New Frontiers in Banking Services Emerging Needs and Tailored Products for Untapped Markets 4 pptx

... way: x ∗ k,t = x k,t − min(x k ) max(x k ) −min(x k ) (3.13) The linear scaling function for [−1, 1], transforming a variable x k into x ∗∗ k , has the following form: x ∗∗ k,t =2· x k,t − min(x k ) max(x k ) −min(x k ) − ... Similarly, do changes in GDP have one process in recession and another in recovery? These are very important questions for forecasting and policy analysis,...

Ngày tải lên: 21/06/2014, 07:20

... bootstrapping the initial training set. As we discuss in Section 4. 2.8, bootstrapping involves resampling the original training set with replace- ment, and then taking repeated forecasts. Bagging is ... Test for Nonlinear Patterns Brock, Deckert, and Scheinkman (1987), further elaborated in Brock, Deckert, Scheinkman, and LeBaron (1996), propose a test for detecting nonlinear...

Ngày tải lên: 21/06/2014, 07:20

... estimation an expanding window. The sample size, of course, becomes larger as we move forward in time. An alternative to the expanding window is the moving window. In this case, for the first forecast ... differencing for obtaining derivatives, and bootstrapping for obtaining significance, in turn. 4. 3.1 Analytic Derivatives One may compute the analytic derivatives of the output...

Ngày tải lên: 21/06/2014, 07:20

... 300 350 40 0 −6 4 −2 0 2 4 6 Linear Network FIGURE 5.12. In- sample errors: VRS model for return forecasting, but in its favor, it does not perform worse in any noticeable way than the linear model. While ... and modify the network models used for estimation and forecasting performance against the linear model. I invite the reader to continue these experiments with artificia...

Ngày tải lên: 21/06/2014, 07:20

... forthcoming. Chen, Racine, and Swanson (2001) have used a ridgelet neural network for forecasting in ation in the United States. McNelis and McAdam (20 04) used a thick model approach (combining ... fall in bank lending, or does the collapse of bank lending lead to a fall in land prices? 176 7. In ation and Deflation: Hong Kong and Japan interval (in this case we are forecas...

Ngày tải lên: 21/06/2014, 07:20

... coefficients and nonlinear functions for extracting one component, brought in the next observation, and applied these coefficients and functions for estimating the new principal component. We used this new ... 0.3888 0.3 344 8 0.2927 0. 246 0.216 Skewness 0 .48 7 0.590 0.582 0.536 0 .40 4 0.5 84 Kurtosis 2.0 64 2.235 2.302 2. 242 2.338 3.553 Max 60.500 53.300 47 .250 47 .500...

Ngày tải lên: 21/06/2014, 07:20

... used functional forms in the neural network literature. 2 .4. 2 Squasher Functions The neurons process the input data in two ways: first by forming lin- ear combinations of the input data and then by “squashing” ... the input vector and the center of that unit, whereas the MLP or feedforward network computes the inner products of the inputs and the weights for that unit. Mandic...

Ngày tải lên: 21/06/2014, 09:20

... bootstrapping the initial training set. As we discuss in Section 4. 2.8, bootstrapping involves resampling the original training set with replace- ment, and then taking repeated forecasts. Bagging is ... point for quite some time during the training period. Unfortunately, there is no silver bullet for avoiding the problems of local minima in nonlinear estimation. There are only str...

Ngày tải lên: 21/06/2014, 09:20