A distribution-free approach to estimating best response values with application to mutual fund performance modeling |
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| Institution: | 1. School of Accounting, Economics and Finance, Deakin University, Melbourne, Australia;2. School of Economics, Finance and Marketing, RMIT University, Melbourne, Australia;1. Department of Business Administration, Munich University, Am Stadtpark 20, 81243 Munich, Germany;2. Banking and Insurance Department, SDA Bocconi, Via Bocconi 8, 20136 Milano, Italy;3. Research Center for Financial Services, Rumfordstrasse 42, 80469 Munich, Germany;4. Department of Business and Economics, Passau University, Innstrasse 27, 94030 Passau, Germany;1. RMIT University, Melbourne, Australia;2. College of Accounting, University of Cape Town, South Africa |
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| Abstract: | Frontier regression models seek to model and estimate best rather than average values of a response variable. Our proposed frontier model has similar intent, but also allows for an additional error term. The composed error approach uses the sum of two error terms, one an inefficiency error and the other as white noise. Previous research proposed assumptions on the distributions of the error components so that the distribution of this total error can be specified. Here we propose a distribution free approach to specifying these errors. In addition, our approach is completely data driven, rendering model specification an unnecessary step. We also outline, step-by-step, an approach to implementing this procedure. Our entire approach is illustrated with a mutual fund data set from the Morning Star database. |
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