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tency. The latter is a big problem when data comes from different sources. For example, most of the major index providers have their own (unique) sector and industry classi cations for each stock. As long as you get all of your information from the same source (assuming that that source uses the same data provider throughout the analysis), you should be ne; but in the real world, data comes from multiple sources and, as a result, becomes very dif cult to analyze on a comparative basis. By simply requesting the underlying data, inputting the data into our own system, and printing the reports ourselves, we can avoid this issue completely. Regardless of what methodology you choose to employ, the information should be treated the same. Just one word of caution: Because so much information is available, it is possible to experience information overload or information crossover. Information crossover occurs when an analyst produces so many reports based on the same data that much of the information reviewed in later reports has already been covered completely or in part in previous reports. The result is an inef cient use of time. Using the portfolio information provided to us by CAM Asset Management, we can input the data into our portfolio analysis system and produce the portfolio summary report in Exhibit 6.1. The report in this exhibit contains a wealth of information on each stock included in the CAM portfolio at the end of last month. This chapter will illustrate a systematic method of evaluating both the summary-level data as well as the detail on each speci c stock in the portfolio.

Listing 3.2 depicts the interfaces of a number of tiny services. Each of these services supports a specific process related to the Order entity, and, taken together, support the processing for one abstraction in this case, the Order entity. The OrderCreationService supports the specific process of creating Order instances (and providing Order Data Transfer Object instances) through its methods. The OrderUpdateService provides a method to update an existing instance of Order, and the OrderApprovalService provides one method to support approval process for Orders. Application client components that support Order processing must utilize each of these different services at different points within the client code, depending on whether an Order is being created or updated, and what state the object is in.

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academic research. This chapter should be of interest to businessoriented readers, too, since recent modelling efforts address business and technology as a whole. 8 introduces the second focus topic, describing service control functionality for mobile networks. It provides an example of powerful functionalities in the mobile network that service management is able to utilize. 9 discusses potential future trends that relate to service management. Both business and technical trends are discussed. 10 provides a summary of the topic area of the book.

so that ; it can also be shown that the mean-square radius of the covariance ellipsoid [which is given by tr ( ) ] grows proportional to the square root of time k .

96 60 215 52 220 98 63 175 51 183 70

Using hypothesis (H1 ), if B1 > 1, we obtain P( X(2k 1)

This book primarily involves deployment of JSP applications on the J2EE server. Let s now discuss the steps of setting up the J2EE environment.

The equation for a power trendline looks like this:

The swap curve is relatively smooth and unaffected by issuance schedules and tax or repo considerations. The bond market curve is much more variegated and internally volatile. This can create problems for bond traders who seek to gain by selling rich bonds and buying cheap ones. Subsequent changes in the yield curve can swamp any pro ts available from current mispricings. The trader can use swaps to reduce the risk of bond trading. For example, swap spreads can be traded to take advantage of an expected

22: JMS The message selection section later in the chapter demonstrates the use of properties for filtering incoming messages. Note Properties should mainly be used for holding message selection criteria. While you can create simple messages with the data entirely in properties, it is not a good idea. JMS providers may not handle data in properties as efficiently as data in the body of a message. However, having appropriate properties defined for message selection can be a very efficient use of resources since it might prevent a JMS provider from sending messages across the wire unnecessarily.

Using Excel s FREQUENCY function presents the easiest way to create a frequency distribution. This function always returns an array, so you must use it in an array formula entered into a multicell range. Figure 7-6 shows some data in range A1:E20 (named Data). These values range from 1 to 500. The range G2:G11 contains the bins used for the frequency distribution. Each cell in this bin range contains the upper limit for the bin. In this case, the bins consist of 1 50, 51 100, 101 150, and so on. See the sidebar, Creating Bins for a Frequency Distribution to discover an easy way to create a bin range.

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