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options-payoff期权收益

Agent Skill

options-payoff 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

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安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:options-payoff(期权收益)
来源仓库:https://github.com/himself65/options-payoff
安装命令:
openclaw skills install options-payoff
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install options-payoff

简介

动态生成交互式期权收益曲线图,支持参数实时调整。

  • 适用于期权头寸分析与盈亏可视化展示场景。options-payoff 属于研究检索类 Skill,可作为该场景下的辅助能力补充。
  • 输入屏幕截图即可解析合约参数并渲染图表。
  • 通过 clawhub 安装,需注意图像识别精度限制。
  • 建议手动核对关键参数防止误读导致图形偏差。

SKILL.md

name
options-payoff
description
>

Options Payoff Curve Skill

Generates a fully interactive HTML widget (via visualize:show_widget) showing:

  • Expiry payoff curve (dashed gray line) — intrinsic value at expiration
  • Theoretical value curve (solid colored line) — Black-Scholes price at current DTE/IV
  • Dynamic sliders for all key parameters
  • Real-time stats: max profit, max loss, breakevens, current P&L at spot

Step 1: Extract Strategy From User Input

When the user provides a screenshot or text, extract:

FieldWhere to find itDefault if missing
Strategy typeTitle bar / leg description"custom"
UnderlyingTicker symbolSPX
Strike(s)K1, K2, K3... in title or leg tablenearest round number
Premium paid/receivedFilled price or avg price5.00
QuantityPosition size1
Multiplier100 for equity options, 100 for SPX100
ExpiryDate in title30 DTE
Spot priceCurrent underlying price (NOT strike)middle strike
IVShown in greeks panel, or estimate from vega20%
Risk-free rate4.3%

Critical for screenshots: The spot price is the CURRENT price of the underlying index/stock, NOT the strikes. For SPX, check market data — as of March 2026 SPX ≈ 5,500. Never default spot to a strike price value.


Step 2: Identify Strategy Type

Match to one of the supported strategies below, then read the corresponding section in references/strategies.md.

StrategyLegsKey Identifiers
butterflyBuy K1, Sell 2×K2, Buy K33 strikes, "Butterfly" in title
vertical_spreadBuy K1, Sell K2 (same expiry)2 strikes, debit or credit
calendar_spreadBuy far-expiry K, Sell near-expiry KSame strike, 2 expiries
iron_condorSell K2/K3, Buy K1/K4 wings4 strikes, 2 spreads
straddleBuy Call K + Buy Put KSame strike, both types
strangleBuy OTM Call + Buy OTM Put2 strikes, both OTM
covered_callLong 100 shares + Sell Call KStock + short call
naked_putSell Put KSingle leg
ratio_spreadBuy 1×K1, Sell N×K2Unequal quantities

For strategies not listed, use custom mode: decompose into individual legs and sum their P&Ls.


Step 3: Compute Payoffs

Black-Scholes Put Price

d1 = (ln(S/K) + (r + σ²/2)·T) / (σ·√T)
d2 = d1 - σ·√T
put = K·e^(-rT)·N(-d2) - S·N(-d1)

Black-Scholes Call Price (via put-call parity)

call = put + S - K·e^(-rT)

Butterfly Put Payoff (expiry)

if S >= K3: 0
if S >= K2: K3 - S
if S >= K1: S - K1
else: 0

Net P&L per share = payoff − premium_paid

Vertical Spread (call debit) Payoff (expiry)

long_call = max(S - K1, 0)
short_call = max(S - K2, 0)
payoff = long_call - short_call - net_debit

Calendar Spread Theoretical Value

Calendar cannot be expressed as a simple expiry function — always use BS pricing for both legs:

value = BS(S, K, T_far, r, IV_far) - BS(S, K, T_near, r, IV_near)

For expiry curve of calendar: near leg expires worthless, far leg = BS with remaining T.

Iron Condor Payoff (expiry)

put_spread = max(K2-S, 0) - max(K1-S, 0)   // short put spread
call_spread = max(S-K3, 0) - max(S-K4, 0)  // short call spread
payoff = credit_received - put_spread - call_spread

Step 4: Render the Widget

Use visualize:read_me with modules ["chart", "interactive"] before building.

Required Controls (sliders)

Structure section:

  • All strike prices (K1, K2, K3... as needed by strategy)
  • Premium paid/received
  • Quantity
  • Multiplier (100 default, show for clarity)

Pricing variables section:

  • IV % (5–80%, step 0.5)
  • DTE — days to expiry (0–90)
  • Risk-free rate % (0–8%)

Spot price:

  • Full-width slider, range = [min_strike - 20%, max_strike + 20%], defaulting to ACTUAL current spot

Required Stats Cards (live-updating)

  • Max profit (expiry)
  • Max loss (expiry)
  • Breakeven(s) — show both for two-sided strategies
  • Current theoretical P&L at spot

Chart Specs

  • X-axis: SPX/underlying price
  • Y-axis: Total USD P&L (not per-share)
  • Blue solid line = theoretical value at current DTE/IV
  • Gray dashed line = expiry payoff
  • Green dashed vertical = strike prices (K2 center strike brighter)
  • Amber dashed vertical = current spot price
  • Fill above zero = green 10% opacity; below zero = red 10% opacity
  • Tooltip: show both curves on hover

Code template

Use this JS structure inside the widget, adapting pnlExpiry() and bfTheory() per strategy:

// Black-Scholes helpers (always include)
function normCDF(x) { /* Horner approximation */ }
function bsCall(S,K,T,r,sig) { /* standard BS call */ }
function bsPut(S,K,T,r,sig) { /* standard BS put */ }

// Strategy-specific expiry payoff (returns per-share value BEFORE premium)
function expiryValue(S, ...strikes) { ... }

// Strategy-specific theoretical value using BS
function theoreticalValue(S, ...strikes, T, r, iv) { ... }

// Main update() reads all sliders, computes arrays, destroys+recreates Chart.js instance
function update() { ... }

// Attach listeners
['k1','k2',...,'iv','dte','rate','spot'].forEach(id => {
  document.getElementById(id).addEventListener('input', update);
});
update();

Step 5: Respond to User

After rendering the widget, briefly explain:

  1. What strategy was detected and how legs were mapped
  2. Max profit / max loss at current settings
  3. One key insight (e.g., "spot is currently 950 pts below the profit zone, expiring tomorrow")

Keep it concise — the chart speaks for itself.


Reference Files

  • references/strategies.md — Detailed payoff formulas and edge cases for each strategy type
  • references/bs_code.md — Copy-paste ready Black-Scholes JS implementation with normCDF

Read the relevant reference file if you're unsure about payoff formula edge cases for a given strategy.

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

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能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

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该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

安装前确认

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