ANALISIS CURRENT RATIO, RETURN ON EQUITY, PRICE EARNING RATIO TERHADAP RETURN SAHAM PADA SEKTOR INDUSTRI DASAR DAN KIMIA YANG TERCATAT DI BURSA EFEK TAHUN 2014-2016 - Wardani, Amalia Agustira (EKONOMIA, 2019)
Amalia Agustira Wardani: Analysis of Current Ratio, Return on Equity, Price Earning Ratio on Stock Returns in the Basic and Chemical Industry Sectors which are listed on the 2014-2016 Stock Exchange. (under Guidance of Supervisor I, Prof. Dr. Eddy Soegiarto and Second Supervisor Mrs. Rina Mashitoh).The Basic and Chemical Industry Sector began to be targeted by investors because this sector is the second highest sector after the financial sector in 2017 managed to record a growth of 17.08% ytd, to see whether this sector is worthy of investment needs to be observed such as by looking at stock returns . In Securities Analysis is known as the fundamental technique and in this technique has several variables that are Current Ratio (CR), Return On Equity (ROE), Price Earning Ratio (PER).The purpose of this study is to test, find out and explain the effect of Current Ratio (CR), Return on Equity (ROE), Price Earning Ratio (PER) on stock returns. The object of this study is the Basic Industry and Chemical Sector that has been and is still listed on the Indonesia Stock Exchange in 2014-2016. The sampling technique was purposive sampling and obtained a sample of 24 companies. The research data used multiple linear regression method with a significant level of 0.05.Based on the results of data analysis using a partial test (t-test) the variable Current Ratio has no significant negative effect on the Stock Return with a regression coefficient of -0.024 with a significance value of 0.841. Return on Equity has no significant positive effect on stock returns with a regression coefficient of 0.214 with a significant level of 0.070. Price Earning Ratio has a significant negative effect on Stock Return with a regression coefficient of -0.275 with a significance level of 0.022. The ability of independent variables in explaining the variation of the dependent variable is 9.8%, the remaining 90.2 is explained by other variables outside the model. The linear regression equation in this study was formulated into:Y=-0,016a-3,678X1+0.010X2-0,00X3+e