bond Analysis

skills CLI
$ npx skills add HKUDS/Vibe-Trading --skill convertible-bond -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install HKUDS/Vibe-Trading convertible-bond --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/HKUDS/Vibe-Trading.git skills-src && mkdir -p .claude/skills && cp -r skills-src/agent/src/skills/convertible-bond .claude/skills/convertible-bond && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
convertible-bond
GitHub stars
35k
Token cost
~1.1k tokens
SKILL.md length
127 words
Files
1
Skills in repo
89
Repo updated
First seen
Licence
MIT

At a glance

Analyzes Chinese A-share convertible bonds with a three-part valuation, clause game analysis, the double-low strategy and a rotation framework for choosing bonds; instructions are in Chinese.

  • Works in 3 steps: 纯债价值(债底) → 转股价值(股性) → 期权价值
  • Valuing a Chinese convertible bond by bond floor, conversion value and option value
  • SKILL.md covers 概述, 可转债基础概念, 三维估值体系 and 条款博弈分析, plus 4 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

The skill treats an A-share convertible bond as a hybrid of a bond floor and an equity option and values it three ways: pure bond value, conversion value and option value. It starts with the basics, including a 100 yuan face value, rising coupons, the conversion price and maturity, and the put, forced redemption and conversion price reset clauses, then gives a matrix that sorts bonds into equity-like, balanced, debt-like and distressed types. The instructions are written in Chinese.

Clause game analysis covers the reset, forced redemption and put triggers, each tied to a stock-price condition over 30 trading days, with factors for judging how likely a reset is. The double-low strategy ranks bonds by price plus conversion premium and comes with an outline of a backtest engine, and the rotation framework scores bonds on price, elasticity, safety, reset odds and underlying stock momentum. A report format is defined for the output.

When your agent uses it

  • Valuing a Chinese convertible bond by bond floor, conversion value and option value
  • Judging whether a conversion price reset, forced redemption or put is likely
  • Ranking convertible bonds with the double-low strategy
  • Screening bonds for a rotation strategy

Example prompts

  • “Compute the conversion value of a convertible with conversion price 15.00 when the stock trades at 18.00.”
  • “Rank the convertibles in this list by double-low value.”
  • “Is a conversion price reset likely for this bond? The major holder still owns most of the issue.”
  • “Build a rotation screen that drops bonds already announced for forced redemption.”

Requirements

  • Market data for the bonds and their underlying stocks

Workflow steps

3 steps, taken from the step headings in SKILL.md.

  1. 纯债价值(债底)
  2. 转股价值(股性)
  3. 期权价值

What it can do on your machine

Read from SKILL.md and the folder at commit 8e43007. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are python and markdown).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

A-Share Convertible Bond Analysis loads about 1.1k tokens when it runs. Until then it costs about 16 tokens; SKILL.md has 127 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~16
When it runs · the whole SKILL.md, loaded when a task matches
~1.1k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from HKUDS/Vibe-Trading at commit 8e43007, republished under its MIT licence (© HKUDS). 127 words, ~1,110 tokens.

Download SKILL.mdSave it as .claude/skills/convertible-bond/SKILL.md (or your agent's skills folder).
name
convertible-bond
description
A股可转债分析——转股/纯债/期权三维估值、下修/强赎/回售博弈、双低策略与转债轮动选债框架
category
asset-class

A股可转债分析

概述

A股可转债是具有"债底保护+股票期权"特征的混合品种。本skill覆盖可转债三维估值、条款博弈分析、双低策略和轮动选债框架。

可转债基础概念

核心要素
要素说明示例
面值100元-
票面利率递增,通常0.3%-2.0%第1年0.4%...第6年2.0%
转股价转换成股票的价格转股价15.00元
到期期限通常6年2024-2030
到期赎回价面值+最后一年利息+补偿110-115元
回售条款股价持续低于转股价70%可回售连续30个交易日中30天<70%
强赎条款股价持续高于转股价130%可强赎连续30个交易日中15天>130%
下修条款可以下调转股价连续30个交易日中15天<85%
关键指标
转股价值 = 面值 / 转股价 × 正股价格
         = 100 / 15.00 × 18.00 = 120.00元

转股溢价率 = (转债价格 - 转股价值) / 转股价值 × 100%
           = (125 - 120) / 120 × 100% = 4.17%

纯债价值 = Σ(票息 / (1+r)^t) + 到期赎回价 / (1+r)^n
         ≈ 85-95元(取决于剩余期限和利率)

纯债溢价率 = (转债价格 - 纯债价值) / 纯债价值 × 100%

三维估值体系

1. 纯债价值(债底)
python
def bond_floor(coupon_rates: list, years_remaining: float,
               redemption_price: float = 110, yield_rate: float = 0.03) -> float:
    """
    Args:
        coupon_rates: 剩余各年票面利率列表,如 [0.8, 1.0, 1.5, 2.0]
        years_remaining: 剩余年限
        redemption_price: 到期赎回价
        yield_rate: 折现率(同期信用债收益率,约2.5-4%)
    Returns:
        纯债价值
    """
    pv = sum(c * 100 / (1 + yield_rate)**i for i, c in enumerate(coupon_rates, 1))
    pv += redemption_price / (1 + yield_rate)**len(coupon_rates)
    return pv

纯债价值含义:

  • 纯债价值越高 → 债底保护越强 → 下跌空间有限
  • 通常纯债价值在 85-100 之间
  • 转债价格跌到纯债价值附近 = "债性转债",安全但弹性小
2. 转股价值(股性)
转股价值 = 100 / 转股价 × 正股当前价

影响因子:
- 正股价格(正相关)
- 转股价(负相关)
- 下修转股价 → 转股价值上升
3. 期权价值
期权价值 = 转债价格 - max(纯债价值, 转股价值)

期权价值高 → 市场看好正股上涨潜力 或 看好下修概率
期权价值低/负 → 便宜(可能有机会)
三维判断矩阵
转股价值纯债价值转债类型策略
>120不重要偏股型跟随正股,关注强赎风险
100-120不重要平衡型进可攻退可守,最佳区间
<100>90偏债型持有吃利息,等下修/正股反弹
<80<85困境型高风险,可能有信用风险

条款博弈分析

下修博弈

触发条件:连续30个交易日中15天正股收盘价低于当期转股价的85%。

下修概率评估:
1. 触发条件已满足/接近满足 → 高概率
2. 大股东持有大量转债未转股 → 高概率(有动力下修)
3. 公司即将面临回售 → 高概率(下修避免回售)
4. 公司现金充裕、无还债压力 → 低概率(无动力下修)
5. 转股会大幅稀释股权 → 低概率(控制权顾虑)

下修后影响:
- 转股价值 = 100 / 新转股价 × 正股价,通常瞬间上升
- 转债价格通常上涨 5-15%
- 但正股可能因稀释预期下跌
强赎博弈

触发条件:连续30个交易日中15天正股收盘价高于转股价的130%。

强赎应对:
1. 公告强赎 → 必须在赎回日前转股或卖出
2. 赎回价通常 100.XX 元 → 远低于转股价值
3. 不转股 = 巨亏(如转债价160元,赎回价100元)

强赎信号:
- 正股价持续>转股价130% → 数天数
- 公司公告"不提前赎回" → 暂时安全
- 转股进度已>90% → 可能不赎回
回售博弈

触发条件:正股价连续30天低于转股价的70%(最后2个计息年度)。

回售 = 投资者有权以面值+利息卖回给公司

公司应对:
1. 下修转股价 → 避免回售
2. 拉升股价 → 避免触发条件
3. 接受回售 → 掏钱还债

投资者策略:
- 在回售期持有纯债价值附近的转债 → 下有回售保底
- 下修预期 → 赚下修收益

双低策略

策略逻辑
双低值 = 转债价格 + 转股溢价率 × 100

双低值越低 → 价格低 + 溢价率低 → 性价比高

筛选条件:
1. 双低值 < 130(严格)或 < 150(宽松)
2. 转债价格 < 115(安全)
3. 转股溢价率 < 30%(弹性)
4. 剩余期限 > 1年(避免到期压力)
5. 信用评级 ≥ AA-(避免信用风险)
双低选债示例
markdown
### 双低排名 Top 10

| 排名 | 转债名 | 价格 | 溢价率 | 双低值 | 评级 | 剩余年限 |
|------|--------|------|--------|--------|------|---------|
| 1 | XX转债 | 105.2 | 12.3% | 117.5 | AA | 3.2年 |
| 2 | YY转债 | 108.5 | 15.6% | 124.1 | AA | 2.8年 |
| ... | ... | ... | ... | ... | ... | ... |
双低策略回测框架
python
class ConvertibleBondEngine:
    """双低策略信号引擎"""
    def generate(self, data_map):
        # 每月末计算双低值
        # 选 Top N 等权配置
        # 下月初调仓
        pass

历史表现参考(A股可转债):

  • 年化收益:10-15%
  • 最大回撤:-8% ~ -15%
  • Sharpe:1.0-1.5
  • 关键风险:信用风险(小盘转债违约)

转债轮动策略

轮动维度
维度指标信号
价格转债价格<110超便宜, 110-120合理, >130偏贵
弹性转股溢价率<10%高弹性, 10-30%中等, >50%纯债
安全纯债价值/价格>0.9安全边际高
下修下修概率大股东持仓+接近触发=高概率
正股正股动量正股趋势向好=弹性来源
轮动流程
1. 全市场筛选(剔除: 已退市/已公告强赎/评级<A+)
2. 计算各维度得分
3. 综合打分排名
4. 选 Top 15-20 只等权配置
5. 每月调仓一次

输出格式

markdown
## 可转债分析: [转债名称/代码]

### 基本信息
| 指标 | 值 |
|------|-----|
| 当前价 | 112.50 |
| 转股价值 | 98.30 |
| 纯债价值 | 92.15 |
| 转股溢价率 | 14.4% |
| 纯债溢价率 | 22.1% |
| 双低值 | 126.9 |
| 剩余年限 | 3.5年 |
| 评级 | AA |

### 三维估值
- **债底保护**: 纯债价值92.15, 下跌空间约18%有保护
- **股性弹性**: 溢价率14.4%偏低, 正股上涨10%转债预计涨8%
- **期权价值**: 转债价格-max(纯债,转股)=14.2, 合理

### 条款博弈
- **下修概率**: 中(正股距下修触发价还有12%空间)
- **强赎风险**: 低(正股距强赎线还有35%)
- **回售保护**: 尚未进入回售期

### 投资建议
双低值126.9,属于性价比区间。建议...

注意事项

  1. 信用风险是最大雷:A股已出现可转债违约案例(搜特转债等),低评级转债谨慎
  2. 强赎倒计时要盯紧:公告强赎后不转股/不卖出会巨亏,每天检查强赎公告
  3. 流动性风险:小盘转债日成交额可能不足100万,大资金进出困难
  4. 条款差异:每只转债条款细节不同(下修比例、强赎天数),必须逐只核查
  5. 到期不转股:如果到期没转股,只拿回面值+利息(110左右),高价买入会亏
  6. 数据获取:可转债数据需通过tushare的可转债接口获取,OHLCV数据可用标准接口
  7. 回测局限:可转债回测需要转股价、强赎/回售信息等额外数据,比股票回测复杂

© HKUDS, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in agent/src/skills/convertible-bond of HKUDS/Vibe-Trading.

Open the folder on GitHubat commit 8e43007

Compare with similar skills

A-Share Convertible Bond Analysis next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

A-Share Convertible Bond Analysis compared with similar skills
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Marketscreenergauss314/skills248—~1.1kAutomated safety check: PassMIT
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Questions about A-Share Convertible Bond Analysis

What does A-Share Convertible Bond Analysis do?

Analyzes Chinese A-share convertible bonds with a three-part valuation, clause game analysis, the double-low strategy and a rotation framework for choosing bonds; instructions are in Chinese. The skill treats an A-share convertible bond as a hybrid of a bond floor and an equity option and values it three ways: pure bond value, conversion value and option value. It starts with the basics, including a 100 yuan face value, rising coupons, the conversion price and maturity, and the put, forced redemption and conversion price reset clauses, then gives a matrix that sorts bonds into equity-like, balanced, debt-like and distressed types.

When should I use A-Share Convertible Bond Analysis?

A-Share Convertible Bond Analysis fits situations like: valuing a Chinese convertible bond by bond floor, conversion value and option value; judging whether a conversion price reset, forced redemption or put is likely; ranking convertible bonds with the double-low strategy; screening bonds for a rotation strategy.

How do I install A-Share Convertible Bond Analysis in Claude Code?

Run `npx skills add HKUDS/Vibe-Trading --skill convertible-bond -a claude-code`. Or copy the skill folder (agent/src/skills/convertible-bond in HKUDS/Vibe-Trading) into .claude/skills/convertible-bond in your project. Claude Code loads it when a task matches its description.

How do I install A-Share Convertible Bond Analysis in Codex?

Run `npx skills add HKUDS/Vibe-Trading --skill convertible-bond -a codex`. Or copy the skill folder (agent/src/skills/convertible-bond in HKUDS/Vibe-Trading) into .agents/skills/convertible-bond in your project. Codex loads it when a task matches its description.

Can I use A-Share Convertible Bond Analysis in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add HKUDS/Vibe-Trading --skill convertible-bond -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/convertible-bond, .gemini/skills/convertible-bond, .github/skills/convertible-bond and .opencode/skills/convertible-bond in your project.

What does A-Share Convertible Bond Analysis need to run?

SKILL.md names no scripts, command-line tools or credentials: A-Share Convertible Bond Analysis is instructions for the agent only. Our summary lists: Market data for the bonds and their underlying stocks.

Does A-Share Convertible Bond Analysis access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is A-Share Convertible Bond Analysis safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does A-Share Convertible Bond Analysis use?

A-Share Convertible Bond Analysis is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does A-Share Convertible Bond Analysis use?

About 1.1k tokens (SKILL.md is roughly 4.4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to A-Share Convertible Bond Analysis?

Skills that share tags, products or a category with A-Share Convertible Bond Analysis: Strategy Performance Report (tradesdontlie/tradingview-mcp, 6.8k stars), Alpha Desk Investment Research (JingHao-Leon/dsh-alpha-desk, 181 stars), Quant Buddy Market Data and Backtesting (pseudo-longinus/quant-buddy-skills, 193 stars) and Marketscreener (gauss314/skills, 248 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains A-Share Convertible Bond Analysis?

HKUDS (a GitHub organization) maintains it in HKUDS/Vibe-Trading, which has 35,163 GitHub stars. The repository holds 89 skills in this directory. The repository was last updated on October 10, 2026.

Source: HKUDS/Vibe-Trading on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.