#### Reading Lists for Beginning Quantitative Analysts

This post is part of a series of reading lists for beginner quantitative analysts. Other posts in the series concentrate on C++ Programming, Numerical Methods and Python Programming:

*Quant Reading List - Derivative Pricing*- Quant Reading List - C++ Programming
- Quant Reading List - Numerical Methods
- Quant Reading List - Python Programming

Not everybody wants to become a theoretical physicist. Some consider the academic environment too relaxed, others are not keen on the politics or the necessity to continually hunt for funding early in their career. A job in quantitative finance offers an attractive alternative.

Financial engineering has both strong theoretical and applied components, is immensely intellectually stimulating and fast-paced. A significant degree of background knowledge and an exceptional academic record are required even to achieve an interview. If you have recently decided that academia is not where your career path lies and you possess strong technical skills then the reading list outlined below will get you started towards becoming a quant.

This is the first part in a multi-part series on textbooks suitable for becoming a quantitative analyst. The remaining parts will focus on implementation, further mathematical excursions, interview skills and numerical methods. This article will concentrate on the theory of financial engineering for those who have not had an exposure to finance before.

## Mathematical Finance

A great place to start learning about the world of derivatives is with the classic text **Options, Futures, and Other Derivatives, 9th Edition** by John Hull. It is relatively light on the mathematics but covers a lot of ground across many financial instruments. It is a useful introduction to derivative markets for those who have not had prior exposure to finance.

Once you are comfortable with the concepts used within the financial industry the next step for a beginning quant analyst is to begin learning about arbitrage and the Black-Scholes model in a more mathematical manner. Dan Stefanica's **A Primer For The Mathematics Of Financial Engineering, 2nd Edition** will provide all of the calculusâ€”differentiation, integration, taylor expansionsâ€”needed to tackle the Black-Scholes equation. It will also cover "the Greeks" and basic risk neutral pricing. This is a great book for somebody who does not have the required undergraduate mathematical background needed for later texts.

At this stage you will be ready to tackle the more challenging texts such as Mark Joshi's **The Concepts and Practice of Mathematical Finance **. This is an excellent book and QuantStart highly recommendeds it. An alternative approach, which is popular with many quants, is provided by **Paul Wilmott Introduces Quantitative Finance, 2nd Edition**. The book is extremely comprehensive and provides many humourous explanations of concepts across mathematical finance.

To round out your knowledge then **Financial Calculus: An Introduction to Derivative Pricing** by Martin Baxter and Andrew Rennie, known colloquially as 'Baxter and Rennie' as well as **An Introduction to the Mathematics of Financial Derivatives, 3rd Edition** by Salih Neftci are also worth picking up. A good working knowledge of the contents of these books is sufficient theory for any front office desk quant interviews.

If you wish to delve deeper into the mathematical theory underpinning derivatives pricing then Bernt Oksendal's **Stochastic Differential Equations: An Introduction with Applications, 6th Edition** is a great start, as it has plenty of stochastic differential equation exercises to work through.

An essential book for Masters in Financial Engineering (MFE) students and practising volatility desk quants is the two volume set by Steven Shreve - Stochastic Calculus for Finance (**Stochastic Calculus for Finance I: The Binomial Asset Pricing Model** and **Stochastic Calculus for Finance II: Continuous-Time Models**). Vol I concentrates on the discrete pricing models while Vol II focuses on continuous models. Be warned that for the Vol II, a strong background in undergraduate mathematics is required - particularly in Real Analysis, Probability Theory and Measure Theory.

## Suggested Reading Chronology

**Options, Futures, and Other Derivatives, 9th Edition**- John Hull**A Primer For The Mathematics Of Financial Engineering, 2nd Edition**- Dan Stefanica**The Concepts and Practice of Mathematical Finance, 2nd Edition**- Mark Joshi**Financial Calculus: An Introduction to Derivative Pricing**- Martin Baxter, Andrew Rennie**Stochastic Calculus for Finance II: Continuous-Time Models**- Steven Shreve

In the next article texts on C++ implementation will be presented to help provide the knowledge you need to begin creating your own derivatives pricing tools.