Artículos de revistas sobre el tema "Trading automatisé"
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Oetama, Raymond Sunardi y Raymond Sunardi Oetama. "DEVELOPING SALES FORCE AUTOMATION PROTOTYPE AT INDONESIAN FURNITURE TRADING COMPANY". IJISCS (International Journal of Information System and Computer Science) 7, n.º 3 (10 de octubre de 2023): 182. http://dx.doi.org/10.56327/ijiscs.v7i3.1537.
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Information technology plays a crucial role in enhancing company performance and driving business growth. Maintaining good customer relationships is essential, and Customer Relationship Management focuses on building customer commitment. Sales Force Automation systems automate sales processes and manage customer interactions. PT. Maju Jaya Kreasindo, a furniture company in East Jakarta, aims to automate its sales force and centralize operational information through a web-based Sales Force Automation system using Electronic Customer Relationship Management. The research adopts the "Prototyping" method, offering a shorter development duration and flexible implementation. Visual Studio Code and Xampp, along with PHP and MySQL, are utilized as development tools. The result is a Sales Force Automation system based on Electronic Customer Relationship Management that assists PT. Maju Jaya Kreasindo in automating its sales force. The design successfully automates tasks, supported by Electronic Customer Relationships and the prototyping method. The Sales Force Automation system passed the functionality evaluation, achieving high user acceptance test scores, and indicating its effectiveness in meeting user requirements.
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Al-Sulaiman, Talal. "Review of Recent Research Directions and Practical Implementation of Low-Frequency Algorithmic Trading". American Journal of Financial Technology and Innovation 2, n.º 1 (26 de febrero de 2024): 1–14. http://dx.doi.org/10.54536/ajfti.v2i1.2354.
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Financial trading has undergone substantial technological evolution, with automation taking center stage, leading to approximately 80% of US market trades being executed by computer systems, predominantly by large financial institutions. The rise of algorithmic trading, poised to engage smaller entities, international markets, and individual traders, drives this article’s exploration of research in this field. Providing a comprehensive overview, it outlines the evolution of trading practices and defines algorithmic trading as a computer-powered tool aiding investment decisions. The article details the steps involved in algorithmic trading, covering opportunity identification, quantitative research, implementation, testing phases, and continuous monitoring. It also examines prevalent programming languages and open-source platforms facilitating algorithm development. Focusing on trading frequencies across financial instruments, it delves into high-frequency trading as a subset, alongside methodologies like technical and fundamental analysis, time series analysis, option trading strategies, and machine learning techniques used in algorithm creation. Categorized by trading frequencies, analytical approaches, involved financial instruments, and analysis objectives, the reviewed papers contribute insights into algorithmic trading’s diverse landscape and methodologies, offering valuable perspectives for industry participants and researchers alike.
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Li, Yeti, Catherine Burns y Rui Hu. "Representing Stages and Levels of Automation on a Decision Ladder". Proceedings of the Human Factors and Ergonomics Society Annual Meeting 60, n.º 1 (septiembre de 2016): 328–32. http://dx.doi.org/10.1177/1541931213601074.
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We propose that representing stages and levels of automation on a decision ladder (DL) could help to identify information requirements for designing automation interfaces. We look at automated financial trading systems, a domain with variable degrees of automation (DOA). We give examples of modelling a financial trading task for two DOAs: basket trading (a low DOA) and trend following trading (a high DOA). On the resulting DLs, both human and automated information-processing activities are presented. The steps and states of knowledge allocated to automation are first categorized by the commonly known four stages of automation, and then shaded to represent the level of automation in each stage. This work advances the understanding of automated trading, and automation in general, and may provide a deeper representation of human-automation interactions and thus better understanding of design requirements.
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Maciel, Leandro y Rosangela Ballini. "Efeitos do pregão eletrônico sobre a eficiência e a volatilidade condicional no mercado de ações brasileiro". Brazilian Review of Finance 17, n.º 1 (15 de octubre de 2019): 80. http://dx.doi.org/10.12660/rbfin.v17n1.2019.76684.
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<p>Stock exchange automation, characterized by the replacement of floor trading systems by electronic trading systems, is one of the main restructuring processes observed in global capital markets in recent decades. This paper investigates the effects of automation in the São Paulo Stock Exchange (B3), which adopted an electronic trading system in October 2005. Empirical analysis of the Bovespa index rejects the random walk hypothesis for the periods before and after B3 automation, and provides evidence of distinct volatility regimes. After automation, there is an increase in the linear dependence of IBovespa returns, suggesting a negative effect of automation on the Brazilian stock market’s efficiency. On the other hand, in the same period, there is evidence for a reduction in the long-term persistence of conditional volatility, in response to shocks to returns.</p>
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Tzelgov, Joseph. "Trading automatic/nonautomatic for unconscious/conscious". Behavioral and Brain Sciences 25, n.º 3 (junio de 2002): 356–57. http://dx.doi.org/10.1017/s0140525x02500066.
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In this commentary I show that the SOC framework implies automaticity of both the materialization of phenomenological conscious experience and the application of the primitives resulting from the emergence of consciousness. In addition, SOC implies that cognition refers to conscious experience. Consequently, I propose automatic/nonautomatic instead of unconscious/conscious as the basic contrast characterizing human cognition.
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Kazantsev, Dmitry A. y Natalya A. Mikhaleva. "PROCUREMENT AUTOMATION AS THE FUTURE OF THE CONTRACT SYSTEM". RUDN Journal of Law 24, n.º 1 (15 de diciembre de 2020): 137–57. http://dx.doi.org/10.22363/2313-2337-2020-24-1-137-157.
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In the era of digital information electronic trading platforms have become an integral attribute to conduct procurement to meet public needs. Nowadays there is a consistent trend is that legislators transfer the vast majority of purchases to the electronic plane through the use of electronic trading platforms. This incentive of the legislator is attributed to a number of advantages of the electronic form of procurement procedures, which allow to increase their transparency and accessibility to an indefinite number of people. However, the role of electronic trading platforms must not be reduced solely to an electronic platform, which allows only to transfer the procurement procedure in a different form. On the contrary, the potential of electronic trading platforms can significantly simplify and automate business activities of customers, increase the efficiency of procurement not only by expanding competition but also by reducing the organizational burden on the parties of the procurement process, both customers and the participants. The purpose of the article is to present for review ways to improve the operation of electronic trading floors to automate the procurement process during competitive procedures for state and municipal needs. Research methods: formal legal, modeling, analysis and synthesis, induction and deduction. The results of the study. The article presents for review ways to optimize the operation of electronic trading platforms by attracting software and hardware when conducting competitive procedures. Ways of automation the procurement process are described, including integration of the functionality of electronic trading platforms with official registries in order to minimize the risk of a possible rejection of a participant’s procurement application when considering the second parts of applications. Other innovative services of the functionality of electronic trading platforms (auto-completion of forms, data inheritance, automated collection of proposals) have been suggested, the implementation of which will simplify and automate the process of conducting competitive procedures, reduce the administrative burden on the customer, ensure transparency and a competitive basis when holding tenders.
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Tkachenko, Olexandr, Mykyta Kutsenko y Hlib Fleshner. "RODOFEBISU – Trading Support System". Digital Platform: Information Technologies in Sociocultural Sphere 5, n.º 2 (27 de diciembre de 2022): 387–400. http://dx.doi.org/10.31866/2617-796x.5.2.2022.270145.
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The purpose of the article is to study, analyze and consider the general problems and prospects of developing software for trading RodOfEbisu with the possibility of automated trading based on a recommendation algorithm.
The research methods are the basic methodologies and algorithms for successful trading. The article considers approaches to the development and operation of software for automated trading.
The novelty of the research is the analysis of modern trading methods in different markets, the results of which can be used in the development of its own trading automation product, which is an assistant and, possibly, can become an independent unit.
Conclusions. The paper investigates the existing views on the modern approach to decision-making and buying, which can be used to develop its own product – a trader’s assistant. Taking into account the results of the analysis, it was decided to develop software for trading RodOfEbisu, which can act as an advisor and executor, with the possibility of using different trading strategies.
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INAGAKI, Toshiyuki. "Adaptive Automation: Sharing and Trading of Control". Proceedings of the Transportation and Logistics Conference 2001.10 (2001): 79–84. http://dx.doi.org/10.1299/jsmetld.2001.10.79.
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Kim, Jin-Gyeom y Bowon Lee. "Automatic P2P Energy Trading Model Based on Reinforcement Learning Using Long Short-Term Delayed Reward". Energies 13, n.º 20 (14 de octubre de 2020): 5359. http://dx.doi.org/10.3390/en13205359.
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Automatic peer-to-peer energy trading can be defined as a Markov decision process and designed using deep reinforcement learning. We consider prosumer as an entity that consumes and produces electric energy with an energy storage system, and define the prosumer’s objective as maximizing the profit through participation in peer-to-peer energy trading, similar to that of the agents in stock trading. In this paper, we propose an automatic peer-to-peer energy trading model by adopting a deep Q-network-based automatic trading algorithm originally designed for stock trading. Unlike in stock trading, the assets held by a prosumer may change owing to factors such as the consumption and generation of energy by the prosumer in addition to the changes from trading activities. Therefore, we propose a new trading evaluation criterion that considers these factors by defining profit as the sum of the gains from four components: electricity bill, trading, electric energy stored in the energy storage system, and virtual loss. For the proposed automatic peer-to-peer energy trading algorithm, we adopt a long-term delayed reward method that evaluates the delayed reward that occurs once per month by generating the termination point of an episode at each month and propose a long short-term delayed reward method that compensates for the issue with the long-term delayed reward method having only a single evaluation per month. This long short-term delayed reward method enables effective learning of the monthly long-term trading patterns and the short-term trading patterns at the same time, leading to a better trading strategy. The experimental results showed that the long short-term delayed reward method-based energy trading model achieves higher profits every month both in the progressive and fixed rate systems throughout the year and that prosumer participating in the trading not only earns profits every month but also reduces loss from over-generation of electric energy in the case of South Korea. Further experiments with various progressive rate systems of Japan, Taiwan, and the United States as well as in different prosumer environments indicate the general applicability of the proposed method.
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Plotnikov, Arkadiy P., Victor P. Glazkov y Roman A. Shishlov. "Modification of long-term volatility trading methods based on a delta-neutral strategy". Vestnik of Samara University. Economics and Management 12, n.º 3 (25 de noviembre de 2021): 70–79. http://dx.doi.org/10.18287/2542-0461-2021-12-3-70-79.
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Delta-neutral trading strategies for trading volatility allow you to make a profit regardless of the direction of change in the price of the underlying asset. Despite their popularity and high efficiency, they are usually made manually, which makes them less systematic and vulnerable to the negative influence of the human factor (emotions, late actions, erroneous submission of applications, etc.). The article proposes a unified delta- neutral strategy, taking into account several parameters for long-term volatility trading through transactions with underlying assets (futures or stocks) and options on these underlying assets, which creates prerequisites for its automation. The use of the strategy helps to increase the liquidity of investment assets traded on the exchange, increases the receipt of taxes, exchange fees and commissions, which brings great socio-economic benefits. Automation of the strategy significantly simplifies calculations, increases the speed of decision-making and can significantly increase the number of transactions made in the financial markets. In addition, the automatic calculation of the optimal values of the method parameters can make a significant contribution to the theoretical research of the modifications of the volatility trading methods.
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Reddy, M. Raghu Ram, P. Deepak, R. Anurag y Asst Prof Mr B. Lokesh. "Novel Automatic Food Trading System Using Blockchain". International Journal for Research in Applied Science and Engineering Technology 11, n.º 6 (30 de junio de 2023): 3598–601. http://dx.doi.org/10.22214/ijraset.2023.54285.
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Abstract: The blockchain functions as a decentralized and collectively maintained ledger that allows anyone to contribute. It provides a secure and readily accessible source of information concerning farms, inventories, and contracts in the agricultural sector, where acquiring such data can sometimes be costly. By tracing the origin of food, blockchain technology supports the establishment of trustworthy food supply chains and fosters trust between producers and consumers. Its reliable data storage capabilities enable the implementation of data-driven solutions to enhance farming practices. Furthermore, when combined with smart contracts, blockchain technology facilitates prompt payments by linking them to recorded data changes within the blockchain.
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Zaripova, Rimma, Alexander Nikitin, Yulia Hadiullina, Elena Pokaninova y Maxim Kuznetsov. "Vendor selection information system on the electronic trading platform for energy supply companies". E3S Web of Conferences 288 (2021): 01072. http://dx.doi.org/10.1051/e3sconf/202128801072.
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The main challenges for industrial companies today are to improve the competitiveness of their products and to adapt and respond quickly to changes in the external environment. Ensuring the effective functioning of an industrial enterprise is largely determined by its procurement activities, including the reliability and consistency of the procurement process. Relevance of the topic is conditioned by the fact that procurement is one of the main components in increasing of competitiveness and efficiency of the enterprise, as the major part of costs in the cost price of the finished products is concentrated exactly in procurement. Reducing costs in procurement is one of the ways to improve the efficiency of the enterprise. This advantage can be achieved through the introduction of modern information technologies, namely automation of the process of selecting suppliers on an electronic trading platform. For this purpose, an information system for selecting suppliers on the electronic trading platform has been developed, which enables a more transparent, fast, profitable and less costly selection of the cheapest and most suitable goods for the operation of energy supplying enterprises. Procurement activities are aimed at ensuring that the energy-supplying undertaking receives the right quantity and quality of raw materials, materials, goods and services at the right time, in the right place, from a reliable and trustworthy supplier with good service and at a favourable price. Automating the supplier selection process on an electronic platform is essential in today's market environment.
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Tungmiharja, Wilson y Elfrida Ratnawati Gultom. "Quo Vadis Kebijakan Pemerintah Terhadap Legalitas Keberadaan Investasi Robot Trading (Expert Advisor) dikaji menggunakan Teori Hukum dan Pembangunan". AL-MANHAJ: Jurnal Hukum dan Pranata Sosial Islam 5, n.º 2 (27 de agosto de 2023): 1411–26. http://dx.doi.org/10.37680/almanhaj.v5i2.3212.
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The purpose of writing this journal is to analyze and understand government policies regarding the legality of trading robots. The development of the times has provided many advances in both the technological and economic fields, technological advances have provided openness to trade in both goods and services. Forex trading is a business activity that offers high profits accompanied by high risks, where individuals must monitor and study the movements of the money market without stopping to make transactions. The existence of trading robots makes it easy to do forex trading due to automation to save time and does not require in-depth understanding of forex trading. The existence of trading robots provides an opportunity for criminal acts to occur in the forex field, one of which is the existence of Illegal Trading Robots which results in losses for users. One of them is the fraudulent investment case of Net 89, which has a trading robot mode, which uses a permit to sell e-books in carrying out trading activities based on trading robots. This problem has resulted in an urgency that can be seen from the enactment of BAPPEBTI Regulation Number 12 of 2022 as a step to regulate the existence of trading robots.
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Liu, Yang, Qi Liu, Hongke Zhao, Zhen Pan y Chuanren Liu. "Adaptive Quantitative Trading: An Imitative Deep Reinforcement Learning Approach". Proceedings of the AAAI Conference on Artificial Intelligence 34, n.º 02 (3 de abril de 2020): 2128–35. http://dx.doi.org/10.1609/aaai.v34i02.5587.
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In recent years, considerable efforts have been devoted to developing AI techniques for finance research and applications. For instance, AI techniques (e.g., machine learning) can help traders in quantitative trading (QT) by automating two tasks: market condition recognition and trading strategies execution. However, existing methods in QT face challenges such as representing noisy high-frequent financial data and finding the balance between exploration and exploitation of the trading agent with AI techniques. To address the challenges, we propose an adaptive trading model, namely iRDPG, to automatically develop QT strategies by an intelligent trading agent. Our model is enhanced by deep reinforcement learning (DRL) and imitation learning techniques. Specifically, considering the noisy financial data, we formulate the QT process as a Partially Observable Markov Decision Process (POMDP). Also, we introduce imitation learning to leverage classical trading strategies useful to balance between exploration and exploitation. For better simulation, we train our trading agent in the real financial market using minute-frequent data. Experimental results demonstrate that our model can extract robust market features and be adaptive in different markets.
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Plotnikov, Arkadiy P., Roman A. Shishlov y Vladimir V. Arsenov. "An algorithm for organizing long volatility trading based on a delta-neutral strategy". Vestnik of Samara University. Economics and Management 13, n.º 3 (22 de noviembre de 2022): 156–73. http://dx.doi.org/10.18287/2542-0461-2022-13-3-156-173.
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The article is devoted to the problem of automation of long volatility trading in the financial market using delta-neutral trading strategies. Most operations on them, as a rule, are performed manually, which makes them less systematic and vulnerable to the negative influence of the human factor (emotions, tardiness of actions, erroneous submission of applications, etc.). To solve this problem, the article proposes a unified algorithm for a delta-neutral strategy, taking into account several parameters for long volatility trading through transactions with futures on underlying assets and options on these futures. For greater clarity, the algorithm is supplemented with a diagram made in BPMN 2.0 notation.
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Șerban, Florentin y Bogdan-Petru Vrînceanu. "A Comparison Between Trend Following (Tidy Little Robot – TLR) and Reversal Trading (Dirty Little Robot – DLR) Algobot Strategies". European Journal of Theoretical and Applied Sciences 1, n.º 5 (1 de septiembre de 2023): 805–22. http://dx.doi.org/10.59324/ejtas.2023.1(5).68.
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Algorithmic trading has become a defining force in modern financial markets, offering traders precision, speed, and automation. This article explores the world of algorithmic trading through the lens of two distinct algobots, Tidy Little Robot (TLR) and Dirty Little Robot (DLR). Developed using Pine Script 5 on the TradingView platform and implemented on the Pionex exchange, these algobots navigate the BTC/USDT perpetual market with a 1-minute timeframe. TLR excels in trend-following scenarios, while DLR specializes in identifying reversals. The study delves into their performance, methodology, implications, interpretations, limitations, and future research prospects, offering valuable insights into the evolving landscape of algorithmic trading.
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Mao, Dianhui, Zhihao Hao, Fan Wang y Haisheng Li. "Novel Automatic Food Trading System Using Consortium Blockchain". Arabian Journal for Science and Engineering 44, n.º 4 (10 de septiembre de 2018): 3439–55. http://dx.doi.org/10.1007/s13369-018-3537-z.
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Yousefi, Neda. "Deep Reinforcement Learning for Tehran Stock Trading". Journal of Novel Engineering Science and Technology 1, n.º 02 (16 de noviembre de 2022): 37–42. http://dx.doi.org/10.56741/jnest.v1i02.171.
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One of the most interesting topics for research, as well as for making a profit, is stock trading. It is known that artificial intelligence has had a great influence on this path. A lot of research has been done to investigate the application of machine learning and deep learning methods in stock trading. Despite the large amount of research done in the field of prediction and automation trading, stock trading as a deep reinforcement-learning problem remains an open research area. The progress of reinforcement learning, as well as the intrinsic properties of reinforcement learning, make it a suitable method for market trading in theory. In this paper, single stock trading models are presented based on the fine-tuned state-of-the-art deep reinforcement learning algorithms (Deep Deterministic Policy Gradient (DDPG) and Advantage Actor Critic (A2C)). These algorithms are able to interact with the trading market and capture the financial market dynamics. The proposed models are compared, evaluated, and verified on historical stock trading data. Annualized return and Sharpe ratio have been used to evaluate the performance of proposed models. The results show that the agent designed based on both algorithms is able to make intelligent decisions on historical data. The DDPG strategy performs better than the A2C and achieves better results in terms of convergence, stability, and evaluation criteria.
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Yousefi, Neda. "Deep Reinforcement Learning for Tehran Stock Trading". Indonesian Journal of Data and Science 3, n.º 3 (31 de diciembre de 2022): 97–106. http://dx.doi.org/10.56705/ijodas.v3i3.53.
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One of the most interesting topics for research and also for making a profit is stock trading. Artificial intelligence has had a great impact on this path. A lot of research has been done to investigate the application of machine learning, and deep learning methods in stock trading. Despite the large amount of research done in the field of prediction and automation trading, stock trading as a deep reinforcement-learning problem remains an open research area. The progress of reinforcement learning as well as the intrinsic properties of reinforcement learning make it a suitable method for market trading in theory. In this paper, single stock trading models are presented based on the fine-tuned state-of-the-art deep reinforcement learning algorithms (Deep Deterministic Policy Gradient (DDPG) and Advantage Actor Critic (A2C)). These algorithms are able to interact with the trading market and capture the financial market dynamics.
The proposed models are compared, evaluated, and verified on historical stock trading data. Annualized return and Sharpe ratio have been used to evaluate the performance of proposed models. The results show that the agent designed based on both algorithms is able to make intelligent decisions on historical data. The DDPG strategy performs better than the A2C and achieves better results in terms of convergence, stability, and evaluation criteria.
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Kolmykova, S. V., R. Yu Cherkashnev y A. V. Belyaev. "Appropriation of Information Systems for Keeping Records of the Implementation Process in Retail Trade". Proceedings of the Southwest State University. Series: Economics. Sociology. Management 13, n.º 4 (8 de noviembre de 2023): 135–47. http://dx.doi.org/10.21869/2223-1552-2023-13-4-135-147.
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Relevance. The modern economy requires a constant increase in the competitiveness of economic entities by reducing uncertainty and minimizing possible risks. As a result, the trading business should be a well-coordinated mechanism aimed at effective management. One of the criteria for effective management is the implementation of competent sales accounting, for the automation of which there are a number of information systems. The purpose of the study is to identify promising aspects of the implementation of information systems aimed at automating the accounting of the sales (sales) process in retail trade. Objectives: a brief overview of information systems as separate specialized programs used to manage sales in retail; development of recommendations for the implementation of software products in non-automated outlets; presentation of the results of automation of business processes through the introduction of information systems. Methodology. In this study, methods of comparative analysis, synthesis, generalization, economic and statistical, as well as graphical methods of information processing were used. Results. The study made it possible to identify promising aspects of the implementation of information systems to automate the accounting of the sales (sales) process in retail trade. The list of relevant information systems of the studied notional area is demonstrated. Recommendations were developed for the implementation of information systems that implement the accounting of retail sales to non-automated outlets. Also, in the course of the work, prospects for the implementation of information ERP systems, in particular, individually configured, taking into account the specifics and features of the company's business processes, were identified. The calculation of the economic efficiency of a pharmacy institution that implements retail trade through the introduction of an information system is presented, as a result of which the importance of automating the accounting of the sales (sales) process is emphasized. Conclusions. Outdated technologies in enterprises significantly complicate the digital transformation of business, despite the variety of ready-made information systems in the subject area under study. The introduction of such systems requires a significant restructuring of organizational changes, business processes, including the adaptation of the accounting system.
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Ermashkevich, Natalia y G. Ron'zhin. "Automation of Business Processes in Small Enterprises and Increasing Their Level of Digitalization Through the Development of Digital Infrastructure Through the «Transformation of the Information Circulation System»". Scientific Research and Development. Economics of the Firm 11, n.º 1 (31 de marzo de 2022): 51–64. http://dx.doi.org/10.12737/2306-627x-2022-11-1-51-64.
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The article is devoted to the study of the possibilities of modern means of automating business processes in small enterprises and increasing their level of digitalization through the development of the digital infrastructure of such companies through reengineering and transformation of the information circulation system. The article shows the possibility of using the developed author's methodology for transforming the information turnover system («TSOI»), which includes a number of algorithms and makes it possible to increase the efficiency of reengineering business processes in small businesses. The authors, within the framework of the article, describe the application of the developed specialized software (software) to automate the process of collecting tender documents from the platforms of electronic trading – «ROSA». The article substantiates the possibility of introducing the developed toolkit into the activities of small enterprises, and also conducts its approbation on the example of reengineering of business processes of a real enterprise. The effectiveness of the proposed toolkit has been proven within the framework of the case under consideration due to the calculations of the economic effects obtained from the implemented tools of the complex of business process automation tools.
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Wahyu Santosa, Perdana. "Determinants of price reversal in high-frequency trading: empirical evidence from Indonesia". Investment Management and Financial Innovations 17, n.º 1 (19 de marzo de 2020): 175–87. http://dx.doi.org/10.21511/imfi.17(1).2020.16.
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This article analyzes whether the factors of the mechanism of high-frequency trading (HFT) or intraday trading affect the process of price reversal and continuation. The price reversal phenomenon is gaining importance rapidly due to the increasingly intensive use of IT/Fintech-based trading automation facilities on the Indonesia Stock Exchange. However, one knows little about how their trading affects volatility and liquidity pressures that cause price reversals. A new research approach uses the factors of market microstructure mechanism based on high-frequency data (HFD-intraday). The research method uses purposive random sampling, which classified price fractions into three groups, specifically low price, medium price, and high price, which are analyzed by logistic panel regression. The research variables used include price reversal (dependent), stock return, trading volume, transaction frequency, volume/frequency (V/F) proxy, volatility, and liquidity. According to low price model research findings, all variables show a significant effect on price reversal; for medium price model, all variables except liquidity show a significant effect on price reversal; and for high price model, all variables have a significant effect on price reversal, except trading volume and volatility. In conclusion, low price shares tend to have higher price reversal probability compared to continuity because they tend to be liquid, low institutional ownership, and minimal reporting/analysis and are controlled by HFTs (uninformed traders). Some variables are not significant because of the bounce effect around the bid-ask spread. AcknowledgmentMany thanks to Armida S. Alisjahbana, Roy H. Sembel, Budiono, Rahardi S. Rahmanto, and the anonymous referee/reviewer for valuable inputs and feedback.
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Hua, Caijian, Sichao Wu, Yan Zhang, Kun Luo, Miaomiao Li y Jiaguo Fu. "A Blockchain-Based Framework for Rural Property Rights Transactions". Electronics 12, n.º 20 (19 de octubre de 2023): 4334. http://dx.doi.org/10.3390/electronics12204334.
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Currently, there are several issues in China’s rural property rights trading, including poor credit reporting, low transaction efficiency, non-standardized transaction contracts, and high costs for rights protection. However, blockchain technology, known for its convenience, security, and traceability, is highly compatible with the requirements of standardization, convenience, and agility in rural property rights trading. Therefore, we propose a system framework for rural property rights trading based on the Hyperledger Fabric consortium blockchain. This framework significantly enhances transaction efficiency, improves the security of rural property rights trading, effectively resolves contract disputes in property rights transactions, and promotes rural revitalization and development. Furthermore, we design the information data structure on the blockchain, present the information flow, and develop smart contracts that utilize automation capabilities to automatically summarize, analyze, and issue alerts based on on-chain data, enabling risk assessment for both buyers and sellers. Additionally, we introduce an improved PBFT consensus algorithm called CA-PBFT, which is based on the PBFT consensus protocol and integrates a scoring model and simplified consensus protocol. CA-PBFT efficiently reduces transaction response latency and improves information throughput. Finally, we develop a prototype system for rural property rights trading and perform a performance comparison and analysis of CA-PBFT against other PBFT-based consensus algorithms in this prototype system. Experimental results demonstrate the feasibility of the prototype system framework for rural property rights trading.
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Zhalezka, B., A. Stadnik y V. Siniauskaya. "TECHNICAL ANALYSIS AND INDICATORS APPLICATION IN ALGORITHMIC MARKETING". Экономическая наука сегодня, n.º 15 (19 de mayo de 2022): 119–30. http://dx.doi.org/10.21122/2309-6667-2022-15-119-130.
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This paper is devoted to the investigation of the stock exchange decision making process by means of technical analysis on the base of indicators. Methods of the basic technical indicators calculation are considered. Trading strategy of the stock exchange decision making based on the new complex specific technical indicator is suggested, which is accounting values of the following basic technical indicators: moving average convergence divergence, parabolic stop and reverse, average directional moving index rating, momentum volume weighted average price. An example of trading strategy automation is considered. Its back testing is realized, which confirms correctness of its application in the stock exchange decision making.
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Journal, IJSREM. "Machine Learning-Based Momentum Strategy for High Frequency Trading and Buy/Sell Calls Using Algorithmic Trading". INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 07, n.º 10 (1 de octubre de 2023): 1–11. http://dx.doi.org/10.55041/ijsrem26553.
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Stock Market Prediction is beneficial to investors. It provides shareholders with useful assistance in making suitable decisions about whether to purchase or sell shares. Accurate stock price prediction is extremely challenging because of multiple factors. Stock prices are influenced by a variety of factors, but the price at any given time is determined by supply and demand in the market. Due to the growing volume of data, it is now impractical, if not impossible for humans to manually analyze data for certain tasks like predicting stock market movements, necessitating automation. The stock price data represents a financial time series data which becomes more difficult to predict due to its characteristics and dynamic nature. Thus, this also means that there is a lot of data to find patterns in. This gives rise to the concept of algorithmic trading, which uses automated, pre-programmed trading strategies to execute orders. Machine learning algorithms explore large amounts of data and search for a model that will achieve the programmer’s goal. Our project’s goal is to use machine learning to implement a momentum strategy. We attempted to predict trading signals using machine learning techniques based on a set of technical indicators and rules.
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Beverungen, Armin y Ann-Christina Lange. "Cognition in High-Frequency Trading: The Costs of Consciousness and the Limits of Automation". Theory, Culture & Society 35, n.º 6 (26 de febrero de 2018): 75–95. http://dx.doi.org/10.1177/0263276418758906.
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Certain strands of contemporary media theory are concerned with the ways in which computational environments exploit the ‘missing half-second’ of human perception and thereby influence, control or exploit humans at an affective level. The ‘technological unconscious’ of our times is often understood to work at this affective level, and high-frequency trading is regularly provided as a primary illustrative example of the contagious dynamics it produces. We challenge and complicate this account of the relation between consciousness, affect and media technologies by drawing on the recent work of N. Katherine Hayles and by focusing in detail on the ways in which the ‘costs of consciousness’ are accounted for and negotiated in high-frequency trading. We suggest that traders actively develop modes of awareness accounting for the costs of consciousness, and that the necessary ‘stupidity’ of high-frequency trading algorithms as well as competition pose limits to the full automation of financial markets.
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Wang, Tonghe, Songpu Ai, Junwei Cao y Yuming Zhao. "A Blockchain-Based Distributed Computational Resource Trading Strategy for Internet of Things Considering Multiple Preferences". Symmetry 15, n.º 4 (26 de marzo de 2023): 808. http://dx.doi.org/10.3390/sym15040808.
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The architecture of cloud–edge collaboration can improve the efficiency of Internet of Things (IoT) systems. Recent studies have pointed out that using IoT terminal devices as destinations for computing offloading can promote further optimized allocation of computational resources. However, in practice, this idea encounters the problem that participants might lack the motivation to take over computational tasks from others. Although the edge and the terminal are provided with symmetrical positions in collaborative offloading, their computational resources and capabilities are asymmetric. To mitigate this issue, this paper designs a distributed strategy for the trading of computational resources. The most prominent feature of our strategy is its multi-preference optimization objective that takes into account the overall satisfaction with task delay, energy cost, trading prices, and user reputation of participants. In addition, this paper proposes a system architecture based on the Blockchain-as-a-Service (BaaS) design to give full play to the good distributed technology features of blockchain, such as decentralization, traceability, immutability, and automation. Meanwhile, BaaS delivers decentralized identifier (DID) based distributed identity infrastructure for the distributed computational resource trading stakeholders as well. In the simulation evaluation, we compare our trading strategy based on a matching mechanism called multi-preference matching (MPM) to trading using the classical double auction (DA) matching mechanism. The results show that our computational resource trading strategy is able to offload and execut more tasks, achieving a better throughput compared to the DA-based strategy.
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Alsulmi, Mohammad y Nourah Al-Shahrani. "Machine Learning-Based Decision-Making for Stock Trading: Case Study for Automated Trading in Saudi Stock Exchange". Scientific Programming 2022 (22 de septiembre de 2022): 1–14. http://dx.doi.org/10.1155/2022/6542862.
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Stock markets are becoming the center of attention for many investors and hedge funds, providing them with a wide range of tools and investment opportunities to grow their wealth and participate in the economy. However, investing in the stock market is not trivial. Stock traders and financial advisors are required to frequently monitor market actions, search for profitable companies, and analyze stock price movements to generate various trading ideas (e.g., selecting a stock symbol and making the decision when to enter or exit a trade), potentially leading to investment returns. Therefore, this study aims to address this challenge through exploring the adaptation of machine learning methods combined with risk management techniques to develop a framework for automating the task of stock trading. We evaluated our framework by creating a diverse portfolio containing several companies listed on the Saudi Stock Exchange (Tadawul) and using the simulated trading actions (executed by the framework) to estimate the portfolio’s returns for 3.7 years. The findings show that in terms of investment returns, the proposed framework is very promising; it has generated over 86% returns and outperformed almost all hedge funds by the top investment banks in Saudi Arabia.
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Peng, Chengyuan y Zihan Zhao. "Exploring New Trends in the Global Foreign Exchange Derivatives Market Based on the European and American Financial Markets". Advances in Economics, Management and Political Sciences 53, n.º 1 (1 de diciembre de 2023): 188–94. http://dx.doi.org/10.54254/2754-1169/53/20230830.
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This research delves into the changes in products and participants in the foreign exchange derivatives market in Europe and America. It uncovers the new trends in the global foreign exchange derivatives market. The European and American financial markets are significant players in foreign exchange trading and financial innovation, as they affect the world through their market fluctuations and policy changes. The study reveals that the foreign exchange derivatives market is undergoing new dynamics and environmental changes. Innovative products are emerging, and the level of transaction automation is increasing. The foreign exchange derivatives market in Europe and the United States has transformed from a simple spot foreign exchange transaction to a diverse trading system that covers major global currencies. The proportion structure of trading participants is also changing over time. In conclusion, this research provides profound insights into the global foreign exchange derivatives market. It aims to provide relevant suggestions and references for market participants and regulators based on its analysis.
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Rabin, Steve. "Automating Trading Partner Collaboration Across the Order Management Life Cycle". Information Systems Management 19, n.º 3 (junio de 2002): 70–73. http://dx.doi.org/10.1201/1078/43201.19.3.20020601/37172.9.
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Schmidt, Hartmut y Peter Iversen. "Automating german equity trading: Bid-ask spreads on competing systems". Journal of Financial Services Research 6, n.º 4 (enero de 1993): 373–97. http://dx.doi.org/10.1007/bf01046076.
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Amoo, Adewale. "Research on Automatic Commodity Trading Method based on Smart Contract". International Journal of Smart Business and Technology 6, n.º 2 (31 de diciembre de 2018): 31–38. http://dx.doi.org/10.21742/ijsbt.2018.6.2.04.
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Seleznova, Olha, Veronica Shmahina y Tetyana Yegorova-Gudkova. "Positive and Ntgative Aspects of Pricing Automation in Digital Marketing". Marketing and Digital Technologies 5, n.º 3 (29 de septiembre de 2021): 43–52. http://dx.doi.org/10.15276/mdt.5.3.2021.4.
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The aim of the article. The relevance of the study is justified by the fact that users of online shopping services are becoming more and more every day and at the same time there is an active spread of online commerce in terms of digital marketing. In the circumstances of the trading company development and the growing number of its outlets, the task of automating pricing, collecting and analyzing information about market prices is becoming increasingly important. Since trade margins vary for different groups of goods, and the final price depends on the input price of the supplier, setting the selling price for the entire range of goods takes a significant amount of time from the management (director or manager) of the company, distracting him from important strategic objectives. Thus, the solution of the problem of pricing automation and definition of its digital aspects will allow to direct valuable time resource on business development, diversification of risks and maintenance of profitability of the enterprise. The purpose of the work is to study the positive and negative aspects of pricing automation in digital marketing. Analyses results. The positive and negative aspects of pricing automation in digital marketing are investigated in the work. The authors disclosed the benefits of implementing a pricing automation system for the management of the enterprise carrying out its business activities in the Internet space: saving time for authorized persons, accelerating the collection, analysis and processing of market prices, setting prices at the enterprise according to established algorithms, minimizing errors during pricing, profit growth, increased motivation. The risks that need to be kept in the mind when implementing any pricing automation systems are highlighted too: the need for refinements in the use of software, the possibility of errors in algorithms, dependence on the software executor, the need to back up data, averaging prices when revaluing goods. There is provided a list and summary of the world's popular software products used to address the research issue: Prisync, Informed, Amazon Repricer from Repricer Express, Skuuudle. The parsing method is considered in detail in the article as one of a popular in the national market. The advantages (automaticity and efficiency, target direction, allocation for processing controversial points of pricing, tracking the dynamics of market prices) and disadvantages (possibility of misreading of algorithms, duration of testing, software cost) of price parsing for Internet retailers are revealed in this work. The novelty of the study lies in the selection of previously unresolved issues of research and application of the process of automation of pricing in the market of IT and Internet retail. Conclusions and directions for further research. Prospects for further exploration should be a more detailed study of pricing automation methods of enterprises operating in the global Internet.
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Angel, James J., Lawrence E. Harris y Chester S. Spatt. "Equity Trading in the 21st Century". Quarterly Journal of Finance 01, n.º 01 (marzo de 2011): 1–53. http://dx.doi.org/10.1142/s2010139211000067.
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The US equity market has changed dramatically in recent years. Increasing automation and the entry of new trading platforms have resulted in intense competition among trading platforms. Despite these changes, traders still face the same challenges as before. They seek to minimize the total cost of trading, including commissions, bid/ask spreads, and market impact. New technologies allow traders to implement traditional strategies more effectively. For example, dark pools and indications of interest are just an updated form of tactics that NYSE (New York Stock Exchange) floor traders used to search for counterparties while minimizing the exposure of their clients' trading interest to prevent front running. Virtually every measurable dimension of US equity market quality has improved. Execution speeds and retail commissions have fallen. Bid-ask spreads have fallen and remain low, although they spiked upward along with volatility during the recent financial crisis. Market depth has increased. Studies of institutional transactions costs find US costs among the lowest in the world. Unlike during the Crash of 1987, the US equity market mechanism handled the increase in trading volume and volatility without disruption. However, our markets lack a market-wide risk management system that would deal with computer-generated chaos in real time, and our regulators should address this. "Make or take" pricing, the charging of access fees to market orders that "take" liquidity and paying rebates to limit orders that "make" liquidity, causes distortions that should be corrected. Such charges are not reflected in the quotations used for the measurement of best execution. Direct access by nonbrokers to trading platforms requires appropriate risk management. Front running orders in correlated securities should be banned.
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Crawford, Broderick, Ricardo Soto, Marco Alarcón San Martín, Hanns de la Fuente-Mella, Carlos Castro y Fernando Paredes. "Automatic High-Frequency Trading: An Application to Emerging Chilean Stock Market". Scientific Programming 2018 (30 de septiembre de 2018): 1–12. http://dx.doi.org/10.1155/2018/8721246.
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This research seeks to design, implement, and test a fully automatic high-frequency trading system that operates on the Chilean stock market, so that it is able to generate positive net returns over time. A system that implements high-frequency trading (HFT) is presented through advanced computer tools as an NP-Complete type problem in which it is necessary to optimize the profitability of stock purchase and sale operations. The research performs individual tests of the algorithms implemented, reviewing the theoretical net return (profitability) that can be applied on the last day, month, and semester of real market data. Finally, the research determines which of the variants of the implemented system performs best, using the net returns as a basis for comparison. The use of particle swarm optimization as an optimization algorithm is shown to be an effective solution since it is able to optimize a set of disparate variables but is bounded to a specific domain, resulting in substantial improvement in the final solution.
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Inagaki, Toshiyuki. "Situation-Adaptive Autonomy: Dynamic Trading of Authority between Human and Automation". Proceedings of the Human Factors and Ergonomics Society Annual Meeting 44, n.º 13 (julio de 2000): 13–16. http://dx.doi.org/10.1177/154193120004401304.
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Litzenberger, Robert, Jeff Castura y Richard Gorelick. "The Impacts of Automation and High Frequency Trading on Market Quality". Annual Review of Financial Economics 4, n.º 1 (octubre de 2012): 59–98. http://dx.doi.org/10.1146/annurev-financial-110311-101744.
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Ramesh, Arjun, A. S. Lakshmi, Chris Joseph Thomas, C. Sivaram Krishnan y Revathy Prasannan. "Investment Portfolio Management System". International Journal for Research in Applied Science and Engineering Technology 11, n.º 8 (31 de agosto de 2023): 169–74. http://dx.doi.org/10.22214/ijraset.2023.55150.
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Abstract: The idea of this project is to automate the process of investing or trading based on users choice , by providing references to financial markets trajectory. This project helps a retail investor to meet his financial goals by automating the process and thereby remains manageable for them. The current projects usually reside on the principle of predicting the trend of the market or particular financial instrument .This can be done by using LSTM or prophet seasonality prediction model to predict non-linear trend in the market. Designing a bot to invest in instruments based on the users requirements will further help in automating the entire process. This ideated system is thought by integrating the smart predicting feature of the machine.
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Petrov, Timothy, Wolfgang Neussner y Maximilian Lackner. "Digitalization of the Process Landscape for Proprietary Bond Trading". Technium Romanian Journal of Applied Sciences and Technology 3, n.º 6 (21 de julio de 2021): 76–89. http://dx.doi.org/10.47577/technium.v3i6.4065.
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On the surface, the process landscape for fixed income securities trading within most banks has changed only slightly in the past four decades. The value chain remains divided amongst front-, middle-, and back office, with IT in support. Front office negotiates deals with customers and other banks, middle office manages risks and reporting, and back office ensures that payments are made in exchange for a transfer of the bonds that have been traded. Though these processes have gradually migrated to electronic mediums, much of the work in all functional areas remains manual. But the advent of digital technologies, primarily process automation software and data integration in an open software architecture, allows banks to dramatically change how the processes along the value chain are carried out. Repetitive and predictable tasks can be performed by automated software, allowing humans to concentrate on complex activities that require flexibility and discretion. Those tasks that remain in the hands of humans can also be made more efficient by extracting data from software applications along the entire process chain and providing them to the human user at the right point in time in the right system.
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Bari, Omar A. y Arvin Agah. "Ensembles of Text and Time-Series Models for Automatic Generation of Financial Trading Signals from Social Media Content". Journal of Intelligent Systems 29, n.º 1 (12 de julio de 2018): 753–72. http://dx.doi.org/10.1515/jisys-2017-0567.
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Abstract Event studies in finance have focused on traditional news headlines to assess the impact an event has on a traded company. The increased proliferation of news and information produced by social media content has disrupted this trend. Although researchers have begun to identify trading opportunities from social media platforms, such as Twitter, almost all techniques use a general sentiment from large collections of tweets. Though useful, general sentiment does not provide an opportunity to indicate specific events worthy of affecting stock prices. This work presents an event clustering algorithm, utilizing natural language processing techniques to generate newsworthy events from Twitter, which have the potential to influence stock prices in the same manner as traditional news headlines. The event clustering method addresses the effects of pre-news and lagged news, two peculiarities that appear when connecting trading and news, regardless of the medium. Pre-news signifies a finding where stock prices move in advance of a news release. Lagged news refers to follow-up or late-arriving news, adding redundancy in making trading decisions. For events generated by the proposed clustering algorithm, we incorporate event studies and machine learning to produce an actionable system that can guide trading decisions. The recommended prediction algorithms provide investing strategies with profitable risk-adjusted returns. The suggested language models present annualized Sharpe ratios (risk-adjusted returns) in the 5–11 range, while time-series models produce in the 2–3 range (without transaction costs). The distribution of returns confirms the encouraging Sharpe ratios by identifying most outliers as positive gains. Additionally, machine learning metrics of precision, recall, and accuracy are discussed alongside financial metrics in hopes of bridging the gap between academia and industry in the field of computational finance.
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Ermolaev, S. S., T. I. Galiev y A. G. Glebova. "Features of modern electronic trading in international financial markets". E-Management 5, n.º 3 (27 de septiembre de 2022): 90–97. http://dx.doi.org/10.26425/2658-3445-2022-5-3-90-97.
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The subject of research is the Internet trading in the American and European financial markets for individuals from the Russian Federation. The relevance of the topic is due to the huge influx of Russian private investors into the global financial market over the past few years, caused by the simplification of the process of opening brokerage accounts, automation of taxation, the possibility of trading via web terminals, as well as significantly changed conditions of online trading in 2022. The whole work is the development of a report on investing in the financial markets of the United States of America and the European Union for citizens of the Russian Federation. The study was conducted using the methods of systematization, grouping and comparison, with their help, analysis and generalization of the results obtained were carried out, conclusions were drawn. It has been established that in the current geopolitical situation and the restrictive measures taken by many multinational banks and companies, private investors of Russian origin have risks of freezing their own assets on brokerage accounts, which can be reduced by opening a brokerage account in companies registered in the territory of countries friendly to the Russian Federation. The article suggests two least risky options for investing in securities of issuers from Europe and USA.
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Rumi, Maruf Hasan, Shukti Bala, A. M. M. Mubassher Shah, Md Abu Sayem y Md Minhajul Abedin. "Future Tradeoff under Fourth Industrial Revolution in Bangladesh: A Study on RMG Sector". International Journal of Social, Political and Economic Research 8, n.º 1 (10 de abril de 2021): 198–215. http://dx.doi.org/10.46291/ijospervol8iss1pp198-215.
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Bangladesh's government has taken the 7th Five Year plan to implement Sustainable Development Goals (SDGs) by promoting favorable trade policies along with industrialization, digitization, and inclusive development. Hence, well-running trade is considered as the promising indicator to achieve SDGs which is growing exponentially in our country. Here, the Readymade Garment (RMG) is the most influential trading sector to contribute enormously in the export-earning. In recent times, the sector is facing massive changes due to the automation of the Fourth Industrial Revolution (FIR). To sustain in this digital competitive trade market, has become a major challenge for the small RMG industries. A huge number of Small and Medium Enterprises (SMEs) in our country have already been shut down due to automation. The large factories are also changing their manufacturing system by installing automation to cope with the demand for global competition. These are creating an unstable condition for RMG trade. The government needs to take a strategic and integrated plan immediately to gain the competitive advantage of FIR. Otherwise, Bangladesh will lose the international market for the RMGs of the country.
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Mayere, Abdulkarim. "Automatic Power Sharing System for Generators". Physics Access 02, n.º 02 (2022): 44–46. http://dx.doi.org/10.47514/phyaccess.2022.2.2.006.
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In this paper, a proposal for the development of a neighbourhood network (n-network) automatic power sharing system that will bring about regulatory paradigm and mobilization of the private sector to lead in deployment of clean energy solutions while letting local residents to buy (consumer) and sell (producer) electricity among the neighbours is presented. Here the neighbourhoods become prosumers. Until now, electricity production and supply has traditionally been implemented via a centralized grid where the power generation companies otherwise known as GenCos generate electricity that is fed through the grid to individual homes. The proposed solution aims to create a peer-to-peer trading system where consumers will identify each other’s needs and willingness to buy and sell electricity. This offers the chance to bypass the traditional electricity grid and create a viable generation and storage microgrid that functions independently.
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Volik, Mariya, Maria Kovaleva y Eleonora Khachaturova. "The concept of implementing a customer interaction system based on CRM Bitrix24". SHS Web of Conferences 94 (2021): 01022. http://dx.doi.org/10.1051/shsconf/20219401022.
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In modern conditions of digitalization, each company seeks to optimize the management of activities based on modern IT. With an increase in the number of trading companies, the more becomes acute problem of attracting and retaining customers. In order to improve the efficiency activity of the company, the leadership needs to optimize the business processes of interaction with customers. The purpose of this work is to study the company's activities for the development and implementation of software, analyze the business process of interaction with clients for its automation based on CRMBitrix24. The description of the investigated business process in the notations «as is» and «to be» showed that the automation of interaction with the company's customers has a number of advantages. In this regard, in the future, it is necessary to develop a Bitrix24 implementation project, a risk management plan and assessment of the economic efficiency of the project.
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Gozman, Daniel y Wendy Currie. "The Role of Investment Management Systems in Regulatory Compliance: A Post-Financial Crisis Study of Displacement Mechanisms". Journal of Information Technology 29, n.º 1 (marzo de 2014): 44–58. http://dx.doi.org/10.1057/jit.2013.16.
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The financial crisis of 2007-2009 and the resultant pressures exerted on policymakers to prevent future crises have precipitated coordinated regulatory responses globally. A key focus of the new wave of regulation is to ensure the removal of practices now deemed problematic with new controls for conducting transactions and maintaining holdings. There is increasing pressure on organizations to retire manual processes and adopt core systems, such as Investment Management Systems (IMS). These systems facilitate trading and ensure transactions are compliant by transcribing regulatory requirements into automated rules and applying them to trades. The motivation of this study is to explore the extent to which such systems may enable the alteration of previously embedded practices. We researched implementations of an IMS at eight global financial organizations and found that overall the IMS encourages responsible trading through surveillance, monitoring and the automation of regulatory rules and that such systems are likely to become further embedded within financial organizations. We found evidence that some older practices persisted. Our study suggests that the institutionalization of technology-induced compliant behaviour is still uncertain.
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Davis, Michael, Andrew Kumiega y Ben Van Vliet. "Ethics, Finance, and Automation: A Preliminary Survey of Problems in High Frequency Trading". Science and Engineering Ethics 19, n.º 3 (9 de noviembre de 2012): 851–74. http://dx.doi.org/10.1007/s11948-012-9412-5.
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Kushnir, O., V. Chaplinsky y D. Maksymenko. "THE USE OF ARTIFICIAL INTELLIGENCE IN TRADING STRATEGIES OF BUSINESS: AUTOMATION AND FORECASTING". Investytsiyi: praktyka ta dosvid, n.º 23 (7 de diciembre de 2023): 69–74. http://dx.doi.org/10.32702/2306-6814.2023.23.69.
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Saifuddin Hossain, Syed. "Bangladesh Customs: Managing Risk for Better Trade". Global Trade and Customs Journal 4, Issue 2 (1 de febrero de 2009): 45–51. http://dx.doi.org/10.54648/gtcj2009007.
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Bangladesh has long been striving towards simplifying its regulatory procedures to ensure better integration into the global trading system. It is in this context that the Bangladesh Customs plays a crucial role in implementing pragmatic risk management procedures to maintain supply–chain security. Automation of customs procedures and enforcing the three–step selectivity process are part of the existing risk management framework. Such regulatory controls are, then, aimed at maximising trade facilitation through effective and efficient functioning of the compliance management framework which comprises of four critical elements: legislative base, client service, compliance assessment, and enforcement/recognition.
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BOLILYI, V. O., O. M. HUTSALIUK, L. P. SUKHOVIRSKA y O. M. LUNHOL. "DEVELOPMENT AND IMPLEMENTATION OF A SOFTWARE PRODUCT “AUTOMATED ACCOUNTING SYSTEM “AXIM” FOR SMALL BUSINESSES IN THE SYSTEM OF FORMATION OF ANALYTICAL SUPPORT". Economic innovations 23, n.º 3(80) (20 de agosto de 2021): 33–40. http://dx.doi.org/10.31520/ei.2021.23.3(80).33-40.
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Topicality. The desire to electronize daily routine processes comes into all spheres of human life: education, entertainment, business, everyday life, etc. It is known that automation of any process not only simplifies human work, but also reduces the time for its execution and improves the quality and effectiveness of this operation.Today, more and more mechanical, monotonous work of people is performed by an automatic or automated system. This is justified by the fact that computer software products perform operations much faster and better than humans.Aim and tasks. Study of the features of development and implementation of the automated accounting system “AXIM” with wide functionality for a small enterprise.Conducted content analysis of literary sources of the economic direction and the programming sphere – to select indicators that affect the functioning of the store, study their relationships to develop a software product for increasing the efficiency of trading company business processes; comparative analysis – to reveal the essence and features of software products implementation to improve the efficiency of trading company business processes; analysis and synthesis techniques – to form a system of indicators for the effectiveness of the software product implementation.Research results. An “AXIM” automated system for selling retail goods has been created, which has great functionality and successfully fulfills its tasks. The software product was introduced and tested at the small trading company “Bonus” of individual entrepreneur Yakovlieva L.I., which is located in the township Smolino of the Kirovohrad region Malovyskivskyi district.Conclusion. The introduction of the created software product at the investigated small trading company “Bonus” of individual entrepreneur Yakovlieva L.I. showed effective usage indicators and made it possible to streamline the accounting, simplify the search for product information, automate the scheme of goods sale and control the goods balance in the store.
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Ojeka, Stephen A. y O. Ailemen Ikpefan. "Electronic Commerce, Automation and Online Banking in Nigeria". International Journal of Innovation in the Digital Economy 3, n.º 1 (enero de 2012): 11–26. http://dx.doi.org/10.4018/jide.2012010102.
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Electronic banking has been around for some time in the form of automatic teller machines and telephone transactions. More recently, it has been metamorphosed by the Internet with a new look and delivery channel for banking services that benefits both customers and banks. The objective of this paper is to find out the correlation between the anticipated benefits/challenges and encountered benefits/challenges. This paper empirically adopted the use of survey research to explore in quantitative terms the various challenges and benefits e-business poses to Nigerian businesses, with particular reference to Banking and Finance Industry. It was found out that there is a statistically significant difference between the anticipated and encountered benefits and major challenges in the potential security breaches faced by the customers. Constant training of employees both local and international on new development in online trading should be encouraged.