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Incorporating Real-Time Financial Data Into Business Curricula

Posted on: Tuesday, 29 November 2005, 03:02 CST

By Holowczak, Richard D

ABSTRACT.

The need to incorporate business and economic data into curricula has been a driver of technology adoption in business schools. Web- based resources and professional data services, such as Reuters and Bloomberg, are being increasingly adopted by business programs to meet this need. There are clear trade-offs to adopting either technological approach. In this article, the author presents examples of incorporating real-time data from professional data services into a variety of business topics.

Several colleges and universities have created academic trading rooms that include professional data and news services that are on par with those found at major brokerage houses, banks, and other institutions in the financial services industry (Alexander, Heck, & McElreath, 2001; Shim, 2003). A common feature of such trading rooms is the real-time market data feeds that can be used to populate graphs, spreadsheets, quote displays, and other front-end applications. For most academic purposes, however, the applications used the most in business curricula rely on the ability to query and manipulate historical data. As the World Wide Web has matured, a number of stable and reliable commercial Web sites now offer increasingly robust access to financial data (e.g., Michelson & Smith, 1999; Pettijohn, Ragan, & Ragan, 2003; Woerheide, 1999; and www.finance.yahoo.com). Given the breadth and depth of data found online for free (or at nominal cost to students), the question arises as to the relative merits of maintaining dedicated academic trading floors that support real-time data.

In this article, I aim to present a number of topics in business that lend themselves to investigation and demonstration using real- time data from commercial data providers. Clearly, such topics have been covered by countless classroom lectures without the aid of technology, beyond perhaps a financial calculator. I believe that the examples presented here provide an interesting perspective on incorporating real-time financial data into a business curriculum.

Our own trading floor, the Bert W. and Sandra Wasserman Trading Floor-Subotnick Financial Services Center in the Zicklin School of Business at Baruch College, City University of New York (CUNY), has been in operation since 2000 and contains a 40-workstation trading floor that receives real-time market data and news via Reuters 3000Xtra service and the Reuters Kobra and PowerPlus Pro applications. Our trading floor has had to deal with all of the issues presented in this article, and we have also implemented a number of the examples demonstrated below in dozens of accounting, computer information systems, finance, economics, international business, and management classes.

The remainder of this article is organized as follows. The following section will outline the requirements for bringing real- time data into an academic trading room. Examples of two different commercial data service tools are presented next, followed by examples of topics that are amenable to supplementation using real- time data.

Working With Real-Time Data in an Academic Trading Room

A number of issues require due consideration when real-time market data are to be delivered in a trading floor environment. Each of the leading data providers, Reuters/Bridge, Bloomberg, Tradestation, eSpeed, and others, have multiple delivery options that include dedicated integrated services digital network (ISDN), digital subscriber line (DSL), or leased line (Tl in North America or El service in Europe) circuits, and direct delivery over the institution's existing Internet connection. Leased or dedicated lines have the advantage of reliability and performance guarantees, but require dedicated hardware and possibly costly monthly service fees (depending on location) to support them. For example, a Tl circuit in Manhattan costs between $300 and $500 per month to lease. At first, delivering data over an institution's existing Internet link may appear as an attractive and cost-effective alternative, given that an existing network infrastructure is already in place. However, as the number of simultaneous users of real-time data increases, the institution may find its Internet connection saturated to the point of uselessness. Upgrading the entire institution's Internet link may then prove too costly. The good news is that the cost of bandwidth and telecommunications services in general has steadily decreased while, at the same time, data providers have put effort into making Internet data delivery more efficient.

In addition to the basic telecommunications services costs and the cost of software client licenses, exchanges charge separate data access fees that are passed along to the end user via the data provider. For example, the New York Mercantile Exchange typically charges $60 per terminal (workstation) per month for access to real- time data from its commodities exchanges. Access to real-time stock futures data in the Euronext-LIFFE market currently costs $33 per terminal per month.

Some schools have been successful at lobbying for exchange fee waivers. The general argument given is that students do not actually trade based on the data and, therefore, do not profit financially from the use of the data. Along the same lines, exchanges have an incentive to get their data into the hands of students so that they will come to embrace the specific exchange once they are in the working world. Many U.S. exchanges, including NASDAQ, already recognize this and provide formal application processes to have exchange fees waived. European markets are beginning to respond to similar requests.

A final hurdle that must be overcome is for faculty and students, the ultimate users of the data products, to learn how to access and manipulate real-time data using the software tools provided by each vendor. Such tools are typically not user friendly and are aimed at professionals, possibly specialists in the financial services industry. Such users tend to view a relatively small subset of the vast universe of data provided by market data services. In contrast to this, students are keen to learn a much broader range of tools and, given the time, will seek to diversify their skills in using these software tools to improve their employment prospects. Providing in-depth instruction into the workings of any one of the major services mentioned above requires enormous effort on the part of both the instructor and the student. This is especially true when contrasted with the plethora of "wizard-driven" applications students regularly encounter in modern computer labs.

In general, real-time data can be accessed through either specific client software provided by the data vendor or a link to a spreadsheet program (Microsoft Excel). For example, Reuters offers the Kobra front-end application (see Figure 1), with a wide range of capabilities including quotations, charting, NASDAQ Level II quotes (see Figure 2), and a variety of other tools used to access market data and news. The Reuters Kobra application provides many prebuilt screens as well as the capability to design custom screens such as the one shown in Figure 1.

FIGURE 1. Reuters Kobra application.

While excellent for demonstration purposes, these applications do not lend themselves to customized model building. For these purposes, bringing data directly into a spreadsheet provides students with the ability to create their own models and analyses from scratch. An example of the Reuters PowerPlus Pro spreadsheet is shown in Figure 3. PowerPlus Pro provides a series of functions that are used to access historical and real-time data. For example, the function RtGet ("IDN_SF", "CSCO.OQ", "BID") retrieves the bid price for Cisco on the NASDAQ exchange. This link is then made live so that it updates in real-time as the best bid price changes in the underlying market. In Figure 3, row 6 displays IBM quotes from the NYSE and row 7 displays the Dreyfus New York Municipal Income, Inc. fund, whose shares are traded on the AMEX. Row 8 displays the e- Mini S & P 500 futures contract with a March 2004 expiration date. Row 9 displays currency data aggregated from several markets by Reuters, with the current Euro quote provided by Barclays. Finally, row 10 displays an electronically traded corn futures contract with a March 2004 delivery date that is traded on the Chicago Board of Trade.

FIGURE 2. Reuters Kobra application displaying NASDAQ Level II quotes for Cisco Systems.

FIGURE 3. PowerPlus Pro with real-time data for NASDAQ and NYSE stocks, currencies, futures, and commodities.

FIGURE 4. Spreadsheet using the Bloomberg Excel add-in showing realtime data for NASDAQ equities.

Similar functions exist as part of an Excel plug-in for Bloomberg, as shown in Figure 4. For example, the function BLP ("CSCO UQ Equity ", , ," [BID] ") will retrieve the most recent, best bid price for Cisco. The link is then made live so that it updates in realtime. Figure 4 also shows the hazards of mixing real- time and delayed quotes. At the time this spreadsheet was created, our center only had permissions in place to receive real-time data into Bloomberg from NASDAQ and not the NYSE. Hence, row 11 displays only the last trade price and volume-weighted average price (VWAP) for IBM on a delayed \feed.

Business Topics and Real-Time Data

The ability to bring live pricing data into a spreadsheet (a tool with which all business students are assumed to be familiar), can be a powerful mechanism by which a number of topics in business can be demonstrated. The examples that follow have been adapted from exercises developed for our undergraduate and graduate business students at the Zicklin School of Business at Baruch College.

Simulated Equities Trading

A common exercise given in many finance classes and trading contests is for students to invest and manage a hypothetical endowment (Liu & Holowczak, 2000). Such exercises are typically done using last trade prices (on perhaps a 15 min delay using a free Web site) or daily close prices, using a Web site or newspaper as the data source. The availability of real-time quote data offers an opportunity for students to go into more depth than typical portfolio management exercises by providing the tools to learn in more detail how a broker works a large order (by breaking it into several smaller orders, for example) and takes a position in the market. At a minimum, students learn which side of the market they need to be on (bid or ask) and how to gauge their performance against measures such as the VWAP. The spreadsheet shown in Figure 5 makes use of Reuters PowerPlus Pro to populate five main sections.

Live market data (shown in the shaded cells) is presented including the bid, ask, and last trade price, as well as the VWAP for the day. This section might be expanded to include many more equities from different industries and traded in different markets.

Students are given a cash endowment ($50,000 in this case) and are told to invest in stocks by taking and closing long positions. In this example, $36,404 has been put into the market to purchase shares. The current market value is an indication of what the balance would be if outstanding shares were liquidated at the current bid price.

FIGURE 5. Order book and real-time prices for a hypothetical portfolio.

FIGURE 6. Equities arbitrage example.

When shares are purchased, the current ask price is copied down and the cash balance decremented. In this example, 1,000 shares of Microsoft were purchased at $25.46.

When shares are sold, the bid price is copied down and the profit or loss on the sale noted while the cash is added back into the current cash balance. In this example, 500 shares of Microsoft were sold at $25.60 and 200 shares were sold at $25.34.

This exercise can be constructed and used by students within a single class period. As students build the spreadsheet step by step, they are required to understand the relationships among the data and the formulas and functions required to perform the necessary calculations. Because the data update in real-time, students witness firsthand concepts such as slippage, volume-weighted price or returns, and bid/ask spread losses. As a project or assignment, it may be conducted over an hour, a day, or longer periods. Each time the student opens up the spreadsheet on the trading floor, prices are updated and the positions adjust automatically.

At a minimum, this exercise reinforces the concepts of the double- auction market and could be a starting point for students studying market microstructure. Although this simple example has limitations, it is relatively straightforward to expand it to include features such as limit orders, commissions on transactions, spreading a large order over a period of time using the available bid and ask lot sizes, measuring each trade against VWAP as a performance metric, or calculating portfolio betas to keep risk in check. Other dimensions that could be explored are to allow short selling or to make use of different instruments (e.g., options on stocks or commodities futures) altogether.

Arbitrage

A second example of the power of real-time market data is as a demonstration of equity arbitrage. When a company's stock trades in two different markets, opportunities may exist to purchase a stock in one market with that market's local currency and sell it in another market to take advantage of discrepancies in the individual market's prices. The objective of this exercise is to show students how a particular kind of arbitrage can be carried out and to concretely show the relationships among the required instrument prices.

Figure 6 shows an example of an equity arbitrage model working in several different markets. Reuters PowerPlus Pro brings in live equity prices and currency prices. One must then set up formulas to represent the bid and ask prices in U.S. currencies. As students construct this model, they are again required to confront issues such as international currencies, exchange rates (e.g., exchanging U.S. dollars for British pounds to purchase stock in the London exchange), how currencies and equities are quoted in different markets (e.g., London quotes equities in lots of 100 shares), and the relative liquidity and spread (difference between bid and ask prices) on these instruments in different markets.

At the time this figure snapshot was taken, an arbitrage opportunity existed by buying shares of Cisco in the NASDAQ market (at $18.59 ask price) and selling them in the London market (at $18.747 bid). Conditional formatting (an Excel feature) can be used so that the cells highlight a different color when the arbitrage opportunity exists. Additional extensions can be made as shown to include other financial markets. To follow up on this model, students might be assigned to extend the model to include transaction fees and other trading costs. The use of real-time data is a requirement for this exercise and generates considerable excitement among students as they build and use arbitrage models.

Subotnick Center Live Events

A final example of the use of realtime data is the presentation of special live events that affect the financial markets. Breaking news events can have significant impact on financial markets. When the U.S. Federal Reserve chairman testifies before Congress or presents open-market committee rate adjustment decisions, when world leaders reveal major policy decisions, or when corporate leaders present news releases and performance statistics, financial markets around the world react within seconds, often with significant impact on the pricing of financial instruments and the volume of transactions.

FIGURE 7. Open Market Committee testimony with live data and news.

Live news coverage of such events coupled with live market data provide a robust and intriguing environment in which students can witness and apply theoretical notions of finance and economics to a real-world context. A Federal Reserve committee decision to lower the prime rate, for example, has implications for everything from bond pricing and equity pricing to the rates on student loans, mortgages, and credit card premiums. Such real-world examples, supported by real-time financial market data and juxtaposed with live video or audio of the events, serve to reinforce in students' minds the many relationships between financial and economic concepts and provide an ideal complement to the related theory they have learned in the classroom. The Subotnick Center holds live events for Federal Reserve Open Market Committee reports, Beige Book releases, and major political events such as President Bush's 8:00 p.m. "deadline for Iraq" broadcast on March 18, 2003. Such events occur at least once a week during a given semester.

An example of a Subotnick Center Live Event held on February 11, 2004, is shown in Figure 7. The equity markets are represented by the e-Mini S & P Futures contract in the top quote and graph windows, and the bond markets are represented by the U.S. Treasury futures (March 2004 expiry). U.S. Federal Reserve Chairman Alan Greenspan's testimony began at approximately 10:30 a.m. As in most cases when he is speaking about the economy, the market reacts to each sentence. For example, as he completes a sentence about his view of unemployment rates, the equity market will tick in accordance. As can be seen in the figure, a full transcript of Greenspan's testimony was released at 11:00 a.m., at which time it was revealed that the U.S. Federal Reserve would not raise rates and was unlikely to raise rates in the near future. The reaction in the market was instant, as evidenced by the jump in equity prices as well as a short-term jump in the bond market. We also have the ability to record the market data and video and to play back the synchronized presentation to classes that meet later in the day or at any other convenient time.

Summary

New technological enhancements to business curricula seem to appear every day, and incorporating educational technology of any kind into a curriculum has never been a trivial task. In business education, the ability to work with Internet and Web resources as well as office productivity tools, including spreadsheets, is virtually mandatory for every student. While there are some pitfalls encountered when working with Internet and Web resources, assignments and projects that use such resources are becoming commonplace. I have demonstrated examples that go one step further by introducing exercises that take advantage of real-time delivery of market data and the tools to manipulate such data.

REFERENCES

Alexander, J. C., Heck, C. C., & McElreath, R. B. (2001). A guide to building a university trading room. Financial Services Review, 10(1-4), 209-220.

Liu, L. G., & Holowczak, R. D. (2000). Using the Reuters 3000Xtra system for financial information education. Online Information Review: The International Journal of Digital Information Research and Use, 24(5), 371-380.

Michelson, S., & Smith, S. D. (1999). Applications of WWW technology in teaching finance. Financial Services Review, 8, 319- 328.

Pettijohn, J. R., Ragan, G. A., & Ragan, K. P. (2003). E-FM: A project for the introductory financialmanagement course designed to involve students with online financial information and analytical tools. Journal of Economics and Finance Education, 2( 1 ), 10-17.

Shim, S. (2003, January/February). Trade secrets. BizEd, 2(2), 22- 27.

Woerheide, W. (1999). The Internet in the personal finance course. Financial Services Review, 8, 305-317.

RICHARD D. HOLOWCZAK

BARUCH COLLEGE, CITY UNIVERSITY OF NEW YORK

NEW YORK, NEW YORK

Copyright HELDREF PUBLICATIONS Sep/Oct 2005

Source: Journal of Education for Business

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