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The finance industry is seeing increased interest in new risk measures and techniques for portfolio optimization when parameters of the model are uncertain. In this book, Fabozzi, Stoyanov, and Rachev intend to break new ground in tying together the theory of probability metrics to both risk measurement and portfolio optimization. Unlike current literature in this field, this book proposes applications to optimal portfolio choice and risk theory, as well as applications to the area of computational finance.

Advanced Stochastic Models, Risk Assessment, and Portfolio Optimization: The Ideal Risk, Uncertainty, and Performance Measures