The objective of this study is to analyze the factors affecting the success of 1800 MHz frequencies auction for the telecommunication of 4 listed companies in the Stock Exchange of Thailand. Including Advanced Info Service Public Company Limited Total Access Communication Public Company Limited True Corporation Public Company Limited and Jasmine International Public Company Limited. The collection of financial data and annual reports were the first quarter of 2010 to the third quarter of 2015. The Logistic Regression Analysis was applied to test the hypothesis. The result of this study found that the total debt to equity ratio and current ratio affected the success of the 1800 MHz frequencies auction at the 0.05 significant level but the net profit margin ratio the asset growth rate the revenue growth rate and the fixed asset turnover ratio did not affect the success of frequencies auction at the 0.05 significant level.

The objective of this research was to explore factors affecting the selection of property plant and equipment revaluation influencing discretionary accruals of listed companies in real estate and construction sector in Stock Exchange of Thailand during the period of 2011 - 2013. Data were collected from 294 samples and analyzed by logistic regression analysis and t-test in order to test the hypothesis. The results revealed that debt and property investment ratios affected the selection of revaluation accounting policies. Furthermore the research revealed that sample firms selecting property plant and equipment revaluation had significantly higher discretionary accruals than those firms who applied cost method at 0.05 significant level of statistics.

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.

The objective of this research is to select a proper cumulative function for trend in an analysis of simultaneous multiple time series data with autocorrelation trend and outliers using a Bayesian method. The proposed model is applied to fluctuate stock price data in the stock exchange of Thailand. The data consist of the closing prices of 5 stocks. The algorithms are written in OpenBUGS and the performance of the model is evaluated via a simulation study in R. The cumulative distribution functions considered here are a Weibull cumulative distribution function and an exponential cumulative distribution. They are compared using RMSE MAPE and MAE as criteria. The research found that an exponential cumulative function for trends gives smaller values of the three criteria in both model fitting and model validation for the4 stocks EA NWR and KTB. However a Weibull cumulative distribution function gives smaller values of three criteria for the PTT in both model fitting and model validation.

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