Abstract:
Business enterprises can get capital funds from external sources to expand business activities either by borrowing form financial in¬stitutions to which they have to repay principal and interest, or by selling security to the public. In the latter case, the security ex¬change has played a significant role as a primary market to mobilize funds from the public for such companies. In addition, the market becomes a secondary one where securityholders can trade securities as desired and price are determined by supply and demand. The bullish and bearish situations in the market were well-reflected by the movement of security price index. According to the study, security prices do not move radomly by are related to some periods in the past. In this context a study should be made of historical price movement relations in order to forecast future price changes. The objectives of this study are as follows:- 1. To analyse historical price data by using Time Series Analysis to find out the appropriate forecasting technique as well as the number of retroactive observations for each security. The method to be selected are Box-Jenkins methodology, Double Moving Average and Double Exponential Smoothing. 2. To identify the relation ship between the SET Index and prices of high-turnover securities. 3. To verify the attitudes of people involed in security exchange activities. In this study, securities are selected from three business groups, namely banks, other financial institutions, and commerce & industry. The selected securities were high-turnover and their price had moved continuously. Among the companies which their securities were selected are the Bangkok Bank Ltd., the Thai Farmer Bank Ltd., the Bank of Ayudhya Ltd., the Industrial Finance Corporation of Thailand, the Jalaprathan Cement Co, Ltd., the Sim City Cement Co, Ltd. and the Maboonkrong Drying and Silo co, Ltd. The security prices used in the study were time series and applied for both daily and weekly data. According to the study results. Box-Jenkin mothodology is more effective in price forecasting as compared with Double Moving Average and Double Exponential Smoothing, except weekly prices form the Bangkok Bank and Maboonkrong Drying & Silo for which the Double Moving Average and Double Exponential Smoothing are well-applicable. It is also found that the SET index related to the selected security priced for only some periods. This implies that we can not continuously forecast the SET index trend from these security prices. Most of the people involed in security exchange activites believe that the prime factors affecting the security price variation are operating income and dividend per share. The difference between drops in price after dividend payment and dividend mainly results form operating income of firm, dividend per share and interest on loans from commercial banks. They are the same factors causing security Price changes. For the frequency to follow security price it is more benefial for speculators, as risk-takers, to keep up with information on pace movements more closely (i,e. daily rather than weekly) while traders, as investors, need not to do so.