This book is an introduction to stochastic analysis and quantitative finance it includes both
theoretical and computational methods. Topics covered are stochastic calculus option pricing
optimal portfolio investment and interest rate models. Also included are simulations of
stochastic phenomena numerical solutions of the Black-Scholes-Merton equation Monte Carlo
methods and time series. Basic measure theory is used as a tool to describe probabilistic
phenomena. The level of familiarity with computer programming is kept to a minimum. To make the
book accessible to a wider audience some background mathematical facts are included in the
first part of the book and also in the appendices. This work attempts to bridge the gap between
mathematics and finance by using diagrams graphs and simulations in addition to rigorous
theoretical exposition. Simulations are not only used as the computational method in
quantitative finance but they can also facilitate an intuitive and deeper understanding of
theoretical concepts. Stochastic Analysis for Finance with Simulations is designed for readers
who want to have a deeper understanding of the delicate theory of quantitative finance by doing
computer simulations in addition to theoretical study. It will particularly appeal to advanced
undergraduate and graduate students in mathematics and business but not excluding
practitioners in finance industry.
