The development of green finance in the EAEU countries based on the assessment of the liquidity of green bonds

Kovalev Vladislav Alekseevich ORCID: 0009-0000-2110-6400 Student, Department of Public Finance, Financial University under the Government of the Russian Federation 125167, Russia, Moscow, Leningradsky Avenue, 49/2 kovalevdocs@mail.ru

Introduction

The relevance of the work is due to the preservation of the ESG agenda in the EAEU countries and the need to develop measures for the development of the green finance market based on empirical studies of the green bond market in the EEA member countries, including the involvement of new participants in the market and improving the investment characteristics of green bonds.

The purpose of the work is to improve green financing in the EAEU countries based on an assessment of the liquidity of green bonds.

The development of green debt financing is one of the factors for the sustainable development of the Russian economy and the achievement of the national development goals of the Russian Federation - the development of green bonds in order to stimulate investment with great socio-economic effects is part of a Unified plan to achieve the national development goals of the Russian Federation for the period up to 2024 and for the planning period up to 2030, and the share of issued green bonds in the total volume of bonds issued on the Russian market is one of the indicators (indicators) of the implementation of the Strategy for the Development of the Financial market of the Russian Federation until 2030. The scientific literature emphasizes the significant role of green finance in the socio-economic development of the state, solving environmental problems and notes that the main investors in green bonds are institutional investors ^[1][2]. In order to improve green financing in the Russian Federation, we are attempting to analyze the liquidity of green bonds in the financial market as one of the factors increasing the involvement of economic agents in participating in debt green financing by placing funds in green bonds.  It is important to note that this is of great importance for the modernization of the debt policy of Russian regions experiencing problems with debt sustainability ^[3].

Investigating the factors of the development of the green bond market, Tarasova Yu. A. and Lyashko E. N., based on the results of regression analysis, refer to them the stability of the economy and the quality of environmental regulation ^[4], Dorofeev M. L. – the development of the financial market and state stimulation of the green bond market ^[5]. The above factors should, first of all, ensure a steady growth rate of funds placed in green bonds, the number of their issues and issuers. The liquidity of green bonds is not a priority for some institutional investors, for example, insurance organizations and non–governmental pension funds, characterized by a long investment horizon and a "buy and hold" strategy, however, the liquidity factor of bonds traded on the Russian financial market cannot be ignored when setting the task of attracting non-institutional investors to green loans - here it is necessary to agree with Dorofeev M. L., stating the need to attract more participants to the green bond market, including individuals. With such a task, the low liquidity of green bonds of medium-sized issuers or low credit quality will not ensure the proper involvement of a wide range of investors whose investment strategy involves taking into account liquidity. Febi, W., Sch?fer, D., Stephan, A. already in 2018, they drew attention to the risk of exceeding demand for green bonds in the face of rapid growth in demand and lack of fiscal incentives for green investments, which is capable of placing green bonds with a coupon rate lower than the broader market of conventional bonds ^[6]. The lower repayment yield on green bonds is explained by Dorofeev M.L. by the willingness of investors to pay extra for participation in green financing in conditions of a high level of transparency of the issuer ^[5]. At the same time, Febi, W., Sch?fer, D., Stephan, A. call it the liquidity premium ^[6]. The thesis of a lower interest rate on green bonds refers to the reasoning about the availability of greenium – a discount on the coupon rate for the status of "green" bonds. The presence or absence of greenium is still being discussed in the research community, so Guseeva I. A. and Bogomolov Ya. M., after analyzing foreign and Russian scientific works, write about the ambiguity and inconsistency of this issue, while finally noting the dependence of the presence of greenium on the current supply and demand ratio ^[7]. In addition, A. N. Belov writes about reducing the adverse risk of price changes and transaction time with a high trading volume, which is an important factor in the development of the green bond market ^[8]. Thus, the significant role of the liquidity level in the pricing of green bonds and the participation of institutional and non-institutional investors in the placement of funds in green financing determines the relevance of studying the current state of liquidity of green bonds in the financial market in the Russian Federation.

At the same time, less attention is paid to the analysis of the investment characteristics of green bonds in the domestic literature than to the institutional factors of their market development. Taking into account the fiduciary responsibility of some institutional investors (for example, non-governmental pension funds) and responsibilities for the formation of balanced and sustainable investment portfolios, low liquidity can play a decisive role in deciding on the participation of institutional investors in green debt financing, while the placement of large capital is a driver for the development of young green bond markets in the EAEU countries – the work of the green bond market is interconnected with the investment policy and activities of insurance organizations and investment funds. Therefore, the study of all the characteristics of the "yield-risk-liquidity" of the analyzed bonds is a priority task along with the study of the conditions of their issue, government support, infrastructure formation and verification, since green bonds are a relatively new and innovative tool in the financial markets of the EAEU, the study of the practice of the participating countries, the development and implementation of measures to integrate green financing into a single The economic space will ensure mutually beneficial growth of the green bond market for all countries at a level not lower than the global one, and create an effective and secure market infrastructure that directly improves the socio-economic situation of the participating countries.

  Research methods and information base

In the study, we evaluate the liquidity indicators of green bonds included in the Sustainable Development Sector of the Moscow Exchange (segment of sustainable development bonds/green bonds) currently in circulation ^[9]. Bond issues with a placement date of at least 3 months as of the date of the study were selected to ensure comparability of estimates of liquidity indicators - we excluded the issue of an instrument with the international identification code of the security (hereinafter – ISIN) "RU000A1067H4" of the issuer of LEGEND LLC, thus, the number of analyzed bond issues amounted to 18 pieces.  

To collect data, we use the methods of the Information and Statistical Server of the Moscow Stock Exchange (hereinafter - ISS) to obtain the specification of financial instruments, the history of transactions on it for the date interval and for the last trading day.

Liquidity, being one of the three main financial characteristics of financial markets and assets, has many interpretations and methods of formalized assessment. Part of the work is devoted to the selection of variables and factors correlating with the liquidity of an asset in the financial market ^[8]. To begin our research, we need models of liquidity indicators with the possibility of categorizing bonds without evaluating the factors influencing the indicators.  Chaikun A. N., guided by the principles of representativeness, information accessibility, approbation and verification, selects liquidity indicators proposed by foreign authors and grouped by 4 projections (time, price, volume, transaction costs) ^[10]. Confirming the words of Chaikun A. N. about the mixing of liquidity characteristics and their frequent correlation with each other, Bystrova D. A. identifies 5 liquidity indicators (urgency, depth and elasticity, volume density and multidimensional indicator), whose measurement methods partially coincide with the liquidity indicators described by Chaikun A. N. ^[11]. Sidorov A. A. considers the aspects of liquidity of a financial asset to be temporary (urgency and compactness) and cost aspects (depth, relaxation) ^[12]. The methodology for calculating the liquidity of securities of the Kazakhstan Stock Exchange is interesting, but it was not used in the study due to the inability to obtain publicly available information on the number of participants of the Moscow Exchange who participated in transactions with securities, which are one of the indicators for calculating liquidity ^[13].

We are conducting a liquidity study of green bonds to reduce the costs and risks of investors trying to reduce the average duration of a transaction (sale of bonds) and maximize the sale price, therefore, we use 3 groups of liquidity indicators: urgency (time), volume and transaction costs.

In the urgency group, we analyze 2 indicators: trading volume – the average daily number of transactions for the purchase and sale of green bonds for the 30 preceding calendar days, designated as Q _m, and the frequency of trading, calculated by formula (1), which demonstrates the trading activity of the bond ^[10].

where R is the trading frequency, %;

B _d – the number of trading days with at least one transaction in the 30 preceding calendar days, pcs.;

B – the number of trading days for the previous 30 calendar days, pcs.;

            In the group of volume indicators, we determine the turnover coefficient calculated by the formula (2) ^[11].

            where TURNOVER is the turnover ratio;

            V _d – the volume of transactions on the bond for the quarter, pcs.;

            V _i – the volume of issue (issue) of the bond, pcs.;

            In the group of transaction cost indicators for each bond, we determine the spread between the purchase and sale prices (bid-ask spread), demonstrating the level of costs for securities transactions ^[10][11]. We determine the indicator of the relative spread calculated by the formula (3) ^[11].

where RQUOTED _t is the relative spread of the price of transactions on the bond on day t, RUB.;

a _t is the lowest purchase price of the bond on day t, RUB.;

b _t is the maximum selling price of the bond on day t, RUB.;

m _t is the average purchase and sale price of a bond on day t, RUB.;

            In addition, we use a relative effective spread that takes into account the price of the last transaction and is calculated using the formula (4) ^[11].

where REFECT _t is the relative effective spread;

            p _t is the closing price of the bond position on day t, RUB;

Calculating spread indicators requires information about each individual transaction, and not about the results of trading over a certain period of time. The AIS allows you to freely access data on transactions only for the last trading day, which makes it impossible for us to get an accurate estimate of the spread in terms of calculating indicators based on data for only one day and the availability of green bonds, which were not traded on the last trading day on the calculation date.

            For each indicator, we assign the bonds the liquidity level LL _b according to the formula (5).

where LL _b is the liquidity level;

LIQ(b) is the result of calculating the liquidity indicator of the bond b;

q ₁ ^x is the first quartile of the liquidity index of the set of bonds under study X;

mediana(x) is the median value of the liquidity indicators of the set of bonds under study X;

q ₃ ^x is the third quartile of the liquidity index of the set of bonds under study X;

The levels are defined as: 0 – illiquid bonds, 1 – low–liquid bonds, 2 - medium-liquid bonds, 3 - highly liquid bonds.

            The selected indicators allow us to assess the level of liquidity of bonds in different projections and according to data for different periods of time. Assigning a liquidity level allows you to rank bonds according to their liquidity in the market relative to each other. It should be noted that the group of selected indicators for measuring liquidity is not exhaustive and has been formed, including taking into account the possibility of conducting research based on data from open sources. It should be noted that the assignment of liquidity levels is carried out for different securities in the order formulated by the authors or the methods of organizations – there is no unified approach.

            The methods used, confirmed by domestic and foreign scientific works, and the information base of the analysis make it possible to ensure the reproducibility of the study, the openness of the results and the statistical significance of calculations based on the sample.  

Results

Having calculated the average daily number of Qm transactions, as shown in Table 1 and Figure 1, we identified 7 bonds for which there were no transactions during the calendar month preceding the settlement date. Trading on 6 of the 7 above–mentioned bonds began before 2020 inclusive - the issues of "pioneers" turned out to be the least liquid according to the first indicator.

Table 1 – Calculated liquidity indicators

Source: calculated and compiled by the author according to the data of the Moscow Stock Exchange ^[9].

Grouping the bonds in table 2 by liquidity levels, we note that the number of illiquid and low-liquid bonds accounted for half of all bonds.

Figure 1 – Average daily number of green bond transactions

Source: calculated and compiled by the author according to the data of the Moscow Stock Exchange ^[9].

Table 2 – Grouping of bonds by average daily number of transactions

Source: calculated and compiled by the author according to the data of the Moscow Stock Exchange ^[9].

Based on the results of the author's calculation of the frequency of bond trades presented in Tables 1 and 3, we note that for all bonds, with the exception of the bond with the ISIN "RU000A101DA6" of the issuer RuSol 1 Specialized Financial Company LLC, during the calendar month, purchase and sale transactions were carried out either every trading day, or none were carried out once – according to this indicator, the green bond market is binary.

Table 3 – Grouping of bonds by trading frequency

Source: calculated and compiled by the author according to the data of the Moscow Stock Exchange ^[9].

To calculate the turnover ratio, we received data on the trading results for the bonds under study for the 3 months preceding the settlement day. The total number of trading days for this period of time is 62. The results obtained, shown in Tables 1 and 4 and shown in Figure 2, demonstrate that despite the equal number of bonds in each group of the liquidity level, the average daily number of transactions does not correlate with turnover – a large number of transactions does not always mediate the opportunity to realize a significant volume of a package of bonds on the exchange. The correlation coefficient between Q _m and TURNOVER was 0.26.

Table 4 – Grouping of bonds by turnover ratio

Source: calculated and compiled by the author according to the data of the Moscow Stock Exchange ^[9].

Figure 2 – Turnover ratio of green bonds

Source: calculated and compiled by the author according to the data of the Moscow Stock Exchange ^[9].

The relative spread cannot be calculated for 8 bonds due to the lack of purchase and sale transactions for them on the last trading day on the settlement date - in table 6, the value of RQUOTED is assigned the value "–", and the liquidity level is 0 for this indicator in table 1.

A smaller spread demonstrates a greater proximity of the price to the average market, therefore, to group the bonds in Table 5, we invert the order of assigning the liquidity level in formula (5), so that bonds with a smaller spread are assigned a higher level. The largest spread (99.89 and 100) for two bonds is explained by the conclusion of transactions on the trading day only for the purchase of instruments.

Based on the results of calculating the relative effective spread shown in Table 1, we note that bonds with ISINs "RU000A103G00" and "RU000A105K85", which had "highly liquid" levels according to the results of the RQUOTED assessment, were assigned "illiquid" and "low liquid" levels according to the REFECT indicator, respectively, and that the spread between the results according to the REFECT indicator is lower than by RQUOTED.

Table 5 – Grouping of bonds by relative spread indicator

Source: calculated and compiled by the author.

By analogy with grouping bonds by relative spread, we group bonds by relative effective spread, which is presented in Table 6.

 Table 6 – Grouping of bonds by relative effective spread

Source: calculated and compiled by the author.

To systematize the results obtained and the liquidity levels, we have reflected in table 7 the studied bonds in the context of the liquidity levels assigned to them for each of the indicators.

To obtain an objective assessment of the liquidity of the green bonds under study and to offset the shortcomings of each of the indicators used, we take into account the results obtained in aggregate and calculate the final indicator using the formula (6), which is rounded to two decimal places.

            where I _b is the final liquidity indicator.

Table 7 – Summary table of liquidity levels

Source: calculated and compiled by the author.

The choice of weights for the values of liquidity levels for each of the indicators is explained as follows: indicators of urgency demonstrate the very possibility of selling bonds, market volume – selling the optimal package of bonds at a certain cost, transaction costs – the ability to sell a package of bonds at the price closest to the average market and with minimal costs. Taking into account the above and the presence of 5 liquidity indicators, in calculating the final indicator, we assume the same significance for our study of each indicator and assign the resulting level of liquidity for each indicator an equal coefficient of 0.20. Given that the ratio of the number of trading days with at least one transaction to the total number of trading days used to calculate the trading frequency indicator R, with the exception of one bond under study, is either 100% or 0%, we assigned a weight for the liquidity level in terms of trading frequency indicator R equal to 0.1. Due to the calculation of transaction indicators in one trading day (which excludes the full statistical significance of the results obtained for these indicators), we reduced the weight of the indicators of this group to 0.15, and assigned a weight of 0.3 to unchanged liquidity levels.

According to formula (6), we have obtained a rating of green bonds in terms of their liquidity, presented in table 8.

Table 8 – Rating of green bonds by liquidity level

Source: compiled by the author according to formula (6) according to calculated liquidity levels.

The rating is based on the liquidity levels of green bonds relative to each other – it is of scientific interest to calculate the rating and relative to the entire market of corporate and government bonds with the same listing level and traded in the same trading mode to study the availability of a discount for liquidity and the difference in liquidity between green and "brown" bonds. The compiled rating of green bonds will contribute to a formalized assessment of the investment characteristics of bonds for investors and the identification of gaps in financial markets for exchange trading authorities.

Discussion

The Russian green bond market has a cluster of illiquid bonds, the feature of which is the placement of bonds on the market until 2020, while the most liquid bonds according to the final rating have been placed since 2020 inclusive. In this regard, it is of scientific interest to further study the liquidity of green bonds based on the factor of the start date of trading on them. With the exception of illiquid bonds, the average standard deviation of the average daily number of transactions on green bonds was 73.81, while the issuers of the two most liquid bonds in this indicator are the Government of the City of Moscow, which has implemented an active policy to inform about the issue of green bonds, and the state corporation VEB.In this case, one of the potential drivers of the development of green finance may be the expansion of the practice of sub-federal green loans, including through development institutions. Despite the fact that the number of daily transactions on bonds is generally less than on stocks, the number of average daily transactions of more than a hundred is observed only for 4 issues of green bonds.   

It should be noted that in conditions when the indicators of urgency and volume of the bond liquidity market vary, for 10 out of 11 bonds, with the exception of illiquid ones, transactions were carried out on 100% trading days – there is an imbalance in the volume of transactions and their frequency, which can be offset, among other things, by expanding the participation of non-institutional investors in debt green financing.

The leadership in the final rating of the issuer's bonds of Sberbank PJSC allows us to put forward an assumption about the key role of the issuer's financial position and its credit rating in ensuring the liquidity of green bonds. This is consistent with the thesis of Febi, W., Sch?fer, D., Stephan, A. that the credit ratings of green bonds depend more on the issuer's condition than on the investment indicators of specific green projects, and in this case the opaque level of risk on green bonds is a factor in the illiquidity of green bonds ^[6].

It should be noted that with the leadership of sub-federal bonds in terms of volume and frequency of trading, they are inferior to corporate bonds in terms of turnover. The volume and frequency of trading are weakly correlated with the indicators (correlation coefficient – 0.31) of the spread, but in general, the relative spread for 8 bonds does not exceed | 1%|.

Let's assume that the measures proposed by the researchers to involve a wide range of people in investing in green bonds will primarily increase the turnover rate of bonds, whereas increasing the supply of green bonds without providing government guarantees will not have a significant impact on the liquidity of the green bond market as a whole. At the same time, one of the methods of solving the problem of having a pool of illiquid bonds can be the instruments of portfolio investment in green bonds proposed by Dorofeev M. L.. In this regard, we see the need to develop an exchange index of the green debt financial instruments sector, including on the Moscow and Kazakhstan stock exchanges, and additional criteria for implementing the Financial Market Development Strategy of the Russian Federation, taking into account not only the share of green bonds in the total amount of bonds, but also the share of green bonds in the portfolios of institutional and non-institutional investors.

The placement of federal green bond loans in the Russian Federation is also seen as potentially successful (which was also previously proposed by Balynin I. V. ^[3]) based on the experience of issuing green government bonds in the Republic of Belarus and the exemption of individuals from taxation on personal income from the sale and repayment of green bonds in order to increase demand for green bonds ^[14][15]. It is important to note that the problem of liquidity of green bonds is also relevant in the Republic of Belarus – the last transaction on the first government bond loan took place more than 2 months ago from the date of the study ^[16]. At the same time, the experience of providing payment of listing fees by issuers of green bonds on preferential terms is also applicable in the Russian Federation. We also note the need to increase the offers of green bonds on the Kazakhstan Stock Exchange, including from non–credit organizations - 6 out of 7 green bonds were placed by banking organizations ^[17], 5 of which were not traded in the last 3 months at the date of the study, and the last trades on green bonds issued by KEGOC JSC The research dates took place earlier than 3 months ago, which calls into question the level of their liquidity and investment attractiveness ^[18].

The versatility of methods and principles for measuring bond liquidity necessitates the use of several or composite indicators and liquidity indicators with proven significance, both in the Russian stock market and in the countries of the Eurasian Economic Union. At the same time, regulatory requirements for the principles of attracting green financing and reporting on green projects can be unified at the EAEU level within the framework of the activities of supranational organizations, for example, the International Association of Exchanges of CIS Countries (IAB CIS) or the Center for Green Bonds of the Astana International Financial Center (AIFC, AIFC). In addition, on the basis of the ICFA, it is possible to hold events to raise awareness of current and potential investors about the principles and mechanisms of green debt financing, which is a relatively new and innovative financial instrument in the financial markets of the EEA member states, which will strengthen strategic cooperation of the EAEU member states in the field of green financing development and increase demand for green bonds (figure - 3).

Figure 3 – Socio-economic effects of the implementation of the author's proposals

Source: developed by the author.

Thus, increasing the liquidity of green bonds and the growth of their market through the implementation of the proposed measures will have positive effects on the socio-economic development of the EAEU countries.

Conclusion

Increasing demand for green bonds is one of the factors in the development of the green debt financing market, therefore, the investment characteristics of green bonds are an important aspect in attracting new participants to the market, including institutional and retail investors, providing the opportunity to form a balanced investment portfolio. We have successfully studied the liquidity indicators by rating green bonds according to their liquidity level. The problems of having a group of illiquid bonds and an imbalance between the indicators of urgency and volume can be solved by creating portfolio investment tools, an index of the green bond sector, participation in attracting green financing from large issuers and high-quality information support for placing green bonds on the market, while increasing demand is a more primary task than increasing supply.

The materials and results of the study are applicable to improve green financing in the EAEU member states for the development of the domestic and foreign market of green debt instruments.

The author proposes to carry out further studies of the liquidity of green bonds on the basis of determining additional liquidity indicators, including studying the time intervals between transactions taking into account price changes, evaluating the liquidity factors of green bonds through regression analysis taking into account their specifics, using liquidity indices calculated on the stock markets of the EAEU member states and analyzing transactions on green bonds for a longer period.

Thanks. The author thanks Igor Viktorovich Balynin, PhD, Associate Professor, Associate Professor of the Department of Public Finance, Faculty of Finance, Financial University under the Government of the Russian Federation for his assistance in conducting scientific research.