Risk Analysis In Finance And Insurance Second Edition
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| Author | : Alexander Melnikov |
| Publisher | : CRC Press |
| Total Pages | : 330 |
| Release | : 2011-04-25 |
| Genre | : Mathematics |
| ISBN | : 1420070525 |
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.
| Author | : Alexander Melnikov |
| Publisher | : CRC Press |
| Total Pages | : 267 |
| Release | : 2003-09-25 |
| Genre | : Mathematics |
| ISBN | : 0203498577 |
Historically, financial and insurance risks were separate subjects most often analyzed using qualitative methods. The development of quantitative methods based on stochastic analysis is an important achievement of modern financial mathematics, one that can naturally be extended and applied in actuarial mathematics. Risk Analysis in Finance
| Author | : Tze Leung Lai |
| Publisher | : CRC Press |
| Total Pages | : 1098 |
| Release | : 2024-10-02 |
| Genre | : Business & Economics |
| ISBN | : 1351643258 |
This book presents statistics and data science methods for risk analytics in quantitative finance and insurance. Part I covers the background, financial models, and data analytical methods for market risk, credit risk, and operational risk in financial instruments, as well as models of risk premium and insolvency in insurance contracts. Part II provides an overview of machine learning (including supervised, unsupervised, and reinforcement learning), Monte Carlo simulation, and sequential analysis techniques for risk analytics. In Part III, the book offers a non-technical introduction to four key areas in financial technology: artificial intelligence, blockchain, cloud computing, and big data analytics. Key Features: Provides a comprehensive and in-depth overview of data science methods for financial and insurance risks. Unravels bandits, Markov decision processes, reinforcement learning, and their interconnections. Promotes sequential surveillance and predictive analytics for abrupt changes in risk factors. Introduces the ABCDs of FinTech: Artificial intelligence, blockchain, cloud computing, and big data analytics. Includes supplements and exercises to facilitate deeper comprehension.
| Author | : Baranoff |
| Publisher | : |
| Total Pages | : |
| Release | : 2009 |
| Genre | : Electronic book |
| ISBN | : 9781936126187 |
| Author | : Gregory Connor |
| Publisher | : Princeton University Press |
| Total Pages | : 400 |
| Release | : 2010-03-15 |
| Genre | : Business & Economics |
| ISBN | : 1400835291 |
Portfolio risk forecasting has been and continues to be an active research field for both academics and practitioners. Almost all institutional investment management firms use quantitative models for their portfolio forecasting, and researchers have explored models' econometric foundations, relative performance, and implications for capital market behavior and asset pricing equilibrium. Portfolio Risk Analysis provides an insightful and thorough overview of financial risk modeling, with an emphasis on practical applications, empirical reality, and historical perspective. Beginning with mean-variance analysis and the capital asset pricing model, the authors give a comprehensive and detailed account of factor models, which are the key to successful risk analysis in every economic climate. Topics range from the relative merits of fundamental, statistical, and macroeconomic models, to GARCH and other time series models, to the properties of the VIX volatility index. The book covers both mainstream and alternative asset classes, and includes in-depth treatments of model integration and evaluation. Credit and liquidity risk and the uncertainty of extreme events are examined in an intuitive and rigorous way. An extensive literature review accompanies each topic. The authors complement basic modeling techniques with references to applications, empirical studies, and advanced mathematical texts. This book is essential for financial practitioners, researchers, scholars, and students who want to understand the nature of financial markets or work toward improving them.
| Author | : Donald R. Van Deventer |
| Publisher | : John Wiley & Sons |
| Total Pages | : 834 |
| Release | : 2013-02-06 |
| Genre | : Business & Economics |
| ISBN | : 1118278550 |
Practical tools and advice for managing financial risk, updated for a post-crisis world Advanced Financial Risk Management bridges the gap between the idealized assumptions used for risk valuation and the realities that must be reflected in management actions. It explains, in detailed yet easy-to-understand terms, the analytics of these issues from A to Z, and lays out a comprehensive strategy for risk management measurement, objectives, and hedging techniques that apply to all types of institutions. Written by experienced risk managers, the book covers everything from the basics of present value, forward rates, and interest rate compounding to the wide variety of alternative term structure models. Revised and updated with lessons from the 2007-2010 financial crisis, Advanced Financial Risk Management outlines a framework for fully integrated risk management. Credit risk, market risk, asset and liability management, and performance measurement have historically been thought of as separate disciplines, but recent developments in financial theory and computer science now allow these views of risk to be analyzed on a more integrated basis. The book presents a performance measurement approach that goes far beyond traditional capital allocation techniques to measure risk-adjusted shareholder value creation, and supplements this strategic view of integrated risk with step-by-step tools and techniques for constructing a risk management system that achieves these objectives. Practical tools for managing risk in the financial world Updated to include the most recent events that have influenced risk management Topics covered include the basics of present value, forward rates, and interest rate compounding; American vs. European fixed income options; default probability models; prepayment models; mortality models; and alternatives to the Vasicek model Comprehensive and in-depth, Advanced Financial Risk Management is an essential resource for anyone working in the financial field.
| Author | : Søren Asmussen |
| Publisher | : Springer Nature |
| Total Pages | : 505 |
| Release | : 2020-04-17 |
| Genre | : Mathematics |
| ISBN | : 3030351769 |
This textbook provides a broad overview of the present state of insurance mathematics and some related topics in risk management, financial mathematics and probability. Both non-life and life aspects are covered. The emphasis is on probability and modeling rather than statistics and practical implementation. Aimed at the graduate level, pointing in part to current research topics, it can potentially replace other textbooks on basic non-life insurance mathematics and advanced risk management methods in non-life insurance. Based on chapters selected according to the particular topics in mind, the book may serve as a source for introductory courses to insurance mathematics for non-specialists, advanced courses for actuarial students, or courses on probabilistic aspects of risk. It will also be useful for practitioners and students/researchers in related areas such as finance and statistics who wish to get an overview of the general area of mathematical modeling and analysis in insurance.
| Author | : Roman Marco Hohl |
| Publisher | : John Wiley & Sons |
| Total Pages | : 440 |
| Release | : 2019-03-25 |
| Genre | : Business & Economics |
| ISBN | : 1119345634 |
Gain a holistic view of agricultural (re)insurance and capital market risk transfer Increasing agricultural production and food security remain key challenges for mankind. In order to meet global food demand, the Food and Agriculture Organisation estimates that production has to increase by 50% by 2050 and requires large investments. Agricultural insurance and financial instruments have been an integral part to advancing productivity and are becoming more important in increasingly globalized and specialized agricultural supply chains in the wake of potentially more frequent and severe natural disasters in today’s key producing markets. Underwriting, pricing and transferring agricultural risks is complex and requires a solid understanding of the production system, exposure, perils and the most suitable products, which vastly differ among developed and developing markets. In the last decade, new insurance schemes in emerging agricultural markets have greatly contributed to the large growth of the industry from a premium volume of US$10.1 billion (2006) to US$30.7 billion (2017). This growth is bound to continue as insurance penetration and exposure increase and new schemes are being developed. Agricultural (re)insurance has become a cornerstone of sovereign disaster risk financing frameworks. Agricultural Risk Transfer introduces the main concepts of agricultural (re)insurance and capital market risk transfer that are discussed through industry case studies. It also discusses best industry practices for all main insurance products for crop, livestock, aquaculture and forestry risks including risk assessment, underwriting, pricing, modelling and loss adjustment. Describes agricultural production risks and risk management approaches Covers risk transfer of production and financial risks through insurance and financial instruments Introduces modelling concepts for the main perils and key data sources that support risk transfer through indemnity- and index-based products Describes risk pricing and underwriting approaches for crop, livestock, aquaculture and forestry exposure in developed and developing agricultural systems Become familiar with risk transfer concepts to reinsurance and capital markets Get to know the current market landscape and main risk transfer products for individual producers, agribusinesses and governments through theory and comprehensive industry case studies Through Agricultural Risk Transfer, you’ll gain a holistic view of agricultural (re)insurance and capital market solutions which will support better underwriting, more structured product development and improved risk transfer.
| Author | : Krishnaiyan Thulasiraman |
| Publisher | : CRC Press |
| Total Pages | : 656 |
| Release | : 2015-05-12 |
| Genre | : Mathematics |
| ISBN | : 1482227061 |
The Handbook of Graph Algorithms, Volume II : Applications focuses on a wide range of algorithmic applications, including graph theory problems. The book emphasizes new algorithms and approaches that have been triggered by applications. The approaches discussed require minimal exposure to related technologies in order to understand the material. Each chapter is devoted to a single application area, from VLSI circuits to optical networks to program graphs, and features an introduction by a pioneer researcher in that particular field. The book serves as a single-source reference for graph algorithms and their related applications.
| Author | : Pavel Čižek |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 534 |
| Release | : 2005 |
| Genre | : Business & Economics |
| ISBN | : 9783540221890 |
Statistical Tools in Finance and Insurance presents ready-to-use solutions, theoretical developments and method construction for many practical problems in quantitative finance and insurance. Written by practitioners and leading academics in the field, this book offers a unique combination of topics from which every market analyst and risk manager will benefit. Covering topics such as heavy tailed distributions, implied trinomial trees, support vector machines, valuation of mortgage-backed securities, pricing of CAT bonds, simulation of risk processes and ruin probability approximation, the book does not only offer practitioners insight into new methods for their applications, but it also gives theoreticians insight into the applicability of the stochastic technology. Additionally, the book provides the tools, instruments and (online) algorithms for recent techniques in quantitative finance and modern treatments in insurance calculations. Written in an accessible and engaging style, this self-instructional book makes a good use of extensive examples and full explanations. Thenbsp;design of the text links theory and computational tools in an innovative way. All Quantlets for the calculation of examples given in the text are supported by the academic edition of XploRe and may be executed via XploRe Quantlet Server (XQS). The downloadable electronic edition of the book enables one to run, modify, and enhance all Quantlets on the spot.
