The objectives of this research are to analyze the relationship between securities price and the efficiency of the account receivable management and to study the model of improving the efficiency of the account receivable management of the agricultural business group in the Stock Exchange of Thailand. The number of data which had been used in this research was 16 random companies of all 22 companies from the listed companies in the Stock Exchange of Thailand agricultural business group by using purposive sampling method. The researcher used both quantitative and descriptive analysis method by bringing the quantitative data analysis from 2006-2010 to descriptive analyzing which had compared between the selling revenue account receivable value allowance for doubtful bad debt account receivable turnover average collection period book value per share primary earnings per share and securities price. The results of analyzing are changing in the account receivable of Chiangmai Frozen Foods Pcl. Lee Pattana Pcl.; changing in the bad debt of Pak Food Pcl.; changing in the average collection period of Thai Rubber Latex Corporation (Thailand) Pcl. Pak Food Pcl.; changing in the book value per share of Pak Food Pcl. Kiang Huat Sea Gull Trading Frozen Food Asian Seafoods Pcl. Asian Seafoods Pcl.; changing in the primary earnings per share of Thai Rubber Latex Corporation (Thailand) Pcl. Thai Luxe Enterprise Pcl. Lee Pattana Pcl. and Kiang Huat Sea Gull Trading Frozen Food Asian Seafoods had related to securities price per share.

The purpose of this study is to compare four forecasting methods on SET Index SET 50 Index and SET 100 index. These methods are Simple Exponential Smoothing Holt’s Method Box-Jenkins Method and Regression Analysis. Two sets of Index data were used in this study. The first one used as a training set was collected at the end of each day from January 2 2008 to September 30 2011. The other one used as a testing set was collected at the end of each day from October 3 2011 to October 14 2011. The diagnostic check was used to test each method. The MAE MSE and MAPE from each method shows that Box-Jenkins is more appropriate to the forecasting of SET Index SET 50 Index and SET 100 Index because its MAE MSE and MAPE are fairly low and have no autocorrelations. This leads to the conclusion that the appropriate models for forecasting of SET Index SET 50 Index and SET 100 Index are ARIMA (212) ARIMA (213) and ARIMA (213) respectively. The most stock market indices are correlated to SET Index SET 50 Index and SET 100 Index is Composite Index of Indonesia

This research is to investigate the effects of efficiency in internal audit review of listed companies in Stock Exchange of Thailand by collecting data from 518 audit committee of listed companies in Stock Exchange of Thailand by using a questionnaire as an instrument. The results of statistics used for analyzing the collected data were simple linear regression analysis and multiple linear regression analysis indicated efficiency in internal audit reviews had positive relationships with corporate performance effectiveness and efficiency in risk management. Moreover effectiveness performance revealed a positive effect on gold achievement. The results obtained from this study could be used as guidelines for developing creating and improving the efficiency in audit committee performance and internal audit practice for organization to create reliability to the public and to be able to survive sustainably in a long period of time.

The purpose of the study was to scrutinize patterns and levels of environmental accounting disclosure of listed companies in eight industries in the Stock Exchange of Thailand. The research applied documentary research methodology and descriptive statistics including percentage distribution and Correlation analysis using Chi – Square at Statistical significance at the 0.05 level. The results of the study showed that five among eight industries including agro- and food industry consumer goods industry industrial goods industry real estate and construction industry and resources industry disclosed their environmental accountings at level 2; specific but not quantitatively measurable. However each company paid the highest attention to the environmental management systems because of its prominent requirements. As for the other three industries which were finance industry service industry and technology industry disclosed their environmental accountings at level 0; no environmental accountings disclosure since they paid limited interest to the environmental accounting during 2009 and 2012. In terms of the relationship between the entrepreneur and the environmental accounting disclosure it was found that the entrepreneur’s five aspects such as the business operational period paid paid-up registered capital total assets total liabilities and total revenues were significantly related at the disclosed level of 0-3.