An Introduction to Financial Option Valuation: Mathematics, Stochastics and Computation, Volume 13

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Cambridge University Press, Apr 15, 2004 - Business & Economics - 273 pages
This is a lively textbook providing a solid introduction to financial option valuation for undergraduate students armed with a working knowledge of a first year calculus. Written in a series of short chapters, its self-contained treatment gives equal weight to applied mathematics, stochastics and computational algorithms. No prior background in probability, statistics or numerical analysis is required. Detailed derivations of both the basic asset price model and the Black-Scholes equation are provided along with a presentation of appropriate computational techniques including binomial, finite differences and in particular, variance reduction techniques for the Monte Carlo method. Each chapter comes complete with accompanying stand-alone MATLAB code listing to illustrate a key idea. Furthermore, the author has made heavy use of figures and examples, and has included computations based on real stock market data.
 

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This is an extremely useful text in the understanding and working of Options focusing on Black-Scholes formula and understanding how and why options are of such great interest. I am a user with very strong math background but with no finance background; this book is written for highly intelligent readers who have a strong grasp of math and finance-or who wish to do so with additional references in these fields.
This is well written even for the lay person who wishes to gain a very satisfying and good understanding of options! Get this book if you are at all interested in options! (Oh, and I am a biochemistry major who is taking Options as a senior level math class....very challenging, but this text makes this very gratifying)!
 

Contents

III
1
IV
2
V
4
VI
6
VII
7
IX
8
X
11
XI
12
LXXXIV
133
LXXXV
135
LXXXVI
137
LXXXVIII
141
LXXXIX
144
XC
145
XCI
148
XCII
149

XII
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XIV
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XV
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XVI
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XVII
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XX
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XXI
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XXIII
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XXIV
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XXVII
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XXVIII
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XXIX
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XXX
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XXXIII
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XXXIV
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XXXV
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XXXVI
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XXXVII
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XL
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XLI
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XLII
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XLIII
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XLIV
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XLV
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XLVI
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XLVII
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XLVIII
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XLIX
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L
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LI
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LII
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LIII
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LIV
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LV
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LVI
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LVII
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LVIII
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LIX
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LX
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LXI
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LXII
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LXIII
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LXIV
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LXVI
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LXVII
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LXVIII
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LXIX
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LXXI
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LXXII
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LXXIV
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LXXV
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LXXVI
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LXXVII
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LXXVIII
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LXXIX
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LXXX
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LXXXII
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LXXXIII
131
XCIII
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XCIV
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XCV
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XCVI
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XCVII
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XCVIII
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XCIX
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C
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CI
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CII
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CIII
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CIV
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CV
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CVI
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CVII
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CVIII
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CIX
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CX
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CXI
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CXII
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CXIII
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CXIV
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CXV
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CXVI
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CXVII
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CXVIII
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CXIX
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CXX
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CXXI
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CXXII
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CXXIII
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CXXIV
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CXXV
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CXXVI
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CXXVII
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CXXVIII
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CXXIX
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CXXX
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CXXXII
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CXXXIV
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CXXXV
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CXXXVI
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CXXXVII
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CXXXVIII
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CXXXIX
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CXL
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CXLI
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CXLII
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CXLIII
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CXLIV
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CXLV
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CXLVI
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CXLVII
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CXLVIII
260
CXLIX
261
CL
262
CLI
265
CLII
267
CLIII
271
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About the author (2004)

Des Higham is a Professor of Mathematics at the University of Strathclyde. His previous books include MATLAB Guide (with Nicholas J. Higham, 2005) and Learning LaTeX (with David F. Griffiths, 1997).

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