The edition "Financial Applications Using Excel Add-in Development in C/C++" is regarded as a fundamental guide for those who want to elevate their Excel usage to a professional level by integrating it with compiled languages. Steve Dalton demonstrates how to create high-performance and flexible add-ins (XLL and DLL) that significantly extend Excel’s capabilities, transforming it into a tool for complex calculations and data analysis.
The author emphasizes applied financial tasks, but the material is universal and applicable in any field where data processing speed and reliability matter. The manual explains the inner workings of Excel, the principles of its API, approaches to memory management, and performance optimization. Separate chapters are dedicated to creating statistical functions, Monte Carlo models, yield curve construction, and the implementation of stochastic models such as SABR.
This textbook stands out by combining deep technical details of C/C++ with the practical development of financial applications. It is not just an API reference but a learning resource that shows how to write add-ins compatible with different versions of Excel while meeting modern performance standards.
Who Should Study This Guide?
It is aimed at professionals who face the challenge of developing Excel extensions:
- Financial engineers and analysts - for building fast derivative models, risk assessments, and complex simulations.
- C/C++ software developers - to learn how to create efficient add-ins and integrate existing libraries into Excel.
- Quants and researchers - for practical implementation of mathematical models directly in Excel.
- Corporate developers - to optimize business processes and reduce reliance on VBA.
- Technical specialists in banking - for maintaining applications handling large data volumes in real-time.
Thus, the edition is considered essential for those working at the intersection of finance and software development who want to enhance automation and performance in their solutions.
What Knowledge Will You Gain?
Reading this manual will provide a systematic understanding of Excel’s architecture and hands-on practice in creating add-ins. You will master:
- Creating DLL and XLL for Excel - development, compilation, and debugging processes explained.
- Working with the Excel C API - detailed description of functions and data structures.
- Performance optimization - memory management and multithreading methods.
- Financial algorithms - examples of Monte Carlo, SABR, CMS products.
- Interoperability with VBA - how to safely call C/C++ functions from macros.
- Practical implementation of statistical and mathematical functions.
Each section is structured so that developers not only absorb theory but can immediately apply it in practice.
Where and How Is the Content Applied?
The material is oriented toward real-world use and integration into workflows:
- Creating user-defined Excel functions that run significantly faster than VBA equivalents.
- Building financial models: yield curves, interest rate trees, stochastic simulations.
- Implementing data analysis algorithms, including interpolation and statistical functions.
- Embedding external C/C++ libraries in Excel for real-time calculations.
- Optimizing large Excel models by moving heavy computations into XLL add-ins.
In this way, Excel becomes a fully-fledged platform for engineering and financial computations.
The Developer's Opinion About the Book
This guide bridges the gap between Excel and low-level programming. In my work, I often encounter the limitations of VBA: with large models, performance degrades, and the code becomes difficult to maintain. The XLL and C/C++ approach solves these issues. I particularly value the chapters on memory and multithreading - aspects usually ignored in simpler courses but crucial for making add-ins production-ready. The manual not only describes the API but also offers architectural advice and strategies for building robust solutions.
The downside is the high entry threshold: readers must know C/C++ and be confident with compilers. But for professionals, this is not a drawback - it’s a natural requirement. Overall, this textbook is regarded as a desk reference for financial engineers and add-in developers. It provides practical techniques tested in real-world tasks and teaches how to build high-performance models that work faster and more reliably than conventional Excel formulas or VBA.
Daniel Thompson, Senior C++ Software Engineer
FAQ for "Financial Applications using Excel Add-in in C/C++"
1. How does this edition differ from VBA guides?
The main difference lies in performance and capabilities. VBA is convenient for rapid prototyping but limited in speed and functionality. This textbook shows how to implement the same tasks in C/C++ using the Excel API, offering performance gains by orders of magnitude. This is especially crucial for Monte Carlo models and large datasets.
2. What is "Financial Applications Using Excel Add-in Development in C/C++" about and why is it useful?
It explains how to develop reliable and fast Excel add-ins using C and C++. Unlike VBA or .NET add-ins, C/C++ enables writing high-performance functions that integrate directly with Excel. The author demonstrates how to design DLL libraries, connect them to Excel, create custom functions, and process arrays, strings, and dates. Special emphasis is placed on financial applications such as derivatives pricing, risk modeling, and time-series analysis.
3. Is the manual suitable for real-world project implementation?
Yes. The author provides not only code examples but also application architecture that can be directly deployed in financial systems. Topics such as error handling, memory management, function testing, and performance optimization are covered. These are critical, since mistakes in financial applications can be costly. Practical chapters include cases like option pricing models and time-series analysis, directly relevant to investment companies.
4. Can the guide be used outside finance?
Yes. While the main focus is on financial examples, the topics of API usage, memory handling, string manipulation, multithreading, and optimization apply to any domain. Developers can create engineering, statistical, or scientific add-ins using the same principles.
5. Does the textbook support Excel integration with C# or .NET?
No, it focuses specifically on C and C++. However, many practices - working with APIs, optimization, DLL structuring - are also useful to those later transitioning to .NET development. For C# tasks, VSTO or modern Excel add-ins are recommended, but this manual provides deep insights into Excel’s architecture that are beneficial regardless.
Information
| Author: | Steve Dalton | Language: | English |
| Publisher: | Wiley | ISBN-13: | 978-0470027974 |
| Publication Date: | September 4, 2007 | ISBN-10: | 0470027975 |
| Print Length: | 584 pages | Category: | C++ Books |
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