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is to Internet-rich buzz. Old word-of-mouth spread slowly. You met a friend on the street or at the of ce. You inserted a remark in a piece of snail mail. You dropped a hint in a phone conversation. You couldn t reach very many people and basically you reached them one at a time. Because word-ofmouth was slow and the number of people involved was small, writes Godin, it was hard for the ideavirus to become truly infectious. As people stop spreading the contagion, the virus begins to die. Consequently, with word-of-mouth, each generation of message receivers and senders is typically smaller than the previous. With Internet-enabled buzz you have an entirely different story. Each buzzing person can reach many more people and they can do so quickly. Think about it, says Godin, you probably have 100, maybe 1,000 e-mail addresses in your address book. How dif cult would it be to send a buzz to all of them It wouldn t be hard at all, and if you don t believe the gurus, try this. Type the following e-mail message:

and Abuses, Journal of Applied Corporate Finance, Volume 10, Number 4, Winter 1998, pp 26 38 Damodaran, Aswath (1997) Corporate Finance Theory and Practice, New York: John Wiley & Sons, Inc Davis, Donald, and Kevin Lee (1997) A Practical Approach to Capital Structure for Banks, Journal of Applied Corporate Finance, Volume 10, Number 1, Spring 1997, pp 33 43 DeMarzo, Peter, and Darrel Duffie (1991) Corporate Financial Hedging with Proprietary Information, Journal of Economic Theory, Volume 53, pp 261 286 DeMarzo, Peter, and Darrel Duffie (1992) Corporate Incentives for Hedging and Hedge Accounting, working paper, Northwestern University Dermine, Jean (1998) Pitfalls in the Application of RAROC in Loan Management, The Arbitrageur, Volume 1, Number 1, pp 21 27 DeStefano, Michel T, and Virginia L Manzer (1999) Financial Institutions Criteria, New York: Standard & Poor s Deutsche Bank (1999) Annual Report, Risk Report, pp 123 139 Dewenter, Kathryn L.

We ll get into the specifics of editing the registry in a moment. But first, Figure 46.1 shows an example of the Registry Editor as it might look when you first open it. The names listed down the left column are keys. Specifically, we refer to them as the standard root keys, because they re at the top (root) of the hierarchy, and each contains subkeys. Each standard root key stores a particular type of information, as summarized in Table 46.1. Note that most keys have a standard abbreviation, like HKCU for HKEY_CURRENT_USER.

Access uses comparison operators to compare Date fields to a value. These operators include less than (<), greater than (>), equal to (=), or a combination of these operators. Notice that Access automatically adds pound sign (#) delimiters around the date value. Access uses these delimiters to distinguish between date and text data. The pound signs are just like the quote marks Access added to the Cars criteria. Because OrigCustDate is a DateTime field, Access understands what you want and inserts the proper delimiters for you. Be aware that Access interprets dates according to the Regional and Language Options (Windows XP) or the Region and Language settings (Windows 7) in the Windows Control Panel. For example, in most of Europe and Asia, #5/6/2012# is interpreted as June 5, 2012, while in the United States this date is May 6, 2012. It is very easy to construct a query that works perfectly but returns the wrong data because of subtle differences in regional settings.

, and Alan C Hess (1997) Risk and Returns in Relationship and Transactional Banks: Evidence from Banks Returns in Germany, Japan, the UK, and the US, working paper 97-23, Financial Institutions Center, The Wharton School, University of Pennsylvania Diamond, Douglas (1984) Financial Intermediation and Delegated Monitoring, Review of Economic Studies, Volume 51, pp 393 414 Diamond, Douglas W, and Raghuram G Rajan (1999) A Theory of Bank Capital, working paper, University of Chicago, Revised: April 1999 Diebold, Francis X, Til Schuermann, and John D Stroughair (1998) Pitfalls and Opportunities in the Use of Extreme Value Theory in Risk Management, working paper 98-10, The Wharton School, Financial Institutions Center, University of Pennsylvania, March 1998 Dixit, Avinash K, and Robert S Pindyck (1994) Investment under Uncertainty, Princeton: Princeton University Press.