Logistic Regression Analysis Application in Financial Efficiency Prediction of Equity Mutual Fund in Thailand
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Abstract
This study has been conducted to construct an efficient financial prediction model and to examine factors affecting the prediction of equity mutual funds in Thailand. This study has adopted and applied the Logistic Regression (LOGIT) of Bankruptcy Prediction, including 274 equity mutual funds samples, each with the maturity of 5 years, and was conducted from 2016 to 2020. The financial efficiency was determined by both the fund’s outperformance and underperformance compared with the SETTRI market index in three performance measurements: Sharpe, Treynor, and Jensen’s alpha. The internal factors consist of financial ratios and fund-specific factors, while the external factors are Gross Domestic Product Growth (GDP Growth). The results from the study revealed that the LOGIT prediction model based on Jensen’s Alpha performed the highest accuracy one year before financial efficiency. It correctly predicted 73.6 percent. In addition, the total asset turnover and fund age statistically significantly affected financial efficiency in all measurements. The study results have confirmed the importance of financial ratios in the prediction model. Moreover, the financial efficiency prediction, which is adopted from the Logistic Regression (LOGIT) of Bankruptcy Prediction, is suggested for further study on another type of mutual fund.
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