Abstract
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.
Highlights
It is important to study the predictability of the time series separately from constructing the specific predictors because in creation of each model we assume some additional hypotheses about the model structure.Our case study is aimed to find possibility of the prediction of ‘success’ within three years’ time interval from 02-JUL-2009 to 29-JUN-2012 for four selected stock and share market indices
The k-NN algorithm with Leave-One-Out CrossValidation with two distance measurements is used as the indicator to test the possibility of prediction
We investigate that there is a possibility of predictions for long-term success for HANGSENG and DAX indices in the result section
Summary
It is important to study the predictability of the time series separately from constructing the specific predictors because in creation of each model we assume some additional hypotheses about the model structure. Our case study is aimed to find possibility of the prediction of ‘success’ within three years’ time interval from 02-JUL-2009 to 29-JUN-2012 for four selected stock and share market indices. This case study is aimed to construct experiments on the data to test if it is possible to predict the long-term success. The possibility of long-term ‘success’ of the selected indices is tested from the results of the experiment in the three years’ time interval. After data pre-processing step, the remaining components are labeled with ‘winner’ companies or ‘loser’ companies (or just ‘winner’, ‘loser’) by using the ‘1/3 average price’ approach For this approach, we compute the average price ratio which is defined as the mean price of the end period divided by the mean price of beginning period. We summarize our result and conclude in the last part
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