The study on the relationship between financial ratios and returns from stock price ratios in the Market for Alternative Investment (MAI) aims to study the relationship between financial ratios and returns from the stock price ratio on the Market for Alternative Investment (MAI) and to the relationship between financial ratios and returns from the ratio of stock prices in the primary market The MAI of the companies with a high yield and the companies with low yield. The data is collected from 32 companies 151 samples listed on the Market for Alternative Investment (MAI). They are separated into 74 high-yield companies and 77 low-yield companies. The data is analyzed using descriptive statistical analysis including mean and standard deviation and inferential statistics including Pearson’s Correlation Coefficient Analysis and multiple regression analysis. The results showed that the working capital ratio (Log10CR) and net profit to equity ratio (ROE) were positively correlated with stock price ratio. The fast working capital ratio (Log10QR) and the net profit margin ratio (ROA) have a negative relationship with stock price ratio. The net profit margin (NPM) and the operating profit to income ratio (OIM) have no relationship with the share price ratio.

This study aims to study the client’s investment behavior in the Long-Term Equity Fund: LTF the clients invest in Krungsri Asset Management Company classified on demographic factors and to study different behavior of individual investor. The sample used in this study includes investors who invest in long-term equity fund (Krungsri’s LTF) amounting to 71518 investors. The sampled people derive from the Taro Yamane’s formula as Convenience sampling method that the confident level is 95% and the tolerance’s acceptance in the selection of the samples is 5% numbered 397 investors. The data collection did during October 2015 which evaluated and analyzed data using statistical software. This study analyzes by using statistics and percentage. This study found that most investors are females aged between 31-40 years married status get a bachelor’s degree have monthly revenue between 15000-30000 baht and their careers are government officers. In terms of investment found that most investors choose a long-term mutual fund (70:30 of dividend). On average each of the investors have investment value approximately 10000 baht per time or less than there is an average investment period over five years and the times to invest in the investment portfolio are the gradual purchases throughout the year. Regarding to the total investment in the mutual fund investors invest about 1-2 locations. In term of the loss’s acceptance has risk level around 10-20%. The investment objective is to receive tax benefits. For suggestions from the research results the asset management company should conduct these investment behaviors to make consideration on creating new products that are suitable for the investment this also reassure investors that their investments will bring benefits and have low risk in addition the confidence in the firmly fixed income and these investments do not cause adverse effects in a long-term investment. This research also makes choices in the matter of the benefits’ payment risk assessment in investment time to invest and so on. In order the fact that investors have choices to invest in the versatile mutual fund.

การวิเคราะห์ข้อมูลการซื้อขายซึ่งประกอบไปด้วย ราคาปิด ผลต่างของราคาปิด ผลต่างของปริมาณการซื้อขาย ผลต่างของดัชนี SETIndex NYMEX crude oil และ DJIA โดยใช้ข้อมูลที่มีช่วงเวลาเป็นวันและข้อมูลผลต่างจะใช้ข้อมูลวันที่คานวณกับข้อมูลในวันก่อนหน้านั้น ซึ่งการประยุกตใชวิธีการ K-NN (K-Nearest Neighbor) การวิเคราะหจังหวะการซื้อขายหุ้นโดยใช้การคาดการณ์จากการที่ K-NN จัดกลุ่มข้อมูลเข้ากับข้อมูลต้นแบบเพื่อพิจารณาว่าข้อมูลในวันถัดไปควรจะเป็นการขึ้นของราคาหรือไม่เพื่อประกอบการตัดสินใจซื้อขาย โดยข้อมูลที่ใช้เป็นข้อมูลในการเป็นแบบจาลอง 710 ชุด และข้อมูลในการทดสอบอีก 181 ชุด ผลจากการใช้ K-NN โดยประสิทธิภาพในการทานายจากการกาหนดค่า k = 21 สูงที่สุดจากการเลือก ค่า k ตั้งแต่ 1 ถึง 29 โดยสามารถทานายได้ถูกต้อง 107 ชุด และทานายผิด 74 ชุดข้อมูล ซึ่งประสิทธิภาพในการทานายคิดเป็นประมาณร้อยละ 59 ซึ่งใช้ประกอบการพิจารณาการซื้อขายได้

The purpose of this research was to study the relationship between profitability and shareholders wealth creation of food and beverage industry in The Stock Exchange of Thailand during the years 2010 to 2014. The study examined the financial data of twenty companies in the food and beverage industry with the highest market capitalization as of July 11th 2014. The study used descriptive statistics for initial data testing and used stepwise multiple regressions for testing the hypothesis. The results of the profitability study using stepwise multiple regression analysis indicated that the Operating Income Margin (OIM) Net Profit Margin (NPM) Return on Assets (ROA) Investment income (INV) and number of board of directors (BOD) were significantly related to shareholders wealth creation of food and beverage industry at the confidence level of 95%. However Firm size (FSIZE) was not statistically related to Shareholders Wealth creation of food and beverage industry.

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.