The purpose of this research is to develop an early warning system model that can anticipate the occurrence of delisting of Islamic stocks (ISSI) using Support Vector Machines (SVM). Financial variables used consist of debt to equity, return on invested capital, asset turn over, quick ratio, current ratio, return on assets, return on equity, leverage, long term debt, and interest coverage. The population of this study is 335 sharia shares registered at ISSI in the period 2012-2017, with a total sample of 102 companies. The results show that the financial variables had a predictive power to the occurrence of delisting of Islamic stocks in the ISSI index. The effect of the independent variable or predictor variable is the financial ratio to the target variable or the dependent variable that is the potential for delisting of Islamic stocks in the ISSI index. With the development of 4 SVM models with different levels of prediction accuracy, SVM Model 1 with an accuracy rate of 71.57%, SVM Model 2 with an accuracy rate of 72.55%, SVM Model 3 with an accuracy rate of 82.35% and SVM Model 4 with an accuracy rate of 100%, it can be concluded that the SVM Model 4 is the best model. .

This research purposed to explored and analyzed those influence from capital adequacy ratios, net interest margins, loan to deposit ratios and non-performing loans towards dividend payout ratios on banks that registered as Buku Empat 2008-2017. Sampling gathered in this research by quantitative approach. Samples which obtained and used were Mandiri Bank, BRI, BNI, and BCA with observation period for 10 years. Data research was secondary data by panel data analysis method. The results shows that capital adequacy ratio had positive and significant influence towards dividend payout ratio, Net interest margin had negative and significant influence towards dividend payout ratio, Loan to deposit ratio had negative and significant impact on dividend payout ratio, non-performing loans had positive and significant impact towards dividends payout ratio.

This study aims to detect empirical evidence regarding the effect of liquidity, leverage, profitability and firm size on bond ratings. The population in this study uses banking companies listed on the Indonesia Stock Exchange in the period 2014-2018. The sampling method used was purposive sampling. 10 banking companies that met the criteria were sampled. The data analysis method used is panel data regression analysis. Panel regression analysis model used is the Fixed Effect model. The data used are secondary data in the form of annual financial ratios. The results of this study on the partial test prove that firm size has an effect on bond ratings. The results also showed that liquidity, leverage, profitability had no effect on bond ratings. The simultaneous test results prove that simultaneously liquidity, leverage, profitability and firm size have a significant effect on the bond rating

This research intends to determine the effect of liquidity, activity, leverage, and profitability on company value. The population of this research is the entire IDX retail trade subsector in 2015-2020 as many as 25 companies and the number of samples is 14 companies. The data analysis method used in the research is Panel Data Regression and the best model is the Random Effect Model. The results of the research partially found that liquidity (CR), activity (TATO), and leverage (DER) did not affect PBV, while profitability (NPM) had a positive effect on PBV. The research results simultaneously found that liquidity (CR), activity (TATO), leverage (DER), and profitability (NPM)  had an impact on PBV.

The purpose of this research is to determine the differences between performance and risks optimal portfolio of Single Index Model (SIM) and Capital Asset Pricing Model (CAPM) in the period August 2017 - January 2020. This research is a descriptive study with a quantitative approach. The data collection technique used is documentation study. Based on the results of the calculation, it is found that there is a difference return of the SIM portfolio to CAPM, there is no difference risk of the SIM portfolio to CAPM, there is a difference performance of the SIM portfolio that evaluated using the Sharpe, Treynor and Jansen methods and there is no difference performance of the CAPM portfolio that evaluated using the Sharpe, Treynor and Jansen method.