Practical C++ Financial Programming

Practical C++ Financial Programming

Language: English

Pages: 396

ISBN: 1430267151

Format: PDF / Kindle (mobi) / ePub

Practical C++ Financial Programming is a hands-on book for programmers wanting to apply C++ to programming problems in the financial industry. The book explains those aspects of the language that are more frequently used in writing financial software, including the STL, templates, and various numerical libraries. The book also describes many of the important problems in financial engineering that are part of the day-to-day work of financial programmers in large investment banks and hedge funds. The author has extensive experience in the New York City financial industry that is now distilled into this handy guide. 

Focus is on providing working solutions for common programming problems. Examples are plentiful and provide value in the form of ready-to-use solutions that you can immediately apply in your day-to-day work. You’ll learn to design efficient, numerical classes for use in finance, as well as to use those classes provided by Boost and other libraries. You’ll see examples of matrix manipulations, curve fitting, histogram generation, numerical integration, and differential equation analysis, and you’ll learn how all these techniques can be applied to some of the most common areas of financial software development. These areas include performance price forecasting, optimizing investment portfolios, and more. The book style is quick and to-the-point, delivering a refreshing view of what one needs to master in order to thrive as a C++ programmer in the financial industry. 

  • Covers aspects of C++ especially relevant to financial programming.
  • Provides working solutions to commonly-encountered problems in finance.
  • Delivers in a refreshing and easy style with a strong focus on the practical.





















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you can use any standards-compliant C++ compiler such as gcc, llvm, or Visual C++. Once you compile the code and generate an executable file, the application can be run with the following results (exact numbers can vary depending on the random numbers used): above strike prob: 0.055 below strike prob: 0.946 between 28 and 32 prob: 0.512 As you can see, the application is able to determine with good precision the probability that the price will finish above or below the strike. This is

checking for the correct type in Python, you should be able to use C++ compile-time checking whenever possible. With boost::python, C++ types are used, and conversion into Python is done automatically and only when needed. Reduce programming effort: using the boost library, you can leverage a lot of code that has been developed to solve the specific problem of exporting C++ classes to Python. By using the Python API directly, you may encounter problems that have already been solved in

the last reference is also destroyed. Shared pointers achieve this behavior through the use of a reference counting mechanism. A counter is maintained by the shared pointer object, which determines how many copies exist for the referenced object. When the shared pointer is destroyed, it checks this counter to determine if other references exist. If the counter is positive, the pointed object is not destroyed. The counter is also updated when a new copy of the shared pointer is created. The

first part, the numerator is calculated as a result of multiplying all of the terms x – x j , something that is not necessary when i = j. The second part is the calculation of the denominator, which is very similar to the first step, as you can confirm looking at the original formula. The values of the denominator are stored in the local variable den. The third step consists of multiplying the value of y by the fraction defined by the numerator and denominator that were computed in the previous

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