In this paper we present a rather general phenomenological theory of tick-by-tick dynamics in financial markets. Many well-known aspects, such as the Levy scaling form, follow as particular cases of the theory. The theory fully takes into account the non-Markovian and non-local character of financial time series. Predictions on the long-time behaviour of the waiting-time probability density are presented. Finally, a general scaling form is given, based on the solution of the fractional diffusion equation.
What role does the business environment play in promoting or restraining firm growth? Recent literature points to a number of factors as obstacles to growth. Inefficient functioning of financial markets, inadequate security and enforcement of property rights, poor provision of infrastructure, inefficient regulation and taxation, and broader governance features such as corruption and macroeconomic stability are all discussed without any comparative evidence on their ordering. Using firm-level survey data on the relative importance of different features of the business environment, the article finds that although firms report many obstacles to growth, not all the obstacles are equally constraining. Some affect firm growth only indirectly through their influence on other obstacles, or not at all. Analyses using directed acyclic graph methodology and regressions find that only obstacles related to finance, crime, and policy instability directly affect firm growth. The finance result is shown to be the most robust. The results have important implications for the priority of reforms. Maintaining policy stability, keeping crime under control, and undertaking financial sector reforms to relax financing constraints are likely to be the most effective routes to promote firm growth.
In traditional banking, repeated deposit-and-lend cycles let a single dollar of reserves support multiple dollars of claims. Decentralized finance produces an analogous structure with tokens. Constructing a Token Graph of 10,200 tokens across 200 blockchains, this paper maps the resulting hierarchy and shows that, by late 2025, each dollar of base assets supports $4.7 of total claims. An embedded yield correction disentangles two channels that raw data conflates: a compositional channel, where lending protocols concentrate in deeper tiers and mechanically raise average yields; and a liquidity channel, where each derivation step reduces secondary-market depth and depresses yields in liquidity-sensitive pools. The liquidity channel concentrates in DEX pools and vanishes in lending pools. A yield decomposition shows that the tier gradient operates entirely through fundamental protocol yields, not incentive-token emissions; quantile regressions reveal that the structural associations concentrate in the upper tail of the yield distribution, with near-zero effects at the median. These findings reframe DeFi's "double counting" as a structural risk question and identify liquidity fragmentation as the primary mechanism associated with yield variation across the token hierarchy.
This study examines active liquidity management by Indian open-ended equity mutual funds. We find that fund managers respond to inflows by increasing cash holdings, which are later used to purchase less-liquid stocks at favourable valuations. Funds with less liquid portfolios tend to maintain larger cash reserves to manage flows. Funds that make active liquidity choices yield statistically and economically significant gross and net returns. The performance differences between funds with varying activeness in altering liquidity highlight the importance of active liquidity management in markets with substantial cross-sectional liquidity differences such as India.
Recent LLMs have demonstrated promising ability in solving finance related problems. However, applying LLMs in real-world finance application remains challenging due to its high risk and high stakes property. This paper introduces FinTrust, a comprehensive benchmark specifically designed for evaluating the trustworthiness of LLMs in finance applications. Our benchmark focuses on a wide range of alignment issues based on practical context and features fine-grained tasks for each dimension of trustworthiness evaluation. We assess eleven LLMs on FinTrust and find that proprietary models like o4-mini outperforms in most tasks such as safety while open-source models like DeepSeek-V3 have advantage in specific areas like industry-level fairness. For challenging task like fiduciary alignment and disclosure, all LLMs fall short, showing a significant gap in legal awareness. We believe that FinTrust can be a valuable benchmark for LLMs' trustworthiness evaluation in finance domain.
The current surge in supply chain finance has significantly alleviated the "capital challenges" faced by domestic related enterprises, enabling enterprises upstream and subsequent stages of the industrial chain to achieve effective circulation of financing services in the supply chain based on the credit of core enterprises. By gathering essential information from the heart of the supply chain, supply chain financing enables efficient resource distribution and aids all stakeholders in making well-informed choices. However, supply chain finance in China still faces numerous obstacles, such as information asymmetry and inefficient credit transmission chains, hindering its long-term development. This paper designs an operational framework for supply chain finance incorporating blockchain technology, clearly defines the participating entities, and analyzes their business relationships. Based upon evolutionary game theory, a supply chain finance financing game model incorporating blockchain technology is constructed. A comparative analysis of the model's equilibrium points and their stability is conducted. The choices of evolutionary equilibrium strategies adopted by small and medium-sized enterprises, key players, and financing entities within this framework are explored, and the influence of blockchain technology on the prerequisites for completing supply chain finance transactions is investigated.
Thomas Henning, Siddhartha M. Ojha, Ross Spoon
et al.
This paper explores how Large Language Models (LLMs) behave in a classic experimental finance paradigm widely known for eliciting bubbles and crashes in human participants. We adapt an established trading design, where traders buy and sell a risky asset with a known fundamental value, and introduce several LLM-based agents, both in single-model markets (all traders are instances of the same LLM) and in mixed-model "battle royale" settings (multiple LLMs competing in the same market). Our findings reveal that LLMs generally exhibit a "textbook-rational" approach, pricing the asset near its fundamental value, and show only a muted tendency toward bubble formation. Further analyses indicate that LLM-based agents display less trading strategy variance in contrast to humans. Taken together, these results highlight the risk of relying on LLM-only data to replicate human-driven market phenomena, as key behavioral features, such as large emergent bubbles, were not robustly reproduced. While LLMs clearly possess the capacity for strategic decision-making, their relative consistency and rationality suggest that they do not accurately mimic human market dynamics.
The emergence of a new type of society in the wake of the information and digital revolution – Society 5.0. – is accompanied by social polarization, contributing to the occurrence and spread of technocratic metaphors with their humanitarian interpretation, generally complicating the formation of new realities and hindering their perception. This began to manifest itself during a period of rapid transformations in monetary circulation, when the cryptocurrency turned into a full-fledged innovative narrative, prompting the authorities to take retaliatory measures to curb the backstage sector of alternative finance. At the same time, there is no holistic, definite and understandable vision of the vector of digital transformation of the payment and settlement space, there is no concretization of the concept, theoretical approaches are not detailed, there is no prototype of the tested solution, no White Paper has been published, a high level of secrecy of piloting results is recorded, etc. Under these conditions, phrases applied to the sphere of money circulation and containing the word «digital» in their formulations most often look like a technocratic metaphor to attract public attention. However, the formal enumeration of breakthrough technologies and the local selective nature of their use as a criterion for digital transformation do not reveal either the essence of the technologies themselves or the «breakthroughs» into society 5.0. The historical perspective of the causal relationship between the cryptocurrency industry and the digital currencies of central banks, as well as an interactive approach to improving the settlement and payment space, taking into account the change in customer-oriented concepts to human-centricity, allow us to identify existing technocratic metaphors regarding the legislative interpretation of the digital ruble and establish the dichotomy of the virtual settlement and payment space (separation into digital and electronic).
This study investigates the impact of learning organization principles on the performance and quality of business operations within organizations in Bosnia and Herzegovina. The research aims to identify key principles of learning organizations that significantly influence perceived business performance and quality of organizational operations, and to evaluate the extent to which organizations in Bosnia and Herzegovina can be considered learning organizations. A quantitative research approach was employed, utilizing a survey method to collect data from 154 employees who are representatives of Bosnian and Herzegovinian companies across various industries. The survey, distributed via Google Forms, measured six dimensions of learning organizations—systems thinking, shared vision, team learning and collaboration, leadership and employee empowerment, organizational culture, and learning environment—alongside four dimensions of business performance and quality—financial performance, internal processes, customer service, and learning, growth, and innovation. Descriptive statistics and regression analysis were used to analyze the data. The results revealed that shared vision, leadership and empowerment, organizational culture, and learning environment significantly and positively influence business performance and quality. However, systems thinking and team collaboration did not show statistically significant effects. The findings suggest that fostering a shared vision, empowering leadership, a supportive organizational culture, and a conducive learning environment are critical for enhancing organizational performance and quality. These insights provide valuable implications for organizations aiming to adopt learning organization principles to improve their business outcomes.
Economic theory. Demography, Business records management