10 Year. Morningstar rated the Global Technology Fund among 196, 196, 186 and 144 Technology funds for the overall rating and the 3-, 5-, and 10-year periods (as applicable) ending 02/28/2017, respectively.
Geometrically an eigenvector, corresponding to a real nonzero eigenvalue, points in a direction that is stretched by the transformation and the eigenvalue is the factor by which it is stretched. If the eigenvalue is negative, the direction is reversed.
What is SVD(singular value decomposition) SVD can be understood from a geometric sense for square matrices as a transformation on a vector. Consider a square n x n matrix M multiplying a vector v to produce an output vector w: w = M*v The singular value decomposition M is the product of three matrices M=U*S*V, so w=U*S*V*v. U and V are orthonormal matrices.