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Heston
Delta Hedging
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Connected Guides
  • The Black–Scholes formula
  • Geometric Brownian motion
  • Correlated Brownian motions and multi-asset models
  • Jumps and the Merton jump-diffusion model
  • Implied volatility and the volatility smile
  • Stochastic volatility and the Heston model

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Heston

Controls

Model parameters
100
20200
100
20200
0.050
00.2
0.0400
0.00010.25
0.0400
0.00010.25
2.00
0.110
0.50
0.012
-0.70
-0.990.99
1.00 years
0.2510
Simulation settings
150
25500
5
130
80
25400
250
1002000
Reference
Initial vol
0.200
Long-run vol
0.200
Feller
not satisfied (-0.0900)
Heston stock paths
Heston variance paths

About this tool

The Heston model lets volatility itself be random: the variance follows a mean-reverting square-root process that is correlated with the stock price. This simulator shows sample paths of price and variance, the effect of mean reversion speed, long-run variance, vol-of-vol and correlation, and prices a European option by Monte Carlo.

Frequently asked questions

Why use stochastic volatility instead of Black–Scholes?

Market option prices imply different volatilities for different strikes (the volatility smile and skew). A random, correlated volatility produces fatter tails and skew, which a single constant volatility cannot.

What does the correlation parameter ρ do?

A negative ρ makes volatility rise when the price falls, the typical equity pattern. It skews the return distribution to the left and steepens the implied volatility skew.

Learn the theory

  • The Black–Scholes formula — How the formula is obtained, what d₁ and d₂ mean, and what the model leaves out.
  • Geometric Brownian motion — The standard model for stock prices: the log-normal distribution, its mean and its median.
  • Correlated Brownian motions and multi-asset models — Building correlated Brownian motions with a Cholesky factor, the two-dimensional Itô rule, and where correlation enters Heston and basket pricing.
  • Jumps and the Merton jump-diffusion model — The Poisson process, compound jumps, the Merton model, and how jumps create fat tails and a smile.
  • Implied volatility and the volatility smile — Inverting Black–Scholes for σ, vega, and what the smile and the term structure say about the model.
  • Stochastic volatility and the Heston model — The Heston variance process, mean reversion, vol-of-vol, the Feller condition, and how correlation and vol-of-vol shape the smile.