Stochastic Calculus for Finance I: The Binomial Asset Pricing ModelStochastic Calculus for Finance evolved from the first ten years of the Carnegie Mellon Professional Master's program in Computational Finance. The content of this book has been used successfully with students whose mathematics background consists of calculus and calculusbased probability. The text gives both precise statements of results, plausibility arguments, and even some proofs, but more importantly intuitive explanations developed and refine through classroom experience with this material are provided. The book includes a selfcontained treatment of the probability theory needed for stchastic calculus, including Brownian motion and its properties. Advanced topics include foreign exchange models, forward measures, and jumpdiffusion processes. This book is being published in two volumes. The first volume presents the binomial assetpricing model primarily as a vehicle for introducing in the simple setting the concepts needed for the continuoustime theory in the second volume. Chapter summaries and detailed illustrations are included. Classroom tested exercises conclude every chapter. Some of these extend the theory and others are drawn from practical problems in quantitative finance. Advanced undergraduates and Masters level students in mathematical finance and financial engineering will find this book useful. Steven E. Shreve is CoFounder of the Carnegie Mellon MS Program in Computational Finance and winner of the Carnegie Mellon Doherty Prize for sustained contributions to education. 
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Review: Stochastic Calculus for Finance I: The Binomial Asset Pricing Model
User Review  Joecolelife  GoodreadsShreve's book is an excellent introduction to basic options pricing. He not only deals with plain vanilla options, but also shows how the binomial model can be used to to value exotic options. Each ... Read full review
Contents
The Binomial NoArbitrage Pricing Model  1 
12 Multiperiod Binomial Model  8 
13 Computational Considerations  15 
14 Summary  18 
15 Notes  20 
Probability Theory on Coin Toss Space  25 
22 Random Variables Distributions and Expectations  27 
23 Conditional Expectations  31 
45 American Call Options  111 
46 Summary  113 
47 Notes  115 
Random Walk  119 
52 First Passage Times  120 
53 Reflection Principle  127 
An Example  129 
55 Summary  136 
24 Martingales  36 
25 Markov Processes  44 
26 Summary  52 
27 Notes  54 
State Prices  61 
32 RadonNikodym Derivative Process  65 
33 Capital Asset Pricing Model  70 
34 Summary  80 
35 Notes  83 
American Derivative Securities  89 
42 NonPathDependent American Derivatives  90 
43 Stopping Times  96 
44 General American Derivatives  101 
56 Notes  138 
InterestRateDependent Assets  143 
62 Binomial Model for Interest Rates  144 
63 FixedIncome Derivatives  154 
64 Forward Measures  160 
65 Futures  168 
66 Summary  173 
67 Notes  174 
Proof of Fundamental Properties of Conditional Expectations  177 
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