Electronic and Algorithmic Trading Technology: The Complete Guide
By Kendall Kim
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About this ebook
Electronic and algorithmic trading has become part of a mainstream response to buy-side traders’ need to move large blocks of shares with minimum market impact in today’s complex institutional trading environment. This book illustrates an overview of key providers in the marketplace. With electronic trading platforms becoming increasingly sophisticated, more cost effective measures handling larger order flow is becoming a reality. The higher reliance on electronic trading has had profound implications for vendors and users of information and trading products. Broker dealers providing solutions through their products are facing changes in their business models such as: relationships with sellside customers, relationships with buyside customers, the importance of broker neutrality, the role of direct market access, and the relationship with prime brokers.
Electronic and Algorithmic Trading Technology: The Complete Guide is the ultimate guide to managers, institutional investors, broker dealers, and software vendors to better understand innovative technologies that can cut transaction costs, eliminate human error, boost trading efficiency and supplement productivity. As economic and regulatory pressures are driving financial institutions to seek efficiency gains by improving the quality of software systems, firms are devoting increasing amounts of financial and human capital to maintaining their competitive edge. This book is written to aid the management and development of IT systems for financial institutions. Although the book focuses on the securities industry, its solution framework can be applied to satisfy complex automation requirements within very different sectors of financial services – from payments and cash management, to insurance and securities. Electronic and Algorithmic Trading: The Complete Guide is geared toward all levels of technology, investment management and the financial service professionals responsible for developing and implementing cutting-edge technology. It outlines a complete framework for successfully building a software system that provides the functionalities required by the business model. It is revolutionary as the first guide to cover everything from the technologies to how to evaluate tools to best practices for IT management.
- First book to address the hot topic of how systems can be designed to maximize the benefits of program and algorithmic trading
- Outlines a complete framework for developing a software system that meets the needs of the firm's business model
- Provides a robust system for making the build vs. buy decision based on business requirements
Kendall Kim
Kendall Kim consults as a Business Analyst and lives in Greenwich, CT. He specializes in delivering technology solutions to Wall Street securities firms. In this role he has been responsible for the specification and implementation of large trading, risk management, and real-time market data systems. He has consulted and worked for firms such as UBS Investment Bank, Deutsche Bank, and Goldman Sachs. Kendall holds a bachelor's degree in Economics from Boston University, Boston, MA and a master's degree in Business Administration from The College of William and Mary, Williamsburg, VA.
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Electronic and Algorithmic Trading Technology - Kendall Kim
Index
Introduction
The objective of this book is to educate financial service professionals responsible for developing, managing, and implementing cutting-edge trade technology. It also provides a guide to institutional investors, broker-dealers, and software vendors with a better understanding of innovative enhancements that can cut transaction costs, minimize human error, boost trading efficiency, and supplement productivity. Economic and regulatory pressures also have an effect in improving technology. Regulation NMS, and the fundamental principle of obtaining the best price for investors when such price is immediately accessible, rather than executing a listed stock solely through an exchange is one regulatory enhancement. Electronic and algorithmic trading is increasingly becoming a mainstream response to institutional investors’ needs to move large blocks of shares with fewer transaction costs, negligible market impact, and information leakage. Constant innovations designed to cut costs and create new efficiencies in the securities industry have forced investment banking firms as well as institutional investment advisors to rethink their trading operations. Algorithms are clearly cost-effective methods for executing low-maintenance equity trades. They have led to head-count shifts and reductions in sales and trading desks. These automated trades can meet the demand of customers who want lower transaction costs. The growth of new technologies in electronic and algorithmic trading has created a new industry for financial professionals. Appropriate protocols and efficient process infrastructure are required to help grow this industry. Investment banks, agency brokers, and investment managers require efficient front-to-back securities processing cycles to make this happen. The whole trade process, which includes execution, confirmation, and reconciliation, has to be in place in order for trades to occur. This book will cover in more detail how this process flow is structured.
Overview of Electronic and Algorithmic Trading
1.1 Overview
Electronic and algorithmic trading has become a significantly larger focus for financial institutions, securities regulators, and different exchanges. Market developments along with tougher regulations have made equity trading more complicated and less profitable. Automation and new technologies have changed the trading game dramatically in the past five years or so. The speed of financial information is outpacing anyone’s forecast. Higher networking speeds through financial engineering are altering the way traders and market participants address the demand for lower commissions and enabling the creation of automated model-based trading. The increase in competition for lower transaction costs has been forcing firms to invest significantly in their trading and processing infrastructure. The proliferation of electronic and algorithmic trading has been staggering on Wall Street. A broker can no longer fulfill order flow without using some method of electronic execution. The traditional clerks running across the trading floor with order slips and men in pits negotiating bid prices may soon be replaced by the sound of traders typing in their parameters onto their broker screens to facilitate order flow using programs and algorithms. In the past, there were limited opportunities to apply technology to the trading process or interact directly with exchanges and market participants. This has all changed with the introduction of programs, direct market access, and algorithmic trading. Although automated trade flow can carry connotations of computerized trading taking over without human supervision, the actual decisions to buy and sell are made by people, not computers. Humans make the final trading decisions and the parameters behind implementing them, but computers may calculate algorithms that route the order flow efficiently and in many cases, computers help the breakdown of trades to each individual stock within the program.
1.2 The Emergence of Electronic Trading Networks
Algorithmic trading has become another method for large brokerage firms to grasp an advantage over their competitors for lower-cost executions; however, smaller players such as agency brokers also see algorithms as a way to level the playing field and infringe on the bigger bulge-bracket firms. Algorithmic trading originated on proprietary trading desks of investment banking firms. It began to expand executing client orders because of new markets and the need to remain in line with new players in the brokerage industry. This has created a more competitive environment for traditional dealers with services such as direct market access through the Internet. According to Manny Santayana, managing director at Credit Suisse’s Advanced Execution Services Group (AES), Algorithmic trading has created a level playing field which ultimately benefits shareholders with smarter, more efficient, and cheaper execution.
NASDAQ and other electronic exchanges have threatened the traditional model of the New York Stock Exchange with their phone-based order flow, and its utilization of floor