Asset Flows Research Articles

Pengaruh Return On Asset, Free Cash Flow, Firm Size, Terhadap Dividend Payout Ratio Dengan Corporate Governance Sebagai Variabel Intervening Pada Perusahaan Manufaktur

This research aims to determine Return on Asset, Free Cash Flow, and Firm Size on Dividend Payout Ratio with Corporate Governance as an intervening variable in manufacturing companies listed on the Indonesia Stock Exchange for the period 2017 - 2021. The sample selection method used is purposive sampling. The total observations in this research were 155 observations consisting of 31 companies. The data analysis technique used in this research is path analysis with the SPSS version 26 analysis tool. The test results of sub structure I show that Return on Asset and Free Cash Flow have a positive effect on Corporate Governance. While Firm Size has no effect on Corporate Governance. The results of sub-structure II testing show that Return on Asset and Free Cash Flow have a positive effect on Dividend Payout Ratio. Meanwhile, Corporate Governance have a negative effect on Dividend Payout Ratio and Firm Size has no effect on Dividend Payout Ratio. The sobel test results show that Corporate Governance is able to mediate the effect of Return on Asset and Free Cash Flow on Dividend Payout Ratio. Meanwhile, Corporate Governance is unable to mediate the effect of Firm Size on the Dividend Payout Ratio.

A theory of net capital flows over the global financial cycle

We develop a theory to account for the relationship between global asset price changes and net capital flows. We show empirically that countries that have a net debt of safe assets experience a rise in net outflows of safe assets (i.e. pay off safe asset debt) when global asset prices fall. This is accomplished through a rise in total net outflows (an increase in net savings) and a drop in net outflows of risky assets (the net sale of foreign risky assets). We develop a multi-country portfolio choice model that can account for these facts. The theory relies on cross-country heterogeneity in the share of an investor’s portfolio invested in risky assets. A global drop in risky asset prices changes relative wealth across countries due to this heterogeneity, which leads to changes in net flows of safe and risky assets. The model is applied to 20 advanced countries and calibrated to reflect observed cross country heterogeneity of net foreign asset positions of safe and risky assets. The implications of the calibrated model for net capital flows are quantitatively consistent with the data.

Design and research of enterprise risk management avoidance system based on KGN-LLM algorithm

With the increasing complexity of enterprise asset management, traditional risk management methods have become inadequate to meet the demands of real-time monitoring and efficient decision-making. In order to improve the efficiency and security of enterprise asset management, this paper proposes a method for reasoning the avoidance of enterprise asset flow management risks based on the KGN-LLM algorithm. It primarily involves the field of financial risk avoidance, including preprocessing and analysis of enterprise asset flow data, constructing a knowledge graph of enterprise asset flow data using the KGN-LLM model, monitoring real-time asset management data, identifying and analyzing risks, evaluating identified risks, and implementing asset management risk avoidance decisions. It is demonstrated that this method of reasoning the avoidance of enterprise asset flow management risks based on the KGN-LLM algorithm can effectively improve the efficiency and security of enterprise asset management.

Pengaruh Earning Per Share, Return On Asset dan Arus Kas terhadap Harga Saham pada Perusahaan yang terdaftar di Jakarta Islamic Index (JII) Periode 2013-2022

This study aims to examine the effect of Earning per Share, Return on Asset and Cash Flow on Stock Prices. The sample used in this study were companies listed on the Jakarta Islamic Index in the period 2013-2022. Testing used quantitative methods with a causality approach and purposive sampling technique, so that 7 companies were obtained and the number of samples obtained was 70 research samples. The data analysis method used is multiple linear regression analysis. The results of the test in this study found that Earning per Share has a positive effect on Stock Price, Return on Asset has a positive effect on Stock Price and Cash Flow has a negative effect on Stock Price.

Application of Graph Theory for Blockchain Technologies

Blockchain technology, serving as the backbone for decentralized systems, facilitates secure and transparent transactional data storage across a distributed network of nodes. Blockchain platforms rely on distributed ledgers to enable secure peer-to-peer transactions without central oversight. As these systems grow in complexity, analyzing their topological structure and vulnerabilities requires robust mathematical frameworks. This paper explores applications of graph theory for modeling blockchain networks to evaluate decentralization, security, privacy, scalability and NFT Mapping. We use graph metrics like degree distribution and betweenness centrality to quantify node connectivity, identify network bottlenecks, trace asset flows and detect communities. Attack vectors are assessed by simulating adversarial scenarios within graph models of blockchain systems. Overall, translating blockchain ecosystems into graph representations allows comprehensive analytical insights to guide the development of efficient, resilient decentralized infrastructures.

The Regulation of Cryptocurrency in China

Abstract As a distributed ledger technology (DLT) application, cryptocurrency has impacted the current financial legal relationship, and its regulation is becoming increasingly important. Some international organizations and countries have ratified laws and regulations concerning cryptocurrency. However, the supervision and regulation of cryptocurrency in China are still encountered some problems, such as consumer protection, the opposition between the global asset flow and the supervision of a single sovereign state, and the difficulty in determining the subject of legal responsibility. To seek solutions to these problems in China, the primary task is to define the legal attribute of cryptocurrency, to balance blockchain innovation and financial risk. At the same time, the regulatory sandbox can be used to regulate blockchain-based cryptocurrency. Among others, the core regulatory measures are establishing the technical standard access system, financing audit registration system, and investor suitability management system of blockchain financial enterprises.

PENGARUH KESULITAN KEUANGAN, MOTIVASI PAJAK, DAN KARAKTERISTIK PERUSAHAAN TERHADAP MANAJEMEN LABA

This research aims to determine whether financial distress, tax motivation, return on asset, financial leverage, sales growth, company size, and free cash flow have an influence on earnings management. The sample used in this study consists of consumer cyclicals and consumer non-cyclicals companies listed on the Indonesia Stock Exchange (IDX) during 2019 - 2022, totalling 62 selected companies as the research sample. The sample selection is conducted by using purposive sampling method, resulting in 62 companies for this research. The analysis utilized a multiple linear regression model. The findings indicate that financial distress, financial leverage, and sales growth have a positive impact on earnings management. This implies that higher levels of financial distress, financial leverage, and sales growth increase the likelihood of earnings management within a company. On the other hand, asset returns and free cash flow show a negative influence on earnings management. This implies that higher levels of, asset returns and free cash flow reduce the likelihood of earnings management practices within a company. Furthermore, variables such as tax motivation and company size do not affect earnings management, indicating that regardless of the figures related to tax motivation and company size, they do not influence the likelihood of earnings management within a company.

International financial subordination in the age of asset manager capitalism

The rise of asset managers as key nodes of financial intermediation has been one of the most fundamental changes in the global economy over recent years. An emerging literature on asset manager capitalism (AMC) discusses these changes and its implications, though largely in the context of corporate governance in advanced capitalist economies. This paper expands the remit of the AMC literature to spaces outside the global capitalist core, and assesses its implications, based on quantitative data on asset manager allocations and flows, and qualitative data from semi-structured interviews. We find that despite the growth of asset managers’ investments into emerging markets, their presence remains limited and that the threat of exit remains present but increasingly tied with global conditions and the composition of benchmark indices. We also find that asset managers’ investments are increasingly focussing on bonds, and are heavily concentrated in a few companies and sectors, revealing a marginal rather than broad-based presence. Finally, we find very limited evidence that asset managers use their voice to influence corporate governance and macroeconomic policy. Overall, asset managers do not seem to fundamentally reshape the characteristics of financial subordination of emerging markets, and the characteristics of AMCs remain, for now, specific to advanced economies.

Building trust takes time: limits to arbitrage for blockchain-based assets

Abstract A blockchain replaces central counterparties with time-consuming consensus protocols to record the transfer of ownership. This settlement latency slows cross-exchange trading, exposing arbitrageurs to price risk. Off-chain settlement, instead, exposes arbitrageurs to costly default risk. We show with Bitcoin network and order book data that cross-exchange price differences coincide with periods of high settlement latency, asset flows chase arbitrage opportunities, and price differences across exchanges with low default risk are smaller. Blockchain-based trading thus faces a dilemma: Reliable consensus protocols require time-consuming settlement latency, leading to arbitrage limits. Circumventing such arbitrage costs is possible only by reinstalling trusted intermediation, which mitigates default risk.

Unraveling the crypto market: A journey into decentralized finance transaction network

The explosive growth of decentralized finance (DeFi) has revolutionized the accessibility and functionality of financial services. To gain valuable insights into this evolving ecosystem, analyzing transaction data using network analysis methodology proves to be highly effective. Network analysis allows us to uncover intricate relationships, patterns, and communities within the DeFi market by examining participant transactions. We model nodes group representing actors or wallet addresses, and edges represent transactions between wallet addresses. This study focuses on three prominent DeFi token-based Ethereum protocols: DAI, UNI, and WBTC. We analyzed 5,802,742 transaction data spanning from January 2022 to January 2023 of those three tokens. Using network topology metrics, we uncover market size, average transaction of each wallet address, market density, and reachability (diameter). We also detect the presence of transaction clusters and grouping quality using the modularity metric. At last, we employ centrality calculation to identify the most important wallet address and their role in the market. We gain insight by comparing those three tokens and reveal valuable insight into patterns and relationships, network dynamics, decentralized nature, and the presence of intermediaries in the token economy market. Our objective is to uncover hidden dynamics and trace asset flows, which can provide valuable information to market participants, regulators, and innovators seeking to optimize the DeFi infrastructure, ensure stability, and mitigate risks. Leveraging the power of network analysis offers the potential to shape the future of DeFi by enhancing efficiency, security, and accessibility, thereby fostering financial inclusion and empowering individuals and businesses globally.

Knowledge and ICT based networks: towards a taxonomy

Abstract Purpose The article proposes a taxonomy of knowledge-based and information and communication technology (ICT) networks based on a systematic literature review. The specific objectives focus on (1) presenting knowledge-based and ICT network models, indicating their theoretical context (trends); (2) identifying proposals for knowledge-based network models in the literature (based on SLR); (3) developing a taxonomy of knowledge-based network models; and (4) indicating the directions of their development. Design/methodology/approach The systematic literature review (SLR) methodology was used, which allows not only for a formalized and objectified synthesis of the existing scientific achievements or for the evaluation of previous research. In addition, the “snowball” method was used, and its application was supported by the use of the ResearchRabbit tool. In addition, the taxonomy method (typological analysis, typological approach) was used. Findings The results of SLR were presented: a list of selected types of knowledge-based and ICT networks along with a discussion of the results, and the author’s proposals for a taxonomy of knowledge-based and ICT networks were presented along with a synthetic description of the leading models. The directions of their development were also indicated. Practical implications (*if any, optional). The practical usefulness of the proposal contained in the study is related to the possibility of using the proposed concept to evaluate various types of network models, which will enable the formulation of diagnostic findings and conducting comparative and dynamic research in the field of analysis and evaluation of knowledge-based and ICT-based network models. Originality/value The added value of the article is related to the development of a proprietary taxonomy of knowledge- and ICT-based networks and, consequently, to the organization and systematization of models of these networks. This taxonomy is a valuable tool for organizing and categorizing information systematically. When it comes to knowledge and ICT-based networks, a taxonomy can help classify and understand the different types and components involved in starting point division into network models that were created as a result of the virtualization process and models that were created as a result of exchange processes and the flow of intangible assets. The added value is also related to the practical usefulness of the developed taxonomy.

Reshaping Charity Channels: How Assets Flow into and out of Donor-Advised Funds

Reshaping Charity Channels: How Assets Flow into and out of Donor-Advised Funds

Innovations in fixed asset accounting

Subject. Fixed assets provide for various types of activities and make up a significant part of the assets of corporations. The growth and improvement of fixed assets characterise the quantitative and qualitative development of a corporation's technical equipment capacity and ensure its sustainable operation. Objectives. The requirements for the presentation and disclosure of accounting information are changing due to the challenges of the global and market economy. Therefore, it is important to consider issues related to the recognition, classification, evaluation, and presentation of economic activities related to the flow of fixed assets. Methodology. The problems related to fixed asset accounting have been studied by many economists from Russia and abroad. A significant number of theoretical works that provoke discussions indicate the need for new approaches to the development of accounting policies and methods of fixed asset accounting in particular. Since corporations use the provisions of the Federal Accounting Standard No. 6/2020 “Fixed Assets”, FSBU 26/2026 “Capital Investments”, and international accounting standards and develop independently their own accounting methods, the accounting policy should be developed with the participation of specialists and people responsible for the presentation and disclosure of information. Results and discussion. Recognition of a fixed asset item in accounting requires the expertise of specialists who can confirm that this item can be used in the ordinary activities of the company for a period exceeding 12 months and that it can deliver economic benefits. Groups of specialists and documents developed by a corporation to outline the conditions for the recognition of fixed asset items are established by bylaws. When recognising a fixed asset item, it is particularly important to determine inventory items and to group them. This is performed by the units of the organisation that ensure the ability of this item to bring economic benefits. If the items meet the conditions for the recognition of fixed asset items, the accountant determines the historical cost of the item. The application of the revalued cost of fixed asset items in accounting, based on the International Financial Reporting Standards (IFRS) 13 “Fair Value Measurement” and (IAS) 36 “Impairment of Assets”, ensures the reliability of financial statements. In case of assets that meet the recognition requirements, but whose value is below the limit established by a corporation, the control of the asset's availability and flow is also regulated by a bylaw. Conclusions. The results of the study can be used by corporations to develop accounting policies related to the systematisation and disclosure of information on fixed assets.

Cross-Chain Asset Transaction Method Based on Ring Signature for Identity Privacy Protection

In recent years, the rapid development of blockchain technology has facilitated the transfer of value and asset exchange between different blockchains. However, achieving interoperability among various blockchains necessitates the exploration of cross-chain technology. While cross-chain technology enables asset flow between different blockchains, it also introduces the risk of identity privacy leakage, thus posing a significant threat to user security. To tackle this issue, this article proposes a cross-chain privacy protection scheme that leverages ring signature and relay chain technology. Specifically, this scheme utilizes RCROSS contracts based on ring signatures to handle cross-chain transactions, thereby ensuring the privacy of both parties involved in the transaction. This cross-chain solution demonstrates practicality and efficiency in facilitating cross-chain asset trading. Furthermore, it effectively combats reuse attacks and man-in-the-middle attacks at the application layer while also providing resistance against denial-of-service attacks at the network layer. To validate the proposed cross-chain solution, we conducted tests by constructing a specific cross-chain scenario and by focusing on the natural gas consumption values generated by the RCROSS contract function used in the application chain. The findings indicate that our proposed solution is highly practical in safeguarding the identity privacy of transaction participants. This article’s framework guarantees reliability, security, and efficiency in cross-chain asset transactions. By incorporating ring-based signatures and relay chain technology, users can confidently protect their identity privacy, thus ensuring secure and smooth cross-chain transactions.

From Asset Flow to Status, Action, and Intention Discovery: Early Malice Detection in Cryptocurrency

Cryptocurrency has been subject to illicit activities probably more often than traditional financial assets due to the pseudo-anonymous nature of its transacting entities. An ideal detection model is expected to achieve all three critical properties of early detection, good interpretability, and versatility for various illicit activities. However, existing solutions cannot meet all these requirements, as most of them heavily rely on deep learning without interpretability and are only available for retrospective analysis of a specific illicit type. To tackle all these challenges, we propose Intention Monitor for early malice detection in Bitcoin, where the on-chain record data for a certain address are much scarcer than other cryptocurrency platforms. We first define asset transfer paths with the Decision Tree based feature Selection and Complement to build different feature sets for different malice types. Then, the Status/Action Proposal module and the Intention-VAE module generate the status, action, intent-snippet, and hidden intent-snippet embedding. With all these modules, our model is highly interpretable and can detect various illegal activities. Moreover, well-designed loss functions further enhance the prediction speed and the model’s interpretability. Extensive experiments on three real-world datasets demonstrate that our proposed algorithm outperforms the state-of-the-art methods. Furthermore, additional case studies justify that our model not only explains existing illicit patterns but also can find new suspicious characters.

EPiC grasshopper: A bottom-up parametric tool to quantify life cycle embodied environmental flows of buildings and infrastructure assets

Reducing the embodied environmental flows of built assets is becoming increasingly important and is a key priority for actors in the built environment to improve life cycle environmental performance. Policies and related targets for embodied environmental flow reductions are emerging. Despite this, tools for quantifying the life cycle embodied environmental flows of built assets are limited in variety and scope. Parametric life cycle assessment (LCA) tools have emerged to address some of these limitations. These tools can enhance decision making, be embedded directly into CAD programs, and offer real-time LCA calculations across multiple design variations. Yet, existing parametric tools for LCA rely on process-based material environmental flow data, limited geometries, limited real-time data visualisation capacity, and often require specialised technical expertise to use. These gaps limit their ability to provide transparent, robust, and rapid assessments. This paper introduces EPiC Grasshopper, an open-source, open-access, bottom-up, parametric tool that enables the quantification of life cycle embodied environmental flows at the early stages of built asset design, bridging the aforementioned gaps. The key characteristics and functionalities of the tool are described, followed by verification (checking that calculations are correct), validation (checking that results are representative of reality), and demonstration of its application to two built asset case studies, i.e. parametrically-defined Australian house and road. The paper shows how the tool can be used to generate designs to meet specific embodied environmental flow targets as well as streamline and increase the uptake of embodied environmental flow assessment and considerations in built asset design workflows.

Based on GSADF model - To study the impact of surging cross-border capital flows and their internal structure on economic growth

This paper measures surges using the Generalized Supremum Augmented Dickey-Fuller (GSADF) model based on capital flows data for 64 economies from 2003:Q1 to 2020:Q4. Then, this paper examines the impact of surges and the internal structure (abnormal liability flows and abnormal asset flows) on economic growth in the recipient economy, and further investigate the heterogeneity among economies with different levels of economic development. This paper finds that surges can positively contribute to economic growth in the recipient economy. In terms of the internal structure of surges, overall, abnormal liability flows have a significant positive effect on economic growth, while abnormal asset flows have no significant effect. Emerging economies perform in line with the overall, while economic growth in developed economies is positively boosted by both abnormal liability flows and abnormal asset flows together. Our research has important reference value for China to prevent risks of surges and their inherent structural changes.

Multinational corporations’ capital allocation decisions across asymmetric risk locations: intertemporal equilibrium and optimal transitional adjustment paths

Abstract Multinational corporations operate across locations with different risk profiles. We examine how multinational corporations address the optimal allocation of capital across multiple locations and analyse the transition path to the intertemporal equilibrium. Our model considers returns, risks and adjustment costs to reflect the dynamics of allocating capital assets across locations over time, as well as the mix of assets across locations in equilibrium. Variational calculus is employed to show that the model confirms standard expectations that where a location’s rates of return on assets increase, or adjustment costs decrease, equilibrium capital allocation and transitional capital flows to that location will increase. Symmetrically, rising (falling) risk increases (decreases) the proportion of the capital asset holdings of a location. The crucial insight is that for the transitional dynamics to intertemporal equilibrium, the optimal relative capital flow response to changes in risk can generate relative portfolio allocations that may initially move in the opposite direction to that implied by the stock equilibrium. Specifically, an increase in risk for the high-risk location may initially result in an increase in the relative capital asset flow to the high-risk location relative to the low-risk location. Empirical research must account for the possibility of non-monotonicity in asset allocation flows to avoid misspecification. Moreover, policy makers will have to anticipate possible pressure for reversal resulting from short-term worsening capital flows. These reflections are mirrored in recent research calls for separating structural and transition effects of institutional change on the investment decisions by multinational corporations.

Research on Policy configuration Scheme based on improved ARIMA Model

In this paper, we use the principle of different models to remove the trend from the stock time series and choose the SARIMA [1, 1, 1][0,1,0] 12 models to fit the stock price. The results show a good prediction performance. Then a ternary transaction strategy is proposed, accurately identifying value changes regarding cash as financial products (expected rate of return = 0%, cost = 0%), and establishes a ternary asset flow model. Combining the expected rate of return and volatility, we model the value of existing financial products. Based on the trend accuracy to evaluate the accuracy of stock price prediction, the SARIMA model shows high accuracy in the verification set, and the maximum root mean square error (RMSE) is 11. 5494. The final five-year return is 51973 times higher than the bank savings and fixed investment return.

Intangible assets as an object of accounting expertise

Subject. This article examines the theoretical and methodological problems of conducting accounting expertise of illegal actions in relation to intangible assets. Objectives. The article aims to analyze the framework of categories and concepts associated with intellectual property, investigate current methods and practices of committing illegal actions with intangible assets, and determine the sequence of expert accounting work and methods of expert research. Methods. For the study, we used the systems and logical approaches, and the general scientific cognition methods. Results. Based on the results of the categorical analysis, the article presents proposals for the elimination of contradictions in regulatory documents and the formation of a single definition and list of types of intellectual property (intangible assets) in them, which most fully reflects the actual state of affairs in this area, as well as proposals on the most important areas of concern of expert accounting research of accounting and intangible asset flow. Conclusions and Relevance. The presented proposals for the elimination of contradictions in regulatory documents and the formation of a single definition and list of types of intellectual property (intangible assets) will most fully reflect the actual state of affairs in this area and reduce risks during control, audit and expert activities. The results of the study can be used in the activities of forensic units of law enforcement agencies, control and audit offices and audit organizations in the examination, control and audit of illegal actions related to intellectual property objects.