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Quantitative Finance · Glossaire

Qu'est-ce que « Surrogate model, differential machine learning » ?

Aussi appelé : surrogate model · differential machine learning

Definition 19.3 Machine Learning for Markets · Chapitre 19 — Deep Hedging and Machine Learning in Pricing

A surrogate model is a fast approximation of a slow function, here a pricer, fitted to its outputs on sampled inputs. Differential machine learning trains the surrogate on the derivatives of the labels with respect to the inputs as well as on the labels, the network’s own derivatives being computed by automatic differentiation (Book 4, chapter 28); with Monte Carlo labels the derivative labels are pathwise (Huge and Savine, 2020).

price RMSEdelta RMSE
training samplesstandarddifferentialstandarddifferential
2560.9270.6790.0660.057
1 0240.4360.2180.0590.021
4 0960.2970.2790.0420.020
Table 19.2. A two-layer surrogate of the Heston call price learned from one-path Monte Carlo payoffs, with and without pathwise delta labels: errors against the Fourier price and its finite-difference delta on 400 test points. Data: ml_hedge.surrogates.
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