IRM & Stock Market

1. IRM & Stock Market Kirk Williams CIS 450 November 4, 2003

2. On the Menu Today… • Integration of IRM and the US Stock Market • We are in the transition from a conventional economy to a knowledge based economy.

3. On the Menu Today… • Stock Market • Information Resource Management • Correlation between the Stock Market and Information Resource Management • Stock Market & Information Resources • Integration of IRM and Stock Market • IRM, Stock Market, and E-Commerce

4. What is the Stock Market? • Marketplace for buying and selling securities • Two types of Stock Markets in US: • Securities Exchanges • NYSE • American Stock Exchange • Midwest Stock Exchange • Pacific Stock Exchange • Philadelphia Stock Exchange • OTC • NASDAQ

5. What is Information Resource Management? Information Resource Management is an emerging discipline that helps managers asses and exploit their information assets for business development. It draws on the techniques of Information Science (libraries) and information systems (IT related) Building a Knowledge Management Infrastructure by Dr. Guy-Alain Amoussou, 2003

6. Goals of Information Resource Management • The goal of IRM is to manage knowledge to support strategic business objectives. • Manage resources such as hardware, software, telecommunications, and databases • Reduce inefficiency & paperwork

7. Importance of Information Resource Management • In this global, knowledge-based economy, corporate success depends on managing information, transforming it into explicit knowledge, and capitalizing off of it • Utilize all components from IT and IS to support business processes

8. What is Information Resource Management? • Apply management techniques to Information on an organizational level. • Policies, standards, processes for managing the organization’s data, information, and knowledge as strategic business resource.

9. So… • What is the correlation between the Stock Market and Information Resource Management? • Let’s find out!!

10. Stock Market & Information Resources • Telecommunication • Data Management • Mobile Data Mining • Software • Hardware

11. Telecommunication Traditional stock exchanges are centralized. The exchange is located in a single physical place, and all data (both market and trades) flow through a single system. The centralized system is responsible for transaction reporting and exchanging assets. Electronic exchanges, like the NASDAQ, allow remotely located traders to connect with the centralized system.An Internet Multicast System for the Stock Market by N. F. MAXEMCHUK and D. H. SHUR, 2001.

12. Telecommunication: • Multiple Data Sequences • Dedicated Access Lines & Private Networks • High Bandwidth Requirement • Network Engineering with primary goal of preventing data loss

13. Telecommunication Issues: • Spoofing • Denial of service • Authorized service for transmission and reception • Encryption • Security

14. Data Management • Stock Markets and brokers require real-time data access and is the ultimate in data management. • Brokers deal with the public over public and private networks • Public portfolio access can be interactive, customizable, and dynamic

15. IRM Data Management Research • Stock market / data management research is improving IRM processes

16. IRM Data Management Research • Clustering of data sets with similar attributes using Euclidean mathematics. Clustering is perhaps the most frequently used data mining algorithm, being useful in it’s own right as an exploratory technique, and also as a subroutine in more complex data mining algorithms such as rule discovery, indexing, summarization, anomaly detection, and classification. Data streams II: Clustering of streaming time series is meaningless by Jessica Lin, Eamonn Keogh, Wagner Truppel,2003.

17. Mobile Data Mining The emergence of powerful mobile devices with reasonable computing and storage capacity is ushering an era of advanced data and computationally intensive mobile applications. Monitoring and mining time-critical data streams in a ubiquitous fashion is one such possibility. Financial data monitoring, process control, regulation compliance, and security applications are some possible domains where such ubiquitous [data] mining is very appealing. Contributed articles on online, interactive, and anytime data mining: MobiMine: monitoring the stock market from a PDA by Hillol Kargupta, Byung-Hoon Park, Sweta Pittie, Lei Liu, Deepali Kushraj, Kakali Sarkar, 2002

18. Mobile Data Mining • Stock Market IRM is not a traditional client-server model • Efficiently represent and communicate the data mining objects over wireless networks • Changing Human Computer Interaction for mobile devices • Minimal power/CPU consumption for compact applications • Again, Security.

19. Mobile Data Mining The graphical techniques for designing interfaces on desktop systems do not apply well to handheld devices. Screen resources are limited; often screens are black and white to reduce cost and power consumption. Memory and processing power are much reduced from desktop systems. Overcoming the Lack of Screen Space on Mobile Computers by Stephen Brewster, 2002

20. Mobile Data Integrity Fair exchange protocols establish fairness and ensure that both participants can engage in the exchange without the risk of suffering a disadvantage (e.g., losing their money without receiving anything for it). In general, fair exchange protocols require the continuous availability of an external trusted third party (TTP), a dedicated site which is trusted by both participants. Implementations of TTPs for fair exchange have been proposed to be based on carefully secured Internet hosts in order to establish trust. Supporting fair exchange in mobile environments by Holger Vogt, Felix C. Gärtner, Henning Pagnia, 2003.

21. Software • Stock Market IRM are web-based systems • What is the language widely used to implement this? • XML ensures data structure in data streams

22. Hardware • Data Warehouses • Data quality and data integrity are issues • Stock markets have Centralized data warehouses serving hundreds of thousands of other servers

23. Distributed systems • Massive amounts of Data Archiving across multiple systems • Data integrity is an issue in any distributed system • Source Data Analysis • Database Structure doesn’t always match contents • Thorough data analysis

24. Epice The point is, ladies and gentleman, is that greed -- for lack of a better word -- is good. Greed is right. Greed works. Greed clarifies, cuts through and captures the essence of the evolutionary spirit. Greed, in all of its forms -- greed for life, for money, for love, knowledge -- has marked the upward surge of mankind. And Greed -- you mark my words -- will not only save Teldar Paper but that other malfunctioning corporation called the USA.Wall Street,1985

25. Integration of IRM and Stock Market • Stock Exchanges and IRM • Stock Market Oversight and IRM • Effects of IRM on stock market investing

26. Stock Exchanges and IRM • The Stock Market’s relationship with IRM is one that entails finance, economics, AI, psychology, and mathematics

27. Stock Market Oversight and IRM • Securities and Exchange Commission The primary mission of the U.S. Securities and Exchange Commission (SEC) is to protect investors and maintain the integrity of the securities markets. As more and more first-time investors turn to the markets to help secure their futures, pay for homes, and send children to college, these goals are more compelling than ever. http://www.sec.gov/about/whatwedo.shtml, 2003

28. Edgar • Electronic Data Gathering, Analysis, and Retrieval system • Historical 10-K and 10-Q reports • Millions of document transactions per month http://www.sec.gov/edgar/aboutedgar.htm, 2003

29. Effect of IRM on Stock Market • Overconfident investors overreact and under react • This causes fluctuations in the stock market

30. Effects of IT and IRM on the Stock Market The ubiquity of online trading services allows individuals to trade without the need to consult a human broker. Also, financial intermediaries and portals have emerged offering market information and trading tips. This information rich environment enhances the cumulative and the individual knowledge of traders, thereby making the market more informed and rational. However, the availability of online trading avenues also introduces a high number of uninformed traders into the systems, thus introducing irrationality into the market. Is more information better? The effect of traders' irrational behavior on an artificial stock market by Wei T. Yue, Alok R. Chaturvedi, Shailendra Mehta, 2000

31. Benefits of IRM in publicly traded corporations • Productivity paradox • Companies that institute IRM increase their value and their stock price Firms that are high IT users are also more likely to adopt work practices that involve a cluster of organizational characteristics, including greater use of teams and broader decision authority. Intangible Assets: How the interaction of Computers and Organizational Structure Affects Stock Market Valuations, Erik Brynjolfsson, Lorin M. Hitt, Shinkyu Yang, 1998

32. Corporate IRM Implementation • Wal-Mart • Amazon • FedEx • Outsourcing IRM experts

33. IRM, Stock Market, and E-Commerce • Rise and Fall of the Dot Com • E-Investing • Automated Consulting • Stock Market Simulation

34. E-Commerce • Did eTrade cause the burst the eBubble? • DotCom: venture capitalists put up cash and that helps a company go to a bank to get backed to go public. Banks and venture capitalists hype the stock, public increasingly market-driven so buys stocks in these worthless companies

35. E-Investing • Implementation of IRM / stock market front-end is web based. • Traditional brokers like Price Waterhouse have been forced into e-commerce to survive

36. Day Trading on the Web • Day Trading on the Web • Dynamic, Real-time stock quotes and transactions • Use your Palm compatible device, WAP enabled cell phone or Pocket PC to place orders for stocks, get real-time stock quotes and account balances, and check order status and transaction history.

37. ETrade www.etrade.com

38. Scottrade

39. Automated Consulting • Forecasting • Maximize returns, minimize risk • Predictive Modeling: statistical techniques, neural networks, genetic algorithms

40. Automated Consulting • Stock market systems are difficult to model • Piecewise Normalization of stock market indices • Indexing time sequences with Fourier Transform • Designing algorithms for stock market indices based on historical data is NP-hard • Discrepancy between the efficient market hypothesis and empirical evidence

41. Stock Market Simulation • IRM Research • Stock Market Game Program (www.smgww.org) • Virtual Stock Exchange (game.marketwatch.com)

42. E-Information • So if IRM is so good on the web, how did places like Enron defraud their workers from 401K benefits? • That’s accounting. This is IRM.

43. IRM & Stock Market • Today we saw how the Stock Market and IRM coexist and support one another.

44. Bibliography Amoussou, Guy-Alain Building a Knowledge Management Infrastructure. September 4, 2003 Brewster, Stephen. Overcoming the Lack of Screen Space on Mobile Computers. Personal and Ubiquitous Computing,Volume 6 Issue 3: January 2002 Brynjolfsson, Erik. Hitt, Lorin M. Yang, Shinkyu. Intangible Assets: How the interaction of Computers and Organizational Structure Affects Stock Market Valuations. Proceedings of the international conference on Information systems. December 1998 http://www.sec.gov/about/whatwedo.shtml. 2003 http://www.sec.gov/edgar/aboutedgar.htm. 2003 Kargupta, Hillol. Park, Byung-Hoon. Pittie, Sweta. Liu, Lei. Kushraj, Deepali. Kakali Sarkar. Contributed articles on online, interactive, and anytime data mining: MobiMine: monitoring the stock market from a PDA. ACM SIGKDD Explorations Newsletter. Volume 3 Issue 2: January 2002 Lin, Jessica. Keogh, Eamonn. Truppel, Wagner. Data streams II: Clustering of streaming time series is meaningless. Proceedings of the 8th ACM SIGMOD workshop on Research issues in data mining and knowledge discovery: June 2003. Maxemchuk, N. F. Shur, D. H.An Internet Multicast System for the Stock Market. ACM Transactions on Computer Systems (TOCS). Volume 19 Issue 3: August 2001 Vogt, Holger. Gärtner Felix C. Pagnia Henning. Supporting fair exchange in mobile environments. Mobile Networks and Applications.Volume 8 Issue 2: April 2003. Yue, Wei T. Chaturvedi,Alok R. Mehta , Shailendra. Is more information better? The effect of traders' irrational behavior on an artificial stock market. Proceedings of the twenty first international conference on Information systems. December 2000.