Over the next few years, the proprietary trading and hedge fund industries will migrate largely to automated trade selection and execution systems. Indeed, this is already happening. While several finance books provide C++ code for pricing derivatives and performing numerical calculations, none approaches the topic from a system design perspective. This book will be divided into two sections-programming techniques and automated trading system ( ATS ) technology-and teach financial system design and development from the absolute ground up using Microsoft Visual C++.NET 2005. MS Visual C++.NET 2005 has been chosen as the implementation language primarily because most trading firms and large banks have developed and continue to develop their proprietary algorithms in ISO C++ and Visual C++.NET provides the greatest flexibility for incorporating these legacy algorithms into working systems. Furthermore, the .NET Framework and development environment provide the best libraries and tools for rapid development of trading systems.
The first section of the book explains Visual C++.NET 2005 in detail and focuses on the required programming knowledge for automated trading system development, including object oriented design, delegates and events, enumerations, random number generation, timing and timer objects, and data management with STL.NET and .NET collections. Furthermore, since most legacy code and modeling code in the financial markets is done in ISO C++, this book looks in depth at several advanced topics relating to managed/unmanaged/COM memory management and interoperability. Further, this book provides dozens of examples illustrating the use of database connectivity with ADO.NET andan extensive treatment of SQL and FIX and XML/FIXML. Advanced programming topics such as threading, sockets, as well as using C++.NET to connect to Excel are also discussed at length and supported by examples.
The second section of the book explains technological concerns and design concepts for automated trading systems. Specifically, chapters are devoted to handling real-time data feeds, managing orders in the exchange order book, position selection, and risk management. A .dll is included in the book that will emulate connection to a widely used industry API ( Trading Technologies, Inc.'s XTAPI ) and provide ways to test position and order management algorithms. Design patterns are presented for market taking systems based upon technical analysis as well as for market making systems using intermarket spreads.
As all of the chapters revolve around computer programming for financial engineering and trading system development, this book will educate traders, financial engineers, quantitative analysts, students of quantitative finance and even experienced programmers on technological issues that revolve around development of financial applications in a Microsoft environment and the construction and implementation of real-time trading systems and tools.
* Teaches financial system design and development from the ground up using Microsoft Visual C++.NET 2005.
* Provides dozens of examples illustrating the programming approaches in the book
* Chapters are supported by screenshots, equations, sample Excel spreadsheets, programming code and interactive CDROM

The financial markets industry is at the same crossroads as the automotive industry in the late 1970s. Margins are collapsing and customization is rapidly increasing. The automotive industry turned to quality and its no coincidence that in the money management industry many of the spectacular failures have been due largely to problems in quality control. The financial industry in on the verge of a quality revolution.
New and old firms alike are creating new investment vehicles and new strategies that are radically changing the nature of the industry. To compete, mutual funds, hedge fund industries, banks and proprietary trading firms are being forced to quicklyy research, test and implement trade selection and execution systems. And, just as in the early stages of factory automation, quality suffers and leads to defects. Many financial firms fall short of quality, lacking processes and methodologies for proper development and evaluation of trading and investment systems.
Authors Kumiega and Van Vliet present a new step-by-step methodology for such development. Their methodology (called K-V) has been presented in numerous journal articles and at academic and industry conferences and is rapidly being accepted as the preferred business process for the institutional trading and hedge fund industries for development, presentation, and evaluation of trading and investment systems. The K-V model for trading system development combines new product development, project management and software development methodologies into one robust system. After four stages, the methodology requires repeating the entire waterfall for continuous improvement.
The discussion quality and its applications to the front office is presented using lessons learned by the authors after using the methodology in the real world. As a result, it is flexible and modifiable to fit various projects in finance in different types of firms. Their methodology works equally well for short-term trading systems, longer-term portfolio management or mutual fund style investment strategies as well as more sophisticated ones employing derivative instruments in hedge funds.
Additionally, readers will be able to quickly modify the standard K-V methodology to meet their unique needs and to quickly build other quantitatively drive applications for finance. At the beginning and the end of the book the authors pose a key question: Are you willing to change and embrace quality for the 21st century or are willing to accept extinction?
The real gem in this book is that the concepts give the reader a road map to avoid extinction.
* Presents a robust process engineering framework for developing and evaluating trading and investment systems
* Best practices along the step-by-step process will mitigate project risk, model risk, and ensure data quality.
* Includes a quality model for backtesting and managing market risk of working systems.