This review is written for many of those switching to quantitative finance from other fields. Hull's book will become an essential foundation-builder for such people.
Let's assume you want to become a quantitative analyst or a risk manager switching from another, preferably quantitative, field. Then in order to get a job you need to have the following:
1. Knowledge of derivatives and markets;
2. Knowledge of statistical methods and data analysis with applications in finance;
3. Computational methods supported by software such as C++ and R to be able to apply theoretical knowledge obtained in 1 and 2;
4. Proof that you have decent understanding of finance through obtaining a designation such as PRM (Since, under our assumption, you enter finance from a different field, you don't have work experience. That is why PRM will be the most suitable for you as you will just need to be well prepared academically to pass the exams and get the designation).
The book under review will be absolutely essential for you for clearing steps 1 and 4. It has been written with the care for the reader in mind.
Hull, in contrast to many other authors, does not try to show off his intellectual superiority by using complicated and abstract language which would normally be designed to make the reader feel miserable. In contrast, he wants the reader to become knowledgeable by carefully guiding him through complicated topics with numerous examples and explanations. The friendliness of exposition does not mean that the rigor is lost though; the book is written with the perfect rigor, but it is achieved without making it too dry and abstract. The scope of coverage is amazing: all major aspects of derivatives and markets connected with them have been covered. Particular importance is that Hull gives lots of practical exercises which should be completed to obtain fluency in the theory and its applications. Only after you work carefully through the book, you can strengthen your skills of (1) by working through other texts, such as Joshi's The Concepts and Practice of Mathematical Finance (Mathematics, Finance and Risk) and More mathematical finance.
To get the grasp of (2) and (3), you can work through Ruppert's Statistics and Data Analysis for Financial Engineering (Springer Texts in Statistics) and Joshi's C++ Design Patterns and Derivatives Pricing (Mathematics, Finance and Risk).
This book, together with the official handbook, will definitely prepare you for PRM, thus fulfilling (4). Without it, preparation for the PRM will be difficult, if you don't have prior financial experience.
I don't know about another high-quality, reader-friendly resource which could compete with Hull's book in providing a strong foundation in becoming a serious financial engineer. When one is entering new field, a good starting book is essential as it will either make the transition easy or frustrating. The book under review will make such transition painless.