Class HedgingSimulator
java.lang.Object
com.quantfinlib.hedging.HedgingSimulator
Monte Carlo delta-hedging engine: runs
DeltaHedger across thousands
of GBM paths in parallel to produce the full hedging-error distribution —
replication error, tail risk (hedging VaR/CVaR), and cost/rebalance
statistics.
Pricing/hedging volatility and realized (path) volatility are separate inputs, so the two classic questions are directly answerable:
- Discretization risk — hedge vol = realized vol: how does the error distribution shrink with rebalancing frequency and band?
- Vol mispricing — hedge vol ≠ realized vol: selling rich (implied > realized) shows up as a positive mean P&L, and vice versa.
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Constructor Summary
Constructors -
Method Summary
Modifier and TypeMethodDescriptionsimulate(BlackScholes.OptionType type, double spot, double strike, double expiryYears, double rate, double carry, double hedgeVol, double realizedVol, int stepsPerPath, int numPaths, DeltaHedger.Config hedgeConfig)
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Constructor Details
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HedgingSimulator
public HedgingSimulator() -
HedgingSimulator
public HedgingSimulator(long seed)
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Method Details
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simulate
public HedgingErrorDistribution simulate(BlackScholes.OptionType type, double spot, double strike, double expiryYears, double rate, double carry, double hedgeVol, double realizedVol, int stepsPerPath, int numPaths, DeltaHedger.Config hedgeConfig) - Parameters:
hedgeVol- volatility used to price and delta-hedge (implied vol)realizedVol- volatility of the simulated underlying pathsstepsPerPath- hedging opportunities per path (e.g. 126 for daily over 6 months)numPaths- Monte Carlo scenarios (2 000+ recommended)
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