Optimal Financial Decision Making under Uncertainty

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:Strong benchmarking philosophy, with contributors explicitly asked to underline current limits and desirable developments in their areas.Theoretical contributions, aimed at advancing the state-of-the-art in the given domain with a clear potential for applicationsThe inclusion of an algorithmic-computational discussion of issues arising on similar valuation problems across different methods.Variety of applications: rarely is itpossible within a single volume to consider and analyze different, and possibly competing, alternative optimization techniques applied to well-identified financial valuation problems.Clear definition of the current state-of-the-art in each methodological and applied area to facilitate future research directions.

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:

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.