The business activities are focused on technical analysis, market sentiment (asymmetric information, rumors, trading noise) and behavoiur imitations. This leads undue biasness decisions. To remove the subjectivity, suggests that this paper a model of neural networks for investors to decide whether buy or sale of shares. The model consists of two wings, C, based on technical analysis and fundamental analysis, on the other. Part of this model the existence of hidden layer between input layer and output layer. Main goals away from subjectivity, this model is not for behavioural factors in modeling.
The basic principle of this model is that the active capital market mispriced and insist different factors people, excessive intake of buy or sell decisions. Therefore, in order to buy a goal model proposed here sell signaling. The basis of this model is again used with the network propagation neural the help. This new spread helps to minimize estimation error caused by time, because the neural network to learn from the mistakes of the past and appreciate the following corrects. The technical analysis in the context of this model ensures objectivity best possible since this analysis only uses the price history. But the fundamental analysis part some subjectivity in May are by different dissimilar because of the holding period and discount rates for investors. In the future, other considerations are possible to minimize subjectivity. In this paper, the model was presented and explained. One area of empirical this model was left to the future.
Check the paper http://papers.ssrn.com/sol3/papers.cfm?abstract_id=940819 for detail.
