实用金融期权估值导论

章节摘录

插图：

前言

The aim of this book is to present a lively and palatable introduction to financialoption valuation for undergraduate students in mathematics, statistics and relatedareas. Prerequisites have been kept to a minimum. The reader is assumed to have abasic competence in calculus up to the level reached by a typical first year mathe-matics programme. No background in probability, statistics or numerical analysisis required, although some previous exposure to material in these areas would un-doubtedly make the text easier to assimilate on first reading.The contents are presented in the form of short chapters, each of which couldreasonably be covered in a one hour teaching session. The book grew out of a finalyear undergraduate class called The Mathematics of Financial Derivatives that Ihave taught, in collaboration with Professor Xuerong Mao, at the University ofStrathclyde. The class is aimed at students taking honours degrees in Mathematicsor Statistics, or joint honours degrees in various combinations of Mathematics,Statistics, Economics, Business, Accounting, Computer Science and Physics. Inmy view, such a class has two great selling points.From a student perspective, the topic is generally perceived as modem, sexy and likelyto impress potential employers.From the perspective of a university teacher, the topic provides a focus for ideas frommathematical modelling, analysis, stochastics and numerical analysis.

内容概要

作者：(英国) 海厄姆 (Higham.D.J.) Desmond J.Higham，英国Strathclyde大学数学系教授，SIAM会士、爱丁堡数学会会士、伦敦数学会会士。主要研究数值分析和随机计算，包括随机计算在数理金融中的应用。Higham是很多期刊的编委，如SLAM Journal on Scientific Computing、the IMA Journal of Numerical Analysis和the Journal of Computational Finance等。另有著作Learning LaTeX和Matlab Guide。

书籍目录

1 Options1.1 What are options?1.2 Why do we study options?1.3 How are options traded?1.4 Typical option prices1.5 Other financial derivatives1.6 Notes and references1.7 Program of Chapter 1 and walkthrough2 Option valuation preliminaries2.1 Motivation2.2 Interest rates2.3 Short selling2.4 Arbitrage2.5 Put-call parity2.6 Upper and lower bounds on option values2.7 Notes and references2.8 Program of Chapter 2 and walkthrough3 Random variables3.1 Motivation3.2 Random variables, probability and mean3.3 Independence3.4 Variance3.5 Normal distribution3.6 Central Limit Theorem3.7 Notes and references3.8 Program of Chapter 3 and walkthrough4 Computer simulation4.1 Motivation4.2 Pseudo-random numbers4.3 Statistical tests4.4 Notes and references4.5 Program of Chapter 4 and walkthrough5 Asset price movement5.1 Motivation5.2 Efficient market hypothesis5.3 Asset price data5.4 Assumptions5.5 Notes and references5.6 Program of Chapter 5 and walkthrough6 Asset price model: Part I6.1 Motivation6.2 Discrete asset model6.3 Continuous asset model6.4 Lognormal distribution6.5 Features of the asset model6.6 Notes and references6.7 Program of Chapter 6 and walkthrough7 Asset price model: PartⅡ7.1 Computing asset paths7.2 Timescale invariance7.3 Sum-of-square returns7.4 Notes and references7.5 Program of Chapter 7 and walkthrough8 Black-Scholes PDE and formulas8.1 Motivation8.2 Sum-of-square increments for asset price8.3 Hedging8.4 Black-Scholes PDE8.5 Black-Scholes formulas8.6 Notes and references8.7 Program of Chapter 8 and walkthrough9 More on hedging9.1 Motivation9.2 Discrete hedging9.3 Delta at expiry9.4 Large-scale test9.5 Long-Term Capital Management9.6 Notes9.7 Program of Chapter 9 and walkthrough10 The Greeks10.1 Motivation10.2 The Greeks10.3 Interpreting the Greeks10.4 Black-Scholes PDE solution10.5 Notes and references10.6 Program of Chapter 10 and walkthrough11 More on the Black-Scholes formulas11.1 Motivation11.2 Where is μ?11.3 Time dependency11.4 The big picture11.5 Change of variables11.6 Notes and references11.7 Program of Chapter 11 and walkthrough12 Risk neutrality12.1 Motivation12.2 Expected payoff12.3 Risk neutrality12.4 Notes and references12.5 Program of Chapter 12 and walkthrough13 Solving a nonlinear equation13.1 Motivation13.2 General problem13.3 Bisection13.4 Newton13.5 Further practical issues13.6 Notes and references13.7 Program of Chapter 13 and walkthrough14 Implied volatility14.1 Motivation14.2 Implied volatility14.3 Option value as a function of volatility14.4 Bisection and Newton14.5 Implied volatility with real data14.6 Notes and references14.7 Program of Chapter 14 and walkthrough15 Monte Carlo method15.1 Motivation15.2 Monte Carlo15.3 Monte Carlo for option valuation15.4 Monte Carlo for Greeks15.5 Notes and references15.6 Program of Chapter 15 and walkthrough16 Binomial method16.1 Motivation16.2 Method16.3 Deriving the parameters16.4 Binomial method in practice16.5 Notes and references16.6 Program of Chapter 16 and walkthrough17 Cash-or-nothing options17.1 Motivation17.2 Cash-or-nothing options17.3 Black-Scholes for cash-or-nothing options17.4 Delta behaviour17.5 Risk neutrality for cash-or-nothing options17.6 Notes and references17.7 Program of Chapter 17 and walkthrough18 American options18.1 Motivation18.2 American call and put18.3 Black-Scholes for American options18.4 Binomial method for an American put18.5 Optimal exercise boundary18.6 Monte Carlo for an American put18.7 Notes and references18.8 Program of Chapter 18 and walkthrough19 Exotic options19.1 Motivation19.2 Barrier options19.3 Lookback options19.4 Asian options19.5 Bermudan and shout options19.6 Monte Carlo and binomial for exotics19.7 Notes and references19.8 Program of Chapter 19 and walkthrough20 Historical volatility20.1 Motivation20.2 Monte Carlo-type estimates20.3 Accuracy of the sample variance estimate20.4 Maximum likelihood estimate20.5 Other volatility estimates20.6 Example with real data20.7 Notes and references20.8 Program of Chapter 20 and walkthrough21 Monte Carlo Part II: variance reduction by antithetic variates21.1 Motivation21.2 The big picture21.3 Dependence21.4 Antithetic variates: uniform example21.5 Analysis of the uniform case21.6 Normal case21.7 Multivariate case21.8 Antithetic variates in option valuation21.9 Notes and references21.10 Program of Chapter 21 and walkthrough22 Monte Carlo Part III: variance reduction by control variates22.1 Motivation22.2 Control variates22.3 Control variates in option valuation22.4 Notes and references22.5 Program of Chapter 22 and walkthrough23 Finite difference methods23.1 Motivation23.2 Finite difference operators23.3 Heat equation23.4 Discretization23.5 FTCS and BTCS23.6 Local accuracy23.7 Von Neumann stability and convergence23.8 Crank-Nicolson23.9 Notes and references23.10 Program of Chapter 23 and walkthrough24 Finite difference methods for the Black-Scholes PDE24.1 Motivation24.2 FTCS, BTCS and Crank-Nicolson for Black-Scholes24.3 Down-and-out call example24.4 Binomial method as finite differences24.5 Notes and references24.6 Program of Chapter 24 and walkthroughReferencesIndex

编辑推荐

《实用金融期权估值导论(英文版)》借助Matlab阐述了期权定价理论的入门知识，讲述隐藏在期权评估背后的数学、随机指数和计算算法。仔细推导了基本的资产价格模型和Black-Scholes公式，并阐述了相关的计算技术，包括二项式、有限差分、Monte CarIo方法的方差缩减技术。生动流畅的文字、丰富的图表、大量的示例以及基于实际证券市场数据的计算，使得这《实用金融期权估值导论(英文版)》非常实用，深受好评。《实用金融期权估值导论(英文版)》自成体系，只需要具有微积分知识背景就可阅读，不需要概率、统计或数值分析的基础。每章末都给出了Matlab例程及练习题，便于读者学习体会。

作者简介

《实用金融期权估值导论(英文版)》是金融期权评估的入门书，讲述隐藏在期权评估背后的数学、随机指数和计算算法。《实用金融期权估值导论(英文版)》文字生动流畅、图表丰富，每章末都有难度不同的习题，还提供了习题答案，非常适合初学者自学。

《实用金融期权估值导论(英文版)》可用作应用数学、金融、保险、管理等专业本科生或研究生的教材，也可供有关领域的研究人员和工作人员参考。

图书封面

---

 实用金融期权估值导论下载

---