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Options Advanced

OrganizationPopular
HKUDS
options-advanced

Advanced options strategies: volatility-surface modeling (SABR / Local Vol), dynamic Greeks rebalancing, calendar spreads, volatility arbitrage and skew trading, and option market-making basics.

Overview

PublisherHKUDS
RepositoryVibe-Trading
Skill nameoptions-advanced
Stars
33.6K
Forks
5.5K
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by HKUDS on GitHub. Read the source before you install it.

Installation

Install the Options Advanced AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/HKUDS/Vibe-Trading.git /tmp/Vibe-Trading
mkdir -p .claude/skills
cp -r /tmp/Vibe-Trading/agent/src/skills/options-advanced .claude/skills/options-advanced
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Options Advanced in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Options Advanced on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Options Advanced is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Advanced Options Strategies

Overview

Go beyond basic option strategies (covered call / protective put) and focus on trading opportunities along the volatility dimension. Core idea: option price = intrinsic value + time value, and advanced trading essentially trades the volatility expectations embedded behind that time value.

Applicable scenarios:

  • Identifying arbitrage opportunities when the volatility surface is abnormal (skew / term structure)
  • Fine-grained management of portfolio Greeks exposures (not just Delta hedging)
  • Building structured strategies across maturities and strikes
  • Practical application in 50ETF / 300ETF / commodity options

Core Concepts

Volatility Surface

Three-dimensional structure: strike × expiry × implied volatility.

Key dimensions:

DimensionMeaningTypical Shape
Smile / SkewIV across strikes for the same expiryChina A-shares: left-skewed (put IV > call IV)
Term StructureIV across expiries for the same strikeNormal case: near-month IV < far-month IV
Surface dynamicsParallel or nonlinear movement of the entire surfaceIn panic, the whole surface lifts, and near-month IV lifts faster

SABR model parameters:

α (alpha): initial volatility level, around 0.2-0.5
β (beta): CEV exponent, equities usually use 0.5-1.0
ρ (rho): correlation between volatility and the underlying, usually -0.3 to -0.7 in China A-shares (negative = left skew)
ν (nu): volatility of volatility (vol of vol), around 0.3-0.8

Local Vol vs SABR:

  • Local Vol (Dupire): backed out from market prices, exact fit but unstable extrapolation
  • SABR: parameterized model, 4 parameters capture surface dynamics and extrapolate more reasonably

Dynamic Greeks Management

First-order Greeks:

GreekMeaningManagement Approach
Delta (Δ)Sensitivity to underlying priceHedge frequency: daily for ATM, every 2-3 days for OTM
Vega (ν)Sensitivity to IVCalendar spreads can isolate Vega exposure
Theta (Θ)Time decayShort-option strategies are naturally positive Theta, but watch Gamma risk
Rho (ρ)Sensitivity to ratesRelevant for long-dated options, usually ignorable for short-dated options

Second-order Greeks:

GreekMeaningKey Scenario
Gamma (Γ)Rate of change of DeltaHighest near ATM and spikes before expiry
VannaSensitivity of Delta to IVCore Greek for skew trading
Volga / VommaSensitivity of Vega to IVImportant when volatility moves sharply

Delta hedge frequency decision:

Hedging cost = trading frequency × slippage per rebalance
Unhedged risk = Gamma exposure × underlying volatility²
Optimal frequency (Zakamouline criterion):
  Trigger hedge when Gamma × S² × σ² × Δt > 2 × transaction_cost
Practical rule: ATM Gamma is large -> hedge daily; OTM -> hedge weekly or on threshold triggers

Analysis Framework

1. Calendar Spread

Principle: sell the near-month option and buy the far-month option at the same strike, profiting from faster near-month Theta decay.

Entry conditions:

  • Normal term structure (near-month IV ≤ far-month IV)
  • Expect the underlying to stay in a narrow range
  • Open the position 20-30 days before near-month expiry

50ETF example:

Underlying: 50ETF current price 2.80
Sell: 50ETF near-month C2800  IV=18%, collect premium 0.045
Buy: 50ETF far-month C2800   IV=20%, pay premium 0.082
Net debit: 0.037 (max loss)
Breakeven: profit if the underlying stays in the 2.76-2.84 range at near-month expiry
Max profit: when near-month expires with the underlying right at 2.80, roughly 0.045 minus the time-decay differential

Risk-control points:

  • Large breakout in the underlying → stop loss (if loss exceeds 50% of net debit)
  • Near-month IV suddenly rises above far-month IV (term-structure inversion) → close position

2. Volatility Arbitrage

Long Gamma strategy (buy volatility):

Scenario: realized volatility is expected to exceed implied volatility
Trade: buy ATM straddle + Delta hedge
Profit source: Gamma-scalping gains > Theta decay
Key metric:
  Breakeven volatility = IV + Theta/Gamma cost
  Example in 300ETF: buy straddle at IV=16%; if realized volatility >18%, the trade is profitable

Short Gamma strategy (sell volatility):

Scenario: realized volatility is expected to stay below implied volatility
Trade: sell ATM straddle + Delta hedge
Profit source: Theta income > hedging loss
Risk control: set max loss = 2x premium received, close when hit

3. Skew Trade

Risk Reversal:

Scenario: skew is too steep (put IV excessively high relative to call IV)
Trade: sell OTM put + buy OTM call (zero-cost or slight net credit)
Exposure: long skew (profit if skew mean-reverts)
50ETF example:
  Sell P2700 IV=22%  collect 0.025
  Buy C2900 IV=16%   pay 0.018
  Net credit 0.007, profiting from skew mean reversion

Butterfly skew trade:

Scenario: localized skew abnormality (IV deviation at a particular strike)
Trade: build a butterfly centered on the abnormal strike
  If IV is too high -> sell that strike (middle leg of the butterfly)
  If IV is too low -> buy that strike

4. Option Market-Making Basics

Quoting strategy:

  • Bid-ask spread = f(Gamma risk, inventory skew, market volatility)
  • Narrow spreads attract flow; wider spreads protect risk
  • Inventory-skew management: if Delta exceeds the limit, tilt quotes to induce the other side to offset inventory

Inventory management:

Delta limit: ±500 underlying-equivalent lots
Gamma limit: daily Gamma PnL should not exceed 2% of account equity
Vega limit: PnL from a 1% IV move should not exceed 1% of account equity
When over the limit: hedge in the market first, adjust quotes second

Output Format

Volatility analysis report:

=== Volatility Surface Analysis ===
Underlying: 50ETF  Current price: 2.80
ATM IV: 18.5%  Historical percentile: 35% (relatively low)
Skew (25D): -3.2% (put IV is 3.2% higher than call IV)  Historical percentile: 70% (relatively steep)
Term Structure: normal (near-month 17.8% < far-month 19.2%)

=== Strategy Recommendation ===
Opportunity: steep skew + low IV
Strategy: Risk Reversal (sell put / buy call) + Calendar Spread
Expectation: skew mean reversion + mild IV rise
Risk control: keep Delta neutral, keep Gamma within ±200 lots

=== Greeks Monitoring ===
Portfolio Delta: +15 (neutral)
Portfolio Gamma: -180 (short Gamma, watch gap risk)
Portfolio Vega: +3200 (long Vega, benefits from higher IV)
Portfolio Theta: -450 / day

Notes

  1. China A-share option characteristics: liquidity in 50ETF / 300ETF options is concentrated in near-month ATM ± 3 strikes; deep OTM and far-month options are illiquid and have large slippage
  2. Margin management: short-option margin changes dynamically with the underlying; keep >30% buffer to avoid margin calls
  3. Expiry-week effect: Gamma rises sharply during the week before expiry, Pin Risk increases, and short-option traders should reduce size early
  4. Market-making barrier: real market making requires high-frequency infrastructure, low latency, and professional risk controls; retail traders should not attempt pure market making
  5. SABR calibration: calibrate parameters daily after the close with market data, then use prior-day parameters plus real-time adjustment at the open
  6. Gamma scalping PnL: actual profit = 0.5 × Gamma × (RV² - IV²) × S² × T; realized volatility must exceed IV by a meaningful margin to cover transaction costs

Dependencies

bash
pip install pandas numpy scipy

Frequently asked questions

What does the Options Advanced AI skill do?

Advanced options strategies: volatility-surface modeling (SABR / Local Vol), dynamic Greeks rebalancing, calendar spreads, volatility arbitrage and skew trading, and option market-making basics.

Why use Options Advanced on TypingMind?

Because you install it once and use it with any model. Options Advanced is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Options Advanced in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/HKUDS/Vibe-Trading/tree/main/agent/src/skills/options-advanced. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Options Advanced?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Options Advanced?

As many as you like. As long as a model supports skills, you can use Options Advanced with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Options Advanced AI skill free?

Yes. It is published on GitHub by HKUDS under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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