Skip to content
Stochastic Calculus / Brownian Motion: Construction and Properties

The Heat Equation and the Generator of Brownian Motion

The Black-Scholes PDE is:

∂V∂t+12σ2S2∂2V∂S2+rS∂V∂S−rV=0.\frac{\partial V}{\partial t} + \frac{1}{2}\sigma^2 S^2 \frac{\partial^2 V}{\partial S^2} + rS\frac{\partial V}{\partial S} - rV = 0.
At first glance this looks like an equation from nowhere. But it is, in fact, the heat equation with a coordinate change — the fundamental PDE that describes how temperature diffuses, which is also exactly the equation governing the expected future payoff of an option as a function of current price and time to expiry.

The connection is: if (Wt)(W_t) is a BM with drift mm and variance σ2\sigma^2, and φ(t,x)=Ex[f(Wt)]\varphi(t, x) = \mathbb{E}_x[f(W_t)] (the expected value of ff at time tt, starting from xx), then φ\varphi satisfies:

∂tφ=Lφ,whereL=m∂x+σ22∂xx.\partial_t \varphi = \mathcal{L} \varphi, \quad \text{where} \quad \mathcal{L} = m\partial_x + \frac{\sigma^2}{2}\partial_{xx}.
The operator L\mathcal{L} is the infinitesimal generator of BM. For driftless BM and f(x)=f(x) = a call payoff, this reduces immediately to the heat equation ∂tφ=12∂xxφ\partial_t \varphi = \frac{1}{2}\partial_{xx}\varphi. The Black-Scholes PDE is this equation in log-price coordinates plus a discounting adjustment.
Learning objectives. By the end of this note you should be able to:
  • Derive the heat equation ∂tpt=12∂xxpt\partial_t p_t = \frac{1}{2}\partial_{xx} p_t for the transition density of SBM.
  • State and apply Theorem 2.10.3: the generator of dd-dimensional BM with drift mm and covariance Γ\Gamma is Lf=m⋅∇f+12∑jkΓjk∂jkf\mathcal{L}f = m \cdot \nabla f + \frac{1}{2}\sum_{jk}\Gamma_{jk}\partial_{jk}f.
  • Verify that φ(t,x)=Ex[f(Wt)]\varphi(t,x) = \mathbb{E}_x[f(W_t)] satisfies ∂tφ=Lxφ\partial_t \varphi = \mathcal{L}_x \varphi with initial condition φ(0,x)=f(x)\varphi(0,x) = f(x).
  • Connect the generator to the Black-Scholes PDE via a change of coordinates.
  • Interpret the Chapman-Kolmogorov equation and the Markov semigroup Ptf(x)=Ex[f(Wt)]P_t f(x) = \mathbb{E}_x[f(W_t)].

In this lesson

  1. The Transition Density of Brownian Motion
  2. The Heat Equation: Heuristic Derivation
  3. The Generator of Brownian Motion
  4. The Backward Kolmogorov Equation
  5. Connection to the Black-Scholes PDE
  6. Example: The Call Option Price as a Heat Kernel Convolution

Before you start

The full lesson, with worked examples and exercise solutions, is for members.

Read the full lesson

New to SelfMadeQuant.com? See membership options or explore the curriculum.