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A broad introduction to expected shortfall and related methodologies as well as risk measures in general is given. The focus of this book is to analyze the usage of new methods to estimate expected shortfall. A connection between asymmetric regression (expectiles) and financial risk is at the heart of a growing body of research in this direction. Other approaches considered in detail are extreme value theory and historical estimation. The methodologies covered here are readily implemented and available at quantlet.de. The aim is to equip the industry participant with new tools from a rapidly advancing field of research while providing the academician a handbook covering a diverse range of topics concerning risk measures.

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Philipp Gschöpf´s experience regarding financial risk management ranges from a position as risk controller in a major European clearing house up to research as a Ph.D. student of Humboldt University´s IRTG 1792 - High Dimensional Non- Stationary Time Series. His current research focuses on applied non-parametric statistics and machine learning.

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