{"product_id":"advanced-modelling-in-finance-using-excel-and-vba-isbn-9780471499220","title":"Advanced Modelling in Finance using Excel and VBA","description":"This new and unique book demonstrates that Excel and VBA can play an important role in the explanation and implementation of numerical methods across finance. Advanced Modelling in Finance provides a comprehensive look at equities, options on equities and options on bonds from the early 1950s to the late 1990s.  \u003cp\u003eThe book adopts a step-by-step approach to understanding the more sophisticated aspects of Excel macros and VBA programming, showing how these programming techniques can be used to model and manipulate financial data, as applied to equities, bonds and options. The book is essential for financial practitioners who need to develop their financial modelling skill sets as there is an increase in the need to analyse and develop ever more complex 'what if' scenarios.\u003c\/p\u003e \u003cul\u003e \u003cli\u003eSpecifically applies Excel and VBA to the financial markets\u003c\/li\u003e \u003cli\u003ePackaged with a CD containing the software from the examples throughout the book\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003e\u003cb\u003eNote:\u003c\/b\u003e CD-ROM\/DVD and other supplementary materials are not included as part of eBook file.\u003c\/p\u003eDieses neue und einzigartige Buch macht deutlich, daß Excel und VBA (Visual Basic für Applikationen) eine wichtige Rolle in der Finanzwelt spielen bei der Erläuterung und Implementierung numerischer Methoden. \"Advanced Modelling in Finance\" behandelt detailliert Aktien, Aktienoptionen und Rentenoptionen der frühen 50er bis in die späten 90er Jahre. Dabei führen die Autoren schrittweise ein die komplexeren Aspekte der Excel- und VBA-Programmierung und erläutern, wie diese Programmierungsverfahren bei Aktien, Renten und Optionen zur Modellierung oder Manipulierung von Finanzdaten eingesetzt werden können. In der modernen Finanzwelt gewinnen Analysen und die Entwicklung von immer komplexeren \"was wäre wenn\"-Szenarios immer mehr an Bedeutung. Deshalb ist dieses Buch die ideale Lektüre für Finanzexperten, die ihre Fertigkeiten im Bereich finanzwirtschaftliche Modellbildung verbessern müssen. Es liefert das nötige Know-How und Praxiswissen. Die beigefügte CD-ROM, enthält die komplette Software für die besprochenen Beispiele. \u003cp\u003ePreface xi\u003c\/p\u003e \u003cp\u003eAcknowledgements xii\u003c\/p\u003e \u003cp\u003e\u003cb\u003e1 Introduction \u003c\/b\u003e\u003cb\u003e1\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e1.1 Finance insights 1\u003c\/p\u003e \u003cp\u003e1.2 Asset price assumptions 2\u003c\/p\u003e \u003cp\u003e1.3 Mathematical and statistical problems 2\u003c\/p\u003e \u003cp\u003e1.4 Numerical methods 2\u003c\/p\u003e \u003cp\u003e1.5 Excel solutions 3\u003c\/p\u003e \u003cp\u003e1.6 Topics covered 3\u003c\/p\u003e \u003cp\u003e1.7 Related Excel workbooks 5\u003c\/p\u003e \u003cp\u003e1.8 Comments and suggestions 5\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart One Advanced Modelling in Excel \u003c\/b\u003e\u003cb\u003e7\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e2 Advanced Excel functions and procedures \u003c\/b\u003e\u003cb\u003e9\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e2.1 Accessing functions in Excel 9\u003c\/p\u003e \u003cp\u003e2.2 Mathematical functions 10\u003c\/p\u003e \u003cp\u003e2.3 Statistical functions 12\u003c\/p\u003e \u003cp\u003e2.3.1 Using the frequency function 12\u003c\/p\u003e \u003cp\u003e2.3.2 Using the quartile function 14\u003c\/p\u003e \u003cp\u003e2.3.3 Using Excel’s normal functions 15\u003c\/p\u003e \u003cp\u003e2.4 Lookup functions 16\u003c\/p\u003e \u003cp\u003e2.5 Other functions 18\u003c\/p\u003e \u003cp\u003e2.6 Auditing tools 19\u003c\/p\u003e \u003cp\u003e2.7 Data Tables 20\u003c\/p\u003e \u003cp\u003e2.7.1 Setting up Data Tables with one input 20\u003c\/p\u003e \u003cp\u003e2.7.2 Setting up Data Tables with two inputs 22\u003c\/p\u003e \u003cp\u003e2.8 XY charts 23\u003c\/p\u003e \u003cp\u003e2.9 Access to Data Analysis and Solver 26\u003c\/p\u003e \u003cp\u003e2.10 Using range names 27\u003c\/p\u003e \u003cp\u003e2.11 Regression 28\u003c\/p\u003e \u003cp\u003e2.12 Goal Seek 31\u003c\/p\u003e \u003cp\u003e2.13 Matrix algebra and related functions 33\u003c\/p\u003e \u003cp\u003e2.13.1 Introduction to matrices 33\u003c\/p\u003e \u003cp\u003e2.13.2 Transposing a matrix 33\u003c\/p\u003e \u003cp\u003e2.13.3 Adding matrices 34\u003c\/p\u003e \u003cp\u003e2.13.4 Multiplying matrices 34\u003c\/p\u003e \u003cp\u003e2.13.5 Matrix inversion 35\u003c\/p\u003e \u003cp\u003e2.13.6 Solving systems of simultaneous linear equations 36\u003c\/p\u003e \u003cp\u003e2.13.7 Summary of Excel’s matrix functions 37\u003c\/p\u003e \u003cp\u003eSummary 37\u003c\/p\u003e \u003cp\u003e\u003cb\u003e3 Introduction to VBA \u003c\/b\u003e\u003cb\u003e39\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e3.1 Advantages of mastering VBA 39\u003c\/p\u003e \u003cp\u003e3.2 Object-oriented aspects of VBA 40\u003c\/p\u003e \u003cp\u003e3.3 Starting to write VBA macros 42\u003c\/p\u003e \u003cp\u003e3.3.1 Some simple examples of VBA subroutines 42\u003c\/p\u003e \u003cp\u003e3.3.2 MsgBox for interaction 43\u003c\/p\u003e \u003cp\u003e3.3.3 The writing environment 44\u003c\/p\u003e \u003cp\u003e3.3.4 Entering code and executing macros 44\u003c\/p\u003e \u003cp\u003e3.3.5 Recording keystrokes and editing code 45\u003c\/p\u003e \u003cp\u003e3.4 Elements of programming 47\u003c\/p\u003e \u003cp\u003e3.4.1 Variables and data types 48\u003c\/p\u003e \u003cp\u003e3.4.2 VBA array variables 48\u003c\/p\u003e \u003cp\u003e3.4.3 Control structures 50\u003c\/p\u003e \u003cp\u003e3.4.4 Control of repeating procedures 51\u003c\/p\u003e \u003cp\u003e3.4.5 Using Excel functions and VBA functions in code 52\u003c\/p\u003e \u003cp\u003e3.4.6 General points on programming 53\u003c\/p\u003e \u003cp\u003e3.5 Communicating between macros and the spreadsheet 53\u003c\/p\u003e \u003cp\u003e3.6 Subroutine examples 56\u003c\/p\u003e \u003cp\u003e3.6.1 Charts 56\u003c\/p\u003e \u003cp\u003e3.6.2 Normal probability plot 59\u003c\/p\u003e \u003cp\u003e3.6.3 Generating the efficient frontier with Solver 61\u003c\/p\u003e \u003cp\u003eSummary 65\u003c\/p\u003e \u003cp\u003eReferences 65\u003c\/p\u003e \u003cp\u003eAppendix 3A The Visual Basic Editor 65\u003c\/p\u003e \u003cp\u003eStepping through a macro and using other debug tools 68\u003c\/p\u003e \u003cp\u003eAppendix 3B Recording keystrokes in ‘relative references’ mode 69\u003c\/p\u003e \u003cp\u003e\u003cb\u003e4 Writing VBA user-defined functions \u003c\/b\u003e\u003cb\u003e73\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e4.1 A simple sales commission function 73\u003c\/p\u003e \u003cp\u003e4.2 Creating Commission(Sales) in the spreadsheet 74\u003c\/p\u003e \u003cp\u003e4.3 Two functions with multiple inputs for valuing options 75\u003c\/p\u003e \u003cp\u003e4.4 Manipulating arrays in VBA 78\u003c\/p\u003e \u003cp\u003e4.5 Expected value and variance functions with array inputs 79\u003c\/p\u003e \u003cp\u003e4.6 Portfolio variance function with array inputs 81\u003c\/p\u003e \u003cp\u003e4.7 Functions with array output 84\u003c\/p\u003e \u003cp\u003e4.8 Using Excel and VBA functions in user-defined functions 85\u003c\/p\u003e \u003cp\u003e4.8.1 Using VBA functions in user-defined functions 85\u003c\/p\u003e \u003cp\u003e4.8.2 Add-ins 86\u003c\/p\u003e \u003cp\u003e4.9 Pros and cons of developing VBA functions 86\u003c\/p\u003e \u003cp\u003eSummary 87\u003c\/p\u003e \u003cp\u003eAppendix 4A Functions illustrating array handling 88\u003c\/p\u003e \u003cp\u003eAppendix 4B Binomial tree option valuation functions 89\u003c\/p\u003e \u003cp\u003eExercises on writing functions 94\u003c\/p\u003e \u003cp\u003eSolution notes for exercises on functions 95\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart Two Equities \u003c\/b\u003e\u003cb\u003e99\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e5 Introduction to equities \u003c\/b\u003e\u003cb\u003e101\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e6 Portfolio optimisation \u003c\/b\u003e\u003cb\u003e103\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e6.1 Portfolio mean and variance 103\u003c\/p\u003e \u003cp\u003e6.2 Risk–return representation of portfolios 105\u003c\/p\u003e \u003cp\u003e6.3 Using Solver to find efficient points 106\u003c\/p\u003e \u003cp\u003e6.4 Generating the efficient frontier (Huang and Litzenberger’s approach) 109\u003c\/p\u003e \u003cp\u003e6.5 Constrained frontier portfolios 111\u003c\/p\u003e \u003cp\u003e6.6 Combining risk-free and risky assets 113\u003c\/p\u003e \u003cp\u003e6.7 Problem One–combining a risk-free asset with a risky asset 114\u003c\/p\u003e \u003cp\u003e6.8 Problem Two–combining two risky assets 115\u003c\/p\u003e \u003cp\u003e6.9 Problem Three–combining a risk-free asset with a risky portfolio 117\u003c\/p\u003e \u003cp\u003e6.10 User-defined functions in Module1 119\u003c\/p\u003e \u003cp\u003e6.11 Functions for the three generic portfolio problems in Module1 120\u003c\/p\u003e \u003cp\u003e6.12 Macros in ModuleM 121\u003c\/p\u003e \u003cp\u003eSummary 123\u003c\/p\u003e \u003cp\u003eReferences 123\u003c\/p\u003e \u003cp\u003e\u003cb\u003e7 Asset pricing \u003c\/b\u003e\u003cb\u003e125\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e7.1 The single-index model 125\u003c\/p\u003e \u003cp\u003e7.2 Estimating beta coefficients 126\u003c\/p\u003e \u003cp\u003e7.3 The capital asset pricing model 129\u003c\/p\u003e \u003cp\u003e7.4 Variance–covariance matrices 130\u003c\/p\u003e \u003cp\u003e7.5 Value-at-Risk 131\u003c\/p\u003e \u003cp\u003e7.6 Horizon wealth 134\u003c\/p\u003e \u003cp\u003e7.7 Moments of related distributions such as normal and lognormal 136\u003c\/p\u003e \u003cp\u003e7.8 User-defined functions in Module1 136\u003c\/p\u003e \u003cp\u003eSummary 138\u003c\/p\u003e \u003cp\u003eReferences 138\u003c\/p\u003e \u003cp\u003e\u003cb\u003e8 Performance measurement and attribution \u003c\/b\u003e\u003cb\u003e139\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e8.1 Conventional performance measurement 140\u003c\/p\u003e \u003cp\u003e8.2 Active–passive management 141\u003c\/p\u003e \u003cp\u003e8.3 Introduction to style analysis 144\u003c\/p\u003e \u003cp\u003e8.4 Simple style analysis 145\u003c\/p\u003e \u003cp\u003e8.5 Rolling-period style analysis 146\u003c\/p\u003e \u003cp\u003e8.6 Confidence intervals for style weights 148\u003c\/p\u003e \u003cp\u003e8.7 User-defined functions in Module1 151\u003c\/p\u003e \u003cp\u003e8.8 Macros in ModuleM 151\u003c\/p\u003e \u003cp\u003eSummary 152\u003c\/p\u003e \u003cp\u003eReferences 153\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart Three Options on Equities \u003c\/b\u003e\u003cb\u003e155\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e9 Introduction to options on equities \u003c\/b\u003e\u003cb\u003e157\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e9.1 The genesis of the Black–Scholes formula 158\u003c\/p\u003e \u003cp\u003e9.2 The Black–Scholes formula 158\u003c\/p\u003e \u003cp\u003e9.3 Hedge portfolios 159\u003c\/p\u003e \u003cp\u003e9.4 Risk-neutral valuation 161\u003c\/p\u003e \u003cp\u003e9.5 A simple one-step binomial tree with risk-neutral valuation 162\u003c\/p\u003e \u003cp\u003e9.6 Put–call parity 163\u003c\/p\u003e \u003cp\u003e9.7 Dividends 163\u003c\/p\u003e \u003cp\u003e9.8 American features 164\u003c\/p\u003e \u003cp\u003e9.9 Numerical methods 164\u003c\/p\u003e \u003cp\u003e9.10 Volatility and non-normal share returns 165\u003c\/p\u003e \u003cp\u003eSummary 165\u003c\/p\u003e \u003cp\u003eReferences 166\u003c\/p\u003e \u003cp\u003e\u003cb\u003e10 Binomial trees \u003c\/b\u003e\u003cb\u003e167\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e10.1 Introduction to binomial trees 167\u003c\/p\u003e \u003cp\u003e10.2 A simplified binomial tree 168\u003c\/p\u003e \u003cp\u003e10.3 The Jarrow and Rudd binomial tree 170\u003c\/p\u003e \u003cp\u003e10.4 The Cox, Ross and Rubinstein tree 173\u003c\/p\u003e \u003cp\u003e10.5 Binomial approximations and Black–Scholes formula 175\u003c\/p\u003e \u003cp\u003e10.6 Convergence of CRR binomial trees 176\u003c\/p\u003e \u003cp\u003e10.7 The Leisen and Reimer tree 177\u003c\/p\u003e \u003cp\u003e10.8 Comparison of CRR and LR trees 178\u003c\/p\u003e \u003cp\u003e10.9 American options and the CRR American tree 180\u003c\/p\u003e \u003cp\u003e10.10 User-defined functions in Module0 and Module1 182\u003c\/p\u003e \u003cp\u003eSummary 183\u003c\/p\u003e \u003cp\u003eReferences 184\u003c\/p\u003e \u003cp\u003e\u003cb\u003e11 The Black–Scholes formula \u003c\/b\u003e\u003cb\u003e185\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e11.1 The Black–Scholes formula 185\u003c\/p\u003e \u003cp\u003e11.2 Black–Scholes formula in the spreadsheet 186\u003c\/p\u003e \u003cp\u003e11.3 Options on currencies and commodities 187\u003c\/p\u003e \u003cp\u003e11.4 Calculating the option’s ‘greek’ parameters 189\u003c\/p\u003e \u003cp\u003e11.5 Hedge portfolios 190\u003c\/p\u003e \u003cp\u003e11.6 Formal derivation of the Black–Scholes formula 192\u003c\/p\u003e \u003cp\u003e11.7 User-defined functions in Module1 194\u003c\/p\u003e \u003cp\u003eSummary 195\u003c\/p\u003e \u003cp\u003eReferences 196\u003c\/p\u003e \u003cp\u003e\u003cb\u003e12 Other numerical methods for European options \u003c\/b\u003e\u003cb\u003e197\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e12.1 Introduction to Monte Carlo simulation 197\u003c\/p\u003e \u003cp\u003e12.2 Simulation with antithetic variables 199\u003c\/p\u003e \u003cp\u003e12.3 Simulation with quasi-random sampling 200\u003c\/p\u003e \u003cp\u003e12.4 Comparing simulation methods 202\u003c\/p\u003e \u003cp\u003e12.5 Calculating greeks in Monte Carlo simulation 203\u003c\/p\u003e \u003cp\u003e12.6 Numerical integration 203\u003c\/p\u003e \u003cp\u003e12.7 User-defined functions in Module1 205\u003c\/p\u003e \u003cp\u003eSummary 207\u003c\/p\u003e \u003cp\u003eReferences 207\u003c\/p\u003e \u003cp\u003e\u003cb\u003e13 Non-normal distributions and implied volatility \u003c\/b\u003e\u003cb\u003e209\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e13.1 Black–Scholes using alternative distributional assumptions 209\u003c\/p\u003e \u003cp\u003e13.2 Implied volatility 211\u003c\/p\u003e \u003cp\u003e13.3 Adapting for skewness and kurtosis 212\u003c\/p\u003e \u003cp\u003e13.4 The volatility smile 215\u003c\/p\u003e \u003cp\u003e13.5 User-defined functions in Module1 217\u003c\/p\u003e \u003cp\u003eSummary 219\u003c\/p\u003e \u003cp\u003eReferences 220\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart Four Options on Bonds \u003c\/b\u003e\u003cb\u003e221\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e14 Introduction to valuing options on bonds \u003c\/b\u003e\u003cb\u003e223\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e14.1 The term structure of interest rates 224\u003c\/p\u003e \u003cp\u003e14.2 Cash flows for coupon bonds and yield to maturity 225\u003c\/p\u003e \u003cp\u003e14.3 Binomial trees 226\u003c\/p\u003e \u003cp\u003e14.4 Black’s bond option valuation formula 227\u003c\/p\u003e \u003cp\u003e14.5 Duration and convexity 228\u003c\/p\u003e \u003cp\u003e14.6 Notation 230\u003c\/p\u003e \u003cp\u003eSummary 230\u003c\/p\u003e \u003cp\u003eReferences 230\u003c\/p\u003e \u003cp\u003e\u003cb\u003e15 Interest rate models \u003c\/b\u003e\u003cb\u003e231\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e15.1 Vasicek’s term structure model 231\u003c\/p\u003e \u003cp\u003e15.2 Valuing European options on zero-coupon bonds, Vasicek’s model 234\u003c\/p\u003e \u003cp\u003e15.3 Valuing European options on coupon bonds, Vasicek’s model 235\u003c\/p\u003e \u003cp\u003e15.4 CIR term structure model 236\u003c\/p\u003e \u003cp\u003e15.5 Valuing European options on zero-coupon bonds, CIR model 237\u003c\/p\u003e \u003cp\u003e15.6 Valuing European options on coupon bonds, CIR model 238\u003c\/p\u003e \u003cp\u003e15.7 User-defined functions in Module1 239\u003c\/p\u003e \u003cp\u003eSummary 240\u003c\/p\u003e \u003cp\u003eReferences 241\u003c\/p\u003e \u003cp\u003e\u003cb\u003e16 Matching the term structure \u003c\/b\u003e\u003cb\u003e243\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e16.1 Trees with lognormally distributed interest rates 243\u003c\/p\u003e \u003cp\u003e16.2 Trees with normal interest rates 246\u003c\/p\u003e \u003cp\u003e16.3 The Black, Derman and Toy tree 247\u003c\/p\u003e \u003cp\u003e16.4 Valuing bond options using BDT trees 248\u003c\/p\u003e \u003cp\u003e16.5 User-defined functions in Module1 250\u003c\/p\u003e \u003cp\u003eSummary 252\u003c\/p\u003e \u003cp\u003eReferences 252\u003c\/p\u003e \u003cp\u003e\u003cb\u003eAppendix Other VBA functions \u003c\/b\u003e\u003cb\u003e253\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eForecasting 253\u003c\/p\u003e \u003cp\u003eARIMA modelling 254\u003c\/p\u003e \u003cp\u003eSplines 256\u003c\/p\u003e \u003cp\u003eEigenvalues and eigenvectors 257\u003c\/p\u003e \u003cp\u003eReferences 258\u003c\/p\u003e \u003cp\u003eIndex 259\u003c\/p\u003e No. 4 bestseller in 'General Finance' (erivativesreview.com, December 2001)  \u003cp\u003e\u003cb\u003eMARY JACKSON\u003c\/b\u003e and \u003cb\u003eMIKE STAUNTON\u003c\/b\u003e have worked together teaching spreadsheet modelling to both graduate students and practitioners since 1985. \u003c\/p\u003e\u003cp\u003e\u003cb\u003eMARY JACKSON\u003c\/b\u003e was Assistant Professor of Decision Sciences at London Business School. She is author of three previous books for John Wiley \u0026amp; Sons: \u003ci\u003eUnderstanding Expert Systems\u003c\/i\u003e (1992), \u003ci\u003eAdvanced Spreadsheet Modelling\u003c\/i\u003e (1988) and \u003ci\u003eCreative Modelling\u003c\/i\u003e (1985). \u003c\/p\u003e\u003cp\u003e\u003cb\u003eMIKE STAUNTON\u003c\/b\u003e is Visiting Lecturer in Numerical Methods at City University Business School and Director of the London Share Price Datbase at London Business School. He is coauthor, with Elroy Dimson and Paul Marsh, of \u003ci\u003eMillennium Book II: 101 Years of Investment Returns\u003c\/i\u003e (2001) and \u003ci\u003eThe Millennium Book: A Century of Investment Returns\u003c\/i\u003e (2000).   \u003c\/p\u003e\u003cp\u003e\u003cb\u003eAdvanced modelling in finance using Excel and VBA\u003c\/b\u003e \u003c\/p\u003e\u003cp\u003eThis unique book demonstrates that Excel and VBA can play an important role in the explanation and implementation of numerical methods across finance. It takes a comprehensive look at equities, options on equities and options on bonds from the early 1950s to the late 1990s. Each area contains both standard material and more advanced topics. \u003c\/p\u003e\u003cp\u003eAll models are developed fully in both spreadsheets, bringing clarity to teaching in finance, and user-defined functions in VBA, giving a ready-made library of portable functions that can be used in Excel.\t   \u003c\/p\u003e\u003cp\u003e\u003cb\u003eAdvanced modelling in finance using Excel and VBA\u003c\/b\u003e \u003c\/p\u003e\u003cp\u003eMary Jackson and Mike Staunton \u003c\/p\u003e\u003cp\u003eThis book will appeal to both graduate students and practitioners. Students will value the Excel spreadsheets allowing them to develop their knowledge of modelling in finance, using a step-by-step approach accompanied by explanations using elementary mathematical statistics and probability. Practitioners will value the VBA functions as a source of up-to-date and efficient programs that can be easily used from Excel.  \u003c\/p\u003e\u003cp\u003eStandard material rovered includes: \u003c\/p\u003e\u003cul\u003e \u003cli\u003eportfolio theory and efficient frontiers\u003c\/li\u003e \u003cli\u003ethe Capital Asset Pricing Model, beta and variance-covariance matrices\u003c\/li\u003e \u003cli\u003eperformance measurement\u003c\/li\u003e \u003cli\u003ethe Black-Scholes option pricing formula\u003c\/li\u003e \u003cli\u003ebinomial trees for options on equities and bonds\u003c\/li\u003e \u003cli\u003eMonte Carlo simulation\u003c\/li\u003e \u003cli\u003ebond yield-to-maturity, duration and convexity\u003c\/li\u003e \u003cli\u003eterm structure models from Vasicek and Cox, Ingersoll and Ross\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003eAdvanced topics covered include: \u003c\/p\u003e\u003cul\u003e \u003cli\u003eValue-at-Risk\u003c\/li\u003e \u003cli\u003estyle analysis\u003c\/li\u003e \u003cli\u003ean improved binomial tree (Leisen \u0026amp; Reimer)\u003c\/li\u003e \u003cli\u003equasi Monte Carlo simulation\u003c\/li\u003e \u003cli\u003evolatility smiles\u003c\/li\u003e \u003cli\u003eBlack, Derman \u0026amp; Toy trees\u003c\/li\u003e \u003cli\u003enormal interest rate trees\u003c\/li\u003e \u003c\/ul\u003e","brand":"Wiley","offers":[{"title":"Default Title","offer_id":47988668694757,"sku":"NP9780471499220","price":143.0,"currency_code":"USD","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/1842\/7735\/files\/9780471499220.jpg?v=1761781192","url":"https:\/\/k12savings.com\/es\/products\/advanced-modelling-in-finance-using-excel-and-vba-isbn-9780471499220","provider":"K12savings","version":"1.0","type":"link"}