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Relevant bibliographies by topics / Automated trading

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Academic literature on the topic 'Automated trading'

Author: Grafiati

Published: 4 June 2021

Last updated: 12 June 2025

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Journal articles on the topic "Automated trading"

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Becker, Brandon, Eugene Lopez, Victoria Berberi-Doumar, Richard Cohn, and Alden S. Adkins. "Automated securities trading." Journal of Financial Services Research 6, no. 4 (1993): 327–41. http://dx.doi.org/10.1007/bf01046074.

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Păuna, Cristian. "Reliable Signals and Limit Conditions for Automated Trading Systems." Review of Economic and Business Studies 11, no. 2 (2018): 9–20. http://dx.doi.org/10.1515/rebs-2018-0070.

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Abstract Automated trading software is a significant part of the business intelligence system in a modern investment company today. The buy and sell orders are built and sent almost instantly by computers using special trading and computational strategies. The trading decisions are made by automated algorithms. In this paper it will be presented one of these mathematical models which generate trading signals based only on the time price series. The algorithm combines several known computing techniques to build a trading indicator to automate the trades. With this method, buy decisions on oversold intervals and sell decisions on overbought price values can be built. Limit conditions in order to close the long and short trades can be also automatically generated. More trading signal types based on this model will be revealed. Trading results obtained with all these signals will be presented in order to qualify this methodology developed especially for algorithmic trading.

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Popławski, Paweł. "Connectivity Solutions in Automated Trading." International Journal of Electronics and Telecommunications 61, no. 4 (2015): 403–8. http://dx.doi.org/10.2478/eletel-2015-0053.

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Abstract The study analyzes the architecture and deployment of direct market access (DMA) solutions for automated trading of securities. It provides an overview of automated trading systems including: trading floor architecture, trading environment connectivity, and DMA solutions. Among a range of factors influencing operational capacities, round-trip latency has been recognized as the key quality differentiator of an automated trading floor. The study identifies potential opportunity costs due to latency levels as a major driver of technological progress in trading in highly liquid market conditions.

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Hanif, Ayub, and Robert Elliott Smith. "Algorithmic, Electronic, and Automated Trading." Journal of Trading 7, no. 4 (2012): 78–86. http://dx.doi.org/10.3905/jot.2012.7.4.078.

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BOLILYI, V. O., O. M. HUTSALIUK, L. P. SUKHOVIRSKA, and 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, no. 3(80) (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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Salam, Abdus, Cut Eva Wani, Nasir, et al. "Pelatihan dan Sosialisasi Automated Trading Systems & Autopilot Manual Trading." Kawanad : Jurnal Pengabdian kepada Masyarakat 2, no. 1 (2023): 64–71. http://dx.doi.org/10.56347/kjpkm.v2i1.102.

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Automated Trading Systems & Autopilot Manual Trading training for 6 days on 10-15 January 2023 provides an understanding of the concepts and workings of ATS and AMT as well as risk management in trading. This training is expected to make participants more independent in trading and able to maximize the use of ATS and AMT to gain profits in their investments. In addition, this training is expected to make a positive contribution in increasing financial literacy and investment in society. However, this needs to be done in a structured and comprehensive manner so that capital market participants understand the potential risks that may arise when using Automated Trading Systems and Autopilot Manual Trading in their investment activities. The recommendation that can be made is to hold regular training and outreach, both by regulators, securities companies, and capital market associations. With effective training and outreach as well as strict supervision, it is hoped that capital market players will be able to optimize their investment potential by avoiding unwanted risks. This training can also help increase awareness and understanding of sharia compliance in investing in the Indonesian sharia capital market.

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Juricek, Jan. "The Use of Artificial Intelligence in Building Automated Trading Systems." International Journal of Computer Theory and Engineering 6, no. 4 (2014): 326–29. http://dx.doi.org/10.7763/ijcte.2014.v6.883.

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Azzini, Antonia, and Andrea G. B. Tettamanzi. "Evolving Neural Networks for Static Single-Position Automated Trading." Journal of Artificial Evolution and Applications 2008 (April 14, 2008): 1–17. http://dx.doi.org/10.1155/2008/184286.

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This paper presents an approach to single-position, intraday automated trading based on a neurogenetic algorithm. An artificial neural network is evolved to provide trading signals to a simple automated trading agent. The neural network uses open, high, low, and close quotes of the selected financial instrument from the previous day, as well as a selection of the most popular technical indicators, to decide whether to take a single long or short position at market open. The position is then closed as soon as a given profit target is met or at market close. Experimental results indicate that, despite its simplicity, both in terms of input data and in terms of trading strategy, such an approach to automated trading may yield significant returns.

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Creamer, Germán, and Yoav Freund. "A Boosting Approach for Automated Trading." Journal of Trading 2, no. 3 (2007): 84–96. http://dx.doi.org/10.3905/jot.2007.688953.

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Buchanan, Mark. "Automated trading better in unlikely places." New Scientist 208, no. 2785 (2010): 23. http://dx.doi.org/10.1016/s0262-4079(10)62743-1.

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Dissertations / Theses on the topic "Automated trading"

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Ansariramandi, Saeed. "Automated Debugging in a Trading System." Thesis, KTH, Skolan för informations- och kommunikationsteknik (ICT), 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-90331.

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Verifying the reliability and functionality of a complex system like a trading system is highly demanding since failure in such a system can cause serious economic problems. Automated random testing is a good solution to find new and rare failures in such a system. Test cases in random testing usually contain a long sequence of actions that debugging them manually to find the root cause of the failure is a very boring and tiresome task. This thesis aims to create a model for automating the task of the debugging to reduce the failed test case to an equivalent test case that only contains relevant actions that together cause the failure. Delta debugging is the core algorithm of the model that simplifies a failed test case by successive testing. The target of the project is TRADExpress system of Cinnober Financial Technology AB. The model is integrated to the random testing framework of the TRADExpress system.

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Mihailovs, Timurs. "Automated high-frequency foreign exchange trading." Thesis, Imperial College London, 2008. http://hdl.handle.net/10044/1/11488.

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Tai, Kam Fong. "Trend following algorithms in automated stock market trading." Thesis, University of Macau, 2011. http://umaclib3.umac.mo/record=b2492841.

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EKSTRÖM, DENNIS. "Automated Foreign Exchange Trading Strategies:Improving Performance Without StrategyModification." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-157699.

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Trading indicators are frequently used among foreign exchange traders in attempts to predict future marketevents. Automated trading strategies can easily be implemented to act on such predictions. Motivated by acuriosity about whether the use of trading in dicators could be improved without actually changing the indicators themselves, this study was conducted in an attempt to investigate opportunities in enhancing strategy profits by restricting strategies from trading during periods deemed as unfavorable. However,conditionally restricting strategies’ trading capabilities by introducing thresholds for strategy activation did not show significant effects on the performance. By examining the accumulated strategy profits both with and without applied thresholds, it was derived that the general characteristics of the performance were withheld. Consequently, it can not be concluded that this study provides a reliable method of enhancing profits through applying restrictions to foreign exchange strategies. Nevertheless, the effects from applying thresholds to strategies, albeit not mainly profitable in this study, motivates further research on advantages from conditionally restricting foreign exchange strategies.

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Kruger, Kurt. "Automated stock trading : a multi-agent, evolutionary approach." Master's thesis, University of Cape Town, 2008. http://hdl.handle.net/11427/14759.

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Includes bibliographical references (leaves 125-130).<br>Stock market trading has garnered much interest over the past few decades as it has been made easier for the general public to trade. It is certainly an avenue for wealth growth, but like all risky undertakings, it must be understood for one to be consistently successful. There are, however, too many factors that influence it for one to make completely confident predictions. Automated computer trading has therefore been championed as a potential solution to this problem and is used in major brokerage houses world-wide. In fact, a third of all EU and US stock trades in 2006 were driven by computer algorithms. In this thesis we look at the challenges posed by the automatic generation of stock trading rules and portfolio management. We explore the viability of evolutionary algorithms, including genetic algorithms and genetic programming, for this problem and introduce an agent-based learning framework for individual and social intelligence that is applicable to general stock markets. Statistical tests were applied to determine whether or not there was a significant difference between the evolutionary trading approach and an accepted benchmark. It was found that while the evolutionary trading agents comfortably realised higher portfolio values than the ALSI, there was insufficient evidence to suggest that the agents outperformed the ALSI in terms of portfolio performance. Additionally, it was observed that while the traders combined knowledge from the expert traders to form complex trading models, these models did not result in any statistically significant positive returns. It must be said, however, that there was overwhelming evidence to suggest that the traders learned rules that were highly successful in predicting stock movement.

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Jones, C. M. "Automated technical foreign exchange trading with high frequency data." Thesis, University of Cambridge, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.343139.

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Szostek, Charlotte. "Decentralised control in financial markets with automated algorithmic trading." Thesis, University of Bristol, 2015. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.738193.

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Leung, Jason W. "Application of machine learning : automated trading informed by event driven data." Thesis, Massachusetts Institute of Technology, 2016. http://hdl.handle.net/1721.1/105982.

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Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2016.<br>This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.<br>Cataloged from student-submitted PDF version of thesis.<br>Includes bibliographical references (pages 61-65).<br>Models of stock price prediction have traditionally used technical indicators alone to generate trading signals. In this paper, we build trading strategies by applying machine-learning techniques to both technical analysis indicators and market sentiment data. The resulting prediction models can be employed as an artificial trader used to trade on any given stock exchange. The performance of the model is evaluated using the S&P 500 index.<br>by Jason W. Leung.<br>M. Eng.

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Salmela, Markus, and Rickard Ström. "Implementing Automated Trading Systems in The Swedish Financial Industry : Establishing a Framework for Successful Diffusion." Thesis, Jönköping University, JIBS, EMM (Entrepreneurship, Marketing, Management), 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-12641.

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<p><strong><p><strong>Purpose: </strong></p><p><em>Our main purpose is to explore, describe and analyze the organizational conduct when implementing automated trading systems (ATS) in companies, investigate the organizational challenges arising from this, and the effects these have on a successful diffusion</em>. As the extent of implementing ATS in the Swedish financial industry has not been explored to any greater extent, it is therefore also imperative to explore this; which will be seen as a secondary purpose to this article.<strong></strong></p><p><strong>Background: </strong></p><p>The study is based on innovation and diffusion theories, as well as those of power structures and organization. Further, an explanation of ATS and its dynamics is provided and discussed to facilitate a definition of the term.</p><p><strong>Method: </strong></p><p>The research has been carried out as an exploratory, descriptive and analytical qualitative study.<strong> </strong>We have conducted case studies of 7 companies that are implementing, or evaluating the implementation, of ATS. The data was collected through interviews.</p><p><strong>Conclusion: </strong></p><p>The majority of the case companies are in the clarifying and routinizing stages of the innovation process. What is found unique with ATS is that it can be implemented partly. The dimensions found central to a smooth diffusion in the companies are the <em>required level of competence-sharing</em> and <em>complexity of implementation.</em></p></strong></p>

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Grega, Martin. "Tvorba automatických obchodních systémů pomocí genetických algoritmů." Master's thesis, Vysoké učení technické v Brně. Fakulta podnikatelská, 2015. http://www.nusl.cz/ntk/nusl-224903.

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The thesis deals with the use of genetic algorithms in the process of creating automated trading systems. The emphasis is on testing the robustness of the developed strategies, their practical applicability in the financial markets and minimizing risk through diversification. The output of this work is a portfolio consisting of three strategies that achieved 31.3% return on capital during the fourth quarter of 2014.

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Books on the topic "Automated trading"

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Durenard, Eugene A. Professional Automated Trading. John Wiley & Sons, Inc., 2013. http://dx.doi.org/10.1002/9781118755846.

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1965-, Tsudikman Vadim, ed. Automated option trading: Create, optimize, and test automated trading systems. FT Press, 2012.

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Conlan, Chris. Automated Trading with R. Apress, 2016. http://dx.doi.org/10.1007/978-1-4842-2178-5.

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1971-, Lee Sang, ed. The high frequency game changer: How automated trading strategies have revolutionized the markets. John Wiley, 2011.

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Young, Andrew R. Expert advisor programming: Creating automated trading systems in MQL for MetaTrader 4. Edgehill Pub., 2010.

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Building automated trading systems: With an introduction to Visual C++.NET 2005. Academic Press, 2007.

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Stock Exchange of Singapore Dealing and Automated Quotation System. Trading bye-laws on SESDAQ securities, SESDAQ listing requirements, central depository procedures, central depository regulations. SESDAQ, 1988.

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Office, General Accounting. Automated Export System: Prospects for improving data collection and enforcement are uncertain : report to the Chairman, Committee on the Judiciary, U.S. Senate. The Office, 1997.

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Tsudikman, Vadim, and Sergey Izraylevich. Automated Option Trading: Create, Optimize, and Test Automated Trading Systems. Financial Times/Prentice Hall, 2012.

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Best Crypto Trading Bots for Automated Trading. Independently Published, 2022.

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Book chapters on the topic "Automated trading"

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Becker, Brandon, Eugene Lopez, Victoria Berberi-Doumar, Richard Cohn, and Alden S. Adkins. "Automated Securities Trading." In Microstructure of World Trading Markets. Springer Netherlands, 1992. http://dx.doi.org/10.1007/978-94-011-2180-4_3.

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Conlan, Chris. "Fundamentals of Automated Trading." In Automated Trading with R. Apress, 2016. http://dx.doi.org/10.1007/978-1-4842-2178-5_1.

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Bigiotti, Alessandro, and Alfredo Navarra. "Optimizing Automated Trading Systems." In Advances in Intelligent Systems and Computing. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-02351-5_30.

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Conlan, Chris. "Organizing and Automating Scripts." In Automated Trading with R. Apress, 2016. http://dx.doi.org/10.1007/978-1-4842-2178-5_10.

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Conlan, Chris. "Looking Forward." In Automated Trading with R. Apress, 2016. http://dx.doi.org/10.1007/978-1-4842-2178-5_11.

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Conlan, Chris. "Source Code." In Automated Trading with R. Apress, 2016. http://dx.doi.org/10.1007/978-1-4842-2178-5_12.

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Conlan, Chris. "Appendix B: Scoping in Multicore R." In Automated Trading with R. Apress, 2016. http://dx.doi.org/10.1007/978-1-4842-2178-5_13.

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Conlan, Chris. "Networking Part I." In Automated Trading with R. Apress, 2016. http://dx.doi.org/10.1007/978-1-4842-2178-5_2.

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Conlan, Chris. "Data Preparation." In Automated Trading with R. Apress, 2016. http://dx.doi.org/10.1007/978-1-4842-2178-5_3.

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Conlan, Chris. "Indicators." In Automated Trading with R. Apress, 2016. http://dx.doi.org/10.1007/978-1-4842-2178-5_4.

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Conference papers on the topic "Automated trading"

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"TOWARDS AUTOMATED SERVICE TRADING." In International Conference on E-business. SciTePress - Science and and Technology Publications, 2006. http://dx.doi.org/10.5220/0001428000380045.

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Varshini Devi, I., B. Natarajan, S. Prabu, R. Anandha Praba, K. Ushanandhini, and K. S. Guruprakash. "Automated Stock Trading using Reinforcement Learning." In 2023 International Conference on Integrated Intelligence and Communication Systems (ICIICS). IEEE, 2023. http://dx.doi.org/10.1109/iciics59993.2023.10421071.

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Chakole, Jagdish, and Manish Kurhekar. "Tutorial on Automated Trading using API." In CODS-COMAD 2023: 6th Joint International Conference on Data Science & Management of Data (10th ACM IKDD CODS and 28th COMAD). ACM, 2023. http://dx.doi.org/10.1145/3570991.3571005.

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Bhat, Aparna Anant, and S. Sowmya Kamath. "Automated stock price prediction and trading framework for Nifty intraday trading." In 2013 Fourth International Conference on Computing, Communications and Networking Technologies (ICCCNT). IEEE, 2013. http://dx.doi.org/10.1109/icccnt.2013.6726675.

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Cliff, Dave. "Simulation-based evaluation of automated trading strategies: a manifesto for modern methods." In The 19th International Conference on Modelling and Applied Simulation. CAL-TEK srl, 2019. http://dx.doi.org/10.46354/i3m.2019.mas.018.

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In many investment banks and major fund-management companies, automated "robot" trading systems now do work that 20 years ago would have required large numbers of human traders to perform: the rise of robot traders is a major success-story for artificial intelligence (AI) research. Although the technical details of currently profitable automated trading systems are closely guarded commercial secrets, the rise of robot trading can be traced back to a sequence of key AI research papers. Each of these key papers relied on minimal abstract simulation models of real financial markets: the simulators provide test-beds for trials in which the performance of different trading strategies could be evaluated and compared. Recent studies have revisited these seminal results, using more realistic simulations of contemporary financial markets, and have cast major doubts on core conclusions drawn in the original publications. Therefore, it seems reasonable to argue that present-day simulation methods are exposing significant problems in past research on automated trading. This position paper presents no new empirical results but instead presents a review of key past papers and an argument, a manifesto, for establishing a shared market-simulator test-bed that adequately reflects current real-world financial markets, for use in future evaluation and comparison of trading strategies.

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Pinto, Rui Maciel Casanova, and Joao Carlos Marques Silva. "Strategic methods for automated trading in Forex." In 2012 12th International Conference on Intelligent Systems Design and Applications (ISDA). IEEE, 2012. http://dx.doi.org/10.1109/isda.2012.6416509.

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Mahajan, Pranit, Yagnesh Salian, Vinayak Jadhav, and Sujata Kulkarni. "A Multi-Strategic Approach to Automated Trading." In 2021 International Conference on Communication information and Computing Technology (ICCICT). IEEE, 2021. http://dx.doi.org/10.1109/iccict50803.2021.9510079.

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Yang, Hongyang, Xiao-Yang Liu, Shan Zhong, and Anwar Walid. "Deep reinforcement learning for automated stock trading." In ICAIF '20: ACM International Conference on AI in Finance. ACM, 2020. http://dx.doi.org/10.1145/3383455.3422540.

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Imaev, D. D., and D. H. Imaev. "Automated trading systems based on order book imbalance." In 2017 XX IEEE International Conference on Soft Computing and Measurements (SCM). IEEE, 2017. http://dx.doi.org/10.1109/scm.2017.7970733.

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Габдрахманова, Ч. Ш. "AUTOMATED INFORMATION SYSTEM OF TRADING ON VIRTUAL SALES." In САПР и моделирование в современной электронике. Брянский государственный технический университет, 2020. http://dx.doi.org/10.51932/9785907271739_71.

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