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title: "Financial Calculus: An Introduction to Derivative Pricing"
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# Financial Calculus: An Introduction to Derivative Pricing

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Buy Financial Calculus: An Introduction to Derivative Pricing by Baxter, Martin, Rennie, Andrew online on desertcart.ae at best prices. ✓ Fast and free shipping ✓ free returns ✓ cash on delivery available on eligible purchase.

Review: As an Msc financial engineering student I underwent a fairly rigerous treatment of martingale pricing but at a pace which left little room to appreciate what was really going on. True, this does not go into PDE methods at all, neither does it discuss practicalities however for what it does cover it is very clear. Along with Nefcti this really provides understanding for those whose mathematical background may have some gaps.
Review: I view this text as a complete outline or guide to the mathematics and ideas of financial calculus and derivative pricing.This is not meant disparagingly. The progression of concepts is clearly explained which is what the authors purport to do. Though discrete processes are discussed involving for instance binomial coefficients (combinations) in the beginning as examples, the real meat of the subject lies in probability applied to continuous processes. Hence knowledge of measure theoretic probability and martingales is required to rigorously complete the arguments. Brownian motion is used to model market fluctuation which stems from ideas of Bachelier. This motion has a Gaussian distribution as discovered by the eclectic genius of Einstein who had the insight to apply the heat equation in his solution. It models noise for instance in electrical engineering. Any differential equation containing this distribution term is referred to as a stochastic differential equation. A solution of it is called a diffusion. A systematic theory of these was developed by Ito with his so-called Ito calculus. The Black-Scholes equation which takes this Brownian motion fluctuation into account which ultimately lets you balance out risk is developed in the text. This equation surprisingly (or not!) is equivalent to the heat equation (there are numerous derivations of this on the web). The solution of the heat equation expressed as an integral has the Gaussian distribution as kernel or weight (Well how about that! Full circle.). As an aside this heat equation equivalence allows Black -Scholes to be solved by finite element methods with financial constraints on the boundaries if the integral proves difficult or not in closed form. The authors recommend the text Probability with Martingales (Cambridge Mathematical Textbooks) for the measure theoretic probability as well as measure theory and martingales. This goes for me too. In this text the Lebesgue integral is first developed through construction of a probability distribution on the unit interval with the use of Caratheodory's Extension Theorem (Williams proves this in an appendix) then a trivial extension to the real line. Elegant-even easier! First rate guide to financial calculus!

## Technical Specifications

| Specification | Value |
|---------------|-------|
| Best Sellers Rank | #379,528 in Books ( See Top 100 in Books ) #1,051 in Pure Mathematics #1,161 in Applied Mathematics #4,011 in Finance |
| Customer reviews | 4.4 4.4 out of 5 stars (50) |
| Dimensions  | 16.51 x 1.27 x 24.13 cm |
| Edition  | 17th ed. |
| ISBN-10  | 0521552893 |
| ISBN-13  | 978-0521552899 |
| Item weight  | 567 g |
| Language  | English |
| Print length  | 244 pages |
| Publication date  | 19 September 1996 |
| Publisher  | Cambridge University Press |

## Images

![Financial Calculus: An Introduction to Derivative Pricing - Image 1](https://m.media-amazon.com/images/I/71fgEyYjRkL.jpg)

## Customer Reviews

### ⭐⭐⭐⭐⭐ Review
*by H***M on 10 March 2013*

As an Msc financial engineering student I underwent a fairly rigerous treatment of martingale pricing but at a pace which left little room to appreciate what was really going on. True, this does not go into PDE methods at all, neither does it discuss practicalities however for what it does cover it is very clear. Along with Nefcti this really provides understanding for those whose mathematical background may have some gaps.

### ⭐⭐⭐⭐⭐ Review
*by P***K on 29 January 2016*

I view this text as a complete outline or guide to the mathematics and ideas of financial calculus and derivative pricing.This is not meant disparagingly. The progression of concepts is clearly explained which is what the authors purport to do. Though discrete processes are discussed involving for instance binomial coefficients (combinations) in the beginning as examples, the real meat of the subject lies in probability applied to continuous processes. Hence knowledge of measure theoretic probability and martingales is required to rigorously complete the arguments. Brownian motion is used to model market fluctuation which stems from ideas of Bachelier. This motion has a Gaussian distribution as discovered by the eclectic genius of Einstein who had the insight to apply the heat equation in his solution. It models noise for instance in electrical engineering. Any differential equation containing this distribution term is referred to as a stochastic differential equation. A solution of it is called a diffusion. A systematic theory of these was developed by Ito with his so-called Ito calculus. The Black-Scholes equation which takes this Brownian motion fluctuation into account which ultimately lets you balance out risk is developed in the text. This equation surprisingly (or not!) is equivalent to the heat equation (there are numerous derivations of this on the web). The solution of the heat equation expressed as an integral has the Gaussian distribution as kernel or weight (Well how about that! Full circle.). As an aside this heat equation equivalence allows Black -Scholes to be solved by finite element methods with financial constraints on the boundaries if the integral proves difficult or not in closed form. The authors recommend the text Probability with Martingales (Cambridge Mathematical Textbooks) for the measure theoretic probability as well as measure theory and martingales. This goes for me too. In this text the Lebesgue integral is first developed through construction of a probability distribution on the unit interval with the use of Caratheodory's Extension Theorem (Williams proves this in an appendix) then a trivial extension to the real line. Elegant-even easier! First rate guide to financial calculus!

### ⭐⭐⭐⭐ Review
*by M***C on 6 February 2012*

Okay this is an intro, but you should have at least an understanding of Calculus. The purpose of this book is not to teach the fundamentals of the math, it teachs the financial pricing theorems, how they are applied to various assets and derivitives, and how to apply it to larger models. The authors provide a very clear foundation of both discrete and continous processes. From Binomial to Brownian motion, this book packs in alot of material. In the later chapters the authors cover the various derivative and asset pricing models, which really puts everything together in a context which will show you how to apply everything. There is clear instruction for the novice in finance. The only real issue I have with this book is that it does cover alot, but is not everything you will ever need to know. But it is a great intro which will enable you to move onto the advanced books on the subject.

## Frequently Bought Together

- Financial Calculus: An Introduction to Derivative Pricing
- Options, Futures, and Other Derivatives, Global Edition
- Stochastic Calculus for Finance I: The Binomial Asset Pricing Model (Springer Finance)

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*Last updated: 2026-05-08*