Abstract
Baumol (1952) applies well-known results from inventory control problems to treasury management, in which an individual facing a transaction demand for cash chooses to hold his liquid funds partly in cash and partly in bonds. An analytical solution is derived under very restrictive assumptions. To focus on more practically relevant settings, dynamic stochastic programming techniques started to make their way into applications in quantitative asset management. Early approaches using linear programming for financial planning tasks with multiple assets and stages are proposed by Charnes et al (1959); Chambers and Charnes (1961); Cohen and Hammer (1967). These models still use a determin-istic framework. Since then many extensions were proposed. Dempster et al (2009) give an extensive overview of the state-of-the-art method s for financial planning under uncertainty.