Eduvest ï¿½ Journal of Universal Studies Volume 3 Number 1, January, 2023 p- ISSN 2775-3735- e-ISSN 2775-3727

THE EFFECT OF GREEN FINANCE ON STOCK PRICE VOLATILITY
Ernst Tunggul Pardomuan Siregar, Bangkit Nata Satria M Insitut Teknologi Sepuluh November Surabaya, Indonesia Email: [email protected], [email protected]
ABSTRACT
This study aims to determine the effect of green finance (green accounting) on stock price volatility.ï¿½ Stock price volatility is the movement of up and down stock prices on the stock exchange. In this study, the sample used was mining companies listed on the Indonesia Stock Exchange for the 2013-2018 period with a total population of 46 companies. With purposive sampling technique, get 18 companies as samples. This study used the panel data regression method with a common effect model approach. The results showed that a green finance has a positive effect on stock price volatility.ï¿½ Information asymmetry as a moderation variable cannot amplify the influence of green finance on stock price volatility, and also the effect of quality environmental and social disclosures on stock price volatility
KEYWORDS	green finance, stock price volatility, information asymmetry
	This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International

INTRODUCTION

ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ï¿½ Injecting capital is not only from the owner of the company, but injecting with a large enough nominal can be obtained through external parties of the company, namely the holders of the sham.ï¿½ In addition, proper air quality plays an important role in the survival of many creatures and is the right of every citizen to be able to feel it.ï¿½ Therefore, investment activities are carried out in companies, especially public companies listed on the Indonesia Stock Exchange. The stock price is a reflection of the company's frequently changing value. At the last time, the share price of a mining company listed on the Indonesia Stock Exchange in 2020 was estimated at 1359.21, the highest figure at 1360.71, and the lowest at 1313.62. These figures show the up-and-down movements of the share prices of mining companies in Indonesia that will always fluctuate and become a reflection of the company's situation. This movement is called stock price volatility. According to (Santioso & Angesti, 2019), stock price volatility is a condition where the stock price deviates (up/down) in the index from the average.

These stock price fluctuations can cause losses or profits for the company, if the volatility of the stock price rises to mean the state of the company in a good position. But on the contrary, if the volatility of the stock price falls, it means that the company is in a bad position or is declining. Mining sector companies are one of the largest producers of B3 (hazardous and toxic materials) waste in Indonesia, and many cases have occurred due to the negligence of mining sector companies that harm the environment and society such as pollution of soil, water, and damage due to excavations carried out. To answer this need, companies can apply green accounting to published financial statements. According to (Zulhaimi, 2015), green accounting is the application of accounting where the company also includes costs for environmental preservation or the welfare of the surrounding environment which is often referred to as environmental costs in the company's expenses. And according to (Lolo & Ricambi, 2019), green accounting or environmental accounting is an accounting that contains the identification, measurement, and allocation of environmental costs, where environmental costs are integrated into business decision makers and w hich are then communicated to stakeholders. The application of green accounting is one of the interests of shareholders, with sacrifices for environmental costs, the company shows concern for the environment and social so that it has a good reputation in the eyes of the public. There have been several previous studies related to green accounting, which were used as the basis for research.

Based on research by (Zulhaimi, 2015), it concluded that the application of green accounting has a positive and significant influence on stock prices after the application of green accounting principles and the company received an award for the application of green accounting principles. However, there are differences based on research by (Blignaut & Wium, 2014), concluding that there is no correlation between the application of environmental accounting and stock price fluctuations because few companies apply the principle of enviromental accounting on the Johannesburg Stock Exchange. Meanwhile, according to (Widyasti & Putri, 2021), it was concluded that eco-efficiency negatively affects the value of the company because the application of eco-effieciency causes large operational costs and causes a decrease in company profits, thus making investors' perceptions decrease which causes a decrease in company value. In addition to green accounting, the quality of environmental and social disclosures is one of the important pieces of information about the company that can affect the volatility of stock prices. This quality of environmental and social disclosure is the disclosure of corporate social responsibility. According to (Delautre & Abriata, 2018), corporate responsibility is seen as a purely voluntary attitude of a targeted company to correct the situation with shareholder disparities (workers, suppliers, environment, and others) in a way that is more than the company legitimately does. Then the hypotheses in this study are as follows:

H1: Green Accounting has a significant positive effect on stock price volatility.

H2: The quality of Environmental and Social Disclosures positively affects stock price volatility.

Agency Theory

Signal Theory

According to (Jensen & Meckling, 1978), agency theory connects aspects of human behavior in this theory assumes that both the owner of capital (principal) and the management manager (agent) are rational parties and have their own interests. According to (Godfrey et al., 2010), agency theory is a theory that explains the relationship between agency and agent. Agents in theoretical agencies are the managing management of the company, and principals in theoretical agencies are shareholders. In theoretical agencies, agents are contracted by principals to manage the company for the benefit of principals. and reduce monitoring costs. The company also expects that the dissemination of information can have an influence on stock price fluctuations and volatility. According to (Novalia & Nindito, 2016), Signalling theory explains why companies emphasize the importance of information issued by companies to the investment decisions of parties outside the company. According to (Lestari & Saitri, 2018), the main benefit of this theory is that the accuracy and timeliness of presenting financial statements to the public is a signal from the company of useful information in the need for decision-making from investors.

Legitimacy Theory

According to (Sagala & Ratmono, 2015), the Theory of Legitimacy is based on the phenomenon of a social contract between an organization and society, where it is necessary that an organization's goals should be congruent with the values that exist in a society. According to (Dowling & Pfeffer, 1975), the theory of legitimacy is a state or state, which arises when an entity's value system is equal and in line with the value system of most environmental value systems where that entity is part of the environment. From the above understanding, it can be concluded, that the theory of legitimacy is a theory that explains that companies as part of the society where the company carries out its operational activities, must adjust or align company values with community values in order to harmonize between the relationships between the two parties. Because the community is part of the stakeholders.

Stock Price Volatility

Stock price volatility is a form of statistical measurement to see fluctuations from price changes

stocks in a given period According to (Anastassia & Firnanti, 2014), Great volatility indicates the possibility of higher profits and losses in the short term. Stock price volatility chartically changes at any time and is difficult to predict. Stock price volatility can be influenced by events outside the company (macro), or events that occur within the company (micro). According to (Ilmiyono, 2017), micro-factors include asset growth, profit growth, cash flow, return on equity (ROE), voluntary disclosure, information disclosure, dividends and company growth. Meanwhile, macro factors include inflation, interest rates, and exchange rates. All information that comes out of a company has an effect on stock price fluctuations, so that if any information is disclosed, there is a re-appraiser of the company's stock price.

Green Finance

According to (Huang et al., 2015), environmental accounting or green accounting is to measure, record, and report the influence of environmental activities of a company on financial status through a set accounting system. According to (Pratiwi & Pravasanti, 2018), the concept of green accounting itself is a combination of environmental benefits and costs in economic decision making, and becomes a tool of environmental management and communication with the community about the company's operational activities. According to (Zulhaimi, 2015), green accounting is the application of accounting in which companies list environmental costs which is used for environmental sustainability and environmental well-being. These costs are in the form of waste management costs, environmental penalties and taxes, cleaning costs, and pollution prevention costs. According to (Purnamawati et al., 2021) green accounting itself consists of saving resources, producing environmentally friendly products or green products, producing cleanly and based on the environment. According to (Shakkour et al., 2018), the role of environmental accounting is to address environmental problems and influence achieving sustainable development in different countries of the world. As well as influencing the attitude of the company in overcoming environmental problems and social responsibility. According to (Tanc & Gokoglan, 2015), the main goal of environmental accounting is to generate and disclose information. Environmental accounting also aims to show the interaction of several areas such as the company and the environment and the economy and environment by publishing the information obtained. According to (Zulhaimi, 2015), the forms of green accounting practices are the use of environmentally friendly raw materials, waste management that does not damage the environment, and CSR.

RESEARCH METHOD

This study uses secondary data in the form of annual reports on all mining sector companies on the Indonesia Stock Exchange for the 2013-2018 period. The data type used is cross section data. Cross-section data is research conducted in a certain time, which is only used for a certain time and is not carried out research at different times to be compared. The data used in this study is the year data in which each company conducts an annual report. The data was obtained from the official website of the Indonesia Stock Exchange (idx.co.id). The criteria in this study are 1) Mining companies listed on the IDX in 2013-2018. 2) Companies that publish annual reports in the period 2013-2018. 3) Companies that report data data required in the study, especially CSR costs during the research period. The analysis technique used in this study used multiple linear regression analysis. Before conducting multiple linear regression analysis, researchers first conducted classical assumption tests, namely normality tests, multicholinearity tests, heteroskedasticity tests, and autocolonization tests. For hypothesis testing, the t-test and coefficient of determination are used to see how strongly the influence of the free variable used on its bound variable is. The variables in this study are as follows:

ï¿½ Green Accounting Green accounting is the application of accounting principles that recognize the existence of expenses incurred for the ligkungan.

Green Accounting measurements will be carried out, through the disclosure of environmental costs incurred by the company. According to Fitria and Wibowo (2015, P.16), environmental costs are costs that occur due to poor environmental quality or because poor environmental quality may occur. The use or expenditure of environmental costs, is of particular concern, because it shows the company's concern for the environment. The formulation of environmental costs used in the study is taken from the amount of CSR costs incurred by the company, the following is the formulation of environmental costs used: (Babalola, 2012, p.48)

𝐵𝑖𝑎𝑦𝑎 𝐿𝑖𝑛𝑔𝑘𝑢𝑛𝑔𝑎𝑛 = 𝐵𝑖𝑎𝑦𝑎 𝐶𝑆𝑅 𝐿𝑎𝑏𝑎 𝐵𝑒𝑟𝑠𝑖ℎ

ï¿½ Quality of Environmental and Social Disclosures

In this study, the measurement of the Quality of Environmental and Social Covering, measured through indicators issued by the Global Reporting Intiative (GRI) G.4. In accordance with the title of the study taken by the researcher, the GRI G.4 category used in this study was environmental and social. In GRI G.4, the environmental category assessment analyzes from the aspects of materials, energy, water, biodiversity, emissions, effluent and waste, products and services, compliance, transportation, others, supplier assessment of the environment, and environmental problem complaint mechanisms. In the social category, the assessment uses the following sub-categories, namely labor practices and employment, human rights, society, and responsibility for products. Environmental and social disclosures from the company will be examined from the annual report issued by the company that is the focus of the research. Researchers will use the dummy method, by assigning a value of 1 to the company that disclosed the item corresponding to the item on the GRI G.4 and assigning a value of 0 to the company that did not disclose the item. Based on previous research found by researchers, the study will calculate the measurement of environmental and social disclosures using the CSDI formula:

𝐶𝑆𝐷𝐼 = 𝑥 𝑛

ï¿½ Stock Price Volatility According to Sugiyono (2016, p.96), dependent variables are variables that are influenced by other variables. The dependent variable used in this study is stock price volatility. For the measurement of stock price volatility, researchers use the following formula (Parkinson's, 1980, p.61-65):

𝑃_𝑉𝑜𝑙𝑖𝑡√ ∑ { 𝐻𝑖𝑡 − 𝐿𝑖𝑡 (𝐻𝑖𝑡 + 𝐿𝑖𝑡)/2 } 2 𝑛 𝑖=1 𝑛

ï¿½ Information Asymmetry In this study, information asymmetry is a moderation between green accounting and the quality of environmental and social disclosures and stock price volatility. The information asymmetry variable in this study will be measured by the bid-ask spread formula. Bid-ask spread is the difference between the highest bid price and the lowest ask price of a stock. Here's the bid-ask spread formula used by researchers:

𝑆𝑃𝑅𝐸𝐴𝐷𝑖𝑡 = 𝐴𝑆𝐾𝑖𝑡 − 𝐵𝐼𝐷𝑖𝑡 (𝐴𝑆𝐾𝑖𝑡 + 𝐵𝐼𝐷𝑖𝑡)/2 𝑥 100%

ï¿½ ROI According to Hamdani and Nurlasaera (2016, p. 74), return on investment is a ratio to see the company's ability to generate profits that will be used to cover investments in the business. The following is the measurement of return of investment used by researchers: (Syamsudin, 2011, p. 63)

𝑅𝑂𝐼 = 𝐿𝑎𝑏𝑎 𝑠𝑒𝑡𝑒𝑙𝑎ℎ 𝑝𝑎𝑗𝑎𝑘 𝑇𝑜𝑡𝑎𝑙 𝐴𝑠𝑒𝑡 𝑥 100%

This test aims to determine the relationship between independent variables and dependent variables The interaction relationship testing formula is called multiple linear regression analysis, as follows:

𝑽𝒐𝒍𝒊𝒕 = 𝒂 + 𝜷𝟏𝑨𝑲𝑯𝒊𝒕 + 𝜷𝟐𝑲𝑳𝑺𝒊 + 𝒆

The following is the MRA model used by researchers on the influence of moderation variables on their research:

Volit = a + β1AKHit + β2KLSit + β3BDSit + β4KNPit + β5AKHit * BDSit + β6KLSit* BDSit + e

Information:

Volit: Stock Price Volatility

and: Constant

β1-6: Koefisien variable

AKHit: Green Accounting i in period t KLSit: Quality of Environmental and Social Disclosures i period t

KNPit: Company Performance i period t BDSit: Bid-ask speard company I period

AKHit*BDSit: Relationship of environmental accounting to information asymmetry

KLSit*BDSit: The relationship of quality of environmental and social disclosures to information asymmetry

RESULT AND DISCUSSION

Analysis

From the table, it can be concluded that the calculation of E-Views above is as follows: Stock price volatility (VOL) resulted in an average value of 0.138210 which shows that out of 18 companies, the average trading volume of buying and selling shares is 13.82%. This indicates that the information published by the company through financial statements, still has little effect on the trading volume of buying and selling stocks. The lowest value is 0.000000 and the highest value is 68.43% with a standard deviation of 1.634951. Green Accounting (AKH) produced an average value of - 1.206565 which shows, that the application of green accounting has not been done well by the company that is the object of research. This indicates that the principles of green accounting, have not been implemented and reported properly by the 18 companies studied. The lowest value is -95.93176 and the largest value is 3.191617 with a standard deviation of 10.17255. The quality of environmental and social disclosures (KLS) resulted in an average value of 0.210479 which shows that the average quality of sustainability report disclosures based on the GRI G4 index was only met by 21.04%. This indicates that of the 18 companies studied as research objects, the quality of environmental and social disclosures is not good when viewed from the aspects determined by the GRI G4. The lowest value is 0.085370 and the largest value is 0.585370 with a standard deviation of 0.107979. Information asymmetry (BDS) resulted in an average value of 27.64209 which shows that the average influence of information asymmetry on investors' stock buying and selling interest is 27.64%. This indicates that information asymmetry has little effect on investors' interest in buying and selling stocks. The lowest value is 0.000000 and the largest value is 136.8644 with a standard deviation of 25.92893. The Company's performance (KNP) as a control variable resulted in an average value of 6.592919. This indicates that the company's performance as measured by the return on investment (ROI) ratio has a major influence on the calculations of investors to predict the rate of return of shares invested in mining sector companies in Indonesia. The lowest value is -64.38720 and the largest value is 75.46760 with a standard deviation of 20.77199.

Test assumptions

In order for the regression model used in this study to be feasible and produce values that match the assumption of multiple linear regression, the data must meet four classical assumption tests, namely the normality test, the heterochedasticity test, the multicholinearity test, and the autocholeration test.

Normality Test

According to Gozhali and Ratmono (2018, p. 145), the normality test aims to test whether in regression models, disruptive or residual variables have a normal distribution. Through this test, if this test is not met then the statistical test results are invalid, especially for small sample sizes. The normality test can be done in two ways, namely by chart analysis and statistical analysis. In this study, researchers will use the Jarquebera (JB) test to conduct the Normality test. According to Gozhali and Ratmono (2018, p. 145), the JB Test is for normality tests for large (asymptotic) samples. When the result of the JarqueBera test is greater than 0.05, it means that the data is normally distributed.

The result of the Jarque-Fallow probability value is greater than the significant level of 0.05 which is 0.704986. So that the data from the research carried out is normally distributed. Heteroskedasticity Test The heteroskedasticity test is performed to test whether there is homoskedasticity or the same variance. A good regression model is if within the regression model there is no heteroskedasticity problem. The test conducted in this study was the White test, to test whether the data used in the study was infected with heteroskedasticity problems or not. When the result of Prob. Chi Square is greater than 0.05, so the data is free from the problem of heteroskedasticity.

Based on Table 2 of White's test results, it can be seen that the value of Prob. ChiSquare, which is 0.3341, which is greater than 0.05, so it can be concluded that the data used in the study did not contract the heteroskedasticity problem Multicholinearity Test The multicholinearity test was carried out to test whether from the regression model there was a correlation between free variables. If between the independent variables X there is perfect multicholinerity, then the regression coefficient of the variable X cannot be determined and the standard value of the error becomes infinite (Ghozali & Ratmono, 2016, p.71). To find out whether there is a correlation between independent variables, it can be seen through the tolerance value and variance inflaction factor (VIF). For tolerance values, the cutoff value that is often used is the tolerance value ≤ 0.10. FIF value, a cutoff value that is often used in research, namely the VIF value ≥ 10.

From Table 3, it can be seen that the value of the centered VIF is smaller than 10. So that between free variables there is no problem of multicolinerity.

Autocorrelation Test

According to Ghozali and Ratmono (2018:121), the purpose of the autocorrelation test is to test whether in a linear regression model there is a correlation between the disturbance (residual) in the t period and the error in the t-1 (previous) period. Autocorrelation tests are performed on observations with consecutive timeframes and those related to each other. A good regression model is if there are no autocorrelation problems. The test used in this study was the Durbin Watson test. The conditions for Durbin Watson testing are Durbin Watson values > dU and (4-Durbin Watson) > dU. The result of Durbin Watson's test was 1.951, with a dU value of 1.78841. Then Durbin Watson's value is greater than dU. While (4-1.951509) is also greater than the dU value, according to these results the research data do not have autocollation problems.

Regression Analysis

Multiple linear analysis is used to derive coefficients that will determine whether the hypothesis created will be accepted or rejected. On the basis of the results of regression analysis with a significance level of 5% obtained the following results: Volit = (-7.58ï¿½10-9) + (5.4ï¿½10-10) AKHit + (4.95ï¿½10-8 ) KLSit + e

1) Constant (a) = -7.58ï¿½10-9. This suggests that if the entire independent variable is considered constant, then the value of the stock price volatility is - 7.58ï¿½10-9.

2) Green accounting regression coefficient = 5.4ï¿½10-10. This shows that if there is an increase of 1 in green accounting assuming other variables remain, then the value of stock price volatility increases by 5.4ï¿½10-10.

3) The regression coefficient of quality of environmental and social disclosure = 4.95ï¿½10-8. This shows that if there is a 1st increase in the quality of environmental and social disclosures assuming other variables remain, then the value of stock price volatility increases by 4ï¿½910-8.

Moderated Regressionn Analysis

The MRA equation is obtained as follows:

Vote = (-7.05ï¿½10-9) + (1.86ï¿½10-10) AKHit + (4.55ï¿½10-8) KLSit + (0.005) BDSit + (1.23ï¿½10-10) KNPit + (1.69ï¿½10- 11) AKHit* BDSit + (2.51ï¿½10-11) KLSit* BDSit + e

It can then be concluded that the probability value between testing moderation variables against the relationship between green accounting to stock price volatility, and the quality of environmental and social disclosures to stock price volatility is 0.5480, and 0.8472, respectively, where the result is > 0.05 then the moderation variable does not affect the relationship of green accounting, and the quality of disclosure of the context and social to stock price volatility.

T-test

The following is an explanation of the results of the partial significance test or t-test of each of the free variables in the research model:

1. Green Accounting (AKH)

As a result of multiple regression analysis, the AKH free variable has a statistical value of 2.138509 with a probability value of 0.0348. The probability value of the AKH indicates a number smaller than the signification rate of 0.05. Then these results show that H1: green accounting positively affects the volatility of the stock price received.

2. Quality of Environmental and Social Disclosure (KLS)

As a result of multiple regression analysis, the KLS free variable has a statistical value of 2.063796 with a probability value of 0.0416. The probability value of the KLS indicates a number smaller than the signification rate of 0.05. Then these results show that H2: information asymmetry positively affects the volatility of stock prices received.

3. Information Asymmetry (BDS)

As a result of the MRA calculation, the BDS moderation variable has a statistical value of 21299872 with a probability value of 0.0000. The statistical value is greater than the t-table which is 1.983 and the probability value is less than the significance level which is 0.05. So this shows that the BDS moderation variable has a positive effect on stock price volatility. However, this DBS variable is referred to as a moderation predictor or predictor variable in this study, because DBS variables only have a significant effect on free variables but are not able to strengthen or weaken the influence of free variables, namely green accounting and the quality of environmental and social disclosures on stock price volatility (free variables).

4. Company Performance (KNP)

The results of multiple regression analysis, the KNP control variable has a statistical value of 1.028254 with a probability value of 0.3062. The probability value of the KNP indicates a number greater than the signification rate of 0.05. So these results show that the KNP variable has no effect on stock price volatility.

5. Green Accounting-Information Asymmetry (AKH*BDS)

The result of the MRA calculation, akh*bds has a t-statistical value of 0.602782 with a probability value of 0.5480. The probability value is greater than the significance level which is 0.05. Based on the results of the analysis, it shows that information asymmetry variables are not able to moderate the influence of green accounting on stock price volatility. It can be concluded, then, that H3: Information asymmetry as a moderation variable reinforces the effect of green accounting on stock price volatility.

6. Quality of Environmental and Socio-Asymmetric Information Disclosure (AKH*BDS)

The result of MRA calculation, KLS*BDS has a t-statistical value of 0.193164 with a probability value of 0.8472. The probability value is greater than the significance level which is 0.05. Based on the results of the analysis, it shows that information asymmetry variables are not able to moderate the influence of the quality of environmental and social disclosures on stock price volatility. It can then be concluded that H4: Information Asymmetry as a moderation variable, amplifying the influence of the quality of environmental and social disclosures on stock price volatility.

R Square Test

The coefficient of determination test aims to find out how much influence the free variable in the regression model has on the bound variable. The value of the coefficient of determination test is seen from the adjusted value of R-squared.

The value of the Coefficient of determination is between zero and one. If the value of the coefficient is closer to 1, then the ability of the independent variable to describe the dependent variable is better. The adjusted value of R2 can be negative, although it is desirable to have a positive value. If the value of the coefficient is equal to 1, then the influence of the independent variable to the dependent variable is perfect, and if it is equal to 0, then there is no influence of the independent variable on the dependent variable. Based on the results of data analysis, it can be seen that the magnitude of the adjusted Rsquared value is 1.000000 or 100%, which means that free variables are able to explain their influence as much as 100% on the dependent variables in the research model

CONCLUSION

This study was conducted to test the effect of green accounting and the quality of environmental and social disclosures on stock price volatility. The conclusions of the study are as follows:

ï¿½ Green accounting has a significant positive effect on stock price volatility.

ï¿½ The quality of environmental and social disclosures has a significant positive effect on stock price volatility.

ï¿½ Information asymmetry as a moderation variable cannot amplify the effect of green accounting on stock price volatility.

The limitations experienced by researchers in conducting research are as follows:

There are some aspects of environmental and social disclosure assessments that are not contained in the annual report, making the assessment less accurate and subjective.

The lack of sources of information explaining green accounting, the quality of environmental and social disclosures, and the asymmetry of information so that researchers cannot fully explain green accounting and the quality of environmental and social disclosures.

Related to the limitations of the research already mentioned above here are some suggestions for further research:

Subsequent research may look for other sources relating to the assessment of environmental and social disclosure aspects, for example from the company's website.

Further research is expected to use government websites or official websites that provide explanatory information on green accounting, social and social disclosures, and information asymmetry.

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