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Stochastic 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 calculus-based 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 self-contained treatment of the probability theory needed for stochastic calculus, including Brownian motion and its properties. Advanced topics include foreign exchange models, forward measures, and jump-diffusion processes.

This book is being published in two volumes. The first volume presents the binomial asset-pricing model primarily as a vehicle for introducing in the simple setting the concepts needed for the continuous-time 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 Co-Founder of the Carnegie Mellon MS Program in Computational Finance and winner of the Carnegie Mellon Doherty Prize for sustained contributions to education.

Average Customer Rating:

Best SC book ever

Customer Rating:

I have the 1st version (pdf), so I hesitated before I make the purchase. Now it turns out that the book is worthy every buck. 1. Use coin tossing space consistently as working sample. Very intuitive, never get the idea lost in abstract concepts. 2. Detailed workout of examples. Very good for self study. 3. Plenty of hands-on homeworks. Not necessarily very challenging. But provide good amount of extra examples. If anything the book can add, I hope it can supply implementations, in Matlab or C++. Well, it may be far stretching for a math book.

Good book	Customer Rating:
excellent book for anybody who is a student of financial calculus . One can get some insight into how financial managers plan portfolios and how they make investment decisions.

Great intro for discrete-time models

Customer Rating:

I studied this book for the first half of a fourth year financial maths subject at univerisity of melbourne. Binomial models are the only feasible model for pricing american derivatives at the moment, so it is worthwhile to learn the mechanics of such practical models. The author proves all his theorems elegantly using mathematical induction. He even uses proability theory and discrete-time martingale theories to simplify the valuation of European-type derivatives (just take conditional expectations and discount straight back to the current time -- instead of doing those backward averaging and discount node by node; both methods are done under the risk-neutral measure).

fantabulous!!!	Customer Rating:
i have read so many books on financial engineering but this one makes all theories so streamlined!!! I read Neftci and I liked it. After reading this, all steps come out clear. The part 2 is fascinating as well. Hail Mugambo!

Great balance between technical and intuitive

Customer Rating:

This book seemed to strike the perfect balance between going through the necessary math and getting the points across without pushing the non-PhD reader overboard. This is a great book for semi-mathematical types who practice in finance, or for mathematicians who are looking to understand the basics of finance. I, being the former, enjoyed having the concepts of stochastic calculus and martingale theory being presented in the absolute simplest of fashions.