Quantitative Finance

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A01=Erik Schloegl
A01=Erik Schlogl
advanced quantitative analysis
Age Group_Uncategorized
Age Group_Uncategorized
American Put Option Prices
Antithetic Sampling
Arbitrage Free Price
asset pricing theory
Author_Erik Schloegl
Author_Erik Schlogl
automatic-update
B09=Dilip B. Madan
B09=M.A.H. Dempster
Binomial Lattice
Binomial Lattice Model
C++ classes and templates
C++ quantitative finance implementation
Category1=Non-Fiction
Category=PB
computational finance
Const Array
Constant Dividend Yield
COP=United States
Coupon Bond
Delivery_Delivery within 10-20 working days
derivative valuation
eq_isMigrated=2
eq_nobargain
extensible code building blocks
financial engineering
Finite Difference Methods
functional C++ code
Implied Volatilities
Inline Void
Instantaneous Forward Rate
Int Argc
Language_English
Member Function
methods and models of quantitative finance
methods in risk management and option pricing
Monte Carlo Estimate
Namespace Std
numerical simulation
Option Price
PA=Available
Price_€50 to €100
PS=Active
quantitative finance models
quantitative finance problems
risk management
Risk Neutral Densities
Risk Neutral Distribution
Risk Neutral Probability
Risk Neutral Probability Distribution
Risk Neutral Probability Measure
SN=Chapman & Hall/CRC Financial Mathematics Series
softlaunch
STL
stochastic modeling
Stochastic Volatility
Underlying Asset
web resource

Product details

  • ISBN 9781584884798
  • Weight: 676g
  • Dimensions: 156 x 234mm
  • Publication Date: 19 Nov 2013
  • Publisher: Taylor & Francis Inc
  • Publication City/Country: US
  • Product Form: Hardback
  • Language: English
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Quantitative Finance: An Object-Oriented Approach in C++ provides readers with a foundation in the key methods and models of quantitative finance. Keeping the material as self-contained as possible, the author introduces computational finance with a focus on practical implementation in C++.

Through an approach based on C++ classes and templates, the text highlights the basic principles common to various methods and models while the algorithmic implementation guides readers to a more thorough, hands-on understanding. By moving beyond a purely theoretical treatment to the actual implementation of the models using C++, readers greatly enhance their career opportunities in the field.

The book also helps readers implement models in a trading or research environment. It presents recipes and extensible code building blocks for some of the most widespread methods in risk management and option pricing.

Web ResourceThe author’s website provides fully functional C++ code, including additional C++ source files and examples. Although the code is used to illustrate concepts (not as a finished software product), it nevertheless compiles, runs, and deals with full, rather than toy, problems. The website also includes a suite of practical exercises for each chapter covering a range of difficulty levels and problem complexity.

Erik Schlögl currently is Professor and Director of the Quantitative Finance Research Centre at the University of Technology, Sydney (UTS), Australia. Erik received his doctorate in Economics from the University of Bonn, Germany, for work on term structure models and the pricing of fixed income derivatives and has gained broad-based experience in computational financial engineering. He has consulted for financial institutions and software developers in Europe, Australia and in the US. His research interests cover a broad area of quantitative finance, in particular model calibration, interest rate term structure modelling, credit risk and the integration of multiple sources of risk. He has published articles in a number of international journals, including Finance & Stochastics, Quantitative Finance, Risk and the Journal of Economic Dynamics and Control. In addition to UTS, he held positions at the University of New South Wales, Australia, and the University of Bonn, Germany.

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