Deep learning models in quantitative finance often operate as black boxes, lacking interpretability and failing to incorporate fundamental economic principles such as no-arbitrage constraints. This paper introduces ARTEMIS (Arbitrage-free Representation Through Economic Models and Interpretable Symbolics), a novel neuro-symbolic framework combining a continuous-time Laplace Neural Operator encoder, a neural stochastic differential equation regularised by physics-informed losses, and a differentiable symbolic bottleneck that distils interpretable trading rules. The model enforces economic plausibility via two novel regularisation terms: a Feynman-Kac PDE residual penalising local no-arbitrage violations, and a market price of risk penalty bounding the instantaneous Sharpe ratio. We evaluate ARTEMIS against six strong baselines on four datasets: Jane Street, Optiver, Time-IMM, and DSLOB (a synthetic crash regime). Results demonstrate ARTEMIS achieves state-of-the-art directional accuracy, outperforming all baselines on DSLOB (64.96%) and Time-IMM (96.0%). A comprehensive ablation study confirms each component's contribution: removing the PDE loss reduces directional accuracy from 64.89% to 50.32%. Underperformance on Optiver is attributed to its long sequence length and volatility-focused target. By providing interpretable, economically grounded predictions, ARTEMIS bridges the gap between deep learning's power and the transparency demanded in quantitative finance.
We develop evaluation methods for measuring the economic decision-making capabilities and tendencies of LLMs. First, we develop benchmarks derived from key problems in economics -- procurement, scheduling, and pricing -- that test an LLM's ability to learn from the environment in context. Second, we develop the framework of litmus tests, evaluations that quantify an LLM's choice behavior on a stylized decision-making task with multiple conflicting objectives. Each litmus test outputs a litmus score, which quantifies an LLM's tradeoff response, a reliability score, which measures the coherence of an LLM's choice behavior, and a competency score, which measures an LLM's capability at the same task when the conflicting objectives are replaced by a single, well-specified objective. Evaluating a broad array of frontier LLMs, we (1) investigate changes in LLM capabilities and tendencies over time, (2) derive economically meaningful insights from the LLMs' choice behavior and chain-of-thought, (3) validate our litmus test framework by testing self-consistency, robustness, and generalizability. Overall, this work provides a foundation for evaluating LLM agents as they are further integrated into economic decision-making.
This study investigates the impact of Foreign Direct Investment (FDI) on economic growth in South Asian countries, utilizing annual panel data from five SAARC member states (Bangladesh, India, Nepal, Pakistan, and Sri Lanka) over the period 1980-2017. Data sourced from the World Development Indicators and Penn World Table were analyzed using static panel models, including Ordinary Least Squares, Fixed Effects, Random Effects, and Generalized Least Squares regressions. The empirical findings reveal that FDI exhibits a consistently positive but statistically insignificant correlation with economic growth across all model specifications. In contrast, domestic investment and human capital development emerge as significant and robust positive determinants of growth. Control variables such as government consumption and inflation show expected negative, though generally insignificant, associations with growth. The results imply that for the sampled South Asian economies, enhancing domestic investment and fostering human capital are more critical for driving economic expansion than relying on FDI inflows. Consequently, policymakers should prioritize strategies that strengthen local investment climates and improve educational and skill-building institutions to boost productivity. While FDI's role remains complementary, its insignificant immediate impact suggests the need for further research into the conditional factors such as institutional quality, financial market development, and trade policies that might mediate its effectiveness in fostering long-term growth within the region.
We develop a Schumpeterian quality-ladder spatial model in which innovation arrivals depend on regional knowledge spillovers. A parsimonious reduced-form diffusion mechanism induces the convergence of regions' average distance to the global frontier quality. As a result, regional differences in knowledge levels stem residually from asymmetries in the spatial distribution of researchers and firms. We analytically characterize the processes of innovation and knowledge diffusion. We then explore how the weight of intra-relative to inter-regional knowledge spillovers interacts with freer trade to shape the spatial distribution of economic activities. If intra-regional spillovers are relatively stronger, a higher economic integration leads to progressive agglomeration. If inter-regional spillovers dominate, researchers and firms may re-disperse after an initial phase of agglomeration as integration increases. This happens because firms and researchers have incentives to relocate to the smaller region, where they can leverage the concentrated knowledge base of the larger region while avoiding congestion in innovation. The smoothness of the dispersion process depends on the particular weight of intra-regional spillovers. If inter-regional spillovers become stronger as trade becomes freer, then the latter induces a monotone dispersion process. When integration is high enough, stable long-run equilibria always maximize the growth rate of the global frontier quality and the average distance to the frontier, irrespective of whether spillovers are mainly local or global.
Abstract The church court was responsible for administering spiritual justice in England. It adjudicated a range of disputes including where people sat in church, defamation allegations, and disagreements over probate, and it pursued its own suits in the regulation of sex, marriage, and the clergy. This chapter begins by outlining patterns of litigation over time and place in the five diocesan courts of Bath and Wells, Exeter, Gloucester, Hereford, and Winchester. It sets out the participation of litigants and witnesses according to gender, age, marital and occupational status, and geography. It shows that legal agency in these courts was not equally available to all. It was contingent on patriarchal norms and constrained by age- and status-related ideas around authority. The second part of the chapter sets female servants within this picture by focusing on their interactions with the court. It demonstrates how issues of consent, obedience, and obligation that underpinned servants’ position further complicate their place within this legal institution. Despite social and legal barriers that made their participation household-centred, female servants could and did come to court to pursue legal justice and their testimonies speak to more than just their positions as household servants.
Nikolay Khabarov, Alexey Smirnov, Michael Obersteiner
Shadow prices are well understood and are widely used in economic applications. However, there are limits to where shadow prices can be applied assuming their natural interpretation and the fact that they reflect the first order optimality conditions (FOC). In this paper, we present a simple ad-hoc example demonstrating that marginal cost associated with exercising an optimal control may exceed the respective cost estimated from a ratio of shadow prices. Moreover, such cost estimation through shadow prices is arbitrary and depends on a particular (mathematically equivalent) formulation of the optimization problem. These facts render a ratio of shadow prices irrelevant to estimation of optimal marginal cost. The provided illustrative optimization problem links to a similar approach of calculating social cost of carbon (SCC) in the widely used dynamic integrated model of climate and the economy (DICE).
Contact tracing and quarantine programs have been one of the leading Non-Pharmaceutical Interventions against COVID-19. Some governments have relied on mandatory programs, whereas others embrace a voluntary approach. However, there is limited evidence on the relative effectiveness of these different approaches. In an interactive online experiment conducted on 731 subjects representative of the adult US population in terms of sex and region of residence, we find there is a clear ranking. A fully mandatory program is better than an optional one, and an optional system is better than no intervention at all. The ranking is driven by reductions in infections, while economic activity stays unchanged. We also find that political conservatives have higher infections and levels of economic activity, and they are less likely to participate in the contact tracing program.
Habeel Alam, Muhammad Ashraful Alam, Nauman Zafar Butt
Agrivoltaics (AV) is a dual land-use approach to collocate solar energy generation with agriculture for preserving the terrestrial ecosystem and enabling food-energy-water synergies. Here, we present a systematic approach to model the economic performance of AV relative to standalone ground-mounted PV (GMPV) and explore how the module design configuration can affect the dual food-energy economic performance. A remarkably simple criterion for economic feasibility is quantified that relates the land preservation cost to dual food-energy profit. We explore case studies including both high and low value crops under fixed tilt bifacial modules oriented either along the conventional North/South (N/S) facings or vertical East/West (E/W) facings. For each module configuration, the array density is varied to explore an economically feasible design space relative to GMPV for a range of module to land cost ratio (M_L) - a location-specific indicator relating the module technology (hardware and installation) costs to the soft (land acquisition, tax, overheads, etc.) costs. To offset a typically higher AV module cost needed to preserve the cropland, both E/W and N/S orientated modules favor high value crops, reduced (<60%) module density, and higher M_L (>25). In contrast, higher module density and an increased feed-in-tariff (FIT) relative to GMPV are desirable at lower M_L. The economic trends vary sharply for M_L< 10 but tend to saturate for M_L> 20. For low value crops, ~15% additional FIT can enable economic equivalence to GMPV at standard module density. The proposed modeling framework can provide a valuable tool for AV stakeholders to assess, predict, and optimize the techno-economic design for AV
The subject of the study is the role and place of cooperative publishing houses in the formation of the domestic consumer market of book products and scientific assessment of organizational, publishing and trade activities of publishing cooperatives in the context of the new economic policy (NEP). The purpose of the scientific article is to study the role and place of cooperative publishing houses in the formation of the domestic consumer market of book products and, through the prism of studying the problems of economic history, to give a scientific assessment of organizational, publishing and trade activities of the NEP. Methods of research. All components of the study are based on fundamental principles – scientific, historicism, objectivity, system, development, priority of concrete verity, pluralism; and also the methods of knowledge of social and economic processes of social development – analysis, synthesis, problem-chronological, comparative analytical, archaeological, retrospective, statistical, a systematic and integrated approach. Research methodology. In the process of the study, the fundamental principles were based on Economic History and History of Economic Thought, the Ukrainian and foreign scientists’ works and experts in this area. Results of work. In the context of this issue, we explored the role and place of cooperative publishing houses in the formation of the domestic consumer market of book products and, through the prism of studying the problems of economic history, gave a scientific assessment of organizational, publishing and trade activities of the NEP. The field of application of results. The results of this research can be applied to study the issues of Economic History and History of Economic Thought, History of the Publishing Industry. Conclusions. Thus, cooperative publishing houses were business-type societies, organizationally and functionally belonged to cooperative societies, and on the other hand - were public associations with editorial, production, economic and socio-cultural functions. Examining the activities of cooperative publishing houses, it can be stated that they occupied an important place in the distribution and printing of various literature: socio-economic, socio-political, agricultural, artistic, children's books, textbooks, natural, military. Consumers of book products of cooperative publishing houses were the most various social and professional groups of the population: workers, peasants, employees, women, youth, military, children. By distributing literature in a country where almost two-thirds of the population was illiterate, publishing houses contributed to the full operation of educational institutions, raising the intellectual and spiritual level of society, creating conditions for the development of science, art, culture and education. There was a completely organic connection between publishers' cooperatives, cultural, educational, and scientific institutions, and a kind of intellectual and spiritual dependence developed due to the high demand for books, as publishers published literature from all fields of knowledge. The activities of cooperative publishing houses of the NEP period, especially the formation of the organizational structure and the implementation of advertising and propaganda work should be taken into account when developing the legal framework of the national program of book publishing in Ukraine.
Anton V. Vykhodtsev, Darren Jang, Qianpu Wang
et al.
The penetration of the lithium-ion battery energy storage system (BESS) into the power system environment occurs at a colossal rate worldwide. This is mainly because it is considered as one of the major tools to decarbonize, digitalize, and democratize the electricity grid. The economic viability and technical reliability of projects with batteries require appropriate assessment because of high capital expenditures, deterioration in charging/discharging performance and uncertainty with regulatory policies. Most of the power system economic studies employ a simple power-energy representation coupled with an empirical description of degradation to model the lithium-ion battery. This approach to modelling may result in violations of the safe operation and misleading estimates of the economic benefits. Recently, the number of publications on techno-economic analysis of BESS with more details on the lithium-ion battery performance has increased. The aim of this review paper is to explore these publications focused on the grid-scale BESS applications and to discuss the impacts of using more sophisticated modelling approaches. First, an overview of the three most popular battery models is given, followed by a review of the applications of such models. The possible directions of future research of employing detailed battery models in power systems' techno-economic studies are then explored.
Our study is one of the first examples of multidimensional and longitudinal disciplinary analysis at the national level based on Crossref data. We present a large-scale quantitative analysis of Ukrainian economics. This study is not yet another example of research aimed at ranking of local journals, authors or institutions, but rather exploring general tendencies that can be compared to other countries or regions. We study different aspects of Ukrainian economics output. In particular, the collaborative nature, geographic landscape and some peculiarities of citation statistics are investigated. We have found that Ukrainian economics is characterized by a comparably small share of co-authored publications, however, it demonstrates the tendency towards more collaborative output. Based on our analysis, we discuss specific and universal features of Ukrainian economic research. The importance of supporting various initiatives aimed at enriching open scholarly metadata is considered. A comprehensive and high-quality meta description of publications is probably the shortest path to a better understanding of national trends, especially for non-English speaking countries. The results of our analysis can be used to better understand Ukrainian economic research and support research policy decisions.
Mohammadreza Rostam, Ryozo Nagamune, Vladimir Grebenyuk
This paper proposes a hybrid Gaussian process (GP) approach to robust economic model predictive control under unknown future disturbances in order to reduce the conservatism of the controller. The proposed hybrid GP is a combination of two well-known methods, namely, kernel composition and nonlinear auto-regressive. A switching mechanism is employed to select one of these methods for disturbance prediction after analyzing the prediction outcomes. The hybrid GP is intended to detect not only patterns but also unexpected behaviors in the unknown disturbances by using past disturbance measurements. \textcolor{black}{A novel forgetting factor concept is also utilized in the hybrid GP, giving less weight to older measurements, in order to increase prediction accuracy based on recent disturbances values.} The detected disturbance information is used to reduce prediction uncertainty in economic model predictive controllers systematically. The simulation results show that the proposed method can improve the overall performance of an economic model predictive controller compared to other GP-based methods in cases when disturbances have discernible patterns.
We establish sharp asymptotically optimal strategies for the problem of online prediction with history dependent experts. The prediction problem is played (in part) over a discrete graph called the $d$ dimensional de Bruijn graph, where $d$ is the number of days of history used by the experts. Previous work [11] established $O(\varepsilon)$ optimal strategies for $n=2$ experts and $d\leq 4$ days of history, while [10] established $O(\varepsilon^{1/3})$ optimal strategies for all $n\geq 2$ and all $d\geq 1$, where the game is played for $N$ steps and $\varepsilon=N^{-1/2}$. In this paper, we show that the optimality conditions over the de Bruijn graph correspond to a graph Poisson equation, and we establish $O(\varepsilon)$ optimal strategies for all values of $n$ and $d$.
Fernando E. Cornes, Guillermo A. Frank, Claudio O. Dorso
The investigation focuses on an on-off protocol for controlling the COVID-19 widespread. The protocol establishes a working period of 4 days for all the citizens, followed by 8 days of lock-down. We further propose splitting people into smaller groups that undergo the on-off protocol, but shifted in time. This procedure is expected to regularize the overall economic activity. Our results show that either the on-of protocol and the splitting into groups reduces the amount of infected people. However, the latter seems to be better for economic reasons. Our simulations further show that the start-up time is a key issue for the success of the implementation.
In this paper the dynamics of an economic system with foreign financing, of integer or fractional order, are analyzed. The symmetry of the system determines the existence of two pairs of coexisting attractors. The integer-order version of the system proves to have several combinations of coexisting hidden attractors with self-excited attractors. Because one of the system variables represents the foreign capital in ow, the presence of hidden attractors could be of a real interest in economic models. The fractional-order variant presents another interesting coexistence of attractors in the fractional order space.
We analyse 'stop-and-go' containment policies that produce infection cycles as periods of tight lockdowns are followed by periods of falling infection rates. The subsequent relaxation of containment measures allows cases to increase again until another lockdown is imposed and the cycle repeats. The policies followed by several European countries during the Covid-19 pandemic seem to fit this pattern. We show that 'stop-and-go' should lead to lower medical costs than keeping infections at the midpoint between the highs and lows produced by 'stop-and-go'. Increasing the upper and reducing the lower limits of a stop-and-go policy by the same amount would lower the average medical load. But increasing the upper and lowering the lower limit while keeping the geometric average constant would have the opposite effect. We also show that with economic costs proportional to containment, any path that brings infections back to the original level (technically a closed cycle) has the same overall economic cost.