Class HedgingSimulator

java.lang.Object

com.quantfinlib.hedging.HedgingSimulator

public final class HedgingSimulator
extends Object

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.

Deterministic for a given seed regardless of thread scheduling.

Constructor Summary

Constructors

Constructor	Description
HedgingSimulator()
HedgingSimulator(long seed)

Method Summary

Modifier and Type	Method	Description
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)	Simulates the hedging error distribution over Monte Carlo paths.

Methods inherited from class Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Details

HedgingSimulator

public HedgingSimulator()

HedgingSimulator

public HedgingSimulator(long seed)

Method Details

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)

Simulates the hedging error distribution over Monte Carlo paths.

Parameters:

hedgeVol - volatility used to price and delta-hedge (implied vol)

realizedVol - volatility of the simulated underlying paths

stepsPerPath - hedging opportunities per path (e.g. 126 for daily over 6 months)

numPaths - Monte Carlo scenarios (2 000+ recommended)