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

Share Price Prediction and Analysis - Essay Example The 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 firm’s 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 concluding 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 used 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 provide least prediction error, investors tend to apply numerous methods thereby comparing their results in a bid to finding the best mo del 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 provide efficient and effective performances on predicting share prices of firms in a stock exchange for purposes of investment (Tom, et al, 2000). Nonetheless, most predictors used single dosage of ANN (Kim and Shin, 2007). Application of single dosage in predicting share prices rarely provides an opportunity 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 nervous 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 Mossman, 2003). The idea of back-propagation algorithm is the basis of Artificial Neural Network in predicting share prices of firms. ANN back propagation function is usually represented by the following function: Where, xi is the sum of inputs, which is multiplied by their respective 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 well as effect relationships of various stock prices. From the concepts or application of DT, investors are