C# for Financial Markets
Daniel J. Duffy
Language: English
Pages: 856
ISBN: 0470030089
Format: PDF / Kindle (mobi) / ePub
A practice-oriented guide to using C# to design and program pricing and trading models
In this step-by-step guide to software development for financial analysts, traders, developers and quants, the authors show both novice and experienced practitioners how to develop robust and accurate pricing models and employ them in real environments. Traders will learn how to design and implement applications for curve and surface modeling, fixed income products, hedging strategies, plain and exotic option modeling, interest rate options, structured bonds, unfunded structured products, and more. A unique mix of modern software technology and quantitative finance, this book is both timely and practical. The approach is thorough and comprehensive and the authors use a combination of C# language features, design patterns, mathematics and finance to produce efficient and maintainable software.
Designed for quant developers, traders and MSc/MFE students, each chapter has numerous exercises and the book is accompanied by a dedicated companion website, http://www.datasimfinancial.com/forum/viewforum.php?f=196&sid=f30022095850dee48c7db5ff62192b34, providing all source code, alongside audio, support and discussion forums for readers to comment on the code and obtain new versions of the software.
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} public void Y(double y) { // Set the y-coordinate yc=y; } } An example of use is: using System; public class TestPoint { public static void Main() { Point p=new Point(); p.X(2.3); p.Y(3.1); // Create point // Set x-coordinate // Set y-coordinate // Prints "Point(2.3, 3.1)" Console.WriteLine("Point({0}, {1})", p.X(), p.Y()); } } 27 28 C# for Financial Markets In this version we see an example of method overloading: we have defined three constructors that have the same name but different.
∂C . ∂t Analytic formulae for the Greeks are known: C ≡ ∂C = e(b−r )T N (d 1 ) ∂S ∂ 2C ∂ C n(d1 )e(b−r )T = ≡ √ 2 ∂S ∂S Sσ T √ ∂C VegaC ≡ = S T e(b−r)T n(d1 ) ∂σ C C ≡ ≡− (3.6) ∂C Sσ e(b−r)T n(d1 ) =− − (b − r )Se(b−r)T N (d 1 ) − r K e−r T N (d 2 ) √ ∂T 2 T where in general n(x) = dN (x). dx We now discuss the implementation of these formulae. We create a class that models option data and that has methods to calculate the option price and its sensitivities. 3.7.3 C# Implementation.
Rows have the same number of columns): // Rectangular arrays int N = 100; int M = 100; Point[,] mesh = new Point[N, M]; // Initialize in a column-major fashion for (int i = 0; i < N; ++i) { for (int j = 0; j < M; ++j) { mesh[i,j] = new Point(i+j, i+j); } } Since the element types are instances of a class we need to initialise their values in the body of the above loop. Instead of using a class we could have taken a struct and there would be no need to initialise the element values because they.
In the collection. s Is the collection read-only? 108 C# for Financial Markets <
Discuss bonds in more detail in Chapter 12. The current chapter has been written for pedagogical reasons and to introduce relevant notation. 7.2 EMBEDDED OPTIONALITY A bond issue may include a provision in its indenture that gives the bondholder and/or the issuer the facility to take some action against the other party. In these cases we speak of embedded optionality. Some examples are: s Call feature: this provision grants the issuer the right to partially or fully retire the debt before the.