Abstract
This article presents an adaptive approach for the ranking of investment funds by fund-of-funds managers. This quantitative tool will help managers rank funds and allocate capital between them for the next few months (for example, for the next quarter) when the available information/data is limited to daily returns for a relatively short time period (for example, the ending quarter). This new family of adaptive algorithms comes in line with those computational methods that fill the gap between more sophisticated approaches (that need more information/data available and more powerful cluster of the analytic computing procedures) and the nonnumerical Laplacian approach (whereby capital is allocated more or less equally between all funds that did not fail in a previous quarter).
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