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options-advanced

Analyze the volatility implied by option prices across strike prices and expiration dates. Compare calendar spreads and other volatility strategies, then assess portfolio risk using Greeks, measures of how option values respond to market changes.

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

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适用场景

  • Compare implied volatility across strikes and expiration dates
  • Evaluate calendar spread strategies
  • Review portfolio risk using Greeks
  • Assess volatility and skew trading opportunities

包含的文件(1)

  • SKILL.md7.8 KB

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

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

pip install pandas numpy scipy

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