000 04777nam a22005055i 4500
001 978-1-4614-8511-7
003 DE-He213
005 20140220082832.0
007 cr nn 008mamaa
008 130917s2013 xxu| s |||| 0|eng d
020 _a9781461485117
_9978-1-4614-8511-7
024 7 _a10.1007/978-1-4614-8511-7
_2doi
050 4 _aHB135-147
072 7 _aKF
_2bicssc
072 7 _aMAT003000
_2bisacsh
072 7 _aBUS027000
_2bisacsh
082 0 4 _a519
_223
100 1 _aShonkwiler, Ronald W.
_eauthor.
245 1 0 _aFinance with Monte Carlo
_h[electronic resource] /
_cby Ronald W. Shonkwiler.
264 1 _aNew York, NY :
_bSpringer New York :
_bImprint: Springer,
_c2013.
300 _aXIX, 250 p. 70 illus., 17 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aSpringer Undergraduate Texts in Mathematics and Technology,
_x1867-5506
505 0 _a1. 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.
520 _aThis 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.
650 0 _aMathematics.
650 0 _aFinance.
650 0 _aNumerical analysis.
650 0 _aDistribution (Probability theory).
650 1 4 _aMathematics.
650 2 4 _aQuantitative Finance.
650 2 4 _aMathematical Modeling and Industrial Mathematics.
650 2 4 _aProbability Theory and Stochastic Processes.
650 2 4 _aNumerical Analysis.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9781461485100
830 0 _aSpringer Undergraduate Texts in Mathematics and Technology,
_x1867-5506
856 4 0 _uhttp://dx.doi.org/10.1007/978-1-4614-8511-7
912 _aZDB-2-SMA
999 _c96062
_d96062