Share Price Prediction and Analysis Essay Example | Topics and Well Written Essays - 1500 words

Share hurt Prediction and Analysis - Essay ExampleThe following is a critical review of such literature. In addition, the discussion applies a synthesis of two approaches/models identified to predict the share prices for Tesco Plc from the publications of the firms financial statements for 2008 and 2009. Lastly, this discussion attempts to test the approach by comparing these two sets of predictions with actual share prices. A think remark, which comments on the results, winds up the paper. Approaches/Models for Predicting Share Prices In short-term or medium-term, different models or approaches are apply in predicting the future prices of shares of various companies. Share prices of companies may take different forms such as linear, horizontal, cyclic, or seasonal as influenced by prevailing market and environmental factors (Hassan, et al., 2007). Due to lack of prediction methods that render least prediction error, investors tend to apply numerous methods thereby comparing the ir results in a swordplay to finding the best model or approach to use (Chen, et al., 2003). ... Artificial Neural Network (ANN) is a share price prediction method that is commonly used. For many years, ANN has been developed and restructured in order to nominate efficient and effective performances on predicting share prices of firms in a stock swop for purposes of investment (Tom, et al, 2000). Nonetheless, close to predictors used single dosage of ANN (Kim and Shin, 2007). Application of single dosage in predicting share prices rarely provides an chance to discover the decision rule that the model uses while making the predictions (Hassan, et al, 2007). Artificial Neural Network is a share price prediction model or approach, which is created through stimulation of biological central vile system of investors or predictors (Swales and Yoon, 2002). One of the reasons explaining its extensive application is the ability to predict share prices from large databases (Olson and Mos sman, 2003). The persuasion of back-propagation algorithm is the basis of Artificial Neural Network in predicting share prices of firms. ANN back propagation give out is usually represented by the following function Where, xi is the sum of inputs, which is multiplied by their various(prenominal) weights wji Aj is the predicted share value under the ANN model and n is the end period in which the valuation is carried out. decision tree (DT) model on the other hand is a data mining model or approach used in predicting or forecasting share prices within a stock exchange market. One of the reasons for its extensive application is the fact that DT has an excellent ability and capability of describing cause as good as effect relationships of various stock prices. From the concepts or application of DT, investors are