The objectives of this research were to study the personal and investment factors affecting decision making for investing in the provident funds of employees at Conference Solution Company Limiteds and its Subsidiaries’ Staffs. The population consisted of 191 staffs from Conference Solution Company Limiteds and Subsidiaries. The research instrument was a questionnaire with using the descriptive statistics Confirmatory Factor Analysis (CFA) and Binary Logistic Regression Analysis to test the hypotheses. The results of the study found that Education Income per month work the risk of investment knowledge of fund and the economy influencing the decision making to select to invest in the provident fund of the Conference Solution Company Limiteds and Subsidiaries.’ staffs at the statistically 0.05 Significant level.

The purpose of this research was to: 1) study the factors that affect the household accounts of people Baan Bang Pho Nuea Pathum thani 2) study the problems and barriers of the household accounts of people Baan Bang Pho Nuea Pathum thani. A questionnaire was used to collect the information through population in of people Baan Bang Pho Nuea Pathum thani. From studying the personal factors it was found that the majority of the population was female ages 41-50 years old 4 family members graduated elementary school average monthly household income in the range of 5000-15000 THB mostly without any financial institutions and most people did household accounts before. Factors affecting household accounts of people Baan Bang Pho Nuea Pathum thani include the necessary to do household accounts to make more savings to know revenue – expenses of families each month to spend carefully and no extravagant and to behave according to the principle of sufficiency economy. Troubles and barriers of making household accounts of Baan Bang Pho Nuea Pathum thani included lack of resource inexperienced lack of help advice from the authorities it’s complicated and waste of time do not want to disclose the facts in household accounts and dislike and ignore the benefits of household accounts

This study examined risk measurement of 3 ASEAN capital markets during year 2009 – 2013. The objective was to study and compare risk of 3 ASEAN capital markets before and after integration of 3 ASEAN member countries : Thailand Malaysia and Singapore. GARCH Model was used for estimating risk in order to measure the daily securities price index of 3 ASEAN member countries The study split the data into two time periods the first period before integration starting from December 1st 2009 to December 1st 2011 and the second period after integration starting from December 1st 2012 to December 1st 2013. The results show volatility which is transferred by the stock exchange and the other stock exchange. The internal and external factors caused the volatility. The level and direction of volatility was likely to depend on balance between listed companies structure and economic structure of those countries characteristic of the stock exchanges and the majority of the investors of those stock exchanges.

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