| 000 | 04301camuu2200325 a 4500 | |
| 001 | 000045777462 | |
| 005 | 20131206180041 | |
| 008 | 131206s2014 flua b 001 0 eng | |
| 010 | ▼a 2013039513 | |
| 020 | ▼a 9781584884798 (hardback) | |
| 035 | ▼a (KERIS)REF000017288523 | |
| 040 | ▼a DLC ▼b eng ▼c DLC ▼e rda ▼d 211009 | |
| 050 | 0 0 | ▼a HG106 ▼b .S35 2013 |
| 082 | 0 0 | ▼a 332.0285/5133 ▼2 23 |
| 084 | ▼a 332.02855133 ▼2 DDCK | |
| 090 | ▼a 332.02855133 ▼b S345q | |
| 100 | 1 | ▼a Schlogl, Erik. |
| 245 | 1 0 | ▼a Quantitative finance : ▼b an object-oriented approach in C++ / ▼c Erik Schlogl. |
| 260 | ▼a Boca Raton : ▼b Chapman and Hall/CRC, ▼c 2014. | |
| 300 | ▼a xv, 338 p. : ▼b ill. ; ▼c 24 cm. | |
| 490 | 1 | ▼a Chapman & Hall/CRC financial mathematics series |
| 504 | ▼a Includes bibliographical references and index. | |
| 520 | ▼a "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. "-- ▼c Provided by publisher. | |
| 520 | ▼a "Preface In the forty years since the seminal article by Black and Scholes (1973), quantitative methods have become indispensable in the assessment, pricing and hedging of financial risk. This is most evident in the techniques used to price derivative financial instruments, but permeates all areas of finance. In fact, the option pricing paradigm itself is being increasingly applied in situations that go beyond the traditional calls and puts. In addition to more complex derivatives and structured financial products, which incorporate several sources of risk, option pricing techniques are employed in situations ranging from credit risk assessment to the valuation of real (e.g. plant) investment alternatives. As quantitative finance has become more sophisticated, it has also become more computationally intensive. For most of the techniques to be practically useful, efficient computer implementation is required. The models, especially those incorporating several sources of risk, have also become more complex. Nevertheless, they often exhibit a surprising amount of modularity and commonality in the underlying method and approach. Ideally, one would want to capitalise on this when implementing the models. C++ is the de facto industry standard in quantitative finance, probably for both of these reasons. Especially for models implemented "in-house" at major financial institutions, computationally intensive algorithms are typically coded in C++ and linked into a spreadsheet package serving as a front-end. The object-oriented and generic programming features of C++, when used properly, permit a high degree of code reusability across different models, and the possibility to encapsulate algorithms and data under a well-defined interface makes the maintenance of implemented models fa"-- ▼c Provided by publisher. | |
| 650 | 0 | ▼a Finance ▼x Mathematical models. |
| 650 | 0 | ▼a Investments ▼x Mathematical models. |
| 650 | 0 | ▼a C++ (Computer program language) |
| 830 | 0 | ▼a Chapman & Hall/CRC financial mathematics series. |
| 945 | ▼a KLPA |
Holdings Information
| No. | Location | Call Number | Accession No. | Availability | Due Date | Make a Reservation | Service |
|---|---|---|---|---|---|---|---|
| No. 1 | Location Main Library/Western Books/ | Call Number 332.02855133 S345q | Accession No. 111708049 | Availability Available | Due Date | Make a Reservation | Service |
Contents information
Table of Contents
A Brief Review of the C++ Programming Language
Getting started
Procedural programming in C++
Object-oriented features of C++
Templates
Exceptions
NamespacesBasic Building Blocks
The Standard Template Library (STL)
The Boost Libraries
Numerical arrays
Numerical integration
Optimisation and root search
The term structure of interest ratesLattice Models for Option Pricing
Basic concepts of pricing by arbitrage
Hedging and arbitrage?free pricing
Defining a general lattice model interface
Implementing binomial lattice models
Models for the term structure of interest ratesThe Black/Scholes World
Martingales
Option pricing in continuous time
Exotic options with closed form solutions
Implementation of closed form solutions
American optionsFinite Difference Methods
The object-oriented interface
The explicit finite difference method
The implicit finite difference method
The Crank/Nicolson schemeImplied Volatility and Volatility Smiles
Calculating implied distributions
Constructing an implied volatility surface
Stochastic volatilityMonte Carlo Simulation
Background
The generic Monte Carlo algorithm
Simulating asset price processes
Discretising stochastic differential equations
Predictor-corrector methods
Variance reduction techniques
Pricing instruments with early exercise features
Quasi-random Monte CarloThe Heath/Jarrow/Morton Model
The model framework
Gauss/Markov HJM
Option pricing in the Gaussian HJM framework
Adding a foreign currency
Implementing closed-form solutions
Monte Carlo simulation in the HJM framework
Implementing Monte Carlo simulationAppendix A: Interfacing between C++ and Microsoft Excel
Appendix B: Automatic Generation of Documentation Using DoxygenReferences
Index
Information Provided By: :
