An innovative textbook for use in advanced undergraduate and graduate courses; accessible to students in financial mathematics, financial engineering and economics.
Introduction to the Economics and Mathematics of Financial Markets fills the longstanding need for an accessible yet serious textbook treatment of financial economics. The book provides a rigorous overview of the subject, while its flexible presentation makes it suitable for use with different levels of undergraduate and graduate students. Each chapter presents mathematical models of financial problems at three different degrees of sophistication: single-period, multi-period, and continuous-time. The single-period and multi-period models require only basic calculus and an introductory probability/statistics course, while an advanced undergraduate course in probability is helpful in understanding the continuous-time models. In this way, the material is given complete coverage at different levels; the less advanced student can stop before the more sophisticated mathematics and still be able to grasp the general principles of financial economics.
The book is divided into three parts. The first part provides an introduction to basic securities and financial market organization, the concept of interest rates, the main mathematical models, and quantitative ways to measure risks and rewards. The second part treats option pricing and hedging; here and throughout the book, the authors emphasize the Martingale or probabilistic approach. Finally, the third part examines equilibrium models―a subject often neglected by other texts in financial mathematics, but included here because of the qualitative insight it offers into the behavior of market participants and pricing.

Introduction to the Economics and Mathematics of Financial Markets

Business & Money

Cvitanic, Jakša

Zapatero, Fernando

Economics

The MIT Press

Solutions manual for an innovative textbook accessible not only to graduate students in mathematical finance and financial engineering but also to undergraduate students and graduate students not specializing in finance.
Solutions manual for an innovative textbook accessible not only to graduate students in mathematical finance and financial engineering but also to undergraduate students and graduate students not specializing in finance. Contains solutions for selected end-of-chapter problems.

Solutions Manual for Introduction to the Economics and Mathematics of Financial Markets (Mit Press)

MIT Press]

Financial Mathematics is an exciting, emerging field of application. The five sets of course notes in this book provide a bird's eye view of the current "state of the art" and directions of research. For graduate students it will therefore serve as an introduction to the field while reseachers will find it a compact source of reference. The reader is expected to have a good knowledge of the basic mathematical tools corresponding to an introductory graduate level and sufficient familiarity with probabilistic methods, in particular stochastic analysis.

Financial Mathematics: Lectures given at the 3rd Session of the Centro Internazionale Matematico Estivo (C.I.M.E.) held in Bressanone, Italy, July 8-13, 1996 (Lecture Notes in Mathematics, 1656)

Biais, Bruno

Björk, Thomas

El Karoui, Nicole

Jouini, Elyes

Rochet, J.C.

Springer

Contract Theory in Continuous-Time Models (Springer Finance)

In recent years there has been a significant increase of interest in continuous-time Principal-Agent models, or contract theory, and their applications. Continuous-time models provide a powerful and elegant framework for solving stochastic optimization problems of finding the optimal contracts between two parties, under various assumptions on the information they have access to, and the effect they have on the underlying "profit/loss" values. This monograph surveys recent results of the theory in a systematic way, using the approach of the so-called Stochastic Maximum Principle, in models driven by Brownian Motion. Optimal contracts are characterized via a system of Forward-Backward Stochastic Differential Equations. In a number of interesting special cases these can be solved explicitly, enabling derivation of many qualitative economic conclusions.

Zhang, Jianfeng

Reference

There has been increased interest in continuous-time Principal-Agent models and their applications. This monograph surveys results of the theory using the approach of the so-called Stochastic Maximum Principle, in models driven by Brownian Motion.

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