1.

Record Nr.

UNINA9910438027703321

Autore

Shonkwiler Ronald W

Titolo

Finance with Monte Carlo / / by Ronald W. Shonkwiler

Pubbl/distr/stampa

New York, NY : , : Springer New York : , : Imprint : Springer, , 2013

ISBN

1-4614-8511-8

Edizione

[1st ed. 2013.]

Descrizione fisica

1 online resource (260 p.)

Collana

Springer Undergraduate Texts in Mathematics and Technology, , 1867-5506

Disciplina

332.01518282

Soggetti

Economics, Mathematical 

Mathematical models

Probabilities

Numerical analysis

Quantitative Finance

Mathematical Modeling and Industrial Mathematics

Probability Theory and Stochastic Processes

Numerical Analysis

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

Description based upon print version of record.

Nota di bibliografia

Includes bibliographical references (pages 245-246) and index.

Nota di contenuto

1. Geometric Brownian Motion and the Efficient Market Hypothesis -- 2. Return and Risk -- 3. Forward and Option Contracts and their Pricing -- 4. Pricing Exotic Options -- 5. Option Trading Strategies -- 6. Alternative to GBM Prices -- 7. Kelly's Criterion -- Appendices -- A. Some Mathematical Background Topics -- B. Stochastic Calculus -- C. Convergence of the Binomial Method -- D. Variance Reduction Techniques -- E. Shell Sort -- F. Next Day Prices Program -- References -- List of Notation -- List of Algorithms -- Index.

Sommario/riassunto

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, ©2009, ISBN: 978-0-387-87836-2; (with J. Herod) Mathematical Biology: An Introduction with Maple and Matlab, Second edition, ©2009, ISBN: 978-0-387-70983-3.