{"product_id":"business-risk-management-isbn-9781118349465","title":"Business Risk Management","description":"\u003cp\u003e\u003cb\u003eA comprehensive and accessible introduction to modern quantitative risk management\u003c\/b\u003e.\u003c\/p\u003e \u003cp\u003eThe business world is rife with risk and uncertainty, and risk management is a vitally important topic for managers. The best way to achieve a clear understanding of risk is to use quantitative tools and probability models.  Written for students, this book has a quantitative emphasis but is accessible to those without a strong mathematical background.\u003c\/p\u003e \u003cp\u003e\u003ci\u003eBusiness Risk Management: Models and Analysis\u003c\/i\u003e\u003c\/p\u003e \u003cul\u003e \u003cli\u003eDiscusses novel modern approaches to risk management\u003c\/li\u003e \u003cli\u003eIntroduces advanced topics in an accessible manner\u003c\/li\u003e \u003cli\u003eIncludes motivating worked examples and exercises (including selected solutions)\u003c\/li\u003e \u003cli\u003eIs written with the student in mind, and does not assume advanced mathematics\u003c\/li\u003e \u003cli\u003eIs suitable for self-study by the manager who wishes to better understand this important field. \u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003eAimed at postgraduate students, this book is also suitable for senior undergraduates, MBA students, and all those who have a general interest in business risk.  \u003c\/p\u003e \u003cp\u003ePreface xiii\u003c\/p\u003e \u003cp\u003e\u003cb\u003e1 What is risk management? 1\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e1.1 Introduction 2\u003c\/p\u003e \u003cp\u003e1.2 Identifying and documenting risk 5\u003c\/p\u003e \u003cp\u003e1.3 Fallacies and traps in risk management 7\u003c\/p\u003e \u003cp\u003e1.4 Why safety is different 9\u003c\/p\u003e \u003cp\u003e1.5 The Basel framework 11\u003c\/p\u003e \u003cp\u003e1.6 Hold or hedge? 12\u003c\/p\u003e \u003cp\u003e1.7 Learning from a disaster 13\u003c\/p\u003e \u003cp\u003e1.7.1 What went wrong? 15\u003c\/p\u003e \u003cp\u003eNotes 17\u003c\/p\u003e \u003cp\u003eReferences 18\u003c\/p\u003e \u003cp\u003eExercises 19\u003c\/p\u003e \u003cp\u003e\u003cb\u003e2 The structure of risk 22\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e2.1 Introduction to probability and risk 23\u003c\/p\u003e \u003cp\u003e2.2 The structure of risk 25\u003c\/p\u003e \u003cp\u003e2.2.1 Intersection and union risk 25\u003c\/p\u003e \u003cp\u003e2.2.2 Maximum of random variables 28\u003c\/p\u003e \u003cp\u003e2.3 Portfolios and diversification 30\u003c\/p\u003e \u003cp\u003e2.3.1 Adding random variables 30\u003c\/p\u003e \u003cp\u003e2.3.2 Portfolios with minimum variance 33\u003c\/p\u003e \u003cp\u003e2.3.3 Optimal portfolio theory 37\u003c\/p\u003e \u003cp\u003e2.3.4 When risk follows a normal distribution 38\u003c\/p\u003e \u003cp\u003e2.4 The impact of correlation 40\u003c\/p\u003e \u003cp\u003e2.4.1 Using covariance in combining random variables 41\u003c\/p\u003e \u003cp\u003e2.4.2 Minimum variance portfolio with covariance 43\u003c\/p\u003e \u003cp\u003e2.4.3 The maximum of variables that are positively correlated 44\u003c\/p\u003e \u003cp\u003e2.4.4 Multivariate normal 46\u003c\/p\u003e \u003cp\u003e2.5 Using copulas to model multivariate distributions 49\u003c\/p\u003e \u003cp\u003e2.5.1 *Details on copula modeling 52\u003c\/p\u003e \u003cp\u003eNotes 58\u003c\/p\u003e \u003cp\u003eReferences 59\u003c\/p\u003e \u003cp\u003eExercises 60\u003c\/p\u003e \u003cp\u003e\u003cb\u003e3 Measuring risk 63\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e3.1 How can we measure risk? 64\u003c\/p\u003e \u003cp\u003e3.2 Value at risk 67\u003c\/p\u003e \u003cp\u003e3.3 Combining and comparing risks 73\u003c\/p\u003e \u003cp\u003e3.4 VaR in practice 76\u003c\/p\u003e \u003cp\u003e3.5 Criticisms of VaR 79\u003c\/p\u003e \u003cp\u003e3.6 Beyond value at risk 82\u003c\/p\u003e \u003cp\u003e3.6.1 *More details on expected shortfall 86\u003c\/p\u003e \u003cp\u003eNotes 88\u003c\/p\u003e \u003cp\u003eReferences 88\u003c\/p\u003e \u003cp\u003eExercises 89\u003c\/p\u003e \u003cp\u003e\u003cb\u003e4 Understanding the tails 92\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e4.1 Heavy-tailed distributions 93\u003c\/p\u003e \u003cp\u003e4.1.1 Defining the tail index 93\u003c\/p\u003e \u003cp\u003e4.1.2 Estimating the tail index 95\u003c\/p\u003e \u003cp\u003e4.1.3 *More details on the tail index 98\u003c\/p\u003e \u003cp\u003e4.2 Limiting distributions for the maximum 100\u003c\/p\u003e \u003cp\u003e4.2.1 *More details on maximum distributions and Fisher–Tippett 106\u003c\/p\u003e \u003cp\u003e4.3 Excess distributions 109\u003c\/p\u003e \u003cp\u003e4.3.1 *More details on threshold exceedances 114\u003c\/p\u003e \u003cp\u003e4.4 Estimation using extreme value theory 115\u003c\/p\u003e \u003cp\u003e4.4.1 Step 1. Choose a threshold u 116\u003c\/p\u003e \u003cp\u003e4.4.2 Step 2. Estimate the parameters ξ and β 118\u003c\/p\u003e \u003cp\u003e4.4.3 Step 3. Estimate the risk measures of interest 119\u003c\/p\u003e \u003cp\u003eNotes 121\u003c\/p\u003e \u003cp\u003eReferences 122\u003c\/p\u003e \u003cp\u003eExercises 123\u003c\/p\u003e \u003cp\u003e\u003cb\u003e5 Making decisions under uncertainty 125\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e5.1 Decisions, states and outcomes 126\u003c\/p\u003e \u003cp\u003e5.1.1 Decisions 126\u003c\/p\u003e \u003cp\u003e5.1.2 States 127\u003c\/p\u003e \u003cp\u003e5.1.3 Outcomes 127\u003c\/p\u003e \u003cp\u003e5.1.4 Probabilities 128\u003c\/p\u003e \u003cp\u003e5.1.5 Values 129\u003c\/p\u003e \u003cp\u003e5.2 Expected Utility Theory 130\u003c\/p\u003e \u003cp\u003e5.2.1 Maximizing expected profit 130\u003c\/p\u003e \u003cp\u003e5.2.2 Expected utility 132\u003c\/p\u003e \u003cp\u003e5.2.3 No alternative to Expected Utility Theory 135\u003c\/p\u003e \u003cp\u003e5.2.4 *A sketch proof of the theorem 139\u003c\/p\u003e \u003cp\u003e5.2.5 What shape is the utility function? 142\u003c\/p\u003e \u003cp\u003e5.2.6 *Expected utility when probabilities are subjective 145\u003c\/p\u003e \u003cp\u003e5.3 Stochastic dominance and risk profiles 148\u003c\/p\u003e \u003cp\u003e5.3.1 *More details on stochastic dominance 152\u003c\/p\u003e \u003cp\u003e5.4 Risk decisions for managers 156\u003c\/p\u003e \u003cp\u003e5.4.1 Managers and shareholders 156\u003c\/p\u003e \u003cp\u003e5.4.2 A single company-wide view of risk 158\u003c\/p\u003e \u003cp\u003e5.4.3 Risk of insolvency 158\u003c\/p\u003e \u003cp\u003eNotes 160\u003c\/p\u003e \u003cp\u003eReferences 161\u003c\/p\u003e \u003cp\u003eExercises 162\u003c\/p\u003e \u003cp\u003e\u003cb\u003e6 Understanding risk behavior 164\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e6.1 Why decision theory fails 165\u003c\/p\u003e \u003cp\u003e6.1.1 The meaning of utility 165\u003c\/p\u003e \u003cp\u003e6.1.2 Bounded rationality 167\u003c\/p\u003e \u003cp\u003e6.1.3 Inconsistent choices under uncertainty 168\u003c\/p\u003e \u003cp\u003e6.1.4 Problems from scaling utility functions 171\u003c\/p\u003e \u003cp\u003e6.2 Prospect Theory 172\u003c\/p\u003e \u003cp\u003e6.2.1 Foundations for behavioral decision theory 173\u003c\/p\u003e \u003cp\u003e6.2.2 Decision weights and subjective values 175\u003c\/p\u003e \u003cp\u003e6.3 Cumulative Prospect Theory 180\u003c\/p\u003e \u003cp\u003e6.3.1 *More details on Prospect Theory 183\u003c\/p\u003e \u003cp\u003e6.3.2 Applying Prospect Theory 185\u003c\/p\u003e \u003cp\u003e6.3.3 Why Prospect Theory does not always predict well 187\u003c\/p\u003e \u003cp\u003e6.4 Decisions with ambiguity 189\u003c\/p\u003e \u003cp\u003e6.5 How managers treat risk 191\u003c\/p\u003e \u003cp\u003eNotes 194\u003c\/p\u003e \u003cp\u003eReferences 194\u003c\/p\u003e \u003cp\u003eExercises 195\u003c\/p\u003e \u003cp\u003e\u003cb\u003e7 Stochastic optimization 198\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e7.1 Introduction to stochastic optimization 199\u003c\/p\u003e \u003cp\u003e7.1.1 A review of optimization 199\u003c\/p\u003e \u003cp\u003e7.1.2 Two-stage recourse problems 203\u003c\/p\u003e \u003cp\u003e7.1.3 Ordering with stochastic demand 208\u003c\/p\u003e \u003cp\u003e7.2 Choosing scenarios 212\u003c\/p\u003e \u003cp\u003e7.2.1 How to carry out Monte Carlo simulation 213\u003c\/p\u003e \u003cp\u003e7.2.2 Alternatives to Monte Carlo 217\u003c\/p\u003e \u003cp\u003e7.3 Multistage stochastic optimization 218\u003c\/p\u003e \u003cp\u003e7.3.1 Non-anticipatory constraints 220\u003c\/p\u003e \u003cp\u003e7.4 Value at risk constraints 224\u003c\/p\u003e \u003cp\u003eNotes 228\u003c\/p\u003e \u003cp\u003eReferences 228\u003c\/p\u003e \u003cp\u003eExercises 229\u003c\/p\u003e \u003cp\u003e\u003cb\u003e8 Robust optimization 232\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e8.1 True uncertainty: Beyond probabilities 233\u003c\/p\u003e \u003cp\u003e8.2 Avoiding disaster when there is uncertainty 234\u003c\/p\u003e \u003cp\u003e8.2.1 *More details on constraint reformulation 240\u003c\/p\u003e \u003cp\u003e8.2.2 Budget of uncertainty 243\u003c\/p\u003e \u003cp\u003e8.2.3 *More details on budgets of uncertainty 247\u003c\/p\u003e \u003cp\u003e8.3 Robust optimization and the minimax approach 250\u003c\/p\u003e \u003cp\u003e8.3.1 *Distributionally robust optimization 254\u003c\/p\u003e \u003cp\u003eNotes 261\u003c\/p\u003e \u003cp\u003eReferences 262\u003c\/p\u003e \u003cp\u003eExercises 263\u003c\/p\u003e \u003cp\u003e\u003cb\u003e9 Real options 265\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e9.1 Introduction to real options 266\u003c\/p\u003e \u003cp\u003e9.2 Calculating values with real options 267\u003c\/p\u003e \u003cp\u003e9.2.1 *Deriving the formula for the surplus with a normal distribution 272\u003c\/p\u003e \u003cp\u003e9.3 Combining real options and net present value 273\u003c\/p\u003e \u003cp\u003e9.4 The connection with financial options 278\u003c\/p\u003e \u003cp\u003e9.5 Using Monte Carlo simulation to value real options 282\u003c\/p\u003e \u003cp\u003e9.6 Some potential problems with the use of real options 285\u003c\/p\u003e \u003cp\u003eNotes 287\u003c\/p\u003e \u003cp\u003eReferences 287\u003c\/p\u003e \u003cp\u003eExercises 288\u003c\/p\u003e \u003cp\u003e\u003cb\u003e10 Credit risk 291\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e10.1 Introduction to credit risk 292\u003c\/p\u003e \u003cp\u003e10.2 Using credit scores for credit risk 294\u003c\/p\u003e \u003cp\u003e10.2.1 A Markov chain analysis of defaults 296\u003c\/p\u003e \u003cp\u003e10.3 Consumer credit 301\u003c\/p\u003e \u003cp\u003e10.3.1 Probability, odds and log odds 302\u003c\/p\u003e \u003cp\u003e10.4 Logistic regression 308\u003c\/p\u003e \u003cp\u003e10.4.1 *More details on logistic regression 313\u003c\/p\u003e \u003cp\u003e10.4.2 Building a scorecard 315\u003c\/p\u003e \u003cp\u003e10.4.3 Other scoring applications 317\u003c\/p\u003e \u003cp\u003eNotes 317\u003c\/p\u003e \u003cp\u003eReferences 318\u003c\/p\u003e \u003cp\u003eExercises 319\u003c\/p\u003e \u003cp\u003e\u003cb\u003eAppendix A Tutorial on probability theory 323\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eA. 1 Random events 323\u003c\/p\u003e \u003cp\u003eA. 2 Bayes’ rule and independence 326\u003c\/p\u003e \u003cp\u003eA. 3 Random variables 327\u003c\/p\u003e \u003cp\u003eA. 4 Means and variances 329\u003c\/p\u003e \u003cp\u003eA. 5 Combinations of random variables 332\u003c\/p\u003e \u003cp\u003eA. 6 The normal distribution and the Central Limit Theorem 336\u003c\/p\u003e \u003cp\u003e\u003cb\u003eAppendix B Answers to even-numbered exercises 340\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eIndex 361\u003c\/p\u003e \u003cb\u003eEdward J. Anderson\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eThe University of Sydney Business School, Australia\u003c\/i\u003e  \u003cp\u003e\u003cb\u003eA comprehensive and accessible introduction to modern quantitative risk management\u003c\/b\u003e.\u003c\/p\u003e \u003cp\u003eThe business world is rife with risk and uncertainty, and risk management is a vitally important topic for managers. The best way to achieve a clear understanding of risk is to use quantitative tools and probability models.  Written for students, this book has a quantitative emphasis but is accessible to those without a strong mathematical background.\u003c\/p\u003e \u003cp\u003e\u003ci\u003eBusiness Risk Management: Models and Analysis\u003c\/i\u003e\u003c\/p\u003e \u003cul\u003e \u003cli\u003eDiscusses novel modern approaches to risk management\u003c\/li\u003e \u003cli\u003eIntroduces advanced topics in an accessible manner\u003c\/li\u003e \u003cli\u003eIncludes motivating worked examples and exercises (including selected solutions)\u003c\/li\u003e \u003cli\u003eIs written with the student in mind, and does not assume advanced mathematics\u003c\/li\u003e \u003cli\u003eIs suitable for self-study by the manager who wishes to better understand this important field.\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003eAimed at postgraduate students, this book is also suitable for senior undergraduates, MBA students, and all those who have a general interest in business risk.  \u003c\/p\u003e","brand":"Wiley","offers":[{"title":"Default Title","offer_id":47988873429221,"sku":"NP9781118349465","price":60.0,"currency_code":"USD","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/1842\/7735\/files\/9781118349465.jpg?v=1761781866","url":"https:\/\/k12savings.com\/products\/business-risk-management-isbn-9781118349465","provider":"K12savings","version":"1.0","type":"link"}