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Risk Analysis in Finance and Insurance 2nd edition [Kietas viršelis]

4.00/5 (2 ratings by Goodreads)
(University of Alberta, Edmonton, Canada)
  • Formatas: Hardback, 328 pages, aukštis x plotis: 234x156 mm, weight: 770 g, 4 Tables, black and white; 9 Illustrations, black and white
  • Išleidimo metai: 25-Apr-2011
  • Leidėjas: Chapman & Hall/CRC
  • ISBN-10: 1420070525
  • ISBN-13: 9781420070521
Kitos knygos pagal šią temą:
Risk Analysis in Finance and Insurance 2nd editionDidesnis paveikslėlis
  • Formatas: Hardback, 328 pages, aukštis x plotis: 234x156 mm, weight: 770 g, 4 Tables, black and white; 9 Illustrations, black and white
  • Išleidimo metai: 25-Apr-2011
  • Leidėjas: Chapman & Hall/CRC
  • ISBN-10: 1420070525
  • ISBN-13: 9781420070521
Kitos knygos pagal šią temą:
Pastovi nuoroda: https://www.kriso.lt/db/9781420070521.html
Raktažodžiai:
Actuarial and financial risks are inherently intertwined, and this book seeks to provide a comprehensive introduction to their approach through quantitative analysis. This new edition includes an expansion of the use of stochastic and probability analysis, along with more coverage of risk-adjusted performance measures and equity-lined insurance. The preface states that it can be used as a textbook at both the undergraduate and graduate levels, as it has been at the University of Alberta, where Melnikov teaches mathematical finance. Annotation ©2011 Book News, Inc., Portland, OR (booknews.com)

Risk Analysis in Finance and Insurance, Second Edition presents an accessible yet comprehensive introduction to the main concepts and methods that transform risk management into a quantitative science. Taking into account the interdisciplinary nature of risk analysis, the author discusses many important ideas from mathematics, finance, and actuarial science in a simplified manner. He explores the interconnections among these disciplines and encourages readers toward further study of the subject. This edition continues to study risks associated with financial and insurance contracts, using an approach that estimates the value of future payments based on current financial, insurance, and other information.

New to the Second Edition

  • Expanded section on the foundations of probability and stochastic analysis
  • Coverage of new topics, including financial markets with stochastic volatility, risk measures, risk-adjusted performance measures, and equity-linked insurance
  • More worked examples and problems

Reorganized and expanded, this updated book illustrates how to use quantitative methods of stochastic analysis in modern financial mathematics. These methods can be naturally extended and applied in actuarial science, thus leading to unified methods of risk analysis and management.

Recenzijos

" 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 2013

Praise 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 Melnikovs covering mathematical approaches to risk analysis in both markets in a consistent manner. Christian Bluhm, Credit Suisse, Zurich, Switzerland

1 Introductory concepts of Financial Risk Management and Related Mathematical Tools
1(32)
1.1 Introductory concepts of the securities market
1(3)
1.2 Probabilistic foundations of financial modeling and pricing of contingent claims
4(8)
1.3 Elements of probability theory and stochastic analysis
12(21)
2 Financial Risk Management in the Binomial Model
33(36)
2.1 The binomial model of a financial market. Absence of arbitrage, uniqueness of a risk-neutral probability measure, martingale representation
33(6)
2.2 Hedging contingent claims in the binomial market model. The Cox-Ross-Rubinstein formula
39(9)
2.3 Pricing and hedging American options
48(4)
2.4 Utility functions and St. Petersburg's paradox. The problem of optimal investment
52(5)
2.5 The term structure of prices, hedging, and investment strategies in the Ho-Lee model
57(6)
2.6 The transition from the binomial model of a financial market to a continuous model. The Black-Scholes formula and equation
63(6)
3 Advanced Analysis of Financial Risks: Discrete Time Models
69(32)
3.1 Fundamental theorems on arbitrage and completeness. Pricing and hedging contingent claims in complete and incomplete markets
69(8)
3.2 The structure of options prices in incomplete markets and in markets with constraints
77(8)
3.3 Hedging contingent claims in mean square
85(6)
3.4 Gaussian model of a financial market in discrete time. Insurance appreciation and discrete version of the Black-Scholes formula
91(10)
4 Analysis of Risks: Continuous Time Models
101(38)
4.1 The Black-Scholes model. "Greek" parameters in risk management, hedging, and optimal investment
101(11)
4.2 Beyond of the Black-Scholes model
112(14)
4.3 Imperfect hedging and risk measures
126(13)
5 Fixed Income Securities: Modeling and Pricing
139(26)
5.1 Elements of deterministic theory of fixed income instruments
139(17)
5.2 Stochastic modeling and pricing bonds and their derivatives
156(9)
6 Implementations of Risk Analysis in Various Areas of Financial Industry
165(24)
6.1 Real options: pricing long-term investment projects
165(8)
6.2 Technical analysis in risk management
173(10)
6.3 Performance measures and their applications
183(6)
7 Insurance and Reinsurance Risks
189(36)
7.1 Modeling risk in insurance and methodologies of premium calculations
189(10)
7.2 Risks transfers via reinsurance
199(9)
7.3 Elements of traditional life insurance
208(7)
7.4 Risk modeling and pricing in innovative life insurance
215(10)
8 Solvency Problem for an Insurance Company: Discrete and Continuous Time Models
225(40)
8.1 Ruin probability as a measure of solvency of an insurance company
225(16)
8.2 Solvency of an insurance company and investment portfolios
241(13)
8.3 Solvency problem in a generalized Cramer-Lundberg model
254(11)
Appendix A Problems
265(34)
A.1 Probability theory and elements of stochastic analysis
265(5)
A.2 General questions on financial markets
270(4)
A.3 Binomial model
274(7)
A.4 The Black-Scholes model
281(3)
A.5 Bond market
284(3)
A.6 Risk and performance measurement
287(6)
A.7 Elements of insurance and actuarial science
293(6)
Appendix B Bibliographic Remarks
299(4)
Bibliography 303(8)
Glossary of Notation 311(2)
Index 313
Alexander Melnikov is a professor in the Department of Mathematical and Statistical Sciences at the University of Alberta. Dr. Melnikovs research interests include mathematical finance and risk management, insurance and actuarial science, statistics and stochastic analysis, and stochastic differential equations and their applications.