The study aims to estimate the effect of current ratio (CR), current liability to inventory (CLI), total asset turnover (TAT), net profit margin (NPM), sales growth (SG), and company size (FS) on profit growth (PG). The research population was 18 companies in the Food and Beverage (F&B) sector listed on the Indonesia Stock Exchange (IDX) from 2014-2018. The data estimation method uses the common effect panel data regression model. The empirical findings show that the CR and CLI ratios have a negative effect on PG, while the TAT, NPM, and SG ratios have a positive effect. Company size is a factor that does not affect the growth of company profits. The results of the study imply that an increase in company profits can be achieved if the company operates efficiently and with low liquidity to encourage higher sales growth. The limitations of the research are as follows: first, this research considers only one type of industry, hence the results of this study would not be the same if applied to another type of industry. Second, the author observes profit growth by using the company’s financial ratios and size and ignores other factors that may affect profit growth, for example, the number of employees, total net sales, and market capitalization.

In unfrictionless markets, one measure of asset pricing is its height of friction. This study develops a three-factor model by loosening the assumptions about stocks without friction, without risk, and perfectly liquid. Friction is used as an indicator of transaction costs to be included in the model as a variable that will reduce individual profits. This approach is used to estimate return, beta and other variable for firms listed on the Indonesian Stock Exchange (IDX). To test the efficacy of friction-adjusted three-factor model, we use intraday data from July 2016 to October 2018. The sample includes all listed firms; intraday data chosen purposively from regular market are sorted by capitalization, which represents each tick size from the biggest to smallest. We run 3,065,835 intraday data of asking price, bid price, and trading price to get proportional quoted half-spread and proportional effective half-spread. We find evidence of adjusted friction on the three-factor model. High/low trading friction will cause a significant/insignificant return difference before and after adjustment. The difference in average beta that reflects market risk is able to explain the existence of trading friction, while the difference between SMB and HML in all observation periods cannot explain returns and the existence of trading friction.