Technology Bundling: Innovation for Online Brokerage Services

Technology Bundling: Innovation for Online Brokerage Services

Alexander Y. Yap (Elon University, USA) and Wonhi Synn (Elon University, USA)
DOI: 10.4018/978-1-61350-162-7.ch005
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This chapter focuses on the theme of service innovation in the electronic brokerage sector. The discussion will cover the theories of “technology bundling” and how bundling together various technologies creates added value for the end-user. The proliferation of different e-trading systems raises the question of which systems provide better and more comprehensive bundled services to online stock traders. Many online brokers now provide low-cost transactions and financial research capabilities, so where is the next level of innovation? The objective of this chapter is to show that several innovations in broker e-services are critical in the following areas: a) how order processes are efficiently managed in financial e-markets; b) how responsive e-trading systems are in handling trading rules and regulations; c) how different systems address unique niches in financial e-markets; and d) improving systems stability and reliability. Combining different systems and technology features in these areas allow brokers to give much better services to their clients.
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Technology Bundling For Online Brokerage Service Innovation



In this chapter, we start analyzing an entire sector (the brokerage service sector) rather than one particular business organization in order to understand the case studies. The reason for using the entire sector as the unit of analysis is that the e-service problems and challenges are similar for the entire sector and is not unique to one organization alone (see next section, which discusses the problem of this sector). More so, the best way to illustrate e-service innovations of online brokers, we need to relate their unique e-service solutions to the problem facing the entire sector.

E-service in this chapter is defined as the service provided by electronic brokerage systems used to facilitate the buying and selling of publicly-traded corporate stocks and financial securities online. If you want to own/buy shares of stocks in companies like Microsoft or IBM, you can trade their shares electronically through e-brokerage systems like Scottrade, E-Trade, and Ameritrade. By trading shares online, you are using an electronic service similar to an online auction system, where sellers and buyers bid for the prices of different stocks and financial securities. Buyers want to get the cheapest prices and sellers want to sell at the highest prices, and the electronic trading systems helps them with that objective – this is a critical e-service for the trillion-dollar global financial market, where stocks, futures, options, bonds, foreign exchange and commodities are traded daily. These electronic brokers do not necessarily own stocks or financial securities. They process the orders electronically by channeling the orders through different networked financial market systems via the New York Stock Exchange, the London Stock Exchange, the Shanghai Stock Exchange and many other stock exchanges around the world.

Another critical e-service that needs to be defined is the service that assists online investors and traders make informed decisions whether to buy or sell stocks and when to execute such trade. E-brokers provide bundled e-services like real-time news reports, real-time charting of stock price movements, the demand and supply of stocks, stock analyst ratings, and research on the company’s financial health. This is how different e-services are “bundled” to help facilitate critical decisions in electronic financial markets. Different information systems, software applications, real-time databases, and networking technologies are used in the bundling of e-services.

In previous studies (Yap and Lin, 2001), the transaction capabilities of online trading systems as well as their knowledge-based components have been explored. These studies showed that earlier web-based trading systems took one to three minutes to execute market orders; whereas, more current systems can execute orders in one to three seconds. Transaction speed is not the real issue anymore. The real concern is whether traders are getting the “best price” for their trade executions. The demand for financial research and knowledge-base services online also needs to be more innovative to distinguish the uniqueness of e-services provided by different e-brokers. So the issue is what more can e-brokers provide their clients? In what areas can e-service innovation take place in the online brokerage sector? To get an idea of where innovation needs to happen, the problems of the online brokerage sector needs to be defined. Only then can we see how innovations in technologies and its bundling can provide solutions to such problems.

Defining the Problem in the Online Brokerage Sector

The problems with the electronic services provided by most online brokerage outfits are threefold. (1) Not all systems comply with the US Securities and Exchange Commission (SEC) Trading Requirements (rules and regulations) - Most information systems used for financial trading have loopholes in terms of preventing traders and investors from breaking SEC rules and US government laws. This is important because many amateur traders are not familiar with laws governing the trading of financial instruments in US financial markets. Breaking the law could be very costly and may prevent a trader from trading stocks again. This is a very serious problem not adequately addressed by e-service systems in the brokerage sector. (2) There is a need to connect fragmented financial electronic markets to reflect more realistic stock quotes. There are financial e-trading systems that are not as broadly networked to different financial electronic markets as other systems. This means that if your online brokerage service is only connected or bundled to two electronic financial markets while another online brokerage service is bundled to eight electronic financial markets, then your online broker’s system may not be able to get you the best “buy” and “sell” price for your stocks like the more connected/networked e-brokers can. Many traders have complained that their orders were not executed at the price they wanted, even if they saw that their stocks momentarily hit those price ranges. This happens when an online trading system is only connected to a few electronic markets. (3) Problem with Systems Stability and Reliability - Some online brokerage systems are not very stable and reliable, and therefore disrupting e-service more often during the electronic trading process. This is also a very serious problem. Imagine if your stock went down from $21.50 to $17.63 and you could not sell it because your online broker’s system was down for three hours. One of the purposes of this study is to test some of the more popular trading systems for more than a year and see how they hold up over time.


This research employs the ‘case research’ methodology. The researchers were involved in the actual use of the financial trading system and so data was acquired on a first-hand basis. The research uses the interpretive approach, which is essentially based on the unique experience of the user. The researchers gather the findings from direct experience and day-to-day interaction with the trading systems, its inherent technological features, and the customer support provided by the e-broker when the system is not working properly.

To be able to do an in-depth analysis, the researchers opened four (4) separate accounts so that four different popular e-trading systems can be tested and compared. However, due to limited space in writing this chapter, we can only cover two cases discussing two different e-trading systems. The two cases chosen for this chapter offered the more innovative e-services in the industry at the time of data gathering. Each e-trading system was used for more than a year. More than fifty trades were conducted on each system, with a frequency of at least once each week. Several systems features were explored to see what value it provided the user. Trading online naturally meant that the researchers acquired their information/data first hand. To validate and confirm some findings, the researchers also engage in dialogues with trading communities through message boards with user reviews.

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Table of Contents
Alexander Y. Yap
Chapter 1
Donald Crooks, John Slayton, John Burbridge
Much has been written about information technology and its role in reinventing financial markets. Today’s markets are truly global, and the... Sample PDF
Information Technology and Financial Markets: Risk, Volatility and the Quants
Chapter 2
Alexander Y. Yap
Trading anytime anywhere ubiquitously is rapidly becoming a popular trading practice in the financial marketspace. When highly volatile financial... Sample PDF
Trading Anytime Anywhere with Ubiquitous Financial Information Systems
Chapter 3
Michael Kampouridis, Shu-Heng Chen, Edward Tsang
In a previous work, inspired by observations made in many agent-based financial models, we formulated and presented the Market Fraction Hypothesis... Sample PDF
The Market Fraction Hypothesis under Different Genetic Programming Algorithms
Chapter 4
Xiaotie Deng, Feng Wang, Keren Dong
Algorithmic trading strategy making is a very important research issue which attracts more and more people’s interests. This chapter will introduce... Sample PDF
Algorithmic Trading Strategy Making: Algorithms and Applications
Chapter 5
Alexander Y. Yap, Wonhi Synn
This chapter focuses on the theme of service innovation in the electronic brokerage sector. The discussion will cover the theories of “technology... Sample PDF
Technology Bundling: Innovation for Online Brokerage Services
Chapter 6
Robert P. Schumaker, Hsinchun Chen
However, using computational approaches to predict stock prices using financial data is not unique. In recent years, interest has increased in... Sample PDF
Predicting Stock Price Movement from Financial News Articles
Chapter 7
Joe Kelley
Virtual reality offers the promise that finally, most of the capabilities of the human mind and senses can be harnessed to improve global financial... Sample PDF
Virtual Reality Support for Trading
Chapter 8
M. Kersch, G. Schmidt
Trading decisions in financial markets can be supported by the use of trading algorithms. To evaluate trading algorithms and to generate orders to... Sample PDF
Survey of Trading Systems for Individual Investors
Chapter 9
Joe Kelley
We sketch a large-scale computable general equilibrium model of the macroeconomy that includes modern features such as financial derivatives. This... Sample PDF
Grid Super-Computable General Equilibrium Models
Chapter 10
Seán O’Riain, Andreas Harth, Edward Curry
With increased dependence on efficient use and inclusion of diverse corporate and Web based data sources for business information analysis... Sample PDF
Linked Data Driven Information Systems as an Enabler for Integrating Financial Data
Chapter 11
Roger F.A. van Daalen
The move towards electronic trading was believed by some to narrow the scope of information available to traders, due to the difference between the... Sample PDF
The Persisting Human Element of the Electronic Trading Habit
Chapter 12
Joe Kelley
We present an extensive dynamic financial model that encompasses most models used today in finance and economics. We show that this model is a good... Sample PDF
DSP Acceleration for Dynamic Financial Models
Chapter 13
Joe Kelley
We propose to use FPGA (Field Programmable Gate Arrays) to solve the nearly insurmountable computational challenges of Financial Network Models.... Sample PDF
FPGA Speedup for Financial Network Models
Chapter 14
Alma Lilia Garcia Almanza, Serafín Martínez Jaramillo, Biliana Alexandrova-Kabadjova, Edward Tsang
The main advantage of creating understandable rules is that users are able to interpret and identify the events that may trigger bankruptcy. By... Sample PDF
Using Genetic Programming Systems as Early Warning to Prevent Bank Failure
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