  This case study tests the possibility of prediction for "success" (or
"winner") components of four stock & shares market indices in a time period of
three years from 02-Jul-2009 to 29-Jun-2012.We compare their performance ain
two time frames: initial frame three months at the beginning
(02/06/2009-30/09/2009) and the final three month frame
(02/04/2012-29/06/2012). To label the components, average price ratio between
two time frames in descending order is computed. The average price ratio is
defined as the ratio between the mean prices of the beginning and final time
period. The "winner" components are referred to the top one third of total
components in the same order as average price ratio it means the mean price of
final time period is relatively higher than the beginning time period. The
"loser" components are referred to the last one third of total components in
the same order as they have higher mean prices of beginning time period. We
analyse, is there any information about the winner-looser separation in the
initial fragments of the daily closing prices log-returns time series. The
Leave-One-Out Cross-Validation with k-NN algorithm is applied on the daily
log-return of components using a distance and proximity in the experiment. By
looking at the error analysis, it shows that for HANGSENG and DAX index, there
are clear signs of possibility to evaluate the probability of long-term
success. The correlation distance matrix histograms and 2-D/3-D elastic maps
generated from ViDaExpert show that the winner components are closer to each
other and winner/loser components are separable on elastic maps for HANGSENG
and DAX index while for the negative possibility indices, there is no sign of
separation.
