Learning Modern C++ for Finance: Foundations for Quantitative Programming (Fourth Early Release)

✍ Scribed by Daniel Hanson

• Publisher: O’Reilly Media, Inc.
• Year: 2023
• Tongue: English
• Leaves: 204
• Edition: 4
• Category: Library

✦ Synopsis

A lot of financial modeling has gravitated toward Python, R, and VBA, but many developers hit a wall with these languages when it comes to performance. This practical book demonstrates why C++ is still one of the dominant production-quality languages for financial applications and systems. Many programmers believe that C++ is too difficult to learn. Author Daniel Hanson demonstrates that this is no longer the case.

Financial programmers coming from Python or another interpreted language will discover how to leverage C++ abstractions that enable safer and quicker implementation of financial models. You'll also explore how popular open source libraries provide additional weapons for attacking mathematical problems. C++ programmers unfamiliar with financial applications will also benefit from this handy guide.

Before launching into programming in C++, it will be useful to present a brief overview of the language the C++ Standard Library, and the ways in which C++ continues to have a major presence in quantitative finance. You may have already felt intimidated by opinions and rumors claiming that C++ is extraordinarily difficult to learn and fraught with minefields. So, in this chapter, we will try to allay these fears by first debunking some of the common myths about C++, and then presenting straightforward examples to help you get up and running.

Learn C++ basics: syntax, inheritance, polymorphism, composition, STL containers, and algorithms
Dive into newer features and abstractions including functional programming using lambdas, task-based concurrency, and smart pointers
Employ common but nontrivial financial models in modern C++
Explore external open source math libraries, particularly Eigen and Boost
Implement basic numerical routines in modern C++
Understand best practices for writing clean and efficient code

✦ Table of Contents

1. An Overview of C++
   C++ and Quantitative Finance
   C++ 11: The Modern Era is Born
   Open Source Mathematical Libraries
   Debunking Myths About C++
   Compiled vs Interpreted Code
   The Components of C++
   C++ Language Features
   The C++ Standard Library
   Compilers and IDE’s
   Basic Review of C++
   Good Old “Hello World!”
   Simple Procedural Programming in C++
   C++ Syntax and Style Guidelines
   Mathematical Operators, Functions, and Constants in C++
   Standard Arithmetic Operators
   Mathematical Functions in the Standard Library
   Constants
   Conclusion
   References
2. Some Mechanics of C++
   The vector Container
   Setting and Accessing Elements of a vector
   Concluding Remarks on STL vectors
   Enum Constants and Classes
   Enum Constants
   Potential Conflicts with Enums
   Enum Classes
   Control Structures
   Conditional Branching
   Iterative Statements
   Aliases
   Type Aliases
   References
   Pointers
   Function and Operator Overloading
   Function Overloading
   Operator Overloading
   Summary
   References
3. Writing User-Defined Functions and Classes in Modules
   Using Modules to Write User-Defined Functions
   A First Example with Non-Member Functions
   Standard Library Header Units
   Modules Prevent Leaking into Other Modules
   A Black-Scholes Module Example
   User-Defined Class Implementation in Modules
   Using Namespaces with Modules
   Summary
4. Dates and Fixed Income Securities
   Representation of a Date
   1.1 Serial Representation and Date Differences
   1.2 Accessor Functions for Year, Month, and Day
   1.3 Validity of a Date
   1.4 Leap Years and Last Day of the Month
   1.5 Weekdays and Weekends
   1.6 Adding Years, Months, and Days
   1.6.1 Adding Years
   1.6.2 Adding Months and End-of-the-Month Cases
   1.6.3 Adding Days
   A Date Class Wrapper
   Class Declaration
   Public Member Functions and Operators
   Private Members and Helper Function
   Class Implementation
   Day Count Bases
   Yield Curves
   Deriving a Yield Curve from Market Data
   A Yield Curve Class
   A Linearly Interpolated Yield Curve Class Implementation
   A Bond Class
   Bond Payments and Valuation
   A Bond Class
   Bond Class Implementation
   A Bond Valuation Example
   Summary
   References
5. Linear Algebra
   Introduction
   valarray and Matrix Operations
   Arithmetic Operators and Math functions
   valarray as a Matrix Proxy
   Eigen
   Lazy Evaluation
   Eigen Matrices and Vectors
   Matrix and Vector Math Operations
   STL Compatibility
   Matrix Decompositions and Applications
   Future Directions: Linear Algebra in the Standard Library
   mdspan (P0009)
   BLAS Interface (P1673)
   Linear Algebra (P1385)
   Summary (Linear Algebra Proposals)
   Chapter Summary
   References
   About the Author