Robotics and Algorithmic Trading: A New Era in Stock Market Trend Analysis

Authors

  • Jaya Chandra Srikanth Gummadi Programmer Analyst, Pioneer Global Inc., Ashburn, Virginia, USA
  • Christopher Ryan Thompson Robotic Process Automation (RPA) Developer, American Robotics, Waltham, MA 02452, USA
  • Narasimha Rao Boinapalli Enterprise Architect, Capgemini, 904 Sylvan Ave, Englewood Cliffs, NJ 07632, USA
  • Rajasekhar Reddy Talla SAP GTS SD OTC Functional Consultant, Elanco Animal Health, Greenfield, Indiana, USA
  • Deekshith Narsina Senior Software Engineer, Capital One, 1600 Capital One Dr, Mclean, VA- 22102, USA

DOI:

https://doi.org/10.18034/gdeb.v10i2.769

Keywords:

Robotics, Algorithmic Trading, Stock Market, Trend Analysis, Financial Technology, Quantitative Finance, Data Analytics, Investment Strategies

Abstract

This paper uses machine learning to examine how robots and algorithmic trading have transformed stock market trend analysis. The main goals are to assess how these sophisticated systems improve prediction accuracy, trading efficiency, market liquidity, and their problems and policy consequences. The research synthesizes academic, industrial, and technical literature using secondary sources. Significant results show that robots and algorithmic trading have enhanced trading speed, accuracy, and market efficiency while increasing market volatility data quality and model overfitting issues. Machine learning improves trend analysis by spotting complicated patterns and improving trading techniques. These advances need solid regulatory frameworks to control risks, including market instability and ethical issues. Policy implications include circuit breakers and transparency standards to promote fair and stable markets. This study emphasizes balancing technology innovation with regulation to provide a safe and fair trade environment.

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Author Biography

  • Rajasekhar Reddy Talla, SAP GTS SD OTC Functional Consultant, Elanco Animal Health, Greenfield, Indiana, USA

    SAP GTS SD OTC Functional Consultant, Elanco Animal Health, Greenfield, Indiana, USA

References

Addimulam, S., Mohammed, M. A., Karanam, R. K., Ying, D., Pydipalli, R., Patel, B., Shajahan, M. A., Dhameliya, N., & Natakam, V. M. (2020). Deep Learning-Enhanced Image Segmentation for Medical Diagnostics. Malaysian Journal of Medical and Biological Research, 7(2), 145-152. https://mjmbr.my/index.php/mjmbr/article/view/687

Addimulam, S., Rahman, K., Karanam, R. K., & Natakam, V. M. (2021). AI-Powered Diagnostics: Revolutionizing Medical Research and Patient Care. Technology & Management Review, 6, 36-49. https://upright.pub/index.php/tmr/article/view/155

Altafini, C. (2016). The Geometric Phase of Stock Trading. PLoS One, 11(8), e0161538. https://doi.org/10.1371/journal.pone.0161538 DOI: https://doi.org/10.1371/journal.pone.0161538

Asadullah, A., Rahman, K., Azad, M. M. (2021). Accurate and Predictable Cardiovascular Disease Detection by Machine Learning. Journal of Cardiovascular Disease Research, 12(3), 448-454.

Beal, J. (2016). Trading Accuracy for Speed in Approximate Consensus. The Knowledge Engineering Review, 31(4), 325-342. https://doi.org/10.1017/S0269888916000175 DOI: https://doi.org/10.1017/S0269888916000175

Boinapalli, N. R. (2020). Digital Transformation in U.S. Industries: AI as a Catalyst for Sustainable Growth. NEXG AI Review of America, 1(1), 70-84.

Bonadio, E., Mcdonagh, L., Arvidsson, C. (2018). Intellectual Property Aspects of Robotics. European Journal of Risk Regulation: EJRR, 9(4), 655-676. https://doi.org/10.1017/err.2018.58 DOI: https://doi.org/10.1017/err.2018.58

Davis, M., Kumiega, A., Van Vliet, B. (2013). Ethics, Finance, and Automation: A Preliminary Survey of Problems in High Frequency Trading. Science and Engineering Ethics, 19(3), 851-74. https://doi.org/10.1007/s11948-012-9412-5 DOI: https://doi.org/10.1007/s11948-012-9412-5

Giunta, G., Benedetto, F. (2012). Empirical Case Study of Binary Options Trading: An Interdisciplinary Application of Telecommunications Methodology to Financial Economics. International Journal of Interdisciplinary Telecommunications and Networking, 4(4), 54-63. https://doi.org/10.4018/jitn.2012100104 DOI: https://doi.org/10.4018/jitn.2012100104

Gummadi, J. C. S., Narsina, D., Karanam, R. K., Kamisetty, A., Talla, R. R., & Rodriguez, M. (2020). Corporate Governance in the Age of Artificial Intelligence: Balancing Innovation with Ethical Responsibility. Technology & Management Review, 5, 66-79. https://upright.pub/index.php/tmr/article/view/157

Karanam, R. K., Natakam, V. M., Boinapalli, N. R., Sridharlakshmi, N. R. B., Allam, A. R., Gade, P. K., Venkata, S. G. N., Kommineni, H. P., & Manikyala, A. (2018). Neural Networks in Algorithmic Trading for Financial Markets. Asian Accounting and Auditing Advancement, 9(1), 115–126. https://4ajournal.com/article/view/95

Kothapalli, S., Manikyala, A., Kommineni, H. P., Venkata, S. G. N., Gade, P. K., Allam, A. R., Sridharlakshmi, N. R. B., Boinapalli, N. R., Onteddu, A. R., & Kundavaram, R. R. (2019). Code Refactoring Strategies for DevOps: Improving Software Maintainability and Scalability. ABC Research Alert, 7(3), 193–204. https://doi.org/10.18034/ra.v7i3.663 DOI: https://doi.org/10.18034/ra.v7i3.663

Kundavaram, R. R., Rahman, K., Devarapu, K., Narsina, D., Kamisetty, A., Gummadi, J. C. S., Talla, R. R., Onteddu, A. R., & Kothapalli, S. (2018). Predictive Analytics and Generative AI for Optimizing Cervical and Breast Cancer Outcomes: A Data-Centric Approach. ABC Research Alert, 6(3), 214-223. https://doi.org/10.18034/ra.v6i3.672 DOI: https://doi.org/10.18034/ra.v6i3.672

Lattemann, C., Loos, P., Gomolka, J., Burghof, H-p., Breuer, A. (2012). High Frequency Trading. Business & Information Systems Engineering, 4(2), 93-108. https://doi.org/10.1007/s12599-012-0205-9 DOI: https://doi.org/10.1007/s12599-012-0205-9

Mohammed, R., Addimulam, S., Mohammed, M. A., Karanam, R. K., Maddula, S. S., Pasam, P., & Natakam, V. M. (2017). Optimizing Web Performance: Front End Development Strategies for the Aviation Sector. International Journal of Reciprocal Symmetry and Theoretical Physics, 4, 38-45. https://upright.pub/index.php/ijrstp/article/view/142

Nagrath, V., Morel, O., Malik, A. S., Saad, M. N., B., M., Meriaudeau, F. (2016). Peer to Peer Trade in HTM5 Meta Model for Agent Oriented Cloud Robotic Systems. Peer-To-Peer Networking and Applications, 9(2), 328-343. https://doi.org/10.1007/s12083-015-0339-x DOI: https://doi.org/10.1007/s12083-015-0339-x

Nizamuddin, M., Natakam, V. N., Kothapalli, K. R. V., Raghunath Kashyap Karanam, R. K., Addimulam, S. (2020). AI in Marketing Analytics: Revolutionizing the Way Businesses Understand Consumers. NEXG AI Review of America, 1(1), 54-69.

Pavone, M., Carpin, S. (2015). Guest Editorial: Special Issue on Constrained Decision-making in Robotics. Autonomous Robots, 39(4), 465-467. https://doi.org/10.1007/s10514-015-9489-1 DOI: https://doi.org/10.1007/s10514-015-9489-1

Rahman, K. (2017). Digital Platforms in Learning and Assessment: The Coming of Age of Artificial Intelligence in Medical Checkup. International Journal of Reciprocal Symmetry and Theoretical Physics, 4, 1-5. https://upright.pub/index.php/ijrstp/article/view/3

Rahman, K. (2021). Biomarkers and Bioactivity in Drug Discovery using a Joint Modelling Approach. Malaysian Journal of Medical and Biological Research, 8(2), 63-68. https://doi.org/10.18034/mjmbr.v8i2.585 DOI: https://doi.org/10.18034/mjmbr.v8i2.585

Rahwan, I., Cebrian, M., Obradovich, N., Bongard, J., Bonnefon, J-F. (2019). Machine Behaviour. Nature, 568(7753), 477,479-486. https://doi.org/10.1038/s41586-019-1138-y DOI: https://doi.org/10.1038/s41586-019-1138-y

Rodriguez, M., Mohammed, M. A., Mohammed, R., Pasam, P., Karanam, R. K., Vennapusa, S. C. R., & Boinapalli, N. R. (2019). Oracle EBS and Digital Transformation: Aligning Technology with Business Goals. Technology & Management Review, 4, 49-63. https://upright.pub/index.php/tmr/article/view/151

Rodriguez, M., Sridharlakshmi, N. R. B., Boinapalli, N. R., Allam, A. R., & Devarapu, K. (2020). Applying Convolutional Neural Networks for IoT Image Recognition. International Journal of Reciprocal Symmetry and Theoretical Physics, 7, 32-43. https://upright.pub/index.php/ijrstp/article/view/158

Thompson, C. R., Talla, R. R., Gummadi, J. C. S., Kamisetty, A. (2019). Reinforcement Learning Techniques for Autonomous Robotics. Asian Journal of Applied Science and Engineering, 8(1), 85-96. https://ajase.net/article/view/94 DOI: https://doi.org/10.18034/ajase.v8i1.94

Wareham, T. (2016). Exploring Algorithmic Options for the Efficient Design and Reconfiguration of Reactive Robot Swarms. EAI Endorsed Transactions on Serious Games, 3(9), 295-302. https://doi.org/10.4108/eai.3-12-2015.2262395 DOI: https://doi.org/10.4108/eai.3-12-2015.2262395

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Published

2021-12-31

Issue

Vol. 10 No. 2 (2021): July - December Issue

Section

Articles

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Copyright (c) 2021 Jaya Chandra Srikanth Gummadi; Christopher Ryan Thompson; Narasimha Rao Boinapalli; Rajasekhar Reddy Talla; Deekshith Narsina

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How to Cite

Gummadi, J. C. S., Thompson, C. R., Boinapalli, N. R., Talla, R. R., & Narsina, D. (2021). Robotics and Algorithmic Trading: A New Era in Stock Market Trend Analysis. Global Disclosure of Economics and Business, 10(2), 129-140. https://doi.org/10.18034/gdeb.v10i2.769
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