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Title: Determining the number of factors in fractionally integrated factor models Authors:  Dominik Ammon - University of Regensburg (Germany) [presenting]
Tobias Hartl - University of Regensburg (Germany)
Rolf Tschernig - Universitaet Regensburg (Germany)
Abstract: Three different approaches are proposed to overcome limitations for factor selection in fractionally integrated factor models. Two of our methods for determining the number of factors include an approach that was designed for identifying the cointegration rank in VAR models. We extend their model selection approach by generalizing it to fractionally integrated factor models. In our two-step procedure, we first estimate the cointegration rank to obtain the non-stationary fractional factors. In the second step, we generalize the model selection criteria to fractionally integrated factors with memory smaller $1/2$ to obtain the number of asymptotically stationary factors. Before carrying out the second step, the non-stationary factors need to be removed from the data. We investigate two alternatives: i) subtract the estimated non-stationary part from the observable variables, ii) project out the non-stationary factors. In our third approach, we directly consider the model selection criteria without prior removing the non-stationary variation in the observable data. In the Monte-Carlo simulations, all three methods show satisfactory results; in particular, the third approach performs surprisingly well.