The scope of this volume is primarily to analyze from different methodological perspectives similar valuation and optimization problems arising in financial applications, aimed at facilitating a theoretical and computational integration between methods largely regarded as alternatives. Increasingly in recent years, financial management problems such as strategic asset allocation, asset-liability management, as well as asset pricing problems, have been presented in the literature adopting formulation and solution approaches rooted in stochastic programming, robust optimization, stochastic dynamic programming (including approximate SDP) methods, as well as policy rule optimization, heuristic approaches and others. The aim of the volume is to facilitate the comprehension of the modeling and methodological potentials of those methods, thus their common assumptions and peculiarities, relying on similar financial problems. The volume will address different valuation problems common in finance related to: asset pricing, optimal portfolio management, risk measurement, risk control and asset-liability management.The volume features chapters of theoretical and practical relevance clarifying recent advances in the associated applied field from different standpoints, relying on similar valuation problems and, as mentioned, facilitating a mutual and beneficial methodological and theoretical knowledge transfer. The distinctive aspects of the volume can be summarized as follows:

First collection of state-of-the-art financial optimization theoretical research

Multi-period Risk Measures and Optimal Investment Policies.- Asset Price Dynamics: Shocks and Regimes.- Scenario Optimization Methods in Portfolio Analysis and Design.- Robust Approaches to Pension Fund Asset Liability Management under Uncertainty.- Liability-driven Investment in Longevity Risk Management.- Pricing Multiple Exercise American Options by Linear Programming.- Optimizing a Portfolio of Liquid and Illiquid Assets.- Stabilization Implementable Decisions in Dynamic Stochastic Programming.- The Growth Optimal Investment Strategy is Secure, Too.- Heuristics for Portfolio Selection.- Optimal Financial Decision Making under Uncertainty.