Return Pattern Analysis
Return Pattern Analysis | Definition
In Russell Style Classification (RSC), a optimization method of analyzing investment style based on the algorithm designed by Yuan An Fan, Ph.D. of the Frank Russell Company. The algorithm is similar to many non-linear optimization programs. The object of the program is to find a set of weights which, when applied to the indexes selected, minimizes the residual squared errors or differences between the optimal weighted set and the input portfolios return series. In the least squares sense, this problem is similar to standard multiple regression but differs (and becomes non-linear) because the weights cannot be less than zero or greater than one and must sum to one.
The results of the optimization are stored in a database for subsequent analysis. The number of optimizations depends on the length of window used to set up the inputs for the optimization. The recommended choice is 60 months or 5 years of data. The first 60 months of index and manager data are analyzed and the means, variances and co-variances (correlations) are passed to the optimizer to find the optimal set of weights. The 61st month is then added to the data set and the first month is dropped, essentially rolling the window one-month ahead, and the optimization is repeated. This rolling of the window and analyzing the data sets continues until the last time point in the data set is reached. The number of optimizations or analyses obtainable is equal to the number of time points (of complete data sets) minus the length of the rolling window, plus one. For example a data set covering 75 time points or months, using a rolling window of 60 months, will yield 16 analyses or optimizations (75 - 60 + 1 = 16)
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Tags: Return Pattern Analysis, Return Pattern, Return Patterns, Investment Returns, Investment Return Analysis, Investments Return, Investments Return Analysis
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