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To perform the attribution analysis, we had to rst calculate the security and segment level returns for the portfolio and the benchmark. One implicit assumption here is that we had access to information about the positions held by the fund during the period. Many times we are interested in evaluating the performance of a manager, and we do not have access to the actual positions that the manager held during the period. One example of this is where a pension consultant or other third party is charged with analyzing a portfolio, or where an investment advisory rm is interested in reverse engineering the performance of a portfolio managed by a rival rm. When we cannot access the portfolio holdings, we cannot use value added decomposition techniques to analyze management decisions. But there are additional tools available for analyzing performance in these situations. Style Analysis is a technique used to discover the management style of a portfolio, using an analysis of the fund s historical returns. The results of a style analysis are a list of market indices that best represent the historical performance of a portfolio, weighted by their implied influence on the funds return. Style analysis was developed by William Sharpe4 and has become a popular methodology with several applications for analyzing portfolios. Enhancements have been made to the basic methodology for the purpose of performance attribution. Attribution using style analysis is sometimes used to isolate the effects of the manager s security selection ability from results attributed to the fund s investment style over the period. Style analysis has the advantage that

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9.5 Frequency sharing between the GSO and non-GSO FSS and other GSO and non-GSO TABLE 9.14 Provisional apfd (or epfdup) limits (see also RR Tables S22.2 and S22.4)

=AVERAGE(A1:A10)

# mkmovixiso -t 2005 Vacation -o movix_vacation.iso movie.avi Your iso image is now in /home/user/movix/movix_vacation.iso You can safely delete temporary directory /tmp/movix-1106024960

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tri uoride-etherate to yield 12-a aryl derivatives and a byproduct 11-b epimers (Scheme 5-16). Their antimalarial activity was higher than qinghaosu, and some compounds were even higher than artemether. Also, some compounds showed other bioactivities.183 187 Recently, a new approach to the synthesis of 12 C-glycosides (Scheme 5-17) was also reported.188 5.5.2 Water-Soluble Qinghaosu Derivatives

Easy to understand: Multiple linear regression models are easy to understand and interpret, because they are represented as a weighted series of independent variables. They can be effective in predicting new data as well as explaining what variables are in uential within the data set. Detect outliers: In addition to this method s use as a prediction model, it can also help identify outliers, that is, those observations that do not follow a linear trend observed by the other entries. Fast: The generation of a multiple linear regression equation is fast, and it enables the rapid exploration of alternative variables since multiple models can be quickly built using different combinations of variables to determine an optimal model.

m := E( [m] ),

S5.204/205/206/207 S5.208A/209

The characteristics of the areas designated for the above features will depend upon the type of station being considered and are given below.

Excel s primary financial functions (PV, FV, PMT, RATE, NPER, CUMIPMT, and CUMPRINC) are very useful, but they have two common limitations:

=SUM({4,0,9})

5

where dim(q) = D 12 is obtained by employing the linear constraint p = Qq + p0 , and p represents the column-wise entries of [ A t ]. This condition seems to be quite restrictive, since many transformation groups have only nonlinear parametrizations, particularly in the presence of rotations; nevertheless, we can always nd a linearly parametrized manifold T q that includes T , with dim(T q ) higher than dim(T ) but as close to it as possible. Afterward, the estimated transform Tq* can be upgraded to the correct manifold by means of a Procrustes analysis, T0 = argmin T Tq*

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