  The calibration of volatility models from observable option prices is a
fundamental problem in quantitative finance. The most common approach among
industry practitioners is based on the celebrated Dupire's formula [6], which
requires the knowledge of vanilla option prices for a continuum of strikes and
maturities that can only be obtained via some form of price interpolation. In
this paper, we propose a new local volatility calibration technique using the
theory of optimal transport. We formulate a time continuous martingale optimal
transport problem, which seeks a martingale diffusion process that matches the
known densities of an asset price at two different dates, while minimizing a
chosen cost function. Inspired by the seminal work of Benamou and Brenier [1],
we formulate the problem as a convex optimization problem, derive its dual
formulation, and solve it numerically via an augmented Lagrangian method and
the alternative direction method of multipliers (ADMM) algorithm. The solution
effectively reconstructs the dynamic of the asset price between the two dates
by recovering the optimal local volatility function, without requiring any time
interpolation of the option prices.
