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For examples of analysis of data by asset classes, I refer the reader back to Tables 3.2 to 3.10. Ideally, system developers would like to see smooth and evenly distributed profits throughout all assets within these tables. However, it is more important that a system displays solid performance vis- -vis risk than that such performance is evenly distributed throughout all assets in our backtested data history. With this caveat in mind, let us compare the various trading system results shown in Tables 3.2 to 3.10 and attempt to draw some conclusions regarding the data. For now, we will narrow the field of study to those systems that generated a profit to maximum drawdown ratio of 3.0 or higher for the entire portfolio (shown here as Tables 7.21 to 7.25). Narrowing the field of study ensures that we do not waste our time and energy analyzing marginally performing trading systems, which we have no intention of trading in real time. Table 7.21 not only generated the largest net profits, but it also exhibited the smoothest distribution of net profits among the various asset classes studied. Tables 7.22 and 7.23 also showed fairly smooth distributions of net profits throughout the various assets. Tables 7.24 and 7.25 are probably the most questionable of the tables analyzed in our asset-by-asset

Higher order terms can be added to this function. The terms on the right hand side of Eq. (10.9-11) represent the following: a40 r 4 : spherical aberration a31 r 3 cos y : coma a20 r 2 : astigmatism a22 r 2 cos2 y : field curvature a11 r cos y : distortion

The comparison between JSP and ASP is rather interesting because these technologies are both similar and dissimilar in many respects. Both technologies provide a simple yet fast method to create dynamic Web pages. Both aim at separating static and dynamic content in order to segregate the work profiles of Web designers and developers. While JSP uses Java as a medium to write the code for dynamic content, ASP uses Visual Basic or other Microsoft-compatible languages. Java, by virtue of its acceptance as a Web application language, is more versatile, powerful, and a full-fledged programming language, and easier to comprehend. A major difference between the two technologies is that JSP is implemented as a part of J2EE while ASP uses the Internet Services Application Programming Interface (ISAPI). In addition to this, Java-based JSP is platform independent with respect to its compatibility with JVM-enabled operating systems and Web servers (non-Microsoft) while ASP is a solution for server-side scripting on the Windows platform. Because we aim to learn to develop applications in JSP and to ease this rather precarious tug-of-war situation, let s list the main strengths of JSP.

1 t r01 (s, t)

^ where sp Yp ; is a penalized spline (discussed below) and g is a parametric function indexed by unknown fixed parameters , with the property that ^ g Yp ; 0; . . . 0; 0 for all : 18:4

s where is the mean for the sample and p is the standard error of the mean (where s x n is the standard deviation of the sample and n is the number of observations). The critical z-score (zC ) is the number of standard deviations for a given con dence level. To obtain this value, a con dence level needs to be de ned. Commonly used, con dence levels include 90%, 95%, and 99%. The critical z-score value is calculated by looking at the area under the normal distribution curve at the speci ed con dence level. As an example, we will use a 95% con dence level, as shown in

Although the basics of using all types of EJBs in code are common to all users of EJBs, how do the individual user application types make use of the beans Surprisingly, there isn't much difference, so take a look at each of the areas in which you are likely to find an EJB popping up its head. Using beans in ordinary applications Ordinary applications, such as command line apps, don't require any extra work on the part of the programmer. Most of the work has to do with getting the updates out of the database and into a collection of text fields and tables, which really does not involve the bean code at all. For example, if you have a text field, this example will obtain the customer's ID, find the related bean, and put the customer's address into the text field:

(8.84)

In order to calculate the balance amount in the account, the value of the transfer amount has to first be extracted from the particular form control by using the request.getParameter() method. It is important to understand that this method accepts string values only. Because monetary calculations involve numeric variables, the variable has to be converted to a string value. This conversion is done using Java s Integer.parseInt() method. Let s now formulate the contents of various scripting elements. The declaration statement will define the variables for the transfer amount and the details of the account number, bank name, and address. The declaration will therefore contain the following statements: