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Risk and Portfolio Analysis: Principles and Methods (Springer Series in Operations Research and Financial Engineering) (en Inglés)
Henrik Hult; Filip Lindskog; Ola Hammarlid (Autor)
·
Springer
· Tapa Dura
Risk and Portfolio Analysis: Principles and Methods (Springer Series in Operations Research and Financial Engineering) (en Inglés) - Henrik Hult; Filip Lindskog; Ola Hammarlid
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Origen: Reino Unido
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Reseña del libro "Risk and Portfolio Analysis: Principles and Methods (Springer Series in Operations Research and Financial Engineering) (en Inglés)"
Investment and risk management problems are fundamental problems for financial institutions and involve both speculative and hedging decisions. A structured approach to these problems naturally leads one to the field of applied mathematics in order to translate subjective probability beliefs and attitudes towards risk and reward into actual decisions. In Risk and Portfolio Analysis the authors present sound principles and useful methods for making investment and risk management decisions in the presence of hedgeable and non-hedgeable risks using the simplest possible principles, methods, and models that still capture the essential features of the real-world problems. They use rigorous, yet elementary mathematics, avoiding technically advanced approaches which have no clear methodological purpose and are practically irrelevant. The material progresses systematically and topics such as the pricing and hedging of derivative contracts, investment and hedging principles from portfolio theory, and risk measurement and multivariate models from risk management are covered appropriately. The theory is combined with numerous real-world examples that illustrate how the principles, methods, and models can be combined to approach concrete problems and to draw useful conclusions. Exercises are included at the end of the chapters to help reinforce the text and provide insight. This book will serve advanced undergraduate and graduate students, and practitioners in insurance, finance as well as regulators. Prerequisites include undergraduate level courses in linear algebra, analysis, statistics and probability.
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