Before leaving Kyoto to go back to Montréal (and enjoy some summer break), I uploaded some lecture notes, on Optimal Transport for Actuarial Science, on HAL (soon on ArXiv).

These lecture notes introduce optimal transport as a mathematical language for actuarial science. They treat losses, premiums, scores, reserves, capital scenarios, climate losses and lifetime distributions as probability measures that can be compared, transported, averaged, stressed and interpolated. The first part develops the main tools: couplings, push-forwards, discrete and continuous Kantorovich problems, duality, Wasserstein distances, quantile transport, barycenters, entropic regularization and statistical optimal transport. The second part applies these tools to risk measures, Wasserstein robustness, pricing and capital, portfolio drift, reserving cash-flow distributions, climate-prevention diagnostics, reinsurance, dependence uncertainty, capital allocation, distributional fairness diagnostics and longevity risk. Later chapters and appendices discuss counterfactual transport, dynamic formulations, unbalanced transport, Schrödinger bridges, cost engineering and computational labs in R. The emphasis is on actuarial modelling choices: the state space, the ground cost, the ambiguity radius, the reference distribution and the interpretation of the transport plan. Transport maps and couplings are used as distributional objects, not as causal claims unless additional assumptions are imposed.

(pictures will be coming in the updated version, this Fall).