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Reference:

Analysis of factors affecting the excess profitability of mutual funds in Russia for 2015-2022

Arshakian Roza Araikovna

Assistant, Department of Econometrics and Mathematical Methods of Economics, Lomonosov Moscow State University

119234, Russia, Moscow, Leninskie Gory str., Msu, 1, building 61

r.roza.arshakyan@mail.ru
Mironenkova Marina Vladimirovna

Lecturer, Department of Econometrics and Mathematical Methods of Economics, Lomonosov Moscow State University

119234, Russia, Moscow, Leninskie Gory str., Msu, 1, building 61

mironenkova.marina@gmail.com

DOI:

10.25136/2409-7802.2023.4.41027

EDN:

PUTWVO

Received:

18-06-2023


Published:

18-01-2024


Abstract: The relevance of the study of financial market instruments is undeniable and well aligned with the achievement of Russia's national development goals until 2030. The subject of this article is the excess return of Russian mutual funds (MF) in the period from 2015 to 2022. The authors analyzed in detail the scientific literature and took as a basis the conclusions and results obtained in previous studies on similar topics. The aim of the study was to find the factors determining the excess return of mutual funds, which is the difference between the return of the funds and the return of the selected benchmark. The study was based on data from Investfunds Internet portal, which provides information on investment assets for a wide range of people. Econometric analysis was conducted based on an unbalanced panel consisting of an average of 185 funds per year. To achieve the objective, we studied already existing econometric models for analyzing excess fund returns and used them to construct a pass-through regression model and a fixed-effects model. Analyzing the performance of mutual funds depending on their parameters will allow investors to get relevant recommendations about which fund should be preferred to buy a share in its portfolio, which corresponds to the scientific novelty of the study. The main conclusion of the study is that using econometric criteria, the fixed-effects model was selected as the best of the constructed models. A notable contribution of the authors to the study of the topic is the identification of the main aspects that investors should pay attention to when choosing a mutual fund, namely funds with a high net asset value, the object of investment of which are stocks and money, and the direction of investment - precious metals.


Keywords:

investment fund, profitability, benchmark, investor, mutual fund, securities, models, regression, assets, effectiveness

This article is automatically translated. You can find original text of the article here.


Introduction

According to the review of key indicators of mutual and equity investment funds, the net inflow of funds into The mutual fund in the second quarter of 2022 turned out to be the highest in the entire history [1], which indicates an increase in confidence in such a tool for increasing income, which inevitably entails the desire of investors to understand what to pay attention to when choosing a particular fund. An analysis of the performance of funds, depending on their parameters, will allow investors to receive up-to-date recommendations on which fund should be preferred to buy a share in its portfolio, which corresponds to the scientific novelty of the study.

The relevance of the study is due to the importance of studying the issues of socio-economic development of the population, including in the context of ensuring the achievement of national development goals approved by Decree of the President of Russia until 2030 [2]. Thus, the purpose of this study is to identify and substantiate significant factors affecting the excess profitability of mutual funds, as well as to analyze their performance over the past 8 years. To achieve the above goal, the following tasks were set: a review of scientific literature on similar topics, the definition of an information base for conducting econometric research, the selection of factors for further econometric research, as well as the construction of econometric models and their description.

The Federal Law "On Investment Funds" defines a mutual fund as "a separate property complex consisting of property transferred to the trust management of a management company by the founders of the trust management with the condition of combining this property with the property of other founders of the trust management, and from the property obtained in the process of such management, the share in ownership of which is certified by a security, issued by the management company" [3]. In other words, a mutual investment fund is an institution of collective investment, which allows you to accumulate funds from a large number of shareholders [4].

Mutual funds have a number of characteristics, depending on which, for example, certain deadlines are set when it is possible to buy or sell shares. Open-ended mutual funds make it possible to buy and sell shares at any time on a business day. Shares of exchange-traded funds are traded on the stock exchange, like other securities, and an investor can buy or redeem them exclusively on the days of the exchange. Interval funds are designed in such a way that an investor can buy or sell a share only several times a year at specifically set time intervals. Shares of closed-end funds can be purchased at the time of formation of the fund, and repaid at the time of its closure. In addition to the timing of purchase and sale, all these funds have different investment principles, for example, open-ended funds prefer assets that can be quickly sold at a fair price, that is, liquid assets. As a rule, it is typical for exchange-traded funds to invest money in the same proportions and portfolio composition as in other indices, for example, such as the RTS index or MICEX. Interval and closed-end funds invest money in less liquid assets, unlike open-end and exchange-traded funds. This creates additional risks, but it can also bring much more profit.

An econometric approach to assessing the profitability of mutual funds

According to A. Abramova et al. [5], the doctrine lacks a unified approach to measuring the effectiveness of mutual funds. But it is important to understand how best to measure such efficiency, since funds are sources of long-term money. As a rule, economists identify the following existing approaches:
1. The subject of the analysis is the style of the fund. The essence of the approach is that profitability is correlated with a set of factors that determine the style of the fund;
2. Unconditional factor models are evaluated. In particular, it is assumed to use the four-factor Carhart model: [6]
a.r(pt+1)=?p+?1pr(m,t+1)+?2pSMBt+1+?3pHMLt+1+?4pMOMt+1+?pt+1
In this formula, r m denotes the excess profitability of a market portfolio, and SMB, HML and MOM are a set of factors that characterize portfolios by the effect of size, value expression and inertia. If the inertia coefficient is not important, then the three-factor model of Fama and French can be used [7].
3. Fundamental characteristics are taken for evaluation, in particular, the size and ratio of expenses, turnover, net inflows, specifics and management efficiency, etc. As a rule, this approach requires the use of cross-sectional regression:
? i,t=? t+? t'X i,t-k, where X i,t-k is a vector of length m from the characteristics of the fund and the manager in the period t – k.
When evaluating the effectiveness of mutual funds, certain difficulties arise, namely:
1. There are no simple benchmarks that can match portfolios. Traditional benchmarks cannot be applied, as the share of foreign securities is growing;
2. there are no formal criteria by which it is possible to classify mutual funds as active or index, and it is necessary to understand their difference in order to assess effectiveness;
3. There are quite significant costs associated with the analysis and collection of information about funds.
In order to ensure a more or less effective, objective assessment of funds, it is necessary to use multifactorial asset pricing models. This approach has a number of advantages. In particular, it allows you to take into account systematic risks and understand the structure of profitability. A sufficiently high explanatory power is another key advantage.
Thus, the article highlights the key problems in the field of evaluating the effectiveness of investment fund management, and also suggests some solution that can significantly increase the information content and objectivity of the assessment.
The article by N.V.Artamonov et al. [8,9] attempts to identify how the yield of government bonds affects the effectiveness of mutual funds. The US fund system is considered as an example. If interest rates are high enough, then this usually has a beneficial effect on mutual funds.
There are a number of traditional approaches that can be used to evaluate the effectiveness of mutual funds. Let's highlight the main two:
1. The benchmark model. The corresponding panel data is analyzed using the formula below:
Rit=?i+?0iRmt+?it
This approach evaluates Jensen's alpha, and if alpha is zero, it means that the result is correct. However, if it is positive, it may indicate excess profits.
It is worth noting that this model has a number of disadvantages. First of all, there is doubt about the fact that only one indicator of profitability is used with the observed strong correlation of stock characteristics with the benchmark. Also, the model does not take into account the variability of the systematic risk of the portfolio.
2. Next, the researchers proposed sequentially three-factor and four-factor models. Moreover, the latter included additional factors such as the size of the fund, book value and market value, as well as an indicator illustrating the difference between high and low returns. The formula of the latest model looks like this:
Rit=?i+?0iRmt+?1iSMBt+?2iHMLt+?3iMOMt+?it
In general, this approach is already much better than the previous one, but it is also imperfect, since it does not take into account the errors associated with timely portfolio adjustments based on market information with adequate management. Therefore, this model has been further expanded in such a way as to provide an assessment of the conditional performance of funds:
Rit=?i+Ai'[zt-1]+?0iRbt+Bi'[zt-1]Rbt+?it
In the course of the research, the authors carried out a primary data selection: funds and information about their key indicators were selected according to certain criteria. The following formula was used, representing the basic specification:
TE=Rit-Rmt=const+ ?1tresit+?2tnait+?3expit+?4turnit+?5vol30it+?6vol90it+?7vol360it+?it
In the course of the research, economists have identified the following results:
1. The level of yield on long-term bonds can act as a full-fledged factor that affects mutual funds in the United States, their profitability;
2.It is advisable to use an active mutual fund management strategy;
3. The presence of opportunities associated with hedging the risk of losing to the market has been revealed.
Thus, the most effective model is one that not only takes into account the full range of various factors that can affect mutual funds under different circumstances, but also certain variables, in particular, the difference between high and low returns, etc. In general, the hypothesis put forward at the beginning of the study about the positive impact of high government bond rates on mutual funds is confirmed.

The information base of the study

To analyze the factors influencing the excessive profitability of mutual funds in Russia, an independent data source for a private investor in Russia, Investfunds [10] and the website of the largest Russian stock exchange holding, the Moscow Exchange, were selected as information resources [11].

The period under review was 8 years: from 2015 to 2022. 

To understand the functioning of the mutual fund market, it is necessary to consider key variables that may have a significant impact on the profitability of mutual funds [12]. We have selected all the factors available for the specified period.

To build econometric models, consider the following indicators (Table 1):

1. The value of the fund's net assets (net assets) (million rubles). The value of the net assets of a mutual investment fund is defined as the difference between the value of the assets of this fund and the amount of liabilities to be fulfilled at the expense of these assets at the time of determining the value of net assets [13].

2. Remuneration of the management company (CC) (%). The remuneration of the CC can be determined either as a percentage of the average annual value of net assets, or as a certain fixed amount [14]. As a rule, this rate ranges from 0.6% to 4%.

3. Remuneration of the depositary and registrar (%). This rate is somewhat more modest and does not exceed 2% per year.

4. Other expenses (%). Other expenses reimbursed from the fund's assets may include, for example, the cost of paying for the services of organizations to complete transactions from the Fund's assets. These expenses are taken into account in the calculation of the official value of the share upon their payment at the expense of the fund's property [15].

5. The amount of funds raised (million rubles). The funds raised are the funds that the fund has managed to receive from clients.

6. The object of investment. Stocks, bonds, funds, monetary, as well as a mixed type will be considered as an investment object. This variable will be entered as a binary variable.

7. The direction of investment. The second fictitious variable is the direction of investment, which is divided into foreign assets, precious metals, as well as domestic assets. This variable will be entered as a binary variable.

Table No. 1. Factors and their designation in models. Source: the table is compiled by the authors.

Indicator

Designation in models

Units of measurement

Net asset value

NAV

Millions of rubles

Remuneration of the management company

RMC

%

Remuneration of the depositary and registrar

RDR

%

Other expenses

OE

%

The amount of funds raised

VAF

Millions of rubles

Investment object: shares

IOSH

-

Investment object: bonds

IOB

-

Investment object: funds

IOF

-

The object of investment: money

IOM

-

Investment direction: foreign assets

DIFA

-

Investment direction: precious metals

DIPM

-

Excessive profitability of mutual funds

ERMF

%

The dependent variable will be the excess profitability of mutual funds in the period from 2015 to 2022. Excess yield is the difference between the increase in the yield of the fund and the yield of the Moscow Exchange index (Table. 2) [16] and is an indicator of the effectiveness of the fund, which depends on various factors, including those that we presented above [17].


Table No.2. The profitability of the Moscow Stock Exchange index. Source: the table is compiled by the authors.

Profitability of the Moscow Stock Exchange index

Year

26,12%

2015

26,76%

2016

-5,51%

2017

12,3%

2018

28,6%

2019

8,0%

2020

15,15%

2021

-43,1%

2022

Before proceeding to the construction of models, it is necessary to consider the correlation matrix to make sure that there is no multicollinearity (Fig.1) [18].

Based on the results of the matrix, it can be concluded that there is no relationship between the variables of more than 80-85%, which means that it will not be necessary to exclude any variable from the data array.

 

Methods and econometric models

Next, we proceed to the construction of econometric models of panel data. To begin with, let's consider a model of end-to-end regression that evaluates all observations over 8 years [19].


Table No. 3. A model of end-to-end regression. Source: the table is compiled by the authors.

Dependent variable

 

ERMF

Log (NAV)

1.374***

(0.267)

RMC

-1.248***

(0.472)

RDR

0.272

(0.715)

OE

0.431

(0.310)

VAF

-0.0001

(0.0002)

IOSH

5.093***

(1.468)

IOB

-2.065

(1.667)

IOF

12.542

(20.896)

IOM

21.591***

(6.768)

DIFA

-5.955**

(2.674)

DIPM

-4.775***

(1.163)

Constant

-3.147

(2.274)

R2

0.048

Adjusted R2

0.042

F Statistic

7.489***

It is also worth considering a model with fixed effects (Table. 4) [19]. The panel data model with fixed effects is based on the panel data structure, which allows you to take into account immeasurable individual differences of objects (effects). In this model, the effects are interpreted as an interfering parameter, and the evaluation is aimed at eliminating them.

Table No. 4. A model with fixed effects. Source: the table is compiled by the authors.

Dependent variable

 

ERMF

Log (NAV)

0.649***

(0.235)

RMC

-0.243

(0.402)

RDR

-0.006

(0.603)

OE

0.273

(0.260)

VAF

-0.0001

(0.0002)

IOSH

4.137***

(1.232)

IOB

-1.021

(1.400)

IOF

13.148

(17.552)

IOM

14.447***

(5.691)

DIFA

-3.591

(2.248)

DIPM

-3.043***

(0.984)

R2

0.031

Adjusted R2

0.020

F Statistic

4.668***

To select the best model, it is necessary to conduct an F– test [20] (Table 5).

Table No.5. F-test for choosing the best model. Source: the table is compiled by the authors.

F test for individual effects

F=98.967, df=7, df2=1611, p-value<2.2e-16

Based on the results of the F test, it can be concluded that the null hypothesis
the correct end-to-end model is rejected in favor of a fixed-end model
effects, since the p-value is extremely small.

Results

The end-to-end regression model turned out to be generally significant at the 1% level, and its coefficient of determination is at 4.8%, which means that the selected variables explained the proportion of variance, or more simply, the variability of the excess yield of mutual funds by 4.8%.  The net asset value is prologarithmic, as there is a large spread in the data, which distorts the regression results. Accordingly, the logarithm of the net asset value, the remuneration of the management company, the object of investment (shares), the object of investment (money) and the direction of investment (precious metals) are significant at the 1% level of significance, and the direction of investment (foreign assets) is significant at the 5% level. This indicates that all of the above variables are necessary and important to explain the dependent variable under study.

Speaking of the fixed-effects model, it is worth noting that it also turned out to be significant at the 1% level. The adjusted coefficient of determination decreased to 2%, that is, it fell by 2.2%, compared with the end-to-end regression model. At the 1% level, they were significant:

1. The logarithm of the net asset value;

2. Investment object: shares;

3. Investment direction: precious metals.

At the 5% level, only such a factor as the object of investment (money) turned out to be significant.

The coefficient of determination in the case of the considered models is quite low, which may indicate that the available factors are not enough to explain the excessive profitability of mutual funds at a higher level. Perhaps further research requires the inclusion of some economic indicators in the model, for example, such as inflation. In addition, the external environment, represented by the political situation in the world, plays an important role in the study of the mutual fund market, which is extremely difficult to take into account in econometric analysis.

Discussion of the research results

Based on the results of the best fixed-effect model, several points can be identified that are worth paying attention to when choosing a mutual fund.

1. With an increase in the value of net assets, all other things being equal, the excess profitability of mutual funds increases. In the work of A.V. Galanova et al. [12], a hypothesis was put forward about the influence of size and cost factors on the excess profitability of mutual funds. The result of testing this hypothesis showed a significant effect of the NPA on the variable under study. Perhaps the result can be explained by the fact that having an advantage in the amount of funds raised and the ABA, funds have more opportunities to choose strategies and obtain excess returns.  According to investors, the higher the value of the fund's net assets, the higher its reliability. But it is important to note that if the selected mutual investment fund is too large (a total of more than 400 million rubles) [21], it will be extremely difficult for it to replace assets in its composition, which will make it less flexible. It is important for an investor to understand which strategy the fund manager adheres to, since knowing this, the investor can assess the degree of risk, as well as the possible expected income.

2. If the object of investment is stocks or money, then, all other things being equal, the excess yield of mutual funds is higher than in the case of investing in bonds or other other assets. According to Pavlova E. V. [22] equity funds are indeed potentially highly profitable, but at the same time they have a higher degree of risk of losing investments. If we divide all investors into those who are prone to risk (riskophile) and those who try to avoid it (riskophobe), then investing savings in stocks is a suitable investment object for the former, but not for the latter. Riskophobes, in turn, are much more comfortable investing their money in bonds or bank deposits, which are a bulwark of reliability, although less profitable. As for money market funds, they are considered to be the least risky and at the same time the most liquid, since funds allow you to sell money if necessary and quickly invest it in other assets [23]. If we consider the dynamics of the value of the two largest monetary funds, we will notice a trend of constant growth, which cannot but attract investors (Fig.2).

Figure No.2. Dynamics of the share price. Source: the table was built by the author based on Investfunds data [10].

3. If the investment direction is precious metals, then, all other things being equal, the excess profitability of mutual funds is lower than in the case of investing in another direction. Let's look at the market situation using the example of 2022. As we can see in the graph below (Fig.3), at the beginning of the special military operation, there was a sharp jump in the indices of precious metals, for example, gold, silver and platinum. According to analysts, since the beginning of the SVO, investors have invested over 4 billion rubles in such funds [24], but by mid-summer 2022, precious metal indices showed extremely low values, and in October of the same year they reached their record lows. In addition, mutual funds for gold have a number of disadvantages, namely high fees for asset management of open-ended funds, as well as additional fees for the purchase or repayment of the fund, depending on the amount or duration of the investment [25].

Figure No.3. Indices of precious metals. Source: the table was built by the author on the basis of Investfunds data [10].

 

References
1. Bank of Russia: [Electronic resource]. Retrieved from https://www.cbr.ru/Collection/Collection/File/42236/rewiew_pif_aif_22Q2.pdf
2. ConsultantPlus: [Electronic resource]. Retrieved from https://www.consultant.ru/law/hotdocs/63714.html
3. ConsultantPlus: [Electronic resource]. Retrieved from http://www.consultant.ru/document/cons_doc_LAW_34237/
4. Nikonenko, V. (2020). Mutual funds as an institution of collective investment. Economics and Business: Theory and Practice, 5-3.
5. Abramova, A., Radygina A., & Chernova M. (2019). Efficiency of portfolio management of equity mutual funds and its assessment. Economic Policy, 4, 8-47.
6. Fedorova, E., Sivak, A. (2012). Comparison of SARM and Fama-French models on the Russian stock market. Finance and Credit, 42(522). 
7. Bezsmertnaya, E., & Kolganova, E. (2023). Modification of the three-factor Fama-French model and its application to assess the effectiveness of portfolio management of investment funds in Russia. Finansy: teoriya i praktika, 27(2), 17-27.
8. Artamonov, N., Voronina, A., Emelyanov, N., Kurbatskii, A. (2020). Evaluation of the impact of government bond yields on the performance of mutual funds on the example of the United States. Applied Econometrics, 58, 55-75.
9. Artamonov, N., Kurbatskii, A. (2023). Excess return on mutual funds in the USA. Vestnik MGIMO-University, 16(3), 244-262.
10. Independent source of data for private investor in Russia Investfunds: [Electronic resource]. Retrieved from https://investfunds.ru/
11. Moscow Exchange: [Electronic resource]. Retrieved from https://www.moex.com/
12. Galanova, A., Dukova, V. (2018). Factors determining the excess return on the securities portfolio of mutual funds. Corporate Finance, 4
13. ConsultantPlus: [Electronic resource]. Retrieved from http://www.consultant.ru/document/cons_doc_LAW_54399/caf6a29f877d8da1136982ea30df39fa1b5e1306/
14. Gusakov, I. (2017). Optimization of the calculation of remuneration of the management company of the unit investment fund. Financial Research, 2(55). 
15. Managing company Arsagera: [Electronic resource]. Retrieved from https://arsagera.ru/
16. Moscow Exchange: [Electronic resource]. Retrieved from https://www.moex.com/ru/index/totalreturn/MCFTR/
17. Kurbatskii, A. (2022). Active Strategy and Other Key Factors of Mutual Funds' Performance. Montenegrin Journal of Economics, 18(3), 99-107.
18. Ragnar Frisch, (1934). Statistical Confluence Analysis by Means of Complete Regression Systems, Institute of Economics, Oslo University, 5.
19. Ratnikova, T. (2006). Introduction to econometric analysis of panel data. Economic Journal of Higher School of Economics, 2
20. GitHub: [Electronic resource]. Retrieved from https://ranalytics.github.io/data-mining/021-Model-Quality-Criteria.html
21. Open Journal: [Electronic resource]. Retrieved from https://journal.open-broker.ru/investments/pravila-opredeleniya-stoimosti-chistyh-aktivov/
22.  Pavlova, E. (2015). Mutual funds: analysis of profitability and advantages of activity. Vestnik NSTEI, 3(46).
23. Gazprombank Investments: [Electronic resource]. Retrieved from https://gazprombank.investments/blog/market/fondy-denezhnogo-rynka/
24. Apex Consulting Group: [Electronic resource]. Retrieved from https://www.pifconsulting.ru/news/news_679.html
25. Investfunds, an independent source of data for private investor in Russia: [Electronic resource]. Retrieved from https://investfunds.ru/indexes/224/

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Peer reviewers' evaluations remain confidential and are not disclosed to the public. Only external reviews, authorized for publication by the article's author(s), are made public. Typically, these final reviews are conducted after the manuscript's revision. Adhering to our double-blind review policy, the reviewer's identity is kept confidential.
The list of publisher reviewers can be found here.

The subject of the study. Based on the title, the article should be devoted to the results of the analysis of factors affecting the excess profitability of mutual funds in Russia for 2015-2022. The content of the article does not contradict the stated topic, but does not disclose it due to the author's immersion in mathematical calculations without economic justification. The problematic aspects of the reviewed article will be outlined in the relevant paragraphs of the review. The research methodology is based on the use of mathematical research methods, which confirms the author's intentions to obtain reasonable conclusions and judgments. It is recommended that the author, after making calculations and forming mathematical judgments based on them, draw economic conclusions. The relevance of the study of issues related to the activities of various economic entities is beyond doubt, since the socio-economic development of the Russian Federation depends on it, including in the context of ensuring the achievement of national development goals approved by the Decree of the President of Russia until 2030. At the same time, the demand for research on this topic among the potential readership is formed precisely on reasonable problems and reasoned recommendations for their solution. From this point of view, the article requires deep substantive revision. The scientific novelty in the material submitted for review is not clearly indicated by the author, but it is present and is due to the results of mathematical calculations. At the same time, these results must be further justified by the conclusions: what exactly do the calculation results indicate? Style, structure, content. The style of presentation is strictly scientific. The structure of the article is built by the author, but its content is surprising, because the section with "research methodology" takes up more than "research results". The content of the article (except for the section with the research methodology) raises a number of questions. In particular, in the introduction it is necessary to clearly identify the purpose and objectives of the study, as well as to justify the relevance of the study. In the section with the results of the study, the author is recommended to present the conclusions from the mathematical calculations made: what problems are we talking about? What should be done to solve them? Attention is drawn to the absence of a section "Discussion of research results", its formation would allow the author of the reviewed article to enter into a meaningful discussion with other researchers. Bibliography. The author has compiled a bibliographic list, but it includes 8 sources, mostly published in 2020 and earlier. The author is recommended to increase the number of studied sources of scientific literature. Moreover, it is necessary to specify the specific electronic resources used by the author in the preparation of the article, including in terms of numerical data. Appeal to opponents. Despite the generated list of sources, the author has not carried out a scientific discussion. At the same time, it is of wide interest from the point of view of identifying differences in conclusions. This would allow the author to look at the problems in a more versatile way. Conclusions, the interest of the readership. Taking into account all the above, the article requires revision, after which, taking into account the high level of relevance of the chosen research topic, the possibility of publication may be considered.

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The reviewed article is devoted to the study of the development of the radioelectronic industry under the influence of changing tax incentives. The research methodology is based on the analysis of statistical data on the functioning of mutual funds in the Russian Federation, the application of mathematical statistics methods of econometric modeling. The authors associate the relevance of the work with the importance of studying issues of socio-economic development of the population, including in the context of ensuring the achievement of national development goals approved by the Decree of the President of Russia until 2030. The scientific novelty of the reviewed study, according to the reviewer, consists in identifying significant factors affecting the excess profitability of mutual funds and the effectiveness of their functioning. The following sections are structurally highlighted in the article: Introduction, Econometric approach to assessing the profitability of mutual funds, Research information base, Methods and econometric models, Results, Discussion of research results, Bibliography. The bibliographic list includes 25 sources – publications of domestic and foreign scientists on the topic of the article, as well as Internet resources to which there are address links in the text confirming the existence of an appeal to opponents. The article considers the following approaches to measuring the effectiveness of mutual funds: when the style of the fund becomes the subject of analysis; when unconditional factor models are evaluated; when fundamental characteristics such as the size and ratio of expenses, turnover, net inflows, specifics and management efficiency, and other characteristics are taken for evaluation. The authors selected an independent data source for a private investor in Russia, Investfunds, and the website of the largest Russian stock exchange holding, the Moscow Exchange, as information resources, seven potentially key factors were considered, hypothetically having a significant impact on the profitability of funds for the period from 2015 to 2022. Based on these data, the values of the pair correlation coefficients reflected in the correlation matrix are calculated, the multicollinearity of the factors is estimated, a model of end-to-end regression is constructed, as well as a model of panel data with fixed effects, and their descriptions are given. Based on the results of the best model with fixed effects, conclusions are formulated that should be paid attention to when choosing a mutual investment fund. The conclusions are succinctly grouped in three points. It should also be noted the shortcomings and indisputable points in the work. Firstly, it seems superfluous to include in the title of the publication an indication of the period for which the data is being analyzed. Secondly, the formulas are designed with a deviation from generally accepted rules. Thirdly, the design of table No. 5 "F-test for choosing the best model" needs to be adjusted, since the table does not contain a subject and predicate, in addition, it contains a text in English, which may not be understandable to all readers, because the article is written in Russian after all. The article reflects the results of the research conducted by the authors, corresponds to the direction of the journal "Finance and Management", contains elements of scientific novelty and practical significance, may arouse interest among readers, and is recommended for publication taking into account the expressed wishes.
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