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

Share Price Prediction and Analysis - Essay ExampleThe undermentioned 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 concluding remark, which comments on the results, winds up the paper. Approaches/Models for Predicting Share Prices In short-run 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 legion(predicate) methods the reby comparing their results in a bid 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 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 luck 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 a nd Mossman, 2003). The conceit of back-propagation algorithm is the basis of Artificial Neural Network in predicting share prices of firms. ANN back propagation endure 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. finish tree (DT) model on the other hand is a data mining model or approach used in predicting or prodigy 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 salutary as effect relationships of various stock prices. From the concepts or application of DT, investors are