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Zusatztext "? a well-chosen collection of topics from risk analysis and management for finance and actuarial science illustrated with solved problems."-Christel Geiss! Mathematical Reviews! November 2013Praise for the First Edition: ? a useful addition to a rapidly expanding field. -Journal of the Royal Statistical Society Here is a comprehensive and accessible introduction to the ideas! methods and probabilistic models that have transformed risk management into a quantitative science and [have] led to unified methods for analyzing insurance and finance risk. -Business Horizons Risk Analysis in Finance and Insurance is a self-contained and highly comprehensive introduction to mathematical finance and its interplay with insurance risk analysis. Students will like the book due to the many worked-out examples deepening the understanding of the theory. A special and probably unique feature of the book is its unified approach to financial and insurance risks. As a consequence of the convergence of financial and insurance markets! practitioners in financial institutions will have great benefit from books like Melnikov's covering mathematical approaches to risk analysis in both markets in a consistent manner. -Christian Bluhm! Credit Suisse! Zurich! Switzerland Informationen zum Autor Alexander Melnikov is a professor in the Department of Mathematical and Statistical Sciences at the University of Alberta. Dr. Melnikov’s research interests include mathematical finance and risk management, insurance and actuarial science, statistics and stochastic analysis, and stochastic differential equations and their applications. Klappentext The development of quantitative methods based on stochastic analysis is a key achievement of modern financial mathematics. This book presents an introduction to the main ideas! methods! and techniques that transform risk management into a quantitative science. Zusammenfassung The development of quantitative methods based on stochastic analysis is a key achievement of modern financial mathematics. This book presents an introduction to the main ideas, methods, and techniques that transform risk management into a quantitative science. Inhaltsverzeichnis Financial Risk Management and Related Mathematical Tools Introductory concepts of the securities market Probabilistic foundations of financial modelling and pricing of contingent claims Elements of probability theory and stochastic analysis Financial Risk Management in the Binomial Model The binomial model of a financial market. Absence of arbitrage! uniqueness of a risk-neutral probability measure! martingale representation Hedging contingent claims in the binomial market model. The Cox-Ross-Rubinstein formula Pricing and hedging American options Utility functions and St. Petersburg's paradox. The problem of optimal investmentThe term structure of prices! hedging and investment strategies in the Ho-Lee model The transition from the binomial model of a financial market to a continuous model. The Black-Scholes formula and equationAdvanced Analysis of Financial Risks: Discrete Time Models Fundamental theorems on arbitrage and completeness. Pricing and hedging contingent claims in complete and incomplete marketsThe structure of options prices in incomplete markets and in markets with constraintsHedging contingent claims in mean square Gaussian model of a financial market in discrete time. Insurance appreciation and discrete version of the Black-Scholes formulaAnalysis of Risks: Continuous Time Models The Black-Scholes model. "Greek" parameters in risk management! hedging and optimal investmentBeyond the Black-Scholes model Imperfect hedging and risk measuresFixed Income Securities: Modeling and PricingElements of deterministic theory of fixed income instruments Stochastic modelling and pricing bonds and their derivatives Implementations of Risk Analysis in Various Area...
