{"product_id":"quantitative-financial-risk-management-isbn-9781118738184","title":"Quantitative Financial Risk Management","description":"\u003cp\u003e\u003cb\u003eA Comprehensive Guide to Quantitative Financial Risk Management\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eWritten by an international team of experts in the field, \u003ci\u003eQuantitative Financial Risk Management: Theory and Practice\u003c\/i\u003e provides an invaluable guide to the most recent and innovative research on the topics of financial risk management, portfolio management, credit risk modeling, and worldwide financial markets.\u003c\/p\u003e \u003cp\u003eThis comprehensive text reviews the tools and concepts of financial management that draw on the practices of economics, accounting, statistics, econometrics, mathematics, stochastic processes, and computer science and technology. Using the information found in \u003ci\u003eQuantitative Financial Risk Management\u003c\/i\u003e can help professionals to better manage, monitor, and measure risk, especially in today's uncertain world of globalization, market volatility, and geo-political crisis.\u003c\/p\u003e \u003cp\u003e\u003ci\u003eQuantitative Financial Risk Management\u003c\/i\u003e delivers the information, tools, techniques, and most current research in the critical field of risk management. This text offers an essential guide for quantitative analysts, financial professionals, and academic scholars.\u003c\/p\u003e \u003cp\u003ePreface xvii\u003c\/p\u003e \u003cp\u003eAbout the Editors xix\u003c\/p\u003e \u003cp\u003e\u003cb\u003eSection One Supervisory Risk Management\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 1 Measuring Systemic Risk: Structural Approaches 3\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eRaimund M. Kovacevic and Georg Ch. Pflug\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eSystemic Risk: Definitions 4\u003c\/p\u003e \u003cp\u003eFrom Structural Models to Systemic Risk 6\u003c\/p\u003e \u003cp\u003eMeasuring Systemic Risk 10\u003c\/p\u003e \u003cp\u003eSystemic Risk and Copula Models 15\u003c\/p\u003e \u003cp\u003eConclusions 20\u003c\/p\u003e \u003cp\u003eReferences 20\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 2 Supervisory Requirements and Expectations for Portfolio-Level Counterparty Credit Risk Measurement and Management 22\u003c\/b\u003e\u003cbr\u003e \u003ci\u003eMichael Jacobs Jr., PhD, CFA\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eIntroduction 22\u003c\/p\u003e \u003cp\u003eReview of the Literature 25\u003c\/p\u003e \u003cp\u003eSupervisory Requirements for CCR 26\u003c\/p\u003e \u003cp\u003eConceptual Issues in CCR: Risk versus Uncertainty 41\u003c\/p\u003e \u003cp\u003eConclusions 44\u003c\/p\u003e \u003cp\u003eReferences 44\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 3 Nonperforming Loans in the Bank Production Technology 46\u003c\/b\u003e\u003cbr\u003e \u003ci\u003eHirofumi Fukuyama and William L. Weber\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eIntroduction 46\u003c\/p\u003e \u003cp\u003eSelective Literature Review 47\u003c\/p\u003e \u003cp\u003eMethod 51\u003c\/p\u003e \u003cp\u003eEmpirical Application 57\u003c\/p\u003e \u003cp\u003eSummary and Conclusion 65\u003c\/p\u003e \u003cp\u003eAppendix 3.1 Bank Names and Type 66\u003c\/p\u003e \u003cp\u003eReferences 67\u003c\/p\u003e \u003cp\u003e\u003cb\u003eSection Two Risk Models and Measures\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 4 A Practical Guide to Regime Switching in Financial Economics 73\u003c\/b\u003e\u003cbr\u003e \u003ci\u003eIain Clacher, Mark Freeman, David Hillier, Malcolm Kemp and Qi Zhang\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eA Brief Look at Markov Regime Switching in Academic Economics and Finance 74\u003c\/p\u003e \u003cp\u003eRegime Switching and Interest Rate Processes 75\u003c\/p\u003e \u003cp\u003eRegime Switching and Exchange Rates 76\u003c\/p\u003e \u003cp\u003eRegime Switching, Stock Returns, and Asset Allocation 77\u003c\/p\u003e \u003cp\u003eSingle-Asset Markov Models 79\u003c\/p\u003e \u003cp\u003eTwo-State Estimation 82\u003c\/p\u003e \u003cp\u003eThree-State Estimation 84\u003c\/p\u003e \u003cp\u003eMarkov Models for Multiple Assets 85\u003c\/p\u003e \u003cp\u003ePractical Application of Regime Switching Models for Investment Purposes 87\u003c\/p\u003e \u003cp\u003eIntuitive Appeal of Such Models 87\u003c\/p\u003e \u003cp\u003eImplementation Challenges 89\u003c\/p\u003e \u003cp\u003eSelecting the “Right\" Model Structure 89\u003c\/p\u003e \u003cp\u003eCalibrating the Selected Model Type to Suitable Data 90\u003c\/p\u003e \u003cp\u003eDrawing the Right Conclusions from the Model 93\u003c\/p\u003e \u003cp\u003eReferences 95\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 5 Output Analysis and Stress Testing for Risk Constrained Portfolios 98\u003c\/b\u003e\u003cbr\u003e \u003ci\u003eJitka Dupačová and Miloš Kopa\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eIntroduction 98\u003c\/p\u003e \u003cp\u003eWorst-Case Analysis 107\u003c\/p\u003e \u003cp\u003eStress Testing via Contamination 110\u003c\/p\u003e \u003cp\u003eConclusions and New Problems 122\u003c\/p\u003e \u003cp\u003eReferences 122\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 6 Risk Measures and Management in the Energy Sector 126\u003c\/b\u003e\u003cbr\u003e \u003ci\u003eMarida Bertocchi, Rosella Giacometti and Maria Teresa Vespucci\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eIntroduction 126\u003c\/p\u003e \u003cp\u003eUncertainty Characterization via Scenarios 128\u003c\/p\u003e \u003cp\u003eMeasures of Risks 132\u003c\/p\u003e \u003cp\u003eCase Studies 137\u003c\/p\u003e \u003cp\u003eSummary 147\u003c\/p\u003e \u003cp\u003eReferences 147\u003c\/p\u003e \u003cp\u003e\u003cb\u003eSection Three Portfolio Management\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 7 Portfolio Optimization: Theory and Practice 155\u003c\/b\u003e\u003cbr\u003e \u003ci\u003eWilliam T. Ziemba\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eStatic Portfolio Theory 155\u003c\/p\u003e \u003cp\u003eImportance of Means 163\u003c\/p\u003e \u003cp\u003eStochastic Programming Approach to Asset Liability Management 167\u003c\/p\u003e \u003cp\u003eSiemens InnoALM Pension Fund Model 182\u003c\/p\u003e \u003cp\u003eDynamic Portfolio Theory and Practice: The Kelly Capital Growth Approach 194\u003c\/p\u003e \u003cp\u003eTransactions Costs 199\u003c\/p\u003e \u003cp\u003eSome Great Investors 201\u003c\/p\u003e \u003cp\u003eAppendix 7.1: Estimating Utility Functions and Risk Aversion 206\u003c\/p\u003e \u003cp\u003eReferences 208\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 8 Portfolio Optimization and Transaction Costs 212\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eRenata Mansini, Wlodzimierz Ogryczak and M. Grazia Speranza\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eIntroduction 212\u003c\/p\u003e \u003cp\u003eLiterature Review on Transaction Costs 215\u003c\/p\u003e \u003cp\u003eAn LP Computable Risk Measure: The Semi-MAD 221\u003c\/p\u003e \u003cp\u003eModeling Transaction Costs 223\u003c\/p\u003e \u003cp\u003eNon-Unique Minimum Risk Portfolio 232\u003c\/p\u003e \u003cp\u003eExperimental Analysis 234\u003c\/p\u003e \u003cp\u003eConclusions 237\u003c\/p\u003e \u003cp\u003eAppendix 238\u003c\/p\u003e \u003cp\u003eReferences 239\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 9 Statistical Properties and Tests of Efficient Frontier Portfolios 242\u003c\/b\u003e\u003cbr\u003e \u003ci\u003ec J Adcock\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eIntroduction 242\u003c\/p\u003e \u003cp\u003eNotation and Setup 245\u003c\/p\u003e \u003cp\u003eDistribution of Portfolio Weights 247\u003c\/p\u003e \u003cp\u003eEmpirical Study 255\u003c\/p\u003e \u003cp\u003eDiscussion and Concluding Remarks 267\u003c\/p\u003e \u003cp\u003eReferences 268\u003c\/p\u003e \u003cp\u003e\u003cb\u003eSection Four Credit Risk Modelling\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 10 Stress Testing for Portfolio Credit Risk: Supervisory Expectations and Practices 273\u003c\/b\u003e\u003cbr\u003e \u003ci\u003eMichael Jacobs Jr.\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eIntroduction and Motivation 273\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eConceptual Issues in Stress Testing: Risk versus Uncertainty 276\u003c\/p\u003e \u003cp\u003eThe Function of Stress Testing 277\u003c\/p\u003e \u003cp\u003eSupervisory Requirements and Expectations 280\u003c\/p\u003e \u003cp\u003eEmpirical Methodology: A Simple ST Example 281\u003c\/p\u003e \u003cp\u003eConclusion and Future Directions 291\u003c\/p\u003e \u003cp\u003eReferences 293\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 11 A Critique of Credit Risk Models with Evidence from Mid-Cap Firms 296\u003c\/b\u003e\u003cbr\u003e \u003ci\u003eDavid E. Allen, Robert J. Powell and Abhay K. Singh\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eIntroduction 296\u003c\/p\u003e \u003cp\u003eSummary of Credit Model Methodologies 297\u003c\/p\u003e \u003cp\u003eOur Empirical Methodology 302\u003cbr\u003e Critique 303\u003c\/p\u003e \u003cp\u003eConclusions 310\u003c\/p\u003e \u003cp\u003eReferences 310\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 12 Predicting Credit Ratings Using a Robust Multicriteria Approach 312\u003c\/b\u003e\u003cbr\u003e \u003ci\u003eConstantin Zopounidis\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eIntroduction 312\u003c\/p\u003e \u003cp\u003eCredit Scoring and Rating 315\u003c\/p\u003e \u003cp\u003eMulticriteria Methodology 319\u003c\/p\u003e \u003cp\u003eEmpirical Analysis 325\u003c\/p\u003e \u003cp\u003eConclusions and Future Perspectives 330\u003c\/p\u003e \u003cp\u003eReferences 331\u003c\/p\u003e \u003cp\u003e\u003cb\u003eSection Five Financial Markets\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 13 Parameter Analysis of the VPIN (Volume-Synchronized Probability of Informed Trading) Metric 337\u003c\/b\u003e\u003cbr\u003e \u003ci\u003eJung Heon Song, Kesheng Wu and Horst D. Simon\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eIntroduction 337\u003c\/p\u003e \u003cp\u003eDefinition of VPIN 341\u003c\/p\u003e \u003cp\u003eComputational Cost 346\u003c\/p\u003e \u003cp\u003eOptimization of FPR 348\u003c\/p\u003e \u003cp\u003eUncertainty Quantification (UQ) 353\u003c\/p\u003e \u003cp\u003eConclusion 360\u003c\/p\u003e \u003cp\u003eReferences 362\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 14 Covariance Specification Tests for Multivariate GARCH Models 364\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eGregory Koutmos\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eIntroduction 364\u003c\/p\u003e \u003cp\u003eCovariance Specification Tests 365\u003c\/p\u003e \u003cp\u003eApplication of Covariance Specification Tests 367\u003c\/p\u003e \u003cp\u003eEmpirical Findings and Discussion 368\u003c\/p\u003e \u003cp\u003eConclusion 370\u003c\/p\u003e \u003cp\u003eReferences 370\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 15 Accounting Information in the Prediction of Securities Class Actions 372\u003c\/b\u003e\u003cbr\u003e \u003ci\u003eVassiliki Balla\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eIntroduction 372\u003c\/p\u003e \u003cp\u003eLiterature Review 375\u003c\/p\u003e \u003cp\u003eMethodology 376\u003c\/p\u003e \u003cp\u003eData 378\u003c\/p\u003e \u003cp\u003eResults 387\u003c\/p\u003e \u003cp\u003eConclusions 394\u003c\/p\u003e \u003cp\u003eReferences 395\u003c\/p\u003e \u003cp\u003eAbout the Contributors 399\u003c\/p\u003e \u003cp\u003eGlossary 413\u003c\/p\u003e \u003cp\u003eIndex 421\u003c\/p\u003e  \u003cp\u003e\u003cb\u003eCONSTANTIN ZOPOUNIDIS, P\u003csmall\u003eH\u003c\/small\u003eD,\u003c\/b\u003e is professor of Financial Engineering and Operations Research at Technical University of Crete in Greece and distinguished research professor at Audencia Nantes School of Management in France. \u003c\/p\u003e\u003cp\u003e\u003cb\u003eEMILIOS GALARIOTIS, P\u003csmall\u003eH\u003c\/small\u003eD (Dunelm), HDR,\u003c\/b\u003e is professor of Finance at Audencia Nantes School of Management in France. He is the founder and director of the Centre for Financial and Risk Management and head of research in the area of finance, risk, and accounting performance at Audencia. He is also joint-Head of the Accounting and Finance Department.    \u003c\/p\u003e\u003cp\u003eThe recent financial crisis is considered the worst since the Great Depression of the 1930s. This disastrous economic crisis caused a domino effect that saw the collapse of large financial institutions, bailouts of banks by governments, declines in stock markets, and a worldwide global recession. This negative experience demonstrates that the economy as a whole, but especially the financial sector, is subject to new and evolving risks.  \u003c\/p\u003e\u003cp\u003e\u003ci\u003eQuantitative Financial Risk Management: Theory and Practice\u003c\/i\u003e offers professionals in the field an invaluable guide to the most current and useful tools of financial management that can be applied to manage, monitor, and measure risk. This guide is especially valuable to help mitigate risk in the context of globalization, market volatility, and economic crisis. With contributions from a team of international experts, this vital resource is comprehensive in scope and includes examinations of financial risk management, risk models, portfolio management, credit risk modeling, and a review of international financial markets.\u003c\/p\u003e\u003cp\u003e  \u003c\/p\u003e\u003cp\u003eThe contributors demonstrate innovative research in the areas of theoretical and empirical analyses, methodologies, and applications of quantitative financial risk management. This volume covers a broad range of topics; for example, it contains information on the measurement of systemic risk, based on the structural approach originating from structural credit risk models. The text explores the most important notions of risk in the energy sector and describes how to cope with these uncertainties with two main tools: construction of scenarios and stochastic programming modeling. It offers a simple and practical stress-testing example that includes a ratings migration matrixbase for determining portfolio credit risk.  \u003c\/p\u003e\u003cp\u003e\u003ci\u003eQuantitative Financial Risk Management\u003c\/i\u003e goes a long way toward advancing the knowledge related to risk management and portfolio optimization, and generates theoretical knowledge with the aim of promoting research within various sectors where financial markets operate.     \u003c\/p\u003e\u003cp\u003e\u003cb\u003eA Comprehensive Guide to Quantitative Financial Risk Management\u003c\/b\u003e  \u003c\/p\u003e\u003cp\u003eWritten by an international team of experts in the field, \u003ci\u003eQuantitative Financial Risk Management: Theory and Practice\u003c\/i\u003e provides an invaluable guide to the most recent and innovative research on the topics of financial risk management, portfolio management, credit risk modeling, and worldwide financial markets.  \u003c\/p\u003e\u003cp\u003eThis comprehensive text reviews the tools and concepts of financial management that draw on the practices of economics, accounting, statistics, econometrics, mathematics, stochastic processes, and computer science and technology. Using the information found in \u003ci\u003eQuantitative Financial Risk Management\u003c\/i\u003e can help professionals to better manage, monitor, and measure risk, especially in today's uncertain world of globalization, market volatility, and geo-political crisis.  \u003c\/p\u003e\u003cp\u003e\u003ci\u003eQuantitative Financial Risk Management\u003c\/i\u003e delivers the information, tools, techniques, and most current research in the critical field of risk management. This text offers an essential guide for quantitative analysts, financial professionals, and academic scholars.\u003c\/p\u003e","brand":"Wiley","offers":[{"title":"Default Title","offer_id":47989895823589,"sku":"NP9781118738184","price":125.0,"currency_code":"USD","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/1842\/7735\/files\/9781118738184.jpg?v=1761785828","url":"https:\/\/k12savings.com\/products\/quantitative-financial-risk-management-isbn-9781118738184","provider":"K12savings","version":"1.0","type":"link"}