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Bear Stearns, which of course was subprimed into oblivion just a few months later, very narrowly missed reporting its own rst-ever yearly loss What explained Bank X s shiny exclusivity In large part, the $4 billion in pro ts generated by a tiny group of traders who had the audacity to bet, late in 2006, on the unexpected (at least according to mathematically and data-intensive things like VaR and credit ratings, and overall conventional wisdom) taking place: that the US mortgage market would shortly unravel dramatically Like the journalist who best covered Bank X s contrarian pro t-making said in late 2007, As recently as a year ago, few on Wall Street thought that the market for home loans made to risky borrowers, known as subprime mortgages, was heading for disaster.

content compared to the traditional media sources, which produce perhaps a few dozen pages of content per day (And that would be for a fairly well-established media entity, because researching and writing is a timely and costly process) At ITtoolbox, the thousands of community members have already done the research and are generating thousands of pages of content, day after day after day Another reason that communities t so neatly into the search model is because of the evolution of search itself Early on, people would search for a simple key term, then go to the web site and start checking out its content Over time, they began searching using more complex key phrases These days, people use search engines to search for a speci c type or piece of information.

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In December 2006, Bank X s CFO summoned his rm s structured credit trading honchos and encouraged them to take a bearish bet on the.

As a result, having high volumes of very granular content is very conducive to drawing traf c to the community (in other words, promoting it) In fact, this search model is becoming the primary way that people use the Internet Searching brings new people into communities and as they become participants, they begin to create content which leads to even more search engine fuel It s a very synergistic model of people creating high volumes of content that is a very potent draw for search engine traf c Another key point: ITtoolbox is open to the public Nonmembers can get into the site via Google, Yahoo!, Ask, or other search engines But the community also has its own search engine, so that a member with a speci c problem can search within the site.

UPDATE customer SET address='10 new st', name='Something New'

Dan and I believe that even a member-only site needs a mechanism by which members can search within the site Dan makes another important point about online communities: If users can t nd the exact information they are looking for, they can generally get the community to generate it for them by participating What happens is that people tend to search and to nd something, but that often generates another question or an extension of the original search As soon as people want to interact with the community to get value, they should become members and provide information about themselves What information they provide depends on the community sponsor s marketing goals and, as noted in the last chapter, may be nothing more than a user name and password..

The integral can be evaluated by an elementary computation and we obtain E(N X ) = 2 (m 2)/2 d (m 1)/2 , which shows that the mean number of zeros is reduced by the perturbation at a geometrical rate as m grows. 6. Polynomial in the scalar product, real roots. Consider again the case in which the polynomials Q(i) are all equal and the covariances depend only on the scalar product [i.e., Q(i) (u, v, w) = Q(u)]. We assume further that the roots of Q, which we denote 1 , . . . , d , are real (0 < 1 d ). We get

This expression is exactly the expression in (7.8) with the notational changes just mentioned and after taking note of the fact that the process is Gaussian, via regression on the condition in each term. Notice that according to the de nition of the Y -processes, E[1A(Y 0 ) ] = E[1Au (X0 , 0 ) ] I I E[1A(Y 1 ) ] = E[ 1Au (X1 , 1 ) ] I I E[Y t1 (t1 ) 1A(Y t1 ) ] = E[Y t1 (t1 ) 1Au (Xt1 , t1 ) ]. I I Second Derivative. Suppose that X satis es H4 . Then, X0 , X1 , Xt1 satisfy H3 , H3 , H2 , respectively. Therefore, Lemma 7.7 applied to these processes can

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