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Personalizing online retailing: Data mining has been used extensively in the area of online retailing, capitalizing on the wealth of digital information that is continually collected. In addition to sales transaction data, information is collected from customer ratings and reviews, the web pages viewed, and information on current product inventory levels. Clustering is often used to generate segments of users, and these groups are annotated with information on product popularity and overall pro tability. Association rules are also employed to identify product combinations that are often purchased together. These results are used to personalize web pages based on the pro le of the customer built over time. They are also matched to similar customers preferences. This personalization includes products the consumer is anticipated to be interested in and educational material, such as white papers. It also makes use of models that prioritize pro table customers. This personalization often takes into account inventory levels to maximize conversion rates and pro ts. Online retailing offers a fertile ground for developing new and novel methods for cross- and up-selling. Ensuring that the data mining results in pro table updates to the online experience is easily tested in the online environment. Subscribers are often divided into groups that make use of a new service and a control group that does not have access to the service. The success of any new service is based on differences recorded for the two groups, such as higher sales or pro ts.

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higher computational complexity. In the next section we describe instead a well-known scale-invariant detector and the related description and matching procedures, achieving near real-time performance. However, once again we remark that in the context of object tracking, the Harris detector is fast and reliable, especially for short-baseline matching. Keypoint matching by re-projection was illustrated in Fig. 1.6 and is summarized in Fig. 4.52. Other examples of the use of Harris keypoints are frameto-frame feature tracking for sparse optical ow computation (Section 4.6.2), and stereo correspondence problems [77].

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When the separation device opens, the grid active power change P and reactive power change Q will go to zero. The behavior of the isolated system will depend

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WHY ARE FUTURES PORTFOLIOS POORLY CORRELATED WITH STOCKS AND BONDS There are two major reasons why futures funds are poorly correlated with bonds and stocks The first lies in the diversity of the futures markets Futures fund managers deal in all sectors of the futures markets Their trading results are not dependent on just bonds and stocks Most futures fund managers are trend-followers During financial bull markets, they buy interest rate and stock index futures and benefit accordingly During downturns in bonds and stocks, however, their losses in the financial area will be largely offset by profits in commodities and foreign currencies which tend to rise at such times They have built in diversification by participating in four different sectors which are usually negatively correlated The second reason has to do with short selling Futures managers are not tied to the long side of any markets.

They can benefit from bear markets in bonds and stocks by shorting futures in these two areas In such an environment, they can hold short positions m the financial markets and long positions in commodities In this way, they can do very well during periods when financial markets are experiencing downturns, especially if inflation is the major culprit And this is precisely when traditional bond and stock market portfolio managers need the most help The late Dr Lintner's research and that of other researchers is based on the track records of Commodity Trading Advisors and publicly-traded futures mutual funds winch are monitored and published by Managed Account Reports (5513 Twin Knolls Road, Columbia, MD 21045).

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8 See Pagan and Schwert (1990), Engle and Ng (1991), and the studies cited in Bollerslev, Chou, and Kroner (1992), page 24. 9 Nelson and Cao (1992) argue that imposing all coef cients to be nonnegative is too restrictive and that some of the coef cients are negative in practice while the conditional variance remains positive (by checking on a case-by-case basis). Consequently, in practice, GARCH parameters are often estimated without nonnegativity restrictions.

The purpose in mentioning it here is simply to alert the reader to work being done in this area and to suggest that the benefits of intermarket trading, which is more commonly practised in the futures markets, may someday become more widely recognized and utilized in the investment community Let's narrow the focus and concentrate on one portion of the futures portfolio the traditional commodity markets This book has focused on this group's importance as a hedge against inflation and its interrelationships with the other three sectorscurrencies, bonds, and stocks.

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