Team-LRN Team-LRN Want to learn more? We hope you enjoy this McGraw-Hill eBook! If you’d like more information about this book, its author, or related books and websites, please click here. Team-LRN MODELING FINANCIAL MARKETS Using Visual Basic.NET and Databases to Create Pricing, Trading, and Risk Management Models BENJAMIN VAN VLIET ROBERT HENDRY McGraw-Hill New York Chicago San Francisco Lisbon London Madrid Mexico City Milan New Delhi San Juan Seoul Singapore Sydney Toronto Team-LRN the United States of A merica. Except as permitted under the United States Copyright Act of 1976, no part of this publication may be reproduced or distributed in any form or by any means, or stored in a database or retrieval system, without the prior written permission of the publisher. 0-07-144288-X The material in this eBook also appears in the print version of this title: 0-07-141772-9 All trademarks are trademarks of their respective owners. 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Manufactured in Team-LRN CONTENTS Acknowledgments v SECTION ONE Trading System Development 1 1 Introduction 3 2 Development Methodology 11 SECTION TWO Introduction to VB.NET: Algorithm Development 31 3 Getting Started with VB.NET 33 4 Value Types and Operators 47 5 Control Structures 65 6 Procedures 81 7 Objects 109 8 Arrays 133 9 Problem Solving 151 10 .NET Type System 171 SECTION THREE Database Programming: Back Testing 185 11 Relational Databases 187 12 ADO.NET 201 13 Structured Query Language 219 14 Introduction to Data Structures 243 15 Advanced Data Structures 257 iii For more information about this title, click here. Team-LRN SECTION FOUR Advanced VB.NET: Implementation 269 16 Software Connectivity and Interoperability 271 17 Connecting to Trading Software 281 18 XML 301 19 XML Protocols in Financial Markets 323 SECTION FIVE Object-Oriented Programming: Risk Management 341 20 Unified Modeling Lanaguage 343 References 379 Acronyms 383 Index 385 iv Contents Team-LRN ACKNOWLEDGMENTS Andrew Kumiega, Nithiphong Vikitset, Anton Karadakov, David Norman, Keith Black, Pamela Reardon, Alex Deitz, Melanie Winter, Siripor n Treetanasaw at, Mulianto The, D ebbie Cernauskas , Michael Modica, Jerold Lavin, Duana Wooters, Thomas E. “Burma” Shea, Sagy Mintz, Kenneth M. Horjus, Mark McCracken, Julia Spaulding, Dave Kuipers, Rich Pombonyo, Paresh Akbari, Cliff Ensing, Brain Huyser, Mark Groenenboom, Bruce Rawlings, Gary Lahey, Hank Perrit, Jack Wing, Varsha Pitre, Michael Ubis, Jason Malkin, and Irma Baines. v Copyright © 2004 by The McGraw-Hill Companies, Inc . C lick here for terms of use. Team-LRN This page intentionally left blank. Team-LRN SECTION ONE Trading System Development I project that, [in the next ten years], the majority of mo ney managers will completely automate their trade entry decisions So, in the very near future, if you have a mouse in your hand, you will be too late. Blair Hull Copyright © 2004 by The McGraw-Hill Companies, Inc . C lick here for terms of use. Team-LRN [...]... have been completed Red text is used to show steps and milestones that have stopped and are currently placing the project at risk Green is used to show scope creep As we have discussed, scope creep can be the most dangerous portion of a project as stakeholders request additions to the project Unnecessary digressions can doom a project, and so it is important to focus on speci c and relevant functionalities... Java In addition you will need to understand how databases are constructed and accessed using computer code to do financial research and develop trading and risk management algorithms and systems All financial research requires data, and the efficient management and storage of data is crucial to the profitable operation of a trading system “Data is the lifeblood of electronic markets, ” as David Norman states... firm uses to access electronic exchange services” (Norman, 2001, p 242) An exchange “back end” is the point where an electronic order reaches the exchange and passes through to the exchange’s matching engine (Norman, 2001, p 242) Electronically routed orders pass from a firm’s front end to the exchange back end and then, once the trade has been executed, again to the front end as a trade-fill confirmation... derivatives markets, related products are often traded on different markets For example, Dow futures trade on the Chicago Board of Trade, S&P 500 futures trade on the Chicago Mercantile Exchange, and S&P 500 cash options trade on the Chicago Board Options Exchange Shares of IBM stock trade on the NYSE and Team-LRN Introduction 9 other stock exchanges, while IBM stock futures trade on One Chicago and NQLX and. .. package with connections to the options markets And Trading Technologies’ X_Trader software is a popular front-end software system for futures trading on electronic markets Thus, we could create a system to trade the CBOE’s S&P 500 cash options, via a market connection through MicroHedge’s API, that could also provide real-time delta hedging with the E-Mini S&P contract on the Chicago Mercantile Exchange... and hardware that connects to exchanges through their application programming interfaces (APIs) APIs can be thought of as “pipelines” to the market over which third parties, such as exchange member trading firms, can access exchange data and place orders electronically Installing and maintaining a communications network for data and order execution, however, involves a terrible tangle of interconnecting... methods 3 Prototype in Excel 4 Check profitability Phase II Back-Test 1 Gather data 2 Clean data 3 Perform in-sample/out-of-sample test Team-LRN Development Methodology 15 4 Check profitability Phase III Implement 1 Build vision and scope document 2 Build objects and program document 3 Program and document the system 4 Paper-trade and check profitability Phase IV Manage Portfolio and Risk 1 Monitor portfolio... routers, switches, and fiber optics, not to mention constant software redevelopment as exchanges upgrade their APIs (Norman, 2001) Rather than incurring the time and expense it takes to build from scratch, it is also possible and much less capital-intensive to license third-party trading software and take advantage of the exchange connections and built-in functionality for data feeds, order entry, and risk... document the structure of a software application Program and Document the System Having proved the trading system to be successful through insample and out-of-sample testing, we proceed with the crossover stage of the system development process In this stage we cross over from Excel’s cell-based environment to VB .NET by converting the system’s functionalities into programming code Paper-Trade and Check... about modeling financial instruments in code and putting the pieces, or models, together to create an automated trading or risk management system using a programming language, which in this case is VB .NET Let’s get started Financial markets are in a constant state of evolution, from buttonwood trees to trading floors to computer screens Over the last 40 years, owing to the invention of computers and the . please click here. Team-LRN MODELING FINANCIAL MARKETS Using Visual Basic. NET and Databases to Create Pricing, Trading, and Risk Management Models BENJAMIN VAN VLIET ROBERT HENDRY McGraw-Hill New. databases are constructed and accessed using computer code to do financial research and develop trading and risk management algorithms and systems. All financial research requires data, and the efficient. takes to build from scratch, it is also possible and much less capital-intensive to license third-party trading software and take advantage of the exchange connections and built-in functionality