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This paper features expectiles in dynamic and stochastic optimization.Expectiles are a family of risk functionals characterized as minimizers ofoptimization problems. For this reason, they enjoy various unique stabilityproperties, which can be exploited in risk averse management, in stochasticoptimization and in optimal control.  The paper provides tight relates of expectiles to other risk functionals andaddresses their properties in regression. Further, we extend expectiles to adynamic framework. As such, they allow incorporating a risk averse aspect incontinuous-time dynamic optimization and a risk averse variant of theHamilton-Jacobi-Bellman equations.

Expectiles In Risk Averse Stochastic Programming and Dynamic Optimization