This text introduces upper division undergraduate/beginning graduate
students in mathematics, finance, or economics, to the core topics of a
beginning course in finance/financial engineering. Particular emphasis
is placed on exploiting the power of the Monte Carlo method to
illustrate and explore financial principles. Monte Carlo is the uniquely
appropriate tool for modeling the random factors that drive financial
markets and simulating their implications.
The Monte Carlo method is introduced early and it is used in conjunction
with the geometric Brownian motion model (GBM) to illustrate and analyze
the topics covered in the remainder of the text. Placing focus on Monte
Carlo methods allows for students to travel a short road from theory to
practical applications.
Coverage includes investment science, mean-variance portfolio theory,
option pricing principles, exotic options, option trading strategies,
jump diffusion and exponential Lévy alternative models, and the Kelly
criterion for maximizing investment growth.
Novel features:
- inclusion of both portfolio theory and contingent claim analysis in a
single text
- pricing methodology for exotic options
- expectation analysis of option trading strategies
- pricing models that transcend the Black-Scholes framework
- optimizing investment allocations
- concepts thoroughly explored through numerous simulation exercises
- numerous worked examples and illustrations
The mathematical background required is a year and one-half course in
calculus, matrix algebra covering solutions of linear systems, and a
knowledge of probability including expectation, densities and the normal
distribution. A refresher for these topics is presented in the
Appendices. The programming background needed is how to code branching,
loops and subroutines in some mathematical or general purpose language.
The mathematical background required is a year and one-half course in
calculus, matrix algebra covering solutions of linear systems, and a
knowledge of probability including expectation, densities and the normal
distribution. A refresher for these topics is presented in the
Appendices. The programming background needed is how to code branching,
loops and subroutines in some mathematical or general purpose language.
Also by the author: (with F. Mendivil) Explorations in Monte
Carlo, (c)2009, ISBN: 978-0-387-87836-2; (with J. Herod) Mathematical
Biology: An Introduction with Maple and Matlab, Second edition,
(c)2009, ISBN: 978-0-387-70983-3.
