Relevant bibliographies by topics / Automated trading systems

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Automated trading systems'

Author: Grafiati
Published: 4 June 2021
Last updated: 25 July 2025

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Journal articles on the topic "Automated trading systems"

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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 overs
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Kandaurov, Dmitry. "HISTORY, CURRENT STATE, AND PROSPECTS FOR THE DEVELOPMENT OF AUTOMATED TRADING SYSTEMS IN THE STOCK MARKET." Bulletin of the South Ural State University series "Economics and Management" 19, no. 1 (2025): 88–98. https://doi.org/10.14529/em250107.

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The paper deals with the rapid development of automated trading systems, which requires a systematisation of knowledge about the methods, models and technologies they use. The subject of the study is automated trading on the stock market. The study of the history of automated trading systems allows to formulate the main hypothesis of the study: the development of automated trading systems based on quan-tum computing and machine learning methods can significantly increase the efficiency of algorithmic trad-ing. The study aims to summarise the existing knowledge, models and methods used by stock
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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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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 con
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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 participa
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Tran, Minh, Duc Pham-Hi, and Marc Bui. "Optimizing Automated Trading Systems with Deep Reinforcement Learning." Algorithms 16, no. 1 (2023): 23. http://dx.doi.org/10.3390/a16010023.

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In this paper, we propose a novel approach to optimize parameters for strategies in automated trading systems. Based on the framework of Reinforcement learning, our work includes the development of a learning environment, state representation, reward function, and learning algorithm for the cryptocurrency market. Considering two simple objective functions, cumulative return and Sharpe ratio, the results showed that Deep Reinforcement Learning approach with Double Deep Q-Network setting and the Bayesian Optimization approach can provide positive average returns. Among the settings being studied
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Zhang, Can, Zhanxin Zhou, and Ruibo Wu. "Optimization of Automated Trading Systems with Deep Learning Strategies." Journal of Industrial Engineering and Applied Science 2, no. 4 (2024): 8–14. https://doi.org/10.5281/zenodo.12780180.

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Automated trading systems have revolutionized the financial markets by executing trades at speeds and frequencies far beyond human capabilities. The integration of deep learning strategies into these systems promises to enhance their performance by better predicting market movements and making more informed trading decisions. This paper explores various deep learning techniques applied to automated trading systems, examining their effectiveness, implementation challenges, and potential benefits. Specifically, we investigate the use of Convolutional Neural Networks (CNNs) for pattern recognitio
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Rushinek, Avi, and Sara Rushinek. "Automated portfolio trading systems forensic forecast audit." International Journal of Auditing Technology 2, no. 1 (2014): 55. http://dx.doi.org/10.1504/ijaudit.2014.064318.

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K, Suraj, Yogesh K, Malavya Manivarnnan, and Dr Mahesh Kumar Sarva. "Exploring Youth Perspectives on Algorithmic Trading: Knowledge, Trust, and Adoption." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 04 (2025): 1–9. https://doi.org/10.55041/ijsrem43789.

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The increasing adoption of algorithmic trading has significantly transformed financial markets by enabling automated decision-making and high-speed trade execution. While institutional investors and hedge funds have widely embraced this technology, its understanding and acceptance among young retail investors, particularly those aged 18 to 25, remain relatively unexplored. As digital trading platforms and fintech innovations continue to gain popularity, assessing the awareness, perception, and preferences of youth regarding algorithmic trading is crucial. This study aims to examine the extent
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ALIEV, Beilak N. "Unification of automated trading systems using the principle of interface segregation." Financial Analytics: Science and Experience 17, no. 3 (2024): 359–66. http://dx.doi.org/10.24891/fa.17.3.359.

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Subject. The article discusses a model for unification of trading strategies architecture based on segregated software interfaces, which will improve the quality of testing of research works aimed at the development of quantitative trading strategies. Objectives. The purpose of the study is to formulate proposals for unification of the architecture of trading strategies for automatic trading systems based on the interface segregation principle. Methods. The study employs the method of empirical observation, analysis of analytical and expert information, practices of software engineering in sys
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Dissertations / Theses on the topic "Automated trading systems"

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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 s
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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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Masoudi, Mohammad Amin. "Robust Deep Reinforcement Learning for Portfolio Management." Thesis, Université d'Ottawa / University of Ottawa, 2021. http://hdl.handle.net/10393/42743.

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In Finance, the use of Automated Trading Systems (ATS) on markets is growing every year and the trades generated by an algorithm now account for most of orders that arrive at stock exchanges (Kissell, 2020). Historically, these systems were based on advanced statistical methods and signal processing designed to extract trading signals from financial data. The recent success of Machine Learning has attracted the interest of the financial community. Reinforcement Learning is a subcategory of machine learning and has been broadly applied by investors and researchers in building trading systems (K
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Repka, Martin. "Investiční modely v prostředí finančních trhů." Master's thesis, Vysoké učení technické v Brně. Fakulta podnikatelská, 2013. http://www.nusl.cz/ntk/nusl-224014.

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This thesis focuses on automated trading systems for financial markets trading. It describes theoretical background of financial markets, different technical analysis approaches and theoretical knowledge about automated trading systems. The output of the present paper is a diversified portfolio comprising four different investment models aimed to trading futures contracts of cocoa and gold. The portfolio tested on market data from the first quarter 2013 achieved 46.74% increase on the initial equity. The systems have been designed in Adaptrade Builder software using genetic algorithms and subs
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Ondo, Ondrej. "Návrh a optimalizace automatického obchodního systému." Master's thesis, Vysoké učení technické v Brně. Fakulta podnikatelská, 2014. http://www.nusl.cz/ntk/nusl-224709.

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This thesis focuses on automated trading systems for foreign exchange markets. It describes theoretical background of financial markets, technical analysis approaches and theoretical knowledge about automated trading systems. The output of the thesis is set of two automated trading systems built for trading the most liquid currency pairs. The process of developing automated trading system as well as its practical start up in Spartacus Company Ltd. is documented in the form of project documentation. The project documentation captures choosing necessary hardware components, their installation an
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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 releva
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Matoušková, Hana. "Testování úspěšnosti vybraných indikátorů technické analýzy na trzích EU." Master's thesis, Vysoká škola ekonomická v Praze, 2010. http://www.nusl.cz/ntk/nusl-75238.

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This diploma thesis deals with the technical analysis with the emphasis on creating, testing and using of trading systems. Its objective is to find out whether it is possible for a trader to design and trade his own profitable trading system with widely accessible tools and methods. First part of the thesis concentrates among other things on the explanation of stock valuation principles, description of tested shares and time period. The second and third chapters fully describe the process of trading system development and the analysis of results of both trading systems. Last chapter is devoted
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Larsen, Fredrik. "Automatic stock market trading based on Technical Analysis." Thesis, Norwegian University of Science and Technology, Department of Computer and Information Science, 2007. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-8707.

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<p>The theory of technical analysis suggests that future stock price developement can be foretold by analyzing historical price fluctuations and identifying repetitive patterns. A computerized system, able to produce trade recommendations based on different aspects of this theory, has been implemented. The system utilizes trading agents, trained using machine learning techniques, capable of producing unified buy and sell signals. It has been evaluated using actual trade data from the Oslo Børs stock exchange over the period 1999-2006. Compared to the simple strategy of buying and holding, som
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Trnik, Erik. "Návrh a optimalizace automatického obchodního systému pro forex." Master's thesis, Vysoké učení technické v Brně. Fakulta podnikatelská, 2017. http://www.nusl.cz/ntk/nusl-318583.

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The master's thesis deals with the design of the proposed automatic trading system especially for daily trading on the currency markets. The aim of the thesis is to create a complex theoretical basis, in the practical part of the work to use the knowledge to create a suitable automatic trading system. The thesis focuses on the technical analysis of the currency markets. The proposed system will be optimally optimized to maximize profitability and stability with application to the most liquid currency pairs.
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Radošinský, Martin. "Využití analýz pro intradenní obchodování na mezinárodním měnovém trhu." Master's thesis, Vysoké učení technické v Brně. Fakulta podnikatelská, 2016. http://www.nusl.cz/ntk/nusl-241469.

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The main aim of this diploma thesis is to analyze the options of trading Forex by combining fundamental and technical analysis in connection to intraday trading. One of the goals is to identify pros and cons of these analysis. Based on the gained information, design trading portfolio consisting of different strategies. Each strategy will be programmed as automated trading system and optimized and tested on historical price data.
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Books on the topic "Automated trading systems"

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

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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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O'Garro, Jamal Sinclair. Learn Algorithmic Trading with Python: Build Automated Electronic Trading Systems Using Python. Apress L. P., 2022.

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Engineer, The Forex. Learn to Program Automated Trading Systems for MetaTrader 4 from Scratch. Independently Published, 2022.

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POLLY, Lina. Day Trading and Options Trading : 10 Day Trading Strategies for Beginners : Options Trading Strategies - a Guide for Beginners : How Automated Trading Systems: Day Trading Rules. Independently Published, 2020.

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Vliet, Benjamin Van. Building Automated Trading Systems: With an Introduction to Visual C++. NET 2005. Elsevier Science & Technology Books, 2007.

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

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Book chapters on the topic "Automated trading systems"

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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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Domowitz, Ian, and Ruben Lee. "Regulation of Automated Trading Systems." In The New Palgrave Dictionary of Economics and the Law. Palgrave Macmillan UK, 2002. http://dx.doi.org/10.1007/978-1-349-74173-1_308.

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Preist, Chris. "Economic Agents for Automated Trading." In Software Agents for Future Communication Systems. Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/978-3-642-58418-3_8.

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Laffoy, Barry, Saraansh Dave, and Mahesh Sooriyabandara. "Automated Trading for Smart Grids: Can It Work?" In Self-Organizing Systems. Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-642-54140-7_1.

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Bhati, Avesh Kumar, Vidya Kumbhar, T. P. Singh, and Sahil K. Shah. "DQN Trader: Reinforcement Learning for Automated Trading." In Lecture Notes in Networks and Systems. Springer Nature Singapore, 2025. https://doi.org/10.1007/978-981-97-8090-7_4.

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Panya, Todsapon, and Manad Khamkong. "Deep Reinforcement Learning for Automated of Asian Stocks Trading." In Studies in Systems, Decision and Control. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-67770-0_37.

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Abouloula, Khalid, Ali Ou-Yassine, and Salah-ddine Krit. "Pattern to build a robust trend indicator for automated trading." In Expert Systems in Finance. Routledge, 2019. http://dx.doi.org/10.4324/9780429024061-15.

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Plikynas, Darius. "Agent-Based Modeling of Fluctuations in Automated Trading Systems." In Introducing the Oscillations Based Paradigm. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-39040-6_10.

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Sherstov, Alexander A., and Peter Stone. "Three Automated Stock-Trading Agents: A Comparative Study." In Agent-Mediated Electronic Commerce VI. Theories for and Engineering of Distributed Mechanisms and Systems. Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11575726_13.

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El Youssefi, Ahmed, Ali Omari Alaoui, Abdelaaziz Hessane, Mohamed Khalifa Boutahir, Imad Zeroual, and Yousef Farhaoui. "Towards an Architecture for an Automated Cryptocurrency Algorithmic Trading System." In Lecture Notes in Networks and Systems. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-88304-0_94.

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Conference papers on the topic "Automated trading systems"

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Bharadwaj, Gurudutt S., David Pratap, and Narayana Darapaneni. "Optimized Automated Stock Trading using DQN and Double DQN." In 2024 International Conference on Intelligent Algorithms for Computational Intelligence Systems (IACIS). IEEE, 2024. http://dx.doi.org/10.1109/iacis61494.2024.10721810.

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Das, Tapas, Saidia Jeelani, Seshanwita Das, Pratibha Giri, and Arnab Chatterjee. "Human Bias in Algorithmic Trading: Evaluating Behavioral Finance Impacts on Automated Systems." In 2024 Second International Conference Computational and Characterization Techniques in Engineering & Sciences (IC3TES). IEEE, 2024. https://doi.org/10.1109/ic3tes62412.2024.10877548.

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M, Mohideen AbdulKader, Kalaichelvi Nallusamy, Jebamalar, and Zulaiha Maryam M. "Automated Decision-Making System for Decentralized Stock Trading using Blockchain Smart Contracts and Quaternion Generative Adversarial Networks." In 2024 4th International Conference on Ubiquitous Computing and Intelligent Information Systems (ICUIS). IEEE, 2024. https://doi.org/10.1109/icuis64676.2024.10866034.

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V, Ariyamala, Kishore Karthik M, and Kumaravel N. "An ML based Stock Prediction and Automated Trading System using ALX." In 2025 5th International Conference on Pervasive Computing and Social Networking (ICPCSN). IEEE, 2025. https://doi.org/10.1109/icpcsn65854.2025.11035240.

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Fan, Yijiao. "Automatic Optimization of Trading Strategies Based on Reinforcement Learning." In 2025 IEEE 14th International Conference on Communication Systems and Network Technologies (CSNT). IEEE, 2025. https://doi.org/10.1109/csnt64827.2025.10968680.

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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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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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Itri, Bouzgarne, Youssfi Mohamed, Qbadou Mohammed, Bouattane Omar, and Touil Mohamed. "Deep reinforcement learning strategy in automated trading systems." In 2023 3rd International Conference on Innovative Research in Applied Science, Engineering and Technology (IRASET). IEEE, 2023. http://dx.doi.org/10.1109/iraset57153.2023.10152925.

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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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Păuna, Cristian. "SMOOTHED HEIKIN-ASHI ALGORITHMS OPTIMIZED FOR AUTOMATED TRADING SYSTEMS." In 2nd International Scientific Conference. Association of Economists and Managers of the Balkans, Belgrade, Serbia, 2018. http://dx.doi.org/10.31410/itema.2018.514.

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