We study de Finetti's optimal dividend problem, including capital injections, under the assumption that uncontrolled assets behave as the additive component of a Markov additive process. We assume that capital injections can be received at any time. Meanwhile, we primarily address cases in which dividends can only be paid at specific, discrete times, and we establish the necessary and sufficient conditions for the optimality of the strategies. Additionally, we prove the optimality of certain Markov-modulated periodic-classical barrier strategies and cover cases where dividends can be paid at any time via approximation. A key feature of this research is our use of a significantly more general Markov additive process than in prior studies, which leads to different proof approaches.
This paper presents a comprehensive sensitivity analysis of the pioneering real-world deployment of computer vision-enabled construction waste sorting in Finland, implemented by a leading provider of robotic recycling solutions. Building upon and extending the findings of prior field research, the study analyzes an industry flagship case to examine the financial feasibility of computer vision-enabled robotic sorting compared to conventional sorting. The sensitivity analysis covers cost parameters related to labor, wages, personnel training, machinery (including AI software, hardware, and associated components), and maintenance operations, as well as capital expenses. We further expand the existing cost model by integrating the net present value (NPV) of investments. The results indicate that the computer vision-enabled automated system (CVAS) achieves cost competitiveness over conventional sorting (CS) under conditions of higher labor-related costs, such as increased headcount, wages, and training expenses. For instance, when annual wages exceed EUR 20,980, CVAS becomes more cost-effective. Conversely, CS retains cost advantages in scenarios dominated by higher machinery and maintenance costs or extremely elevated discount rates. For example, when the average machinery cost surpasses EUR 512,000 per unit, CS demonstrates greater economic viability. The novelty of this work arises from the use of a pioneering real-world case study and the improvements offered to a comprehensive comparative cost model for CVAS and CS, and furthermore from clarification of the impact of key cost variables on solution (CVAS or CS) selection.
Seyed Mohammad Hadi Shahamat, Mahdi Mohammad Bagheri, Ali Raispour Rajabali
et al.
Abstract
The purpose of this research is to present a model of portfolio management in investment funds based on behavioral financial variables. The method of this research was applicable in terms of purpose, and of descriptive-survey type. The statistical population of the research includes 10 experts who have a PhD. degree in financial management or accounting and university professors. The method of data collection was a researcher-made questionnaire and analyzed using structural and interpretive modeling. The results showed that in the first level, the most effective components included: control of the fear of surviving profit, normalization of conservative behaviors, and control of regret-avoidance behaviors. In the second level, the components influencing the first level, i.e. paying attention to self-control behaviors, having a written investment strategy, paying attention to the principles of mental accounting; and in the third level, the components influencing the second level, which include behavioral optimism and pessimism, Paying attention to risk-averse and risk-taking behaviors and, controlling mass behaviors; and the most effective component at the fourth level includes the effect of inclination. In the Mik Mak model, most of the variables were also included in the linked variables, which have a strong influence and also a strong dependence force.
Extended Abstract
Introduction
The behavior of investors as those who seek to optimize profit, omniscient, and infinitely rational, is difficult to understand in the real world. Even assuming that investors are aware of everything, the fact that they may have to interact in information search processes and that they may have rational limitations has been ignored (Barasud & Zamardian, 2019). The uncertainty in analyzing investment risk against expected market returns means that portfolio management has been a thoughtful challenge for portfolio managers. Fund managers should change their portfolios at regular intervals and should add a tendency style. Portfolio management is the allocation of assets, diversification and rebalancing of assets up to higher than the limit set. Asset allocation is the division of assets in the portfolio between risky and risk-free asset classes. Typically, investing requires the careful design of an investment policy statement that appeals to the unique needs of investors. Diversification is sharing risk and reward across asset classes because it is difficult to determine which particular subset of assets is likely to perform better than another. Therefore, diversification is a process of expanding the number of assets in a portfolio in order to minimize investment risk (Doeh Agblobi et al, 2020). Thus, in this research, the researcher intends to answer the basic question: what is the model of portfolio management in investment funds based on behavioral financial variables?
Theoretical Framework
Portfolio management
Portfolio management is the art and science of deciding on investment texture and strategy, matching investments with objectives, allocating assets to individuals and institutions, and balancing risk against performance (Bkhit, 2019).
Behavioral finance
Behavioral finance studies how psychological phenomena affect financial behavior. Financial behavior studies how people behave in determining financial matters. Behavioral finance is a new theoretical branch in finance that is defined by combining the knowledge of psychology, sociology and other social sciences (Meisa Dai et al, 2021).
Investment funds
On the other hand, in most of the developed countries, investment funds are considered as the central core of the capital market and they direct huge amounts of wandering capital to the productive and active sectors of the society every month. By adopting appropriate policies, these funds can play an essential role in reducing inflation, increasing production, and improving the efficiency of managers. Fortunately, the investment funds industry in Iran was established in 2007 with a delay of several decades, but with a lot of acceptance from the investors. Considering the irreplaceable role of these funds in allocating optimal financial resources in the capital market, evaluating the type of transactions in these companies and the effect of their type of ownership on the type of transactions of these financial intermediaries can provide valuable information to investors (Shams & Esfandiari Moghadam, 2016).
Bennett et al, (2023) mentioned that it was implemented as a behavioral finance approach for pricing decentralized financial assets. They found that decentralized finance provides a better explanation of asset pricing in rapidly evolving markets than traditional financial theory. Investor attention, sentiment, discoveries and biases, and network effects interact to form a highly volatile and dynamic market.
Keshavarz et al, (2021) in a research on investment strategies based on technical indicators: evidence of behavioral reactions of investors in the Tehran Stock Exchange. The results showed that according to the coefficient of variation and the correlation test, the results indicate that the indicators of moving average, exponential moving average, and relative power, compared to other indicators, are more indicative of the behavioral reactions of investors.
Research methodology
The method of this research was applicable in terms of purpose, and of descriptive-survey type. The statistical population of the research includes 10 experts who have a PhD. degree in financial management or accounting and university professors. The method of data collection was a researcher-made questionnaire.
Research findings
Data analysis using structural and interpretive modeling. The results showed that in the first level, the most effective components included: control of the fear of surviving profit, normalization of conservative behaviors, and control of regret-avoidance behaviors. In the second level, the components influencing the first level, i.e. paying attention to self-control behaviors, having a written investment strategy, paying attention to the principles of mental accounting; and in the third level, the components influencing the second level, which include behavioral optimism and pessimism, Paying attention to risk-averse and risk-taking behaviors and, controlling mass behaviors; and the most effective component at the fourth level includes the effect of inclination. In the Mik Mak model, most of the variables were also included in the linked variables, which have a strong influence and also a strong dependence force.
Conclusion
The present research was conducted by presenting the model of portfolio management in investment funds based on behavioral financial variables. The results obtained in this research is aligned and in the same direction with the results of Bennett et al, (2023), Fuladi et al, (2021), Keshavarz et al, (2021), Sajid (2021), Leković (2020), Lotfolah Hamdani (2020) and Asadi Qarajalo & Abdo Tabrizi (2019). Bennett et al, (2023) mentioned that it was implemented as a behavioral finance approach for pricing decentralized financial assets. They found that decentralized finance provides a better explanation of asset pricing in rapidly evolving markets than traditional financial theory. Investor attention, sentiment, discoveries and biases, and network effects interact to form a highly volatile and dynamic market.
Therefore, it is suggested to investigate the effects between these variables using structural equation models in future researches. Also, other methods of uncertainty modeling, including fuzzy DEA, should be used to model these indicators.
Before closing venture capital financing rounds, lawyers conduct diligence that includes tying out the capitalization table: verifying that every security (for example, shares, options, warrants) and issuance term (for example, vesting schedules, acceleration triggers, transfer restrictions) is supported by large sets of underlying legal documentation. While LLMs continue to improve on legal benchmarks, specialized legal workflows, such as capitalization tie-out, remain out of reach even for strong agentic systems. The task requires multi-document reasoning, strict evidence traceability, and deterministic outputs that current approaches fail to reliably deliver. We characterize capitalization tie-out as an instance of a real-world benchmark for legal AI, analyze and compare the performance of existing agentic systems, and propose a world model architecture toward tie-out automation-and more broadly as a foundation for applied legal intelligence.
We construct a novel event-level Capital Control Measures (CCM) dataset covering 196 countries from 1999 to 2023 by leveraging prompt-based large language models (LLMs). The dataset enables event study analysis and cross-country comparisons based on rich policy attributes, including action type, intensity, direction, implementing entity, and other multidimensional characteristics. Using a two-step prompt framework with GPT-4.1, we extract structured information from the IMF's Annual Report on Exchange Arrangements and Exchange Restrictions (AREAER), resulting in 5,198 capital control events with 27 annotated fields and corresponding model reasoning. Secondly, to facilitate real-time classification and extension to external sources, we fine-tune an open-source Meta Llama 3.1-8B model, named CCM-Llama, trained on AREAER change logs and final status reports. The model achieves 90.09\% accuracy in category classification and 99.55\% in status prediction. Finally, we apply the CCM dataset in an empirical application: an event study on China, Australia, and the US. The results show that inward capital control measures significantly reduce fund inflows within one month, and restrictive policies tend to have stronger effects than liberalizing ones, with notable heterogeneity across countries. Our work contributes to the growing literature on the use of LLMs in economics by providing both a novel high-frequency policy dataset and a replicable framework for automated classification of capital control events from diverse and evolving information sources.
Yuliia Kazmina, Eelke M. Heemskerk, Emilia van der Kooij
et al.
The promise of equal opportunity is a cornerstone of modern societies, yet upward economic mobility remains out of reach for many. Using a decade of population-scale social network data from the Netherlands, covering over a billion family, school, workplace, and neighborhood ties, we examine how structural inequality and social capital jointly shape economic trajectories. Parental background is a strong early predictor of economic outcomes, but its influence fades over time. In contrast, bridging social capital is what positively predicts long-term mobility, particularly for economically disadvantaged groups. Reducing the dimensionality of an individual's network composition, we identify two key dimensions: exposure to affluent contacts and socioeconomic diversity of one's network. These are sufficient to capture the core aspects of social capital that matter for economic mobility. Overall, our findings demonstrate that while inherited advantage shapes the starting point of economic trajectory, social capital can powerfully reshape it, especially for the poor.
Consensus protocols used today in blockchains often rely on computational power or financial stakes - scarce resources. We propose a novel protocol using social capital - trust and influence from social interactions - as a non-transferable staking mechanism to ensure fairness and decentralization. The methodology integrates zero-knowledge proofs, verifiable credentials, a Whisk-like leader election, and an incentive scheme to prevent Sybil attacks and encourage engagement. The theoretical framework would enhance privacy and equity, though unresolved issues like off-chain bribery require further research. This work offers a new model aligned with modern social media behavior and lifestyle, with applications in finance, providing a practical insight for decentralized system development.
This paper incorporates fixed capital into a multi-sectoral input-output model to reassess the Okishio Theorem. We establish the existence of a critical wage elasticity strictly less than unity, beyond which cost-reducing technical progress leads to a declining equilibrium rate of profit. This implies that profit rates may fall even under Kaldor's Stylized Facts or a moderately declining labour share, significantly extending the theorem's domain of validity. Game-theoretic analysis reveals a strict Prisoner's Dilemma structure underlying technical adoption. Empirical evidence from Chinese industrial data confirms that fixed capital intensity exerts a significant dampening effect on the profit-enhancing impact of productivity growth.
The integration of Artificial General Intelligence (AGI) into economic production represents a transformative shift with profound implications for labor markets, income distribution, and technological growth. This study extends the Constant Elasticity of Substitution (CES) production function to incorporate AGI-driven labor and capital alongside traditional inputs, providing a comprehensive framework for analyzing AGI's economic impact. Four key models emerge from this framework. First, we examine the substitution and complementarity between AGI labor and human labor, identifying conditions under which AGI augments or displaces human workers. Second, we analyze how AGI capital accumulation influences wage structures and income distribution, highlighting potential disruptions to labor-based earnings. Third, we explore long-run equilibrium dynamics, demonstrating how an economy dominated by AGI capital may lead to the collapse of human wages and necessitate redistributive mechanisms. Finally, we assess the impact of AGI on total factor productivity, showing that technological growth depends on whether AGI serves as a complement to or a substitute for human labor. Our findings underscore the urgent need for policy interventions to ensure economic stability and equitable wealth distribution in an AGI-driven economy. Without appropriate regulatory measures, rising inequality and weakened aggregate demand could lead to economic stagnation despite technological advancements. Moreover this research suggests a renegoation of the Social Contract.
Ostaev Gamlet, Klychova Guzaliya, Valiev Ayrat
et al.
The aim of the study is to systematize the problems of innovation and technological development of livestock breeding in the region and to determine the guidelines for the development of biological and information technologies, which involves updating the organizational and economic mechanism of agricultural production management and obtaining new competitive products. In the course of the study, the indicators of innovative development of the industry in the Orenburg region were analyzed on the basis of the data of the Territorial Service of State Statistics. In the article the authors summarized the materials of the modern innovative development of the livestock industry in the region and revealed that in recent years there have been positive shifts in the size of investments and costs for research and development of agrarian science in the industry. The study identified the factors that hinder the innovative development of the agro-industrial complex of the Orenburg region. The deficit of own sources of working capital formation was and remains the main problem of aging means of production. The existing level of state support allowed agricultural organizations in the region to increase the average annual level of profitability, but it is important to implement modern science-based systems of innovative transformation of the industry with the transition to a new technological way of life with minimal dependence on the impact of external climatic and biological factors.
Choosing an appropriate exchange rate regime is crucial for economic policy, particularly for developing countries seeking to establish robust macroeconomic frameworks to mitigate external shocks. However, such nations, including those reliant on oil and natural gas exports, often face challenges in selecting suitable regimes, exacerbated by a lack of traditional advice. The debate around this issue intensified in the aftermath of the 2014 oil price decline. In response, Jeffrey Frankel proposed the currency-plus-commodity basket (CCB) arrangement in 2017, blending the benefits of floating and pegging. This study applies the CCB system to Algeria, aiming to evaluate its impact compared to the current managed floating regime from 2001 to 2021, on indicators of internal (inflation rates) and external (change in foreign exchange reserves) balance using monthly data. Employing wavelet analysis and robustness tests, specifically quantile-on-quantile regression (QQR), the findings suggest that the CCB regime surpasses managed floating in maintaining monetary stability and achieving internal and external balance. Moreover, it provides greater flexibility and stimulates the domestic economy through its ability to stabilize terms of trade via active countercyclical monetary policy. Nonetheless, further discussion, adjustment, experimentation, and development of the proposed regime are warranted.
Introduction. The period from 1957 to 1963 is an important period in the history of the city of Elista. In 1957 the autonomy of the Kalmyk people was restored, the statute of the capital city of the republic was returned to Elista, and the city itself received a powerful impetus for its further development. Since the city did not have its own resources for reconstruction, financial and other types of material assistance played the main role in this process from the state and population migrations organized by it. The great importance that population migrations had for Elista, the largest city in Kalmykia, makes it necessary to study this aspect in the past life of the city, which, moreover, was not specifically studied. The study aims to highlight the migration policy of the state during the years of the restoration of the republic and the most massive migrations in the history of the city, to show their impact on the development of the city. The article was prepared on the basis of documents of the state authorities of the Kalmyk ASSR, stored in the National Archive of the Republic of Kalmykia. The research was carried out based on historical-comparative and historical-genetic research methods. Results. In 1957–1963, there was a sharp surge in population migrations in Elista, caused by the restoration of Kalmykia as an administrative-territorial entity in 1957 and the granting of the city the legal status of its capital. The state allocated large funds for the restoration and further development of the socio-economic structure of the city, but there was a shortage of personnel and labor resources in general for the development of capital investments. To solve this problem, the authorities attracted Kalmyks returning from places of deportation to the city, conducted recruitment among workers from other subjects, invited military personnel demobilized by their army, and sent graduates of vocational schools to the city. As a result, the shortage of workers was largely overcome, which made it possible in 1964 to abandon new mass organized relocations to the city. Conclusions. The massive influx of population in 1957–1963 had a great impact on the demographic, social and national structure of the population. The population of Elista has increased dramatically, especially among young people, which has improved the demographic indicators of citizens, their social composition has changed, which has transformed into an urban one, the city has turned from a mono-national into a multi-national one.
History of Asia, Political institutions and public administration - Asia (Asian studies only)
We study the impact of regulatory capital constraints on fire sales and financial stability in a large banking system using a mean field game model. In our model banks adjust their holdings of a risky asset via trading strategies with finite trading rate in order to maximize expected profits. Moreover, a bank is liquidated if it violates a stylized regulatory capital constraint. We assume that the drift of the asset value is affected by the average change in the position of the banks in the system. This creates strategic interaction between the trading behavior of banks and thus leads to a game. The equilibria of this game are characterized by a system of coupled PDEs. We solve this system explicitly for a test case without regulatory constraints and numerically for the regulated case. We find that capital constraints can lead to a systemic crisis where a substantial proportion of the banking system defaults simultaneously. Moreover, we discuss proposals from the literature on macroprudential regulation. In particular, we show that in our setup a systemic crisis does not arise if the banking system is sufficiently well capitalized or if improved mechanisms for the resolution of banks violating the risk capital constraints are in place.
The purpose of this research was to identify the factors affecting financing of small and medium-sized enterprises in the Tehran Stock Exchange (TSE). The method of this study was to use the multiple regression model and panel data to test the hypotheses. The statistical population included 63 small and medium-sized companies admitted to the TSE, which were tested for the period of 2006 to 2021. The contribution was the use of market cap as a criterion for determining small and medium-sized companies. According to the findings, company size has a significant effect on internal financing. In addition, company size had a significant relationship with external financing through debt and share issuance. Also, there was a significant relationship between intangible assets and internal financing, while the ages of the small and medium sized enterprises did not have a significant relationship with external financing. It is suggested that small and medium-sized enterprises pay more attention to the significant variables for financing.
Keywords: Financing, Debt, Equity, Intangible Assets, Small and Medium-Sized Enterprises.
Introduction
The primary focus of this study was to investigate the financing of the capital structure of Small and Medium-sized Enterprises (SMEs) in Iran. SMEs play a crucial role in the economies of both developed and developing countries. According to the theory posed by Schumacher, a renowned German economist, as presented in the book "Small is Beautiful", creating job opportunities in rural areas and small towns can be achieved by making modest investments to generate employment, utilizing relatively simple production methods and leveraging local resources to establish small industries. SMEs serve as the backbone of the developing world's economy (Memarnejad, 2019).
In today's world, financing has become a significant concern for countries, whether they are developing or developed. A well-designed capital structure possesses the potential and capacity to adapt to changes in the surrounding environment and, in turn, influences its surroundings by generating appropriate returns.
SMEs play a crucial role in poverty alleviation, wealth creation, and fostering greater participation of marginalized sections of society, such as youth and women, in the economic development of nations. The growth of these enterprises strengthens the democratic ethos and civil society, while also encouraging entrepreneurs to actively engage in the economic, political, and social fabric of their countries. In fact, in most nations, the majority of employment opportunities are generated by SMEs. For instance, in the 30 high-income countries belonging to the Organization for Economic Cooperation and Development, two-thirds of the total workforce can be attributed to SMEs (Memarnejad, 2019).
This study aimed to highlight the significance and role of SMEs in Iran's economy. However, certain selection criteria were applied, such as: a) selecting companies with fiscal years ending in March and no changes in their fiscal year, b) encountering incomplete data for some companies, and c) excluding banks, financial institutions, and financial investment companies due to their distinct nature of operations. Consequently, the number of companies studied was reduced to 63. Therefore, caution should be exercised when generalizing the findings of this study to other entities within the industry under consideration.
Moreover, it is important to note that financing is influenced by various macroeconomic factors, including the inflation rate, gross domestic product, interest rates on facilities, and exchange rates. However, these factors were not incorporated into this study, and consequently, might impact the results.
Various factors, such as asset structure, age, profitability, growth, and industry, have been identified as key determinants that can significantly influence the capital structure (Hall, 2002). Indeed, a wide range of variables have been found to impact the choice of an appropriate capital structure (Chen, 2004; Çekrezi, 2013). Additionally, this study examined factors that could potentially affect both the capital structure and profitability of companies. Recognizing that the capital structure can impact the overall value of a company, it is crucial to investigate the factors that effectively and predictably influence it. Numerous authors have conducted studies in this area, leading to the development of theories, such as the static equilibrium theory, the pecking order theory, and the agency theory.
The static equilibrium theory emphasizes the balance between the tax shield of interest rate and the costs associated with debt issuance. According to this theory, a company should strive to achieve an optimal level of debt that maximizes its profitability. When the value of the tax benefit exceeds the present value of the costs associated with debt issuance, the company is considered to be at an optimal equilibrium point. Therefore, a manager aiming to maximize shareholders' wealth should carefully select a level of debt for the company that ensures the resulting tax shield outweigh the current value of the costs associated with debt creation (Rasiah & Kim, 2011).
Another prominent theory of capital structure is the pecking order theory, initially proposed by Myers and Majluf. This theory suggests a preference for financing investment projects using internal funds, such as retained earnings (internal financing), rather than relying on external resources obtained through equity issuance and debt issuance. According to this theory, managers prioritize utilizing retained earnings for funding their projects. Once the accumulated earnings are depleted, they turn to debt issuance as a source of financial resources. Finally, when it becomes impractical to take on additional debt, they resort to share issuance to meet their financial needs (Rasiah & Kim, 2011).
On the other hand, the agency theory posits that the optimal capital structure is achieved by minimizing the costs arising from conflicts of interest between stakeholders (Jensen and William, 1976). In this context, agency costs play a significant role in funding decisions due to the potential conflicts that may arise between shareholders and debt holders.
The size of an enterprise has a profound impact on its capital structure (Rajan & Zingales, 1995; Titman & Wessels, 1988). Small firms, in particular, face unique challenges compared to larger businesses as they have often limited access to external sources of capital, such as debt. Consequently, they are compelled to make alternative financing decisions (Ang, 1991). This supports the notion that SMEs are more susceptible to financial difficulties and confront higher levels of uncertainty and risk compared to newer, smaller firms (Engel & Stiebale, 2013; Rosenbusch Brinckmann & Müller, 2013).
Based on the proposed conceptual framework, the following hypotheses were put forth:
Hypothesis 1: The size of small and medium-sized enterprises exhibits a significant relationship with internal financing.
Hypothesis 2: The size of small and medium-sized enterprises demonstrates a significant relationship with external financing in the form of debt.
Hypothesis 3: The size of small and medium-sized enterprises displays a significant relationship with external financing through equity issuance.
Intangible assets possess the potential to create valuable knowledge-based competitive advantages, thereby fostering future growth (Barney, 1991; Hitt et al., 2001). However, these assets are often challenging to transfer to other businesses, making it difficult to secure external funding sources (Brierley, 2001; Revest and Sapio, 2012). Firms with intangible assets face a greater problem of asymmetric information as these assets are difficult to value. This, in turn, reduces their opportunities to obtain external financing (Clarysse et al., 2003; Harris et al., 1991).
Based on the above, the following hypothesis was proposed:
Hypothesis 4: Intangible assets exhibit a significant relationship with internal financing in small and medium-sized enterprises.
The age of a company also plays a crucial role in determining its capital structure. Faulkender (2005) highlights an interesting point, suggesting that younger firms have less established track records and may not be as recognized by their more experienced competitors. Consequently, small and medium-sized enterprises often struggle to secure sufficient financial resources (Demirel & Parris, 2015). The pecking order theory further supports the notion that internal financing should be prioritized followed by debt financing (Myers & Majluf, 1984). Based on the aforementioned cases, the following hypotheses were proposed:
Hypothesis 5: The age of small and medium-sized enterprises exhibits a significant relationship with external financing through equity issuance.
Hypothesis 6: The age of small and medium-sized enterprises demonstrates a significant relationship with external financing in the form of debt.
Materials & Methods
The aim of this study was to examine the impact of size, age, and intangible asset variables on the dependent funding variable. Additionally, control variables, such as the operating cash, operating income ratio, current account ratio, fixed asset ratio, and working capital, were included. This study was conducted through a literature review, analyzing relevant literature and employing descriptive and inferential analyses of the data. The statistical population for this study consisted of small and medium-sized collected listed in the Tehran Stock Exchange (TSE). A sample of 63 companies was selected for the period of 2006-2021. The hypotheses were based on the models proposed by Neville & Lucy (2022) and Aghaei (2015). Regression analysis was employed to test the effect of factors on the models of internal financing, external financing, and ownership ratio. Three regression models were utilized and their definitions and methods of obtaining the variables were explained as follows:
INTRNLit=β0+β1INTANGPERCit+β2CURRENTRATIOit+β3FIXEDASSETit+β4SIZEit+β5OPERATINGCASHTOINCOMEit+β6WORKINGCAPITALit+eit Model (1)
Model 2 was employed to test the hypotheses regarding the factors influencing external financing (debt). In this model, the following variables were considered: INTRNL is internal financing represented as a percentage of the total capital. It is calculated by dividing the capital increase from reserves, cash inflows, and current receivables by the total capital. INTANGPER is intangible asset ratio determined by dividing the value of intangible assets by the total assets listed on the balance sheet. CURRENTRATIO is current ratio calculated by dividing current assets by current liabilities. FIXEDASSETRATIO is fixed asset ratio obtained by dividing fixed assets by total assets. SIZE is size of the enterprises measured by using the logarithm of the book value of assets. OPERATINGCASHBYINCOME is the relationship between operating cash and operating profit calculated by dividing operating cash by operating profit. WORKINGCAPITAL is net working capital calculated as the difference between current assets and liabilities. These variables were analyzed in Model 2 to assess their impacts on external financing (debt) and test the hypotheses.
DEBTit=β0+β1AGEit+β2CURRENTRATIOit+β3FIXEDASSETit+β4SIZEit+β5OPERATINGCASHTOINCOMEit+β6WORKINGCAPITALit+eit Model (2)
In the above model, DEBT represents the proportion of total debt to total assets, indicating the extent to which the company is financed through debt. AGE refers to the age of the enterprises calculated based on the logarithm of the number of years of activity. In addition to these variables, other control variables, such as the capital ratio, current ratio, operating cash ratio, and working capital were included.
Model 3 was developed to test and validate the assumptions regarding the factors influencing the ownership ratio. The aim of this model was to investigate the variables that contributed to determining the ownership structure of the sample enterprises.
EQUITYit=β0+β1AGEit+β2WORKINGCAPITALit+β3CURRENTRATIOit+β4FIXEDASSETit+β5SIZEit+β6OPERATINGCASHTOINCOMEit +eit Model (3)
EQUITY represents the shareholder ratio, which is calculated by dividing the total funding by the total capital. Selection of the dependent and independent variables was based on the study conducted by Neville and Lucy (2022).
Findings
The data used in this study were combined at the enterprise-year level and econometric diagnostic tests were conducted. Based on the evidence, Hypothesis 1, which posited a significant relationship between the size of SMEs and internal financing, was confirmed. Additionally, Hypothesis 4, which suggested a significant relationship between intangible assets and internal financing, was also supported. The results of Model 1 can be observed in Table 1.
Table 1: The results of estimating model 1
Variable
Coefficient
t statistic
Significance level
OPERATINGCASHTOREVENUE
-0.73
-2.00
0.04
SIZE
0.03
3.01
0.00
WORKINGCAPITAL
-4.18
-1.39
0.16
CURRENTRATIO
-0.04
-1.13
0.25
FIXEDASSETRATIO
-0.14
-0.94
0.34
INIBLETANGIBLEASSETRATIO
7.46
2.19
0.03
C
-0.76
-2.34
0.02
AR(1)
0.01
0.47
0.63
F statistic probability
0.00
4.27
Durbin Watson statistics
2.39
Coefficient of Determination
0.58
Adjusted coefficient of determination
0.44
According to the Table 1, the coefficient of the variable of working capital is found to be significant at the given significance level, indicating a direct relationship with external financing (debt). On the other hand, the variables, such as size, operating cash ratio, current ratio, and fixed asset ratio, exhibit a significant and inverse relationship with external financing.
Based on the evidence, Hypothesis 2, which suggested a significant relationship between the size of small and medium-sized enterprises and external financing (debt), was confirmed. However, Hypothesis 6, which proposed a significant relationship between the age of small and medium-sized enterprises and external financing (debt), was not supported. The results of Model 2 are presented in Table 2.
Table 2: The results of estimating Model 2
Variable
Coefficient
t statistic
Significance level
AGE
0.03
1.57
0.11
SIZE
-0.24
-15.09
0.00
OPERATINGCASHTOINCOME
-0.043
-2.40
0.01
CURRENTRATIO
-0.07
-11.68
0.00
FIXED ASSETRATIO
-0.14
-4.14
0.00
WORKINGCAPITAL
1.91
2.11
0.03
C
-51.90
-1.53
0.12
AR(1)
0.74
21.90
0.00
F statistic probability
0.00
69.31
Durbin Watson statistics
2.11
Coefficient of Determination
0.89
Adjusted coefficient of determination
0.87
Based on the Table 2, the variables of size, fixed asset ratio, current ratio, and operating cash ratio are found to be significantly and positively associated with the ownership ratio, while the working capital ratio exhibits a significant and negative relationship.
Based on the evidence, Hypothesis 3, which suggested a significant relationship between the size of small and medium-sized enterprises and external financing (proprietary rights), was confirmed. However, Hypothesis 5, which proposed a significant relationship between the age of SMEs and external financing (proprietary rights), was not supported. The results of Model 3 are presented in Table 3.
Table 3: The results of Hypothesis Test Model 3
Variable
Coefficient
t statistic
Significance level
AGE
-0.02
-0.24
0.80
SIZE
0.21
15.41
0.00
WORKING CAPITAL
-2.00
-3.14
0.00
FIXED ASSET RATIO
0.15
4.45
0.00
CURRENT RATIO
0.07
12.42
0.00
OPERATING CASH TO INCOME
0.03
1.97
0.04
C
29.80
0.24
0.81
AR(1)
0.71
22.70
0.00
F statistic probability
0.00
0.01
Durbin Watson statistics
2.01
Coefficient of Determination
0.87
Adjusted coefficient of determination
0.85
Discussion & Conclusions
The findings of this study supported the 1st and 3rd hypotheses, which suggested a positive and significant relationship between company size and the dependent variables of internal financing and ownership ratio, respectively. Conversely, company size exhibited a negative and significant relationship with debt, in line with the second hypothesis. Additionally, the results indicated a significant positive relationship between intangible assets and internal financing, aligning with the 4th hypothesis. These findings suggested that small and medium-sized companies relied more on internal financing and utilize less debt, which aligned with the pecking order theory. This is consistent with the study conducted by O'Brien (2003). Furthermore, the study did not find a significant relationship between the age of SMEs and internal and external financing (capital structure), contradicting the 5th hypothesis. In conclusion, the results of this study highlighted the importance of company size and intangible assets in determining the financing choices of SMEs. These findings contributed to our understanding of the capital structure decisions made by SMEs. Regarding the relationship between the size of small and medium-sized enterprises and their internal and external financing, the findings align with the studies conducted by Neville and Lucy (2022), Sunaina (2020), and Aghaei et al. (2014). However, the results differ from those of Ozkan (2001), which can be attributed to variations in the economic structure, such as inflation rate and exchange rate, of the countries. Furthermore, the results support the findings of Neville and Lucy (2022) and O'Brien (2003), regarding the relationship between intangible assets, such as ideas, intellectual property, brands, business methods, and internal financing. It was confirmed that companies with a higher proportion of intangible assets faced more challenges and barriers when seeking external financing, which is consistent with the hierarchical theory.
Regarding the relationship between the age of small companies and external financing, specifically through debt and ownership rights, the findings of this study are consistent with the studies conducted by Gregory (2005), Neville and Lucy (2022), and Wasiuzzaman and Nurdin (2019). However, the results differ from the study conducted by Faulkner et al. (2006), which focused on credit limits and the distinction between the public debt market (bonds) and the private debt market (banks). In their study conducted in England, they found a negative relationship between debt and age of company. The disparity in findings could be attributed to the different economic structures of the countries. This variation highlighted the importance of considering the specific context and economic conditions when analyzing the relationship between company age and external financing.
The article is devoted to the problem of developing mechanisms to increase the sustainability of the digital investment ecosystem, in which the main participants are investors, borrowers or other persons attracting investments, the Bank of Russia as a regulator, a professional organization. The purpose of this study is to identify ways to trust the system of digital investment platforms by developing financial compliance methods for ecosystem participants. In the course of the study, methods of statistical analysis, generalization and grouping of compliance risk assessment, ecosystem modeling with the allocation of functions and actions of its participants were used. The ecosystem approach was used as a basic approach, which allows revealing interactions and assessing the impact of the risks of one participant on the stability of the ecosystem as a whole.
The study found that participants are exposed to high compliance risks that can lead to a system default and cause systemic risks of a chain of bankruptcies due to defaults, changes in rules and restrictions. The level of compliance risk for crowdfunding participants was 27%, and the analysis of operators’ declarations identifies 23 types of risks that an investor takes on and which carry the threat of loss of invested capital. High risks and their diversification led to the conclusion that it is necessary to build investment compliance control procedures into the investment ecosystem, which can be carried out by audit organizations as assurance tasks. The results of the study are of practical importance for the development of the methodological apparatus of compliance in the process of carrying out activities by audit organizations and the development of a system for regulating the activities of investment ecosystems by the Bank of Russia.
This paper presents an empirical analysis of the capital asset pricing model using trading data for the Chinese A-share market from 2000 to 2019. Firstly, the standard CAPM is tested using a Fama-MacBetch regression and although the results successfully test the three core hypotheses, the resulting beta risk does not have a significant impact on returns. Secondly, the Fama-French three-factor model, which uses a combination of market, size and value factors to price capital assets, is analysed, showing that it is able to capture most of the variation in A-share market returns, with an adjusted R-squared greater than 0.88 for the 25 portfolios constructed. Finally, the paper takes into account the "shell value contamination" problem caused by IPO regulation in the Chinese stock market, and minimises its impact by excluding stocks in the lowest 30% of the market capitalisation, which allows some of the anomalous results in the three-factor model to be effectively corrected. Although this paper does not present a more innovative approach, it is unique in its data selection and presents a detailed presentation of the data processing and regression analysis process, which 1) illustrates the applicability of capital asset pricing models in the Chinese market; and 2) provides a set of open source materials for the basic learning of capital asset pricing models.
Moritz A. Drupp, Zachary M. Turk, Ben Groom
et al.
While the global economy continues to grow, ecosystem services tend to stagnate or decline. Economic theory has shown how such shifts in relative scarcities can be reflected in project appraisal and accounting, but empirical evidence has been sparse to put theory into practice. To estimate relative price changes in ecosystem services to be used for making such adjustments, we perform a global meta-analysis of contingent valuation studies to derive income elasticities of marginal willingness to pay (WTP) for ecosystem services to proxy the degree of limited substitutability. Based on 735 income-WTP pairs from 396 studies, we find an income elasticity of WTP of around 0.6. Combined with good-specific growth rates, we estimate relative price change of ecosystem services of around 1.7 percent per year. In an application to natural capital valuation of forest ecosystem services by the World Bank, we show that natural capital should be uplifted by around 40 percent. Our assessment of aggregate public natural capital yields a larger value adjustment of between 58 and 97 percent, depending on the discount rate. We discuss implications for policy appraisal and for estimates of natural capital in comprehensive wealth accounts.