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|Title: ||Prediction and performance evaluation of BDI forecasting models : Cross efficiency, the directional distance function and the AVS utility function|
|Authors: ||YU, Ming-Miin;BULUT, Emrah|
|Issue Date: ||2017-11-01
|Abstract: ||In the study, we propose a nonparametric efficiency measurement approach for the forecasting model selection problem. Three autoregressive models and three fuzzy time series approaches are employed for the calibration of data structure to depict the trend. The directional distance function and portfolio theory are further used to evaluate the performance of BDI predictions. A directional distance function is defined that looks for possible increases in accuracy and skewness, and decreases in variance obtained by cross efficiencies of those forecasting models. We also establish a link to proper indirect accuracy- variance -skewness (AVS) utility function for various users in various utilities. An empirical section on a set of forecasting Baltic Dry Index (BDI) forecasting models serves as an illustration.
The workshop is supported by JSPS (Japan Society for the Promotion of Science), Grant-in-Aid for Scientific Research (B), #25282090, titled “Studies in Theory and Applications of DEA for Forecasting Purpose.
|Appears in Collections:||[運輸科學系] 演講及研討會|
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