Narrow Results

The emergence of decentralized finance (DeFi) allows arbitrageurs to obtain risk-free income from price gaps of cryptocurrency tokens in many global markets. Several automated arbitrage techniques have been invented to profit from single or multiple platforms, including Centralized and Decentralized Exchange (CEX and DEX), triangular, and DEX-Fait. This paper proposes the arbitrage strategy of cross-cryptocurrency exchanges (ASCEX), a novel automated arbitrage strategy for CEX-DEX platforms, to maximize profit and loss (PNL) using a token route searching algorithm. Based on feature comparison, ASCEX outperforms the existing trading strategies available. Our actual trade experiment shows that ASCEX can generate up to 0.95% monthly risk-free profit compared to 0.34% trading on DEX alone.

In the beginning (the early 1960s), the long-term goal of automated reasoning (although the field at the time was not known by that name) was the design and implementation of a program whose use would lead to "real" and significant contributions to mathematics by offering sufficient power for the discovery of proofs. The realization of that goal appeared to be at least six decades in the future. However, with amazement and satisfaction, we can report that fewer than four decades were required. In this article, we present evidence for this claim, thanks to W. McCune's program OTTER. Our focus is on various landmarks, or milestones, of two types. One type concerns the formulation of new strategies and methodologies whose use greatly enhances the power of a reasoning program. A second type focuses on actual contributions to mathematics and (although not initially envisioned) to logic. We give examples of each type of milestone, and, perhaps of equal importance, demonstrate that advances are far more likely to occur if the two classes are closely intertwined. We draw heavily on material presented in great detail in the new book Automated Reasoning and the Discovery of Missing and Elegant Proofs, published by Rinton Press.

This study explores the use of rough-set methods for marketing decision support systems in the retail business. A tutorial presentation of Rough Set Data Analysis (RSDA) in the context of knowledge discovery from time series databases is given. We show how an RSDA model can be used to develop a marketing decision support system which can capture the complex relationships between marketing factors, such as advertising and promotion, and the total impact on sales levels in order to find influential advertising strategies. This information is used by the business manager to make faster and better strategy decisions for the business to survive in the rapidly changing and competitive environments. The data set used for RSDA application example contains weekly investments in different media categories: TV, radio, cinema, morning press, evening press, popular press, special interest press, and outdoor posters; for seven makes of cars in the Swedish market.

Over the last few decades, Corporate Social Responsibility (CSR) disclosures become a powerful driver of overall stakeholders’ development while the relationship between CSR and its performance has provided conflicting results due to the most used intersecting circle representation of assessment of CSR. This study fills an important gap by analyzing the framework of CSR assessment practices on identification of five criteria and 17 indicators encompassing the strategies of accountability, transparency and compliance of CSR. To achieve the goal of CSR, the strategies have been defined in connection with different literatures and quaternary survey for criteria selection, where the criteria are expressed in a fuzzy horizon. This multi-criteria decision-making (MCDM) model has been solved using a fuzzy analytical networking process and balanced scorecard (BSC) method to develop selection strategy and criteria for implementation of CSR. The paper’s outcomes help administrators of corporate sectors, particularly in developing countries, to follow sustainable actions as CSR providers effectively and to gain a significant reasonable advantage. The findings exposed the CSR assessment structure and interrelationships among BSC perspectives/criteria and indicators on which managers are needed to emphasize to get optimum CSR performance. In this study, the most important strategy and criteria to perform optimum CSR level are as follows: “accountability of CSR project” is the best strategy; “Project team work, incentives, Environmental resources, Communication for motivation, Reporting initiative of stockholders, CSR project with stockholder capital, Strategic governance, Mission sustainability, political role, Human resources”, respectively, are criteria.