Introducing Financial Mathematics

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A01=Mladen Victor Wickerhauser
advanced financial mathematics applications
asset pricing theory
Author_Mladen Victor Wickerhauser
Backward Induction
Binomial Tree
Black Scholes Formula
Bond Discounts
Call Option
Category=PBT
Category=PBW
computational finance methods
convex analysis
Convex Cone
CRR Model
Cumulative Distribution Function
derivatives
discrete time models
Dual Cone
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
European Style Call
European Style Call Option
Ex-dividend Date
Forward Contract
Forward Start
Forward Start Option
Implied Volatility Surface
linear algebra
Macsyma scripts
Margin Account
market data
mathematical modeling
Matlab
Octave
Octave/Matlab
OctaveMatlab
Option Premiums
pricing
programming
quantitative finance
real data
Risk Neutral Probabilities
Riskless Asset
Riskless Return
Spot Price
stochastic processes
Strike Price
Underlying Asset
Underlying Asset Prices
volatility

Product details

  • ISBN 9781032359854
  • Weight: 562g
  • Dimensions: 156 x 234mm
  • Publication Date: 09 Nov 2022
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Hardback
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Introducing Financial Mathematics: Theory, Binomial Models, and Applications seeks to replace existing books with a rigorous stand-alone text that covers fewer examples in greater detail with more proofs. The book uses the fundamental theorem of asset pricing as an introduction to linear algebra and convex analysis. It also provides example computer programs, mainly Octave/MATLAB functions but also spreadsheets and Macsyma scripts, with which students may experiment on real data.The text's unique coverage is in its contemporary combination of discrete and continuous models to compute implied volatility and fit models to market data. The goal is to bridge the large gaps among nonmathematical finance texts, purely theoretical economics texts, and specific software-focused engineering texts.

Mladen Victor Wickerhauser is professor of mathematics and statistics at Washington University, St. Louis. He holds a PhD from Yale University. ​Professor Wickerhauser’s research interests include harmonic analysis, wavelets, and numerical algorithms for data compression. He has six US patents and 118 publications, one of which led to an algorithm used by the FBI to encode fingerprint images.

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