The Effect of Financial Performance on Stock Returns in Consumer Goods Sector Companies Listed on The Indonesia Stock Exchange for the 2016-2021 Period

Valeriani Pau Tuni Lasa, Matrodji H.Mustafa

Faculty of Economics and Business, Universitas Mercu Buana, Jakarta, Indonesia

Email: [email protected], [email protected]

Keywords

ABSTRACT

Return on asset, Curent ratio, Debt to asset ratio, Total asset turnover,Size��

This research aims to analyze and examine the factors that influence the stock return of the consumer goods sector listed on the Indonesia Stock Exchange. The research data is annual data for the observation period from 2016 to 2021 obtained from the company's annual report. The sampling method used was purposive sampling. From 57 companies as a population, 15 companies were taken as samples. Then based on the Chow test and Hausman test, the data analysis method used in this study is panel data regression with Fixed Effect Mode. The results of the study have shown that Return on Assets has a positive effect on stock returns, Debt to Assets ratio has a negative effect on stock returns, while current ratio, Total Asset turnover, and Size have no effect on stock returns.

INTRODUCTION

Consumer goods sector companies are industries engaged in manufacturing that process raw materials into finished materials, where later the products produced will be consumed by the wider community. Based on data in pusatis.com republished by cepagram.com, stocks that entered the Consumer Goods sector in 2020 were divided into 5 Subsectors, namely: Food and Beverages, Cigarettes (Tobacco Manufacturers), Pharmaceuticals, Cosmetics And Household and Houseware. The Consumer Goods Sector of the Food and Beverages Sub-Sector is projected to be one of the sectors that can be used as a mainstay in supporting manufacturing growth and the national economy. The Consumer Goods Sector of the Food and Beverages Sub-Sector also has promising prospects and good company performance with the stock price of each company that tends to be relatively stable so that this will make investors interested in investing in this sector.

In the face of increasingly fierce business competition among various public or household consumption provider companies, Fast Moving Consumer Goods (FMCG) companies that have been listed on the Indonesia Stock Exchange, must have good financial performance, So as to increase investment.

Investment is a commitment to a number of funds or other resources with the aim of obtaining a number of benefits in the future (Tandelilin, 2014:2). The purpose of investing is to get a return, which is the result (profit or loss) obtained from an investment. For investors, there are two things that are often a concern in deciding their investment choices, namely determining the expected return and the amount of risk that must be borne as a logical consequence of investment decisions that have been taken (Ang, 1997) make investment decisions.

Financial performance has a very important role for a company, especially for public companies (issuers), where in its operational activities are supported by investor funding in the use of its capital. Companies that have positive performance, not only maintain the existence and growth of the company, but can also be one of the attractions of investors to continue to invest. From the list of companies in table 1.1 contained in the appendix, it can be seen that there are companies that have long been listed on the Indonesia Stock Exchange and some have only registered their companies a few years ago. The increasing number of companies in this industry from year to year indicates that business competition in the consumer goods sector is getting tighter, so these companies certainly cannot be separated from the need for good financial performance.

Financial performance can basically be said as an evaluation of the company which includes assets, liabilities, equity, costs, and overall profitability. Fahmi, 2018 stated that: "Financial performance is an analysis conducted to see the extent to which the company has implemented financial rules properly and correctly". So it can be said that financial performance performance is the achievement of a company's form of achievement in its financial management activities over a certain period of time.�

The capital market is a market for various long-term financial instruments with a maturity of more than one year, such as stocks, debt securities (bonds), mutual funds, and various derivative instruments from securities or securities. The capital market is a means of funding for companies and governments, and as a means of investment activities for fund owners (investors). The capital market is not just a market that has buying and selling transactions. The capital market has a big role for a country's economy because the capital market performs two functions at once, namely the economic function and the financial function.

Business in the capital market is an attractive business today, because business in the capital market can be said to be a fairly stable business. Therefore, companies that have been listed on the Indonesia Stock Exchange, should have good financial performance so as to attract investors. With the listing of the company on the Indonesia Stock Exchange, of course, the goal is to make it easier to access funding for the continuity and growth of its business.

The financial performance of a company (issuer) can be seen from its financial statements. So as to be able to describe the overall financial condition, both related to the collection of funds and the distribution of funds. Measurement of a company's financial performance, generally can be seen from the liquidity ratio, activity ratio, solvency ratio, and profitability ratio.

Investors before investing in certain stocks on the capital market (Indonesia Stock Exchange), of course, analyze their financial performance first, this is done to get a holistic picture of the company, one of which is an overview of stocks. In other words, stock returns are one of the most important things for investors and companies. In this case, stock returns can be used as a tool to measure company performance by investors in investing in the capital market which is certainly to get a rate of return on funds invested in company shares.

Return is the result obtained from investment, return can be in the form of realized returns that have occurred or expected returns that have not occurred but are expected to occur in the future (Hartono, n.d). Meanwhile, according to (Gitman, L. J., & Michael, 2010). Stock return is a rate of return for ordinary shares and is a cash payment received due to ownership of a share at the beginning of investment. Thus, it can be said that stock return is the rate of return or profit obtained by investors on a number of investment funds invested in shares of certain companies in the capital market. Before investors invest their capital, investors can forecast expected stock income in the future, or predict stock returns on their investment.

In 2020, the return of the stock market is lower, even smaller than the bond index. Whereas in the previous year, stock returns always exceeded the bond index. Overall, issuers posted a 10% decline in revenue in 2020. However, amid the slowdown in the performance of the issuer, retail investors experienced rapid growth (beritasatu.com, 2021). The performance of ISHG over the past 10 years can be seen in the following figure:

Table 1. Composite Stock Price Index (ISHG)

Year	JCI year-end	Annual Acquisition	Accumulated Acquisition
2012	4.316,69	12,94%	12,94%
2013	4.274,18	-0,98%	11,83%
2014	5.226.95	22,29%	36,76%
2015	4.593,01	-12,13%	20,17%
2016	5.296,71	15,32%	38,59%
2017	6,355,65	19,99%	66,29%
2018	6.194,50	-2,54%	62,08%
2019	6.299,54	1,70%	64,08%
2020	5,979,07	-5,09%	56,44%
2021	6,581,48	10,08%	72,20%
JCI Performance 10-year Annualized (CAGR)			5,59%

����������������� Source: idx.co.id, 2022 (processed bolasalju.com, 2022)

The decline in returns caused by the slowdown in the performance of issuers can be seen in the following performance of the Composite Stock Price Index (ISHG), where in 2020 there was a sharp decline.

Figure 1. Composite Stock Price Index (ISHG)

Source: idx.co.id, 2021

Stock indices can basically be used as a marker of investment market conditions globally. Stocks are volatile, can go up or down as well as commodity prices in the market. The occurrence of ups and downs in stock prices is something natural, this is because the movement is determined by the forces of supply and demand in the capital market. When demand is high, the price will rise, and vice versa when supply is high, the price will decrease.

� (Sudarsono & Sudiyatno, 2016) stated that many factors affect stock returns, including fundamental and technical information. Fundamental information focuses on the performance of the company issuing the shares and the economic analysis that will affect the future of the company. It can also be said that fundamentals relate to financial ratios and events that directly or indirectly affect the financial performance of the company. While technical information is market data from stocks, such as the price and volume of stock sales transactions to determine the value of shares regardless of the performance of the company that issued the shares.

�In this study, the author uses financial ratios related to fundamental analysis to build a research model. This study examines and analyzes the effect of financial performance on stock returns in consumer goods sector companies listed on the Indonesia Stock Exchange for the 2016-2021 period. The ratios used are: Liquidity Ratio represented by current ratio, Activity Ratio represented by total assets turnover, Profitability Ratio represented by Return on assets, Solvency ratio represented by Debt to Asset Ratio, and Firm Size.

Current Ratio is used to measure a company's ability to meet its short-term debt. Total assets turnover is used to measure the extent of the company's effectiveness in managing its assets to generate sales or to compare sales gains with assets owned. Return on assets is used to measure the company's ability to generate profits for the company with its assets. Debt to Asset Ratio is used to assess debt to total assets. Firm Size is used to indicate the size of a company.

To prove the relationship between stock returns and financial ratios such as curent ratio, total asset turnover, return on assets, and debt to asset ratio and Firm Size has been done by many researchers. As research conducted by (Mayuni & Surrjaya, 2018). from the results of her research, it is known that Firm Size does not have a significant effect on stock returns, while research conducted by (Aisah & Mandala, 2016) found that Firm Size has a significant effect on stock returns.

�Research conducted by (Basalama et al., 2017) that Current Ratio, Return on Asset Ratio simultaneously affect stock returns. The results of different studies were stated by �(Yuliana & Artati (2022) where the results of the study stated that Return on Assets (ROA), Current Ratio (CR), had no effect on stock returns.� Then the results of Nissa's research (2017) found that Total Asset Turn Over (TATO) has a positive effect on stock returns. While (Thrisye & Simu. 2013) stated that Total Asset Turn Over (TATO) on stock returns did not have a significant effect.

Another different study was also put forward by (Hermawan, 2012) who found that the Debt to Asset ratio has a positive effect on stock returns. This is different from research conducted by (Wulandari & Hakiman, 2019), which shows that the Debt to Asset ratio has no effect on stock returns, It is also different found in Asian research (2020) where the Debt to Asset ratio has a negative effect on stock returns. The author was motivated to conduct the study because of the differences from the results of research conducted by previous researchers, researchers interested in reconfirming the performance conditions of the consumer goods sector with the period 2016 to 2021. The selection of a 6-year period from 2016 to 2021 is considered representative to describe the consumer goods sector to be studied.

Another thing that motivates the author to conduct research is because the stock price of companies in the consumer goods sector shows a downward tendency as presented in the following chart:

Figure 2. Consumer Goods Index for the Period 2012 � 2021

Source : indonesia-investments.com, 2022

During the period 2012 to 2021, the consumer goods sector index showed a decline in recent years, as seen in 2019 to 2020. Although in 2021 there began to increase slightly, this indicates that stock returns have also decreased. Overall, the consumer goods sector in 2021 Gain/Loss YTD amounted to -8.10%.

METHODS

In this study, the design used was the Normality Research Design. Habit is the Principle of Cause and Effect.� The scope of this research is Shares outstanding on the Indonesia Stock Exchange (IDX), The stocks used in this study are issuers of the Consumer Goods sector in the 2016 to 2021 period. The population in this study is the Coonsumer Goods Company of the food and beverage sub-sector listed on the Indonesia Stock Exchange (IDX) for the period 2016 to 2021 with a population of 31 companies for 6 years. In this study, the sampling technique used is Purposive Sampling, where the sampling determination uses certain criteria.

RESULTS AND DISCUSSION

Analysis

Panel Data Registration Model

In the panel data registration model, testing was carried out to determine the right registration model in this study. In testing models, three alternative methods are used, namely Common� effect models, Fixed effect models, and Random effect models. The following are the results of the test:

1. Common effect model

Common effect models are estimators that combine �time series data with cross sections, namely by using �the Ordinary Last Square �approach to estimate the parameters Common effect models �ignore differences in�� individual dimensions or time or �with other intentions, namely the behavior of data between individuals is the same in various time periods. Here are the results of Common effect models:

Table 2. Common Effect Model Estimation Results

Variable	Coefficient	Std. Error	t-Statistic	Prob.
C	0.269312	0.298063	0.903542	0.3688
ROA?	0.945437	0.303748	3.112569	0.0025
CR?	-0.002195	0.006407	-0.342554	0.7328
TATTOO?	0.076770	0.074399	1.031859	0.3051
DTA?	-0.212059	0.128584	-1.649195	0.1028
SIZE?	-0.028528	0.030127	-0.946905	0.3464
R-squared	0.162052	Mean dependent var		0.106181
Adjusted R-squared	0.112174	S.D. dependent var		0.436805
S.E. of regression	0.411577	Akaike info criterion		1.126700
Sum squared resid	14.22925	Schwarz criterion		1.293354
Log likelihood	-44.70152	Hannan-Quinn criter.		1.193905
F-statistic	3.248981	Durbin-Watson stat		2.102537
Prob(F-statistic)	0.009900

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2. �Fixed effect model

In this study using Fixed� effect Model, where Fixed effect �model is a method that examines the estimation of panel data registration parameters, namely by using the technique of adding �dummy variables, this method is often called �the Least dummy variable model. The fixed effect model emphasizes that the intercepts of each individual are different while� the slopes between individuals are the same. In this method, use dummy variables to find intercept differences between individuals. The following are the results of Fixed effect Model:

Table 3. Fixed Effect Model Estimation Results

Variable	Coefficient	Std. Error	t-Statistic	Prob.
C	-0.574278	1.559008	-0.368361	0.7137
ROA?	1.656759	0.379667	4.363720	0.0000
CR?	0.005218	0.006450	0.808992	0.4213
TATTOO?	0.019859	0.222839	0.089119	0.9292
DTA?	-0.367274	0.174935	-2.099486	0.0394
SIZE?	0.080800	0.173355	0.466098	0.6426
	Effects Specification
Cross-section fixed (dummy variables)
R-squared	0.370760	Mean dependent var		0.106181
Adjusted R-squared	0.199967	S.D. dependent var		0.436805
S.E. of regression	0.390698	Akaike info criterion		1.151368
Sum squared resid	10.68516	Schwarz criterion		1.706881
Log likelihood	-31.81157	Hannan-Quinn criter.		1.375384
F-statistic	2.170808	Durbin-Watson stat		2.572720
Prob(F-statistic)	0.010189

3. Random effect model

The random effect� model is a method that uses differences in the characteristics of individuals with the time that the error accommodates �in the model. Then there are two components that contribute to the formation� of errors, �namely individual and time, so random �errors in the Random effect Model will be broken down into �errors for the combined components of time and error. Here are the results of the Random effect model:

Table 4. Random Effect Model Estimation Results

Variable	Coefficient	Std. Error	t-Statistic	Prob.
C	0.269312	0.282943	0.951827	0.3439
ROA?	0.945437	0.288339	3.278904	0.0015
CR?	-0.002195	0.006082	-0.360860	0.7191
TATTOO?	0.076770	0.070625	1.087001	0.2801
DTA?	-0.212059	0.122061	-1.737327	0.0860
SIZE?	-0.028528	0.028599	-0.997508	0.3214
	Effects Specification
			S.D.	Rho
Cross-section random			0.000000	0.0000
Idiosyncratic random			0.390698	1.0000
	Weighted Statistics
R-squared	0.162052	Mean dependent var		0.106181
Adjusted R-squared	0.112174	S.D. dependent var		0.436805
S.E. of regression	0.411577	Sum squared resid		14.22925
F-statistic	3.248981	Durbin-Watson stat		2.102537
Prob(F-statistic)	0.009900
	Unweighted Statistics
R-squared	0.162052	Mean dependent var		0.106181
Sum squared resid	14.22925	Durbin-Watson stat		2.102537

Panel Data Registration Model Selection

To determine the right panel data regression test, the thing to do is to test the data with all test models. Based on the test results of the model selection, it can be concluded that the conclusions of the panel data regression model are:

1. Chow Test

In this test, there is a selection of models to be used, namely between the common effect model �and� the fixed effect model. The guidelines to be used in making chow test conclusions� are as follows:

H0: The selected model is the Common effect .

Ha : The selected model is Fixed effect .

If the Prob number > alpha 5% then Ho is accepted, i.e. the common effect is chosen. If the Prob number is < or equal to alpha 5% then Ho is rejected, i.e. Fixed effect is chosen. The following are the test results of the Chow test �:

Table 5. Chow Model Test Results

Effects Test	Statistics	d.f.	Prob.
Cross-section F	1.658414	(14,70)	0.0850
Cross-section Chi-square	25.779904	14	0.0276

Based on the results in table 5 above, it can be seen that the prob cross-section �value is smaller than 0.05, which is 0.027, then from these results H_o is rejected which means �the Fixed Efect model to be selected but a hausman test will be carried out� to determine the best results between the� Random Effect Model �or Fixed Effect Model models.

2. Hausman Test

In this test there is a selection of models to be used, namely between Fixed Effect Model �and Random Effect Model. The guidelines to be used in making conclusions of the Hausman test� are as follows:

H0: The selected model is a random effect .

Ha : The selected model is� fixed effect.

In this test it can be seen in the p-value if the results obtained are less than 5% (Significant) then the estimation model that will be used is Fixed effect, but if the p-value exceeds 5% (not significant) then the estimation model that will be used is random effect �. The following are the test results of the Hausman test �:

Table 6. Hausman Model Test Results

Test Summary	Chi-sq. Statistics	Chi-sq. d.f.	Prob.
Cross-section random	15.089850	5	0.0100

Based on the results in table 6 above, it can be seen that the random cross-section prob value is smaller than 0.05, which is 0.01, then based on these results, the� model to be selected is the Fixed Effect Model model, and there is no need to test the lagrange multiplier because �the Fixed Effect Model model has been selected as the best model.

3. Panel Data Registration Model Selection Conclusion

Table 7. Conclusion of registration model selection

Dependent Variables	Independent Variables	Chow Model Test	Hausman Model Test	Conclusion
Stock Price	Return on assets Curent ratio Debt to total asset ratio Total Asset turnover Size	Prob > 0.05 then �H0 rejected, estimation using Fixed effect model	Prob < 0.05 then �H0� rejected, estimation using Fixed effect model	Estimation using Fixed Effect model

4. Panel Data Regression Analysis

Panel Data Registration Analysis in this study uses Fixed Effect� method for diagram model. The selection �of Fixed Effect as a method of panel data analysis in this study had previously been tested through �the chow� test and� the Hausaman test, so that it was concluded that �the Fixed Effect� method �was the most appropriate for the research diagram model. The following are the results of data testing using the Fixed Effect Model:

Table 8. Fixed Effect model Estimation Results

Variable	Coefficient	Std. Error	t-Statistic	Prob.
C	-0.574278	1.559008	-0.368361	0.7137
ROA?	1.656759	0.379667	4.363720	0.0000
CR?	0.005218	0.006450	0.808992	0.4213
TATTOO?	0.019859	0.222839	0.089119	0.9292
DTA?	-0.367274	0.174935	-2.099486	0.0394
SIZE?	0.080800	0.173355	0.466098	0.6426
	Effects Specification
Cross-section fixed (dummy variables)
R-squared	0.370760	Mean dependent var		0.106181
Adjusted R-squared	0.199967	S.D. dependent var		0.436805
S.E. of regression	0.390698	Akaike info criterion		1.151368
Sum squared resid	10.68516	Schwarz criterion		1.706881
Log likelihood	-31.81157	Hannan-Quinn criter.		1.375384
F-statistic	2.170808	Durbin-Watson stat		2.572720
Prob(F-statistic)	0.010189

From the Regression results, the constant value of each company for 2016-2021 was also obtained, namely with the following results:

Table 9. Cross-section Fixed Effect

	CODE	Effect
1.	AISA	0.171266
2.	ALTO	0.252564
3.	ADES	0.244649
4.	CEKA	0.029971
5.	DLTA	-0.332783
6.	ICBP	-0.307312
7.	INDF	-0.252851
8.	MLBI	-0.491560
9.	MYOR	-0.120328
10	BREAD	-0.059064
11.	SKBM	-0.029215
12	SKLT	0.654600
13.	STTP	0.031216
14.	PSDN	0.451144
15.	ULTJ	-0.242296

�

Based on the results of the analysis using eviews 10, the Registration model of this study can be formulated as follows:�

Yit = α1+α2D2+...+αnDn+β1X1i + β2 X2i + ... + β n Xni+ εi

Yit = -0.574278 + 1.656759 ROAit + 0.005218 CRit + 0. 019859 TATOit � 0.367274 DTAit + 0.010189 SIZEit

�� ������ Based on the equation that has been obtained Above, then the explanation is as follows:

1.) The value of the constant coefficient of -0.574278 means that if all variables ROA, CR, TATTOO, DAR, and SIZE have a value equal to zero (0), then the dependent variable namely return will have a value of -0.574278 equal to the constant.

2.) The variable Return on assets produces a probability value of 0.0000 with a positive coefficient of 1.656759 so it can be concluded that the variable Return on assets has a positive effect on stock returns.

3.) The Current Ratio variable produces a probability value of 0.4213 with a coefficient of 0.005218 so it can be concluded that the Current Ratio variable has no effect on stock returns.

4.) The variable Total asset turnover produces a probability value of 0.9292 with a coefficient of 0.019859 so it can be concluded that the variable Total Asset turnover has no effect on stock returns.

5.) The variable Debt to Total Asset Ratio produces a probability value of 0.0394 with a negative coefficient of -0.367274 so it can be concluded that the variable Debt to Total Asset Ratio has a negative effect on stock returns.

6.) The Firm Size variable produces a probability value of 0.6426 with a coefficient of 0.080800 so it can be concluded that the Firm Size variable has no effect on stock returns.

1. Simultaneous Test ( Test F)

The F test is used to determine the effect of the independent variable on the dependent variable in a study simultaneously or together. Using a significant level of 0.05 Simultaneous Test (Test F) can be formulated as follows:

If Prob > 0.05 then_H0 is� accepted and H1 is rejected (no significant effect) meaning that Return on assets, Curent Ratio, Debt to Equity Ratio, and total Asset turnover simultaneously have no effect on the value of stock returns.

If Prob < 0.05 then H 0 _is� rejected and H1 is accepted ( significant effect) meaning Return on assets, Curent Ratio, Debt to Equity Ratio, and total Asset turnover simultaneously affect the value of stock returns.

Table 10. Results of Simultaneous Test Analysis

Dependent Variables	Independent Variables	F-Statistic Value	Value of Prob(F-statistic)
Stock Return	Return on assets Curent ratio Debt to Total Asset Ratio Total Asset turnover Size	2.170808	0.010189������

The results of Test F above show that the value of Prob (F-statistic) �is 0.010189 smaller than 0.05. Which means that H0 is rejected and H1 is accepted (significant effect), where Return on assets, Curent Ratio, Debt to Total Asset Ratio, total Asset turnover, and Size simultaneously have a significant effect on the value of stock returns.

2. Test Coefficient of Determination (Test R²)

The Coefficient of Determination (R2) aims to measure how much the percentage of independent or independent variables in explaining dependent or bound variables in percent units in a research regression model. The following are the results of the coefficient of determination test in this study:

Table 11. Test Results of Coefficient of Determination

Dependent Variables	Independent Variables	R-Square value	Adjusted R-Square Value
Stock Return	Return on assets Curent ratio Debt to Total Asset Ratio Total Asset turnover Size	0.370760	0.199967������

Based on Table 11 above, the R-Square �value is 0.370760.This shows that 37.07% Stock Return (Y)� is influenced by Return on Assets, Curent Ratio, Debt to Total Asset Ratio, total asset turnover, and Size, while 62.93% is influenced by other factors outside this study.

3. Partial Test (Test t)�

According to (Ghozali, 2011), the t test can show how far the influence of an independent variable individually (partially) in explaining the variation of the dependent variable.� Here is the testing hypothesis:

H0 accepted: Prob (t-static) > 0.05 which means that the independent variable has no partial effect on the dependent variable.��

H1 rejected : Prob (t-static) < 0.05 which means that the independent variable has a partial effect on the dependent variable.��

The results of the T Test on independent and dependent variables in this study can be seen as follows:

Table 12. Panel Data Registration Using Fixed Effect Model

Variable	Coefficient	Std.error	T-Statistic	Prob
C ROA CR DAR TATTOO SIZE	-0.574278 1.656759 0.005218 -0.367274 0.019859 0.080800	1.559008 0.379667 0.006450 0.174935 0.222839 0.173355	-0.368361 4.363720 0.808992 -2.099486 0.089119 0.466098	0.7137 0.0000 0.4213 0.0394 0.9292 0.6426

Based on the test results in table 12, it can be explained as follows:

1. The Effect of Return On Assets on Stock Return

Table 13. �Return On Assets to Stock Return

Hubs Between Variables	Coefficient	Prob	Conclusion
Return On Assets to Stock Return	1.656759	0.0000	Positive Influence

The results of the Panel Data Registration �(Fixed Effect Model)� show that the relationship between �Return On Assets and �Stock Return has a� probability value below 0.05 (0.0000) with a coefficient of 1.656759. which means that partially Return On Asset has a positive effect on� Stock Return.

2. The Effect of Curent Ratio on Stock Return

Table 14.� Curent Ratio to Stock Return

Hubs Between Variables	Coefficient	Probe	Conclusion
Curent Ratio	0.005218	0.4213	No Effect

The results of the Panel Data Regration �(Fxied Effect Model) show that the� relationship between �Curent Ratio� and �Stock Return has� a probability value above 0.05 (0.4213) with a coefficient of 0.005218. which means that partially Curent Ratio has no effect on� Stock Return.

3. The Effect of Debt to Total Asset Ratio on Stock Return

Table 15. Debt to Total Asset Ratio to Stock Return

Hubs Between Variables	Coefficient	Prob	Conclusion
Debt to Total Asset Ratio	-0.367274	0.0394	�negative influence

The results of the Panel Data Regration �(Fixed Effect Model) show that the� relationship between �Debt to Total Asset Ratio and �Stock Return has a� probability value below 0.05 (0.0394) with a coefficient of -0.367274 which means that partially Debt to Total Asset Ratio has a negative effect on �Stock Return.

4. The Effect of Total Asset Turnover on Stock Return

Table 16. Total Asset Turnover to Stock Return

Hubs Between Variables	Coefficient	Prob	Conclusion
Total Asset Turnover	0.019859	0.9292	No Effect

The results of the Panel Data Registration �(Fixed Effect Model)� show that the relationship between Total Asset Turnover and �Stock Return has� a probability value above 0.05 (0.9292) with a coefficient of 0.019859. which means that partially� Total Asset Turnover �has no effect on� Stock Return.�

5. The Effect of� Firm Size� on Stock Return

Table 17. Firm Size to Stock Return

Hubs Between Variables	Coefficient	Prob	Conclusion
Firm Size	0.080800	0.64226	No Effect

The results of the Panel Data Regration �(Fixed Effect Model) show that the� relationship between �Firm Size and �Stock Return has� a probability value above 0.05 (0.6426) with a coefficient of 0.080800. which means that partially Firm Size �has no effect on� Stock Return.���

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Discussion

Based on the results of the research described above, this subchapter will explain the results of the tests carried out.� The discussion was carried out by describing the strong influence between independent variables consisting of Return on Assets, Curent Ratio, Debt to total Asset Ratio, total asset turnover, and Size on� stock returns for the period 2016 to 2021. Then the explanation of the influence between variables will then be compared with the empirical evidence obtained and the theory that supports the hypothesis. The following are the stages of discussion:

The Effect of Return on Assets on Stock Return

Return on Assets describes a company's ability to generate probabilities. The increasing Return on Assets means the company's performance is in good condition, because the company can utilize the assets owned very well. So that it can make investors interested in investing in the company which will make� stock returns rise.

This shows that� the return on assets seems fully supportive for improving the performance of consumer goods industry companies� listed on the IDX in 2016-2021. The results of this study also support the results of previous research conducted by (Dewi, 2018) which also proves that Return on Assets affects �stock returns. A positive return on assets indicates that the capital invested in all assets to be used for the company's operations is able to provide profits for the company. This can make investors place this ratio when determining� stock returns so that� Return on assets �affects stock returns.

The Effect of Curent Ratio on Stock Return

Based on theory, the higher the value of the current ratio, the more current assets owned by the company compared to the amount of current liabilities that must be paid off. However, companies that� have a high current ratio do not necessarily have high stock returns also because a high current� ratio does not always have a good impact on the company because �a high Curent ratio �can indicate a large amount of funds that are installing, which in turn can reduce the company's ability to earn profits (Sawir, 2019). Reduced ability of a company to generate profits will make investors assume that� the returns to be generated by the company will also be small. if this happens then the direction �of the Curent ratio effect on� stock returns� becomes inconsistent and depends on the effectiveness of the company in using its current assets. This can make investors rarely put this ratio when determining� stock returns so that� the Curent Ratio has no effect on stock returns.

The results of this study found that the Curent Ratio has no effect on� stock returns (Y). Results This study is in line with the results of previous research conducted by (Yuliarti & Diyani, 2017) which also proved that the Curent Ratio has no significant effect on �stock returns.

The Effect of Debt to Total Asset Ratio on Stock Return

Debt to Total Asset Ratio �is a ratio used to measure the ratio between total debt and total assets. From the results of these measurements, if it turns out that the ratio is high, the funding of assets with more debt which will be more difficult for the company to get additional loans because it is feared that the company will not be able to pay the debt debt owned with the assets owned. Conversely, if� the Debt to Asset Ratio is low, the smaller the company's assets are financed by debt. This can make investors place this ratio when determining� stock returns so that� the Debt to Total Asset Ratio �has a negative effect on stock returns.

The results of this study state that �the Debt to Total Asset Ratio �has a negative effect on stock return (Y), where� the Debt to total asset ratio partiallyhas a negative effect on ��stock returns. The results of this study are in line with the results of previous research conducted by Asia (2020) also proving that the Debt to Total Asset Ratio has a negative effect on �stock returns.

The Effect of Total Asset Turnover on Stock Return

Total Asset Turnover serves to measure the company's ability to generate sales from its total assets by comparing net sales with total average assets. The faster the level of asset turnover of a company, the amount of profit generated will also be high, and vice versa the longer the level of asset turnover of a company, the amount of profit generated will also be lower. This can make investors rarely put this ratio when determining� stock returns so that Total Asset Turnover does not affect stock returns.

Although the results of� the partial Total Asset Turnover study� cannot be said to be in accordance with the singalling theory, this result also shows that investors will also consider other financial ratios when placing investments. In this case, the effect of Total Asset Turnover must be viewed holistically together with other variables.

The results of this study state that Total Asset Turnover has no effect on� stock Return (Y). The results of this study are in line with the results of previous research conducted by (Hanivah & Wijaya, 2018) which also proved that Total Asset Turnover has no effect on �stock returns.

The Effect of Firm Size on Stock Return

Firm Size is a scale where can be classified large and small a company from total assets, net sales, and basic capitalization of the company, Larger company size will help make it easier to obtain additional funds in the capital market compared to small companies. But investors also should not only look at the size of the company, because large-sized companies do not always have large total assets derived from the capital owned by the company, because the capital owned by the company can also be sourced from loan funds that later must be paid which can result in small stock returns. This can make investors rarely put this ratio when determining� stock returns so that Firm Size does not affect stock returns.

The results of this study state that Firm Size has no effect on� stock Return (Y). This research is in line with the results of previous research conducted by (Mayuni & Suarjaya, 2018) which also proved that Firm Size has no effect on �stock returns.

CONCLUSION

��������� Based on the results of the above research related to the effect of Liquidity, Activity, Profitability, Solvency, and Firm Size Ratios on the return of shares in the consumer goods sector listed on the Indonesia Stock Exchange for the 2016-2021 period, which has previously been described through the introductory sub-chapter, theoretical studies, data processing, and the discussion discussed in the previous chapter, the following conclusions can be described: (1) Return on Assets has a significant positive effect on stock returns.�������� (2) Curent ratio has no effect on stock returns. (3) Debt to total Asset Ratio has a negative effect on stock returns. (4) Total Asset turnover has no effect on stock returns. (5) Firm Size has no effect on stock returns. Variable Profitability proxied by Return on Asset and Variable Solvibility proxied Debt to Total Asset Ratio can be used as one of the signals for investors in the capital market to invest in shares The stock will later be able to increase the company's valuation. While other variables such as Curent ratio, Total asset ratio, and Size although not influential but if used with other influential variables it can be a complementary variable that helps increase accuracy in making decisions.

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