Investment decision in the Taiwan stock market based on the dynamic behavior of P-E ratio
Wen - Hao Yang
An - Pin Chen
|關鍵字:||本益比;每股盈餘;倒傳遞類神經網路;Price-to-earning ratio (PER);earnings per share (EPS);Back Propagation Neural Network (BPN)|
The price-earnings (P-E) ratio is a common used tool to evaluate a value of company by the domestic legal person and the investment and finance organization currently. However, because of more basal dissimilarity, usually there appear the different standard and the gained analyzing result is also probably different. So, on the market while making use of the price-earnings ratio to evaluate the reasonable stock price of a company, people usually evaluate the level of stock price based on the concept of the static state. Sometimes there is company that chooses the low price earnings ratio, and its stock price growth is not high. However, the company with high price-earnings ratio, there appears special condition of an explosion growth in the individual stock. This research apply Neural Network to have the characteristic of the excellent learning. It is originally a static and fixed zone investment behavior. By the network train to learn the physical running of the company’s P-E ratio and the behavior of the stock price motion and by the effect of weighted index and the industry market P-E ratio to company’s P-E ratio, we can estimate the trend behavior of the P-E ratio and the future variety of the P-E ratio. It will contribute to measuring the reasonable stock value of a company to make" the decision mode of the static state P-E ratio" applied to the type of Neural Network to help investors to increase investment return rate (IRR) by the dynamic P-E ratio operation mode in the long-term investment strategy of stock choosing.