Stochastic Knothe–Rosenblatt: Light-speed Calibration of Stochastic Local Volatility Models

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Highly relevant for derivatives desks and risk managers who need to calibrate complex stochastic local volatility models quickly and accurately for pricing and hedging exotic options. The 'light-speed' calibration claim addresses a major bottleneck in quantitative finance.

The theoretical framework is advanced (optimal transport, martingale problems). However, the numerical implementation relies on the Martingale Sinkhorn algorithm, which is described as simple to implement and efficient. Integrating it as an overlay on existing SV models requires careful handling of joint laws.

The paper provides detailed theoretical foundations, algorithmic steps (Algorithm 1), and specific numerical parameters (Table 1). It references open-source implementations (QuantLib) and provides supplementary material links. However, the specific C++ implementation code for the SKR algorithm is not explicitly hosted in a public repository within the text.