## Paul Wilmott Introduces Quantitative Finance [Paperback]by Paul Wilmott- RRP:
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Usually ships within 2 to 4 working days Also Available as an eBook:## Description of Paul Wilmott Introduces Quantitative FinancePaul Wilmott Introduces Quantitative Finance, Second Edition is an accessible introduction to the classical side of quantitative finance specifically for university students. Adapted from the comprehensive, even epic, works Derivatives and Paul Wilmott on Quantitative Finance, Second Edition, it includes carefully selected chapters to give the student a thorough understanding of futures, options and numerical methods. Software is included to help visualize the most important ideas and to show how techniques are implemented in practice. There are comprehensive end-of-chapter exercises to test students on their understanding.In praise of Paul Wilmott and his previous works Some people write for fame, some for money. Most academics write books to impress the professor down the corridor so that one day they will be the professor down the corridor everyone is trying to impress. Uniquely, Paul Wilmott writes to inform and educate his readers, to convey ideas, and, most importantly, to show them how to do it. His greatest admirers are his readers. So, instead of endorsements from the great and the good, here are the words of his fans. Their sometimes unique spelling has been retained. I found it to be easily the best book that I have read/worked through on the subject. I thought it might amuse you to know that I think your book got me a job! I'd like to say that this is a great book but you already know that! I'm a junior derivatives trader in Mexico City. I've seen your book and I have only one coment: SEXY! Loved your book, which is a breath of fresh air, amongst all those arid derivatives books!! It really is in a class of its own. I have wasted so much money on stupid derivative books which too elementary or way too complicated. Purchased both Quant Finance and Derivatives a couple of days ago. Will not be able to afford steak or wine for weeks as a result. BTW, I want to congratulate you for the ∗best∗ book in Financial Engineering I've read in the last years. After reading the book I'd like to follow one of your courses, but they are way too expensive. Congratulations for your brilliant book. What I like about it is that it has this no-nonsense kind of approach that you'd expect in a physics text and it spells out the "stuff between the equations". Congratulation to your book Derivatives !!! The way you describe, present, and deliver Derivative knowledge is unique! One can feel your passion on the topic. It's a pleasure to read, study, re-read... Congratulations on a great new book - 'PW on Quant Finance'. I bought the DERIVATIVES one but cannot afford this one!! I am fanatical follower of your book "Derivatives". You are best and this not flattery. Sorry from my English! We use it for the part of our Banking and Risk Management course and it's much more comprehensive than the books that we have recommended in our study guide. Your book “Derivatives: the Theory and Practice of Financial Engineering” is the best in the market so far. I shall waste no more precious words but to say that I am very simpathetic to your humor and irony...what most don't always seem to understand: irony is one of the GREAT filters to access knowledge in this world and an elegant one for that matter. your book rocks Congratulations to the success of your book (I got my copy of it for Christmas). I would like to thank you for writing Derivatives. Derivatives is the Greatest! Thank you, thank you, thank you! Just read the first 7 chapters of Derivatives, and it speaks to me. complete, brilliant and amusing, stimulating for some original ideas and examples, didactically ready to be used by Students; it employs mathematical tools as tools only, not as a target; it is the last but the best book on derivatives in my library. You're book truly struck me as fun, informative and brilliant! Us American would say 'Awesome Dude!!!' I had a course on derivatives and your book was not suggested by the teacher (a stupid teacher). Love you for ever, baby. xxx M ## Title Information- ISBN:
- 9780470319581
- Pages:
- 728 pages
- Format:
- Paperback
- Product Code:
- 168530
- Publisher:
- John Wiley & Sons Ltd
- Published:
- 29/06/2007
- Edition:
- 2nd Edition
Write a review of this book ## Customer Reviews from Amazon## About Paul WilmottPaul Wilmott, described by the Financial Times as 'cult derivatives lecturer,' is one of the world's leading experts on quantitative finance and derivatives. He is the proprietor of an innovative magazine on quantitative finance and a highly popular community website (www.wilmott.com). He is the principal of the financial consultancy and training firm, Wilmott Associates, and the Course Director for the Certificate in Quantitative Finance. He has researched and published widely on financial engineering.## Contents of Paul Wilmott Introduces Quantitative Finance1. Products and Markets: Equities, Commodities, Exchange Rates, Forwards and Futures1.1 Introduction 1.2 Equities 1.2.1 Dividends 1.2.2 Stock splits 1.3 Commodities 1.4 Currencies 1.5 Indices 1.6 The time value of money 1.7 Fixed-income securities 1.8 Inflation-proof bonds 1.9 Forwards and futures 1.9.1 A first example of no arbitrage 1.10 More about futures 1.10.1 Commodity futures 1.10.2 FX futures 1.10.3 Index futures 1.11 Summary 2. Derivatives 2.1 Introduction 2.2 Options 2.3 Definition of common terms 2.4 Payoff diagrams 2.4.1 Other representations of value 2.5 Writing options 2.6 Margin 2.7 Market conventions 2.8 The value of the option before expiry 2.9 Factors affecting derivative prices 2.10 Speculation and gearing 2.11 Early exercise 2.12 Put-call parity 2.13 Binaries or digitals 2.14 Bull and bear spreads 2.15 Straddles and strangles 2.16 Risk reversal 2.17 Butterflies and condors 2.18 Calendar spreads 2.19 LEAPS and FLEX 2.20 Warrants 2.21 Convertible bonds 2.22 Over the counter options 2.23 Summary 3. The Binomial Model 3.1 Introduction 3.2 Equities can go down as well as up 3.3 The option value 3.4 Which part of our 'model' didn't we need? 3.5 Why should this 'theoretical price' be the 'market price'? 3.5.1 The role of expectations 3.6 How did I know to sell ½ of the stock for hedging? 3.6.1 The general formula for ? 3.7 How does this change if interest rates are non-zero? 3.8 Is the stock itself correctly priced? 3.9 Complete markets 3.10 The real and risk-neutral worlds 3.10.1 Non-zero interest rates 3.11 And now using symbols 3.11.1 Average asset change 3.11.2 Standard deviation of asset price change 3.12 An equation for the value of an option 3.12.1 Hedging 3.12.2 No arbitrage 3.13 Where did the probability p go? 3.14 Counter-intuitive? 3.15 The binomial tree 3.16 The asset price distribution 3.17 Valuing back down the tree 3.18 Programming the binomial method 3.19 The greeks 3.20 Early exercise 3.21 The continuous-time limit 3.22 Summary 4. The Random Behavior of Assets 4.1 Introduction 4.2 The popular forms of 'analysis' 4.3 Why we need a model for randomness: Jensen's inequality 4.4 Similarities between equities, currencies, commodities and indices 4.5 Examining returns 4.6 Timescales 4.6.1 The drift 4.6.2 The volatility 4.7 Estimating volatility 4.8 The random walk on a spreadsheet 4.9 The Wiener process 4.10 The widely accepted model for equities, currencies, commodities and indices 4.11 Summary 5. Elementary Stochastic Calculus 5.1 Introduction 5.2 A motivating example 5.3 The Markov property 5.4 The martingale property 5.5 Quadratic variation 5.6 Brownian motion 5.7 Stochastic integration 5.8 Stochastic differential equations 5.9 The mean square limit 5.10 Functions of stochastic variables and Itô's lemma 5.11 Interpretation of Itô's lemma 5.12 Itô and Taylor 5.13 Itô in higher dimensions 5.14 Some pertinent examples 5.14.1 Brownian motion with drift 5.14.2 The lognormal random walk 5.14.3 A mean-reverting random walk 5.14.4 And another mean-reverting random walk 5.15 Summary 6. The Black-Scholes Model 6.1 Introduction 6.2 A very special portfolio 6.3 Elimination of risk: delta hedging 6.4 No arbitrage 6.5 The Black-Scholes equation 6.6 The Black-Scholes assumptions 6.7 Final conditions 6.8 Options on dividend-paying equities 6.9 Currency options 6.10 Commodity options 6.11 Expectations and Black-Scholes 6.12 Some other ways of deriving the Black-Scholes equation 6.12.1 The martingale approach 1 6.12.2 The binomial model 6.12.3 CAPM/utility 6.13 No arbitrage in the binomial, Black-Scholes and 'other' worlds 6.14 Forwards and futures 6.14.1 Forward contracts 6.15 Futures contracts 6.15.1 When interest rates are known, forward prices and futures prices are the same 6.16 Options on futures 6.17 Summary 7. Partial Differential Equations 7.1 Introduction 7.2 Putting the Black-Scholes equation into historical perspective 7.3 The meaning of the terms in the Black-Scholes equation 7.4 Boundary and initial/final conditions 7.5 Some solution methods 7.5.1 Transformation to constant coefficient diffusion equation 7.5.2 Green's functions 7.5.3 Series solution 7.6 Similarity reductions 7.7 Other analytical techniques 7.8 Numerical solution 7.9 Summary 8. The Black-Scholes Formulæ and the 'Greeks' 8.1 Introduction 8.2 Derivation of the formulæ for calls, puts and simple digitals 8.2.1 Formula for a call 8.2.2 Formula for a put 8.2.3 Formula for a binary call 8.2.4 Formula for a binary put 8.3 Delta 8.4 Gamma 8.5 Theta 8.6 Speed 8.7 Vega 8.8 Rho 8.9 Implied volatility 8.10 A classification of hedging types 8.10.1 Why hedge? 8.10.2 The two main classifications 8.10.3 Delta hedging 8.10.4 Gamma hedging 8.10.5 Vega hedging 8.10.6 Static hedging 8.10.7 Margin hedgin 8.10.8 Crash (Platinum) hedging 8.11 Summary 9. Overview of Volatility Modeling 9.1 Introduction 9.2 The different types of volatility 9.2.1 Actual volatility 9.2.2 Historical or realized volatility 9.2.3 Implied volatility 9.2.4 Forward volatility 9.3 Volatility estimation by statistical means 9.3.1 The simplest volatility estimate: constant volatility/moving window 9.3.2 Incorporating mean reversion. 9.3.3 Exponentially weighted moving average. 9.3.4 A simple GARCH model 9.3.5 Expected future volatility 9.3.6 Beyond close-close estimators: range-based estimation of volatility 9.4 Maximum likelihood estimation 9.4.1 A simple motivating example: taxi numbers 9.4.2 Three hats 9.4.3 The math behind this: find the standard deviation 9.4.4 Quants' salaries 9.5 Skews and smiles 9.5.1 Sensitivity of the straddle to skews and smiles 9.5.2 Sensitivity of the risk reversal to skews and smiles 9.6 Different approaches to modeling volatility 9.6.1 To calibrate or not? 9.6.2 Deterministic volatility surfaces 9.6.3 Stochastic volatility 9.6.4 Uncertain parameters 9.6.5 Static hedging 9.6.6 Stochastic volatility and mean-variance analysis 9.6.7 Asymptotic analysis of volatility 9.7 The choices of volatility models 9.8 Summary 10. How to Delta Hedge 10.1 Introduction 10.2 What if implied and actual volatilities are different? 10.3 Implied versus actual, delta hedging but using which volatility? 10.4 Case 1: Hedge with actual volatility, s 10.5 Case 2: Hedge with implied volatility, ˜s 10.5.1 The expected profit after hedging using implied volatility 10.5.2 The variance of profit after hedging using implied volatility 10.6 Hedging with different volatilities 10.6.1 Actual volatility = Implied volatility 10.6.2 Actual volatility > Implied volatility 10.6.3 Actual volatility < Implied volatility 10.7 Pros and cons of hedging with each volatility 10.7.1 Hedging with actual volatility 10.7.2 Hedging with implied volatility 10.7.3 Hedging with another volatility 10.8 Portfolios when hedging with implied volatility 10.8.1 Expectation 10.8.2 Variance 10.8.3 Portfolio optimization possibilities 10.9 How does implied volatility behave? 10.9.1 Sticky strike 10.9.2 Sticky delta 10.9.3 Time-periodic behavior 10.10 Summary 11. An Introduction to Exotic and Path-dependent Options 11.1 Introduction 11.2 Option classification 11.3 Time dependence 11.4 Cashflows 11.5 Path dependence 11.5.1 Strong path dependence 11.5.2 Weak path dependence 11.6 Dimensionality 11.7 The order of an option 11.8 Embedded decisions 11.9 Classification tables 11.10 Examples of exotic options 11.10.1 Compounds and choosers 11.10.2 Range notes 11.10.3 Barrier options 11.10.4 Asian options 11.10.5 Lookback options 11.11 Summary of math/coding consequences 11.12 Summary 12. Multi-asset Options 12.1 Introduction 12.2 Multidimensional lognormal random walks 12.3 Measuring correlations 12.4 Options on many underlyings 12.5 The pricing formula for European non-path-dependent options on dividend-paying assets 12.6 Exchanging one asset for another: a similarity solution 12.7 Two examples 12.8 Realities of pricing basket options 12.8.1 Easy problems 12.8.2 Medium problems 12.8.3 Hard problems 12.9 Realities of hedging basket options 12.10 Correlation versus cointegration 12.11 Summary 13. Barrier Options 13.1 Introduction 13.2 Different types of barrier options 13.3 Pricing methodologies 13.3.1 Monte Carlo simulation 13.3.2 Partial differential equations 13.4 Pricing barriers in the partial differential equation framework 13.4.1 'Out' barriers 13.4.2 'In' barriers 13.5 Examples 13.5.1 Some more examples 13.6 Other features in barrier-style options 13.6.1 Early exercise 13.6.2 Repeated hitting of the barrier 13.6.3 Resetting of barrier 13.6.4 Outside barrier options 13.6.5 Soft barriers 13.6.6 Parisian options 13.7 Market practice: what volatility should I use? 13.8 Hedging barrier options 13.8.1 Slippage costs 13.9 Summary 14. Fixed-income Products and Analysis: Yield, Duration and Convexity 14.1 Introduction 14.2 Simple fixed-income contracts and features 14.2.1 The zero-coupon bond 14.2.2 The coupon-bearing bond 14.2.3 The money market account 14.2.4 Floating rate bonds 14.2.5 Forward rate agreements 14.2.6 Repos 14.2.7 STRIPS 14.2.8 Amortization 14.2.9 Call provision 14.3 International bond markets 14.3.1 United States of America 14.3.2 United Kingdom 14.3.3 Japan 14.4 Accrued interest 14.5 Day-count conventions 14.6 Continuously and discretely compounded interest 14.7 Measures of yield 14.7.1 Current yield 14.7.2 The yield to maturity (YTM) or internal rate of return (IRR). 14.8 The yield curve 14.9 Price/yield relationship 14.10 Duration 14.11 Convexity 14.12 An example 14.13 Hedging 14.14 Time-dependent interest rate 14.15 Discretely paid coupons 14.16 Forward rates and bootstrapping 14.16.1 Discrete data 14.16.2 On a spreadsheet 14.17 Interpolation 14.18 Summary 15. Swaps 15.1 Introduction 15.2 The vanilla interest rate swap 15.3 Comparative advantage 15.4 The swap curve 15.5 Relationship between swaps and bonds 15.6 Bootstrapping 15.7 Other features of swaps contracts 15.8 Other types of swap 15.8.1 Basis rate swap 15.8.2 Equity swaps 15.8.3 Currency swaps 15.9 Summary 16. One-factor Interest Rate Modeling 16.1 Introduction 16.2 Stochastic interest rates 16.3 The bond pricing equation for the general model 16.4 What is the market price of risk? 16.5 Interpreting the market price of risk, and risk neutrality 16.6 Named models 16.6.1 Vasicek 16.6.2 Cox, Ingersoll & Ross 16.6.3 Ho & Lee 16.6.4 Hull & White 16.7 Equity and FX forwards and futures when rates are stochastic 16.7.1 Forward contracts 16.8 Futures contracts 16.8.1 The convexity adjustment 16.9 Summary 17. Yield Curve Fitting 17.1 Introduction 17.2 Ho & Lee 17.3 The extended Vasicek model of Hull & White 17.4 Yield-curve fitting: for and against 17.4.1 For 17.4.2 Against 17.5 Other models 17.6 Summary 18. Interest Rate Derivatives 18.1 Introduction 18.2 Callable bonds 18.3 Bond options 18.3.1 Market practice 18.4 Caps and floors 18.4.1 Cap/floor parity 18.4.2 The relationship between a caplet and a bond option 18.4.3 Market practice 18.4.4 Collars 18.4.5 Step-up swaps, caps and floors 18.5 Range notes 18.6 Swaptions, captions and floortions 18.6.1 Market practice 18.7 Spread options 18.8 Index amortizing rate swaps 18.8.1 Other features in the index amortizing rate swap 18.9 Contracts with embedded decisions 18.10 Some examples 18.11 More interest rate derivatives 18.12 Summary 19. The Heath, Jarrow & Morton and Brace, Gatarek & Musiela Models 19.1 Introduction 19.2 The forward rate equation 19.3 The spot rate process 19.3.1 The non-Markov nature of HJM 19.4 The market price of risk 19.5 Real and risk neutral 19.5.1 The relationship between the risk-neutral forward rate drift and volatility 19.6 Pricing derivatives 19.7 Simulations 19.8 Trees 19.9 The Musiela parameterization 19.10 Multi-factor HJM 19.11 Spreadsheet implementation 19.12 A simple one-factor example: Ho & Lee 19.13 Principal Component Analysis 19.13.1 The power method 19.14 Options on equities, etc. 19.15 Non-infinitesimal short rate 19.16 The Brace, Gatarek & Musiela model 19.17 Simulations 19.18 PVing the cashflows. 19.19 Summary 20. Investment Lessons from Blackjack and Gambling 20.1 Introduction 20.2 The rules of blackjack 20.3 Beating the dealer 20.3.1 Summary of winning at blackjack 20.4 The distribution of profit in blackjack 20.5 The Kelly criterion 20.6 Can you win at roulette? 20.7 Horse race betting and no arbitrage 20.7.1 Setting the odds in a sporting game 20.7.2 The mathematics 20.8 Arbitrage 20.8.1 How best to profit from the opportunity? 20.9 How to bet 20.10 Summary 21. Portfolio Management 21.1 Introduction 21.2 Diversification 21.2.1 Uncorrelated assets 21.3 Modern portfolio theory 21.3.1 Including a risk-free investment 21.4 Where do I want to be on the efficient frontier? 21.5 Markowitz in practice 21.6 Capital Asset Pricing Model 21.6.1 The single-index model 21.6.2 Choosing the optimal portfolio 21.7 The multi-index model 21.8 Cointegration 21.9 Performance measurement 21.10 Summary 22. Value at Risk 22.1 Introduction 22.2 Definition of Value at Risk 22.3 VaR for a single asset 22.4 VaR for a portfolio 22.5 VaR for derivatives 22.5.1 The delta approximation 22.5.2 The delta/gamma approximation 22.5.3 Use of valuation models 22.5.4 Fixed-income portfolios 22.6 Simulations 22.6.1 Monte Carlo 22.6.2 Bootstrapping 22.7 Use of VaR as a performance measure 22.8 Introductory Extreme Value Theory 22.8.1 Some EVT results 22.9 Coherence 22.10 Summary 23. Credit Risk 23.1 Introduction 23.2 The Merton model: equity as an option on a company's assets 23.3 Risky bonds 23.4 Modeling the risk of default 23.5 The Poisson process and the instantaneous risk of default 23.5.1 A note on hedging 23.6 Time-dependent intensity and the term structure of default 23.7 Stochastic risk of default 23.8 Positive recovery 23.9 Hedging the default 23.10 Credit rating 23.11 A model for change of credit rating 23.12 Copulas: pricing credit derivatives with many underlyings 23.12.1 The copula function 23.12.2 The mathematical definition 23.12.3 Examples of copulas 23.13 Collateralized debt obligations 23.14 Summary 24. RiskMetrics and CreditMetrics 24.1 Introduction 24.2 The RiskMetrics datasets 24.3 Calculating the parameters the RiskMetrics way 24.3.1 Estimating volatility 24.3.2 Correlation 24.4 The CreditMetrics dataset 24.4.1 Yield curves 24.4.2 Spreads 24.4.3 Transition matrices 24.4.4 Correlations 24.5 The CreditMetrics methodology 24.6 A portfolio of risky bonds 24.7 CreditMetrics model outputs 24.8 Summary 25. CrashMetrics 25.1 Introduction 25.2 Why do banks go broke? 25.3 Market crashes 5.4 CrashMetrics 25.5 CrashMetrics for one stock 25.6 Portfolio optimization and the Platinum hedge 25.6.1 Other 'cost' functions 25.7 The multi-asset/single-index mode 25.7.1 Assuming Taylor series for the moment 25.8 Portfolio optimization and the Platinum hedge in the multi-asset model 25.8.1 The marginal effect of an asset 5.9 The multi-index model 25.10 Incorporating time value 25.11 Margin calls and margin hedging 25.11.1 What is margin? 25.11.2 Modeling margin 25.11.3 The single-index model 5.12 Counterparty risk 25.13 Simple extensions to CrashMetrics 25.14 The CrashMetrics Index (CMI) 25.15 Summary 26. Derivatives **** Ups 26.1 Introduction 26.2 Orange County 26.3 Proctor and Gamble 26.4 Metallgesellschaft 26.4.1 Basis risk 26.5 Gibson Greetings 26.6 Barings 26.7 Long-Term Capital Management 26.8 Summary 27. Overview of Numerical Methods 27.1 Introduction 27.2 Finite-difference methods 27.2.1 Efficiency 27.2.2 Program of study 27.3 Monte Carlo methods 27.3.1 Efficiency 27.3.2 Program of study 27.4 Numerical integration 27.4.1 Efficiency 27.4.2 Program of study 27.5 Summary 28. Finite-difference Methods for One-factor Models 28.1 Introduction 28.2 Grids 28.3 Differentiation using the grid 28.4 Approximating ? 28.5 Approximating ? 28.6 Approximating + 28.7 Example 28.8 Bilinear interpolation 28.9 Final conditions and payoffs 28.10 Boundary conditions 28.11 The explicit finite-difference method 28.11.1 The Black-Scholes equation 28.11.2 Convergence of the explicit method 28.12 The Code #1: European option 28.13 The Code #2: American exercise 28.14 The Code #3: 2-D output 28.15 Upwind differencing 28.16 Summary 29. Monte Carlo Simulation 29.1 Introduction 29.2 Relationship between derivative values and simulations: equities, indices, currencies, commodities 29.3 Generating paths 29.4 Lognormal underlying, no path dependency 29.5 Advantages of Monte Carlo simulation 29.6 Using random numbers 29.7 Generating Normal variables 29.7.1 Box-Muller 29.8 Real versus risk neutral, speculation versus hedging 29.9 Interest rate products 29.10 Calculating the greeks 29.11 Higher dimensions: Cholesky factorization 29.12 Calculation time 29.13 Speeding up convergence 29.13.1 Antithetic variables 29.13.2 Control variate technique 29.14 Pros and cons of Monte Carlo simulations 29.15 American options 29.16 Longstaff & Schwartz regression approach for American options 29.17 Basis functions 29.18 Summary 30. Numerical Integration 30.1 Introduction 30.2 Regular grid 30.3 Basic Monte Carlo integration 30.4 Low-discrepancy sequences 30.5 Advanced techniques 30.6 Summary A. All the Math You Need. . . and No More (An Executive Summary) A.1 Introduction A.2 e A.3 log A.4 Differentiation and Taylor series A.5 Differential equations A.6 Mean, standard deviation and distributions A.7 Summary B. Forecasting the Markets? A Small Digression B.1 Introduction B.2 Technical analysis B.2.1 Plotting B.2.2 Support and resistance B.2.3 Trendlines B.2.4 Moving averages B.2.5 Relative strength B.2.6 Oscillators B.2.7 Bollinger bands B.2.8 Miscellaneous patterns B.2.9 Japanese candlesticks B.2.10 Point and figure charts B.3 Wave theory B.3.1 Elliott waves and Fibonacci numbers B.3.2 Gann charts B.4 Other analytics B.5 Market microstructure modeling B.5.1 Effect of demand on price B.5.2 Combining market microstructure and option theory B.5.3 Imitation B.6 Crisis prediction B.7 Summary C. A Trading Game C.1 Introduction C.2 Aims C.3 Object of the game C.4 Rules of the game C.5 Notes C.6 How to fill in your trading sheet C.6.1 During a trading round C.6.2 At the end of the game D. Contents of CD accompanying Paul Wilmott Introduces Quantitative Finance, second edition E. What you get if (when) you upgrade to PWOQF2 Bibliography Index |
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