Bayesian Risk Management

Author: Matt Sekerke
Publisher: John Wiley & Sons
ISBN: 1118708601
Format: PDF, Mobi
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A risk measurement and management framework that takes model risk seriously Most financial risk models assume the future will look like the past, but effective risk management depends on identifying fundamental changes in the marketplace as they occur. Bayesian Risk Management details a more flexible approach to risk management, and provides tools to measure financial risk in a dynamic market environment. This book opens discussion about uncertainty in model parameters, model specifications, and model–driven forecasts in a way that standard statistical risk measurement does not. And unlike current machine learning–based methods, the framework presented here allows you to measure risk in a fully–Bayesian setting without losing the structure afforded by parametric risk and asset–pricing models. Recognize the assumptions embodied in classical statistics Quantify model risk along multiple dimensions without backtesting Model time series without assuming stationarity Estimate state–space time series models online with simulation methods Uncover uncertainty in workhorse risk and asset–pricing models Embed Bayesian thinking about risk within a complex organization Ignoring uncertainty in risk modeling creates an illusion of mastery and fosters erroneous decision–making. Firms who ignore the many dimensions of model risk measure too little risk, and end up taking on too much. Bayesian Risk Management provides a roadmap to better risk management through more circumspect measurement, with comprehensive treatment of model uncertainty.

Optimal Financial Decision Making under Uncertainty

Author: Giorgio Consigli
Publisher: Springer
ISBN: 3319416138
Format: PDF, Mobi
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The scope of this volume is primarily to analyze from different methodological perspectives similar valuation and optimization problems arising in financial applications, aimed at facilitating a theoretical and computational integration between methods largely regarded as alternatives. Increasingly in recent years, financial management problems such as strategic asset allocation, asset-liability management, as well as asset pricing problems, have been presented in the literature adopting formulation and solution approaches rooted in stochastic programming, robust optimization, stochastic dynamic programming (including approximate SDP) methods, as well as policy rule optimization, heuristic approaches and others. The aim of the volume is to facilitate the comprehension of the modeling and methodological potentials of those methods, thus their common assumptions and peculiarities, relying on similar financial problems. The volume will address different valuation problems common in finance related to: asset pricing, optimal portfolio management, risk measurement, risk control and asset-liability management. The volume features chapters of theoretical and practical relevance clarifying recent advances in the associated applied field from different standpoints, relying on similar valuation problems and, as mentioned, facilitating a mutual and beneficial methodological and theoretical knowledge transfer. The distinctive aspects of the volume can be summarized as follows: Strong benchmarking philosophy, with contributors explicitly asked to underline current limits and desirable developments in their areas. Theoretical contributions, aimed at advancing the state-of-the-art in the given domain with a clear potential for applications The inclusion of an algorithmic-computational discussion of issues arising on similar valuation problems across different methods. Variety of applications: rarely is it possible within a single volume to consider and analyze different, and possibly competing, alternative optimization techniques applied to well-identified financial valuation problems. Clear definition of the current state-of-the-art in each methodological and applied area to facilitate future research directions.

Coherent Stress Testing

Author: Riccardo Rebonato
Publisher: John Wiley & Sons
ISBN: 0470971487
Format: PDF, Mobi
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In Coherent Stress Testing: A Bayesian Approach, industry expert Riccardo Rebonato presents a groundbreaking new approach to this important but often undervalued part of the risk management toolkit. Based on the author's extensive work, research and presentations in the area, the book fills a gap in quantitative risk management by introducing a new and very intuitively appealing approach to stress testing based on expert judgement and Bayesian networks. It constitutes a radical departure from the traditional statistical methodologies based on Economic Capital or Extreme-Value-Theory approaches. The book is split into four parts. Part I looks at stress testing and at its role in modern risk management. It discusses the distinctions between risk and uncertainty, the different types of probability that are used in risk management today and for which tasks they are best used. Stress testing is positioned as a bridge between the statistical areas where VaR can be effective and the domain of total Keynesian uncertainty. Part II lays down the quantitative foundations for the concepts described in the rest of the book. Part III takes readers through the application of the tools discussed in part II, and introduces two different systematic approaches to obtaining a coherent stress testing output that can satisfy the needs of industry users and regulators. In part IV the author addresses more practical questions such as embedding the suggestions of the book into a viable governance structure.

Statistical Models and Methods for Financial Markets

Author: Tze Leung Lai
Publisher: Springer Science & Business Media
ISBN: 0387778276
Format: PDF, Mobi
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The idea of writing this bookarosein 2000when the ?rst author wasassigned to teach the required course STATS 240 (Statistical Methods in Finance) in the new M. S. program in ?nancial mathematics at Stanford, which is an interdisciplinary program that aims to provide a master’s-level education in applied mathematics, statistics, computing, ?nance, and economics. Students in the programhad di?erent backgroundsin statistics. Some had only taken a basic course in statistical inference, while others had taken a broad spectrum of M. S. - and Ph. D. -level statistics courses. On the other hand, all of them had already taken required core courses in investment theory and derivative pricing, and STATS 240 was supposed to link the theory and pricing formulas to real-world data and pricing or investment strategies. Besides students in theprogram,thecoursealso attractedmanystudentsfromother departments in the university, further increasing the heterogeneity of students, as many of them had a strong background in mathematical and statistical modeling from the mathematical, physical, and engineering sciences but no previous experience in ?nance. To address the diversity in background but common strong interest in the subject and in a potential career as a “quant” in the ?nancialindustry,thecoursematerialwascarefullychosennotonlytopresent basic statistical methods of importance to quantitative ?nance but also to summarize domain knowledge in ?nance and show how it can be combined with statistical modeling in ?nancial analysis and decision making. The course material evolved over the years, especially after the second author helped as the head TA during the years 2004 and 2005.

Fundamental Aspects of Operational Risk and Insurance Analytics

Author: Marcelo G. Cruz
Publisher: John Wiley & Sons
ISBN: 1118573005
Format: PDF, Docs
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A one-stop guide for the theories, applications, and statistical methodologies essential to operational risk Providing a complete overview of operational risk modeling and relevant insurance analytics, Fundamental Aspects of Operational Risk and Insurance Analytics: A Handbook of Operational Risk offers a systematic approach that covers the wide range of topics in this area. Written by a team of leading experts in the field, the handbook presents detailed coverage of the theories, applications, and models inherent in any discussion of the fundamentals of operational risk, with a primary focus on Basel II/III regulation, modeling dependence, estimation of risk models, and modeling the data elements. Fundamental Aspects of Operational Risk and Insurance Analytics: A Handbook of Operational Risk begins with coverage on the four data elements used in operational risk framework as well as processing risk taxonomy. The book then goes further in-depth into the key topics in operational risk measurement and insurance, for example diverse methods to estimate frequency and severity models. Finally, the book ends with sections on specific topics, such as scenario analysis; multifactor modeling; and dependence modeling. A unique companion with Advances in Heavy Tailed Risk Modeling: A Handbook of Operational Risk, the handbook also features: Discussions on internal loss data and key risk indicators, which are both fundamental for developing a risk-sensitive framework Guidelines for how operational risk can be inserted into a firm’s strategic decisions A model for stress tests of operational risk under the United States Comprehensive Capital Analysis and Review (CCAR) program A valuable reference for financial engineers, quantitative analysts, risk managers, and large-scale consultancy groups advising banks on their internal systems, the handbook is also useful for academics teaching postgraduate courses on the methodology of operational risk.

Risk Modeling Assessment and Management

Author: Yacov Y. Haimes
Publisher: John Wiley & Sons
ISBN: 1119017998
Format: PDF, Mobi
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Presents systems-based theory, methodology, and applications in risk modeling, assessment, and management This book examines risk analysis, focusing on quantifying risk and constructing probabilities for real-world decision-making, including engineering, design, technology, institutions, organizations, and policy. The author presents fundamental concepts (hierarchical holographic modeling; state space; decision analysis; multi-objective trade-off analysis) as well as advanced material (extreme events and the partitioned multi-objective risk method; multi-objective decision trees; multi-objective risk impact analysis method; guiding principles in risk analysis); avoids higher mathematics whenever possible; and reinforces the material with examples and case studies. The book will be used in systems engineering, enterprise risk management, engineering management, industrial engineering, civil engineering, and operations research. The fourth edition of Risk Modeling, Assessment, and Management features: Expanded chapters on systems-based guiding principles for risk modeling, planning, assessment, management, and communication; modeling interdependent and interconnected complex systems of systems with phantom system models; and hierarchical holographic modeling An expanded appendix including a Bayesian analysis for the prediction of chemical carcinogenicity, and the Farmer’s Dilemma formulated and solved using a deterministic linear model Updated case studies including a new case study on sequential Pareto-optimal decisions for emergent complex systems of systems A new companion website with over 200 solved exercises that feature risk analysis theories, methodologies, and application Risk Modeling, Assessment, and Management, Fourth Edition, is written for both undergraduate and graduate students in systems engineering and systems management courses. The text also serves as a resource for academic, industry, and government professionals in the fields of homeland and cyber security, healthcare, physical infrastructure systems, engineering, business, and more.

Statistical Arbitrage

Author: Andrew Pole
Publisher: John Wiley & Sons
ISBN: 1118160738
Format: PDF, ePub, Mobi
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While statistical arbitrage has faced some tough times?as markets experienced dramatic changes in dynamics beginning in 2000?new developments in algorithmic trading have allowed it to rise from the ashes of that fire. Based on the results of author Andrew Pole?s own research and experience running a statistical arbitrage hedge fund for eight years?in partnership with a group whose own history stretches back to the dawn of what was first called pairs trading?this unique guide provides detailed insights into the nuances of a proven investment strategy. Filled with in-depth insights and expert advice, Statistical Arbitrage contains comprehensive analysis that will appeal to both investors looking for an overview of this discipline, as well as quants looking for critical insights into modeling, risk management, and implementation of the strategy.

Investment Theory and Risk Management Website

Author: Steven Peterson
Publisher: John Wiley & Sons
ISBN: 1118129598
Format: PDF, Mobi
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A unique perspective on applied investment theory and risk management from the Senior Risk Officer of a major pension fund Investment Theory and Risk Management is a practical guide to today′s investment environment. The book′s sophisticated quantitative methods are examined by an author who uses these methods at the Virginia Retirement System and teaches them at the Virginia Commonwealth University. In addition to showing how investment performance can be evaluated, using Jensen′s Alpha, Sharpe′s Ratio, and DDM, he delves into four types of optimal portfolios (one that is fully invested, one with targeted returns, another with no short sales, and one with capped investment allocations). In addition, the book provides valuable insights on risk, and topics such as anomalies, factor models, and active portfolio management. Other chapters focus on private equity, structured credit, optimal rebalancing, data problems, and Monte Carlo simulation. Contains investment theory and risk management spreadsheet models based on the author′s own real–world experience with stock, bonds, and alternative assets Offers a down–to–earth guide that can be used on a daily basis for making common financial decisions with a new level of quantitative sophistication and rigor Written by the Director of Research and Senior Risk Officer for the Virginia Retirement System and an Associate Professor at Virginia Commonwealth University′s School of Business Investment Theory and Risk Management empowers both the technical and non–technical reader with the essential knowledge necessary to understand and manage risks in any corporate or economic environment.

Risk Wise

Author: Polly Morland
Publisher: Profile Books
ISBN: 1782831568
Format: PDF, Kindle
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Risk often gets a bad press. From the seemingly unnecessary actions of extreme sportspeople to the excessive risk appetites of serial entrepreneurs, the term 'risky' is often seen as synonymous with 'reckless', 'foolhardy' or even downright dangerous. But could any of us live in a world without risk, and would it be desirable to do so? Through a series of nine wonderfully rich pen portraits, Polly Morland takes us on a journey through the world of risk, looking not at the extremes or exceptions, but at the routine risks we accept and embrace as part of our everyday lives, often unconsciously. Meet the families who have lived happily on the slopes of Mount Vesuvius for generations; the Paris Opera ballet dancer facing up to the physical, psychological and reputational risks her profession demands; the New York City forensic engineer for whom being first on the scene is just part of the day job. And marvel at the parents and playworkers who every day balance the risks and rewards of how much autonomy and independence to afford growing children. The stories in Risk Wise address fundamental questions about risk and our perceptions about risk-taking. It argues that being risk wise - the ability to understand and accept risk as a force for good - is an essential part of the human experience and a route to living a full and rewarding life.

Risk Modeling for Appraising Named Peril Index Insurance Products

Author: Shadreck Mapfumo
Publisher: World Bank Publications
ISBN: 1464810494
Format: PDF
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Named peril index insurance has great potential to address unmet risk management needs for agricultural insurance in developing economies, potentially contributing to increased agricultural sustainability and improved food security. However, the development and appraisal of index insurance business lines is not without challenges. Insurers must rigorously evaluate the quality of the products they offer and take care to ensure that distributors and policyholders understand the benefits and limits of the purchased coverage. Without these important steps to ensure responsible insurance practices, insurers can damage the implementation and potential of index insurance in the market. Risk Modeling for Appraising Named Peril Index Insurance Products: A Guide for Practitioners helps stakeholders in the named peril index insurance industry appraise new and existing products. Part 1 of the guide provides a summary of the insights and decisions required for the insurer to make an informed decision to launch and expand an index insurance business line. Insurance managers are the primary audience for part 1. Part 2 provides a step-by-step guide to calculating the decision metrics used by the insurance manager in part 1. These metrics are calculated using probabilistic modeling that provides insights into risks related to the index insurance product. Actuarial analysts are the primary audience for part 2. In an increasingly competitive insurance market, creative product development and imaginative business strategies are becoming the norm. This guide will help emerging market insurers who seek to stay on the cutting edge to successfully and sustainably penetrate new market segments.