A randomised sequential procedure to determine the number of factors - Trapani, Lorenzo (Taylor & Francis, 2017)
This paper proposes a procedure to estimate the number of common factors k in a static approximate factor model. The building block of the analysis is the fact that the first k eigenvalues of the covariance matrix of the data diverge, whilst the others stay bounded. On the grounds of this, we propose a test for the null that the i-th eigenvalue diverges, using a randomised test statistic based directly on the estimated eigenvalue. The test only requires minimal assumptions on the data, and no assumptions are required on factors, loadings or idiosyncratic errors. The randomised tests are then employed in a sequential procedure to determine k.