پیوندهای مفید
اخبار و اعلانات
آمار
| تعداد نشریات | 161 |
| تعداد شماره‌ها | 6,532 |
| تعداد مقالات | 70,502 |
| تعداد مشاهده مقاله | 124,117,804 |
| تعداد دریافت فایل اصل مقاله | 97,223,535 |
درآمدی بر ابعاد حقوقی معاملات الگوریتمی بازار بورس و اوراق بهادار | ||
| مطالعات حقوق خصوصی | ||
| دوره 53، شماره 2، مرداد 1402، صفحه 185-204 اصل مقاله (367.36 K) | ||
| نوع مقاله: مقاله پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22059/jlq.2023.358779.1007766 | ||
| نویسندگان | ||
| حانیه ذاکری نیا* 1؛ زهرا غلامپور2؛ محمود باقری3 | ||
| 1استادیار، دانشکدۀ حقوق و علوم سیاسی دانشگاه شیراز، شیراز، ایران. | ||
| 2دانشجوی دکتری، حقوق خصوصی، دانشکدۀ حقوق و علوم سیاسی دانشگاه شیراز، شیراز، ایران. | ||
| 3دانشیار، دانشکدۀ حقوق و علوم سیاسی دانشگاه تهران، تهران، ایران. | ||
| چکیده | ||
| با نقش‌آفرینی گستردۀ الگوریتم‌های هوش مصنوعی در ابعاد مختلف زندگی بشری، معاملات اشخاص در بازارهای متنوع نیز رنگ و بوی تازه‌ای به خود گرفته است. به‌کارگیری الگوریتم‌ها در تحلیل داده‌های بازار، شناخت موقعیت‌های سرمایه‌گذاری مناسب، انتخاب بهینۀ سبد سهام، ثبت سفارش‌ها، انعقاد و اجرای قراردادها، تنها گوشه‌ای از کاربردهای این مغزهای متفکر و مرموز در عرصۀ معاملات حقوقی است. با توجه به نیاز مبرم بازار بورس و اوراق بهادار به ابزارهای کمکی، با حجم انفجاری اطلاعات معامله‌گران، عرضه‌کنندگان و سهام منتشره، معاملات الگوریتمی در بازار سرمایه رونق ویژه‌ای یافته‌اند؛ عرصه‌ای که نه‌تنها با مقررات حاکم بر قراردادهای خصوصی، بلکه با الزامات ناظر بر نقش تنظیم‌گر دولت در بازارهای مزبور نیز مدیریت و کنترل می‌شوند. نحوۀ انطباق‌پذیری الگوریتم‌های معاملاتی با قوانین حقوقی، موجد سؤالات تازه‌ای شده است که پرداختن به هر کدام، افق‌های نوپدیدی از عرصه‌های حقوق قراردادی، حقوق رقابت، مسئولیت مدنی و ... را پیش روی خوانندگان می‌گشاید. این پژوهش ضمن بررسی ابعاد حقوقی معاملات الگوریتمی در بازار سرمایه، به طرح چالش‌هایی از منظر اقتصادی و حقوقی می‌پردازد و با ارائۀ راهکارهایی چند، می‌کوشد مسیر علاقه‌مندان این حوزه را در مطالعات آینده هموار سازد. | ||
| کلیدواژه‌ها | ||
| بازار بورس و اوراق بهادار معاملات الگوریتمی؛ معاملات پربسامد (HFT)؛ هوش مصنوعی. | ||
| عنوان مقاله [English] | ||
| An Introduction to Legal Aspects of Algorithmic Trading in the Stock and Securities Market | ||
| نویسندگان [English] | ||
| Haniyeh Zakerinia1؛ Zahra Gholampour2؛ Mahmoud Bagheri3 | ||
| 1Assistant Professor of Private Law, Faculty of Law and Political Sciences, Shiraz University, Shiraz, Iran. | ||
| 2PhD Student, Private Law, Faculty of Law and Political Sciences, Shiraz University, Shiraz, Iran. | ||
| 3Associate Professor of Private Law, Faculty of Law and Political Sciences, University of Tehran, Tehran, Iran. | ||
| چکیده [English] | ||
| Abstract The term algorithm in various disciplines has its roots in algebra which is one important part of mathematics. Algebra in the course of time has contributed to many developments and achievements in various disciplines such as economics, informatics science, and computer science; and through this process, algorithm transactions have emerged. With the widespread use of artificial intelligence algorithms in various aspects of human life, individuals' transactions in various markets have also taken on a fresh new-look. Nowadays, what is considered as algorithmic transactions in the securities markets has some practical demonstrations. The use of algorithms of artificial intelligence in technical analysis of the market data, the proposal for entering into an optimal transaction with a trader, and then a decision to make a transaction in a specific time and within a specific bid and ask scope which is contemplated by the trader is an example of such innovation. The use of algorithms in market data analysis, identifying appropriate investment opportunities, selecting optimal stock portfolios, placing orders, and formation and execution of contracts, are just a few aspects of the applications of these thoughtful and mysterious brains in the legal trading arena. Due to the unique features of algorithms in terms of speed, accuracy and intelligence, they have been very effective in the financial efficiency of the market players and have been very popular among retail consumers, institutional investors and issuers of securities. Given the market's compelling need for auxiliary tools, the explosive volume of traders' transaction information, issuers, and publicly traded stocks, algorithmic trading in the capital market has flourished; an area that is not only managed and controlled by the regulations governing private contracts but also by the requirements of the government's regulatory role in these markets. However, despite the above-mentioned advantages, there have been challenges associated with this process. Such challenges include unfilled expectations of the counterparties in the transactions, the ambiguities and vagueness of the decision, and the way the algorithm functions. Also the competitive fractions among the traders and market players, lack of legal, regulatory, and technical transparency in the process of algorithmic transactions, undermining of principles of equity and good faith, and weakness in the protection of the consumers are problems that follow the association of the artificial intelligence in capital markets transactions. The adaptability of trading algorithms to legal rules has raised new questions, each of which opens up new horizons in contract law, competition law, civil liability, etc. In practice, with the expansion of the use of this kind of transaction, legal experts and legislators could have a better mental adjustment and awareness in facing the consequences and corollaries of algorithmic transactions in the securities markets and this readiness and awareness shall ensue many advantages. This study, while examining the legal dimensions of algorithmic trading in the capital market, addresses economic and legal challenges and strives to pave the way for interested parties in this field with several proposed solutions for future studies. This paper, therefore, through giving a picture of such algorithmic transactions in the securities markets and capital markets seeks to highlight and demonstrate the intersection between law and artificial intelligence with a focus on the legal challenges associated with the capital market. The paper also seeks to attract the attention of the readers and experts in this field to set the necessary guidelines and encourage them to adopt a scientific approach in dealing with such a phenomenon. For this purpose in this paper, we shall first discuss the concepts and species of algorithmic transactions and then by positing the legal challenges associated with such transactions, shall seek to come up with solutions to tackle such legal challenges. The contribution of this work is offering some framework and safe legal infrastructure for the promotion of the use of algorithmic transactions in the securities market. | ||
| کلیدواژه‌ها [English] | ||
| Algorithmic trading, High-Frequency Trading (HFT), Artificial Intelligence, Stock and Securities Market. | ||
| مراجع | ||
|
منابع
الف) فارسی
ب) خارجی
17. Andrews, Leighton; Bilel Benbouzid; Jeremy Brice; Lee A. Bygrave; David Demortain; Alex Griffiths; Martin Lodge; Andrea Mennicken; Karen Yeung (2017). Algorithmic Regulation. Published by the Centre for Analysis of Risk and Regulation at the London School of Economics and Political Science, 1-49, available at: https://www.lse.ac.uk/accounting/assets/CARR/documents/D-P/Disspaper85.pdf (Accessed 06 May 2023) 18.Angstadt, Janet M. (2011). What will be the legacy of the ‘Flash Crash?’ Developments in US equities market regulation. Capital Markets Law Journal, 6(1), 80-91, available at: https://doi.org/10.1093/cmlj/kmq033 (Accessed 06 May 2023) 19. Barfield, Woodrow (2021). The Cambridge Handbook of The Law of Algorithms. Cambridge University Press. 20. Colby Robert, L.D., Erik R. Sirri (2010). Consolidation and competition in the US equity markets. Capital Markets Law Journal, 5(2), 169-196, available at: https://doi.org/10.1093/cmlj/kmq004 (Accessed 06 May 2023) 21. Ebers, Martin, Marta Cantero Gamito (2021). Algorithmic Governance and Governance of Algorithms; Legal and Ethical Challenges, Springer. 22. Ebers, Martin, Susana Navas (2020). Algorithms and Law, Cambridge University Press. 23. Ezrachi, Ariel; Maurice E. Stucke (2016). Virtual Competition—The Promise and Perils of the Algorithm-Driven Economy (OUP 2016). Harvard University Press. 24. Fitsilis, Fotios (2019). Imposing Regulation on Advanced Algorithms, Springer. 25. Fortune Business Insights: Market Research Report, (2023). Algorithmic Trading Market Size, Shae & Covid-19 Impact Analysis, By Type (Stock Market, Foreign Exchange, Exchange-Traded Fund, Bonds, Cryptocurrencies and Others), By Deployment (Cloud and On-Premise), By End-user (Short-term traders, Long-term traders, Retail Investors and Institutional Investors), and Regional Forecast, 2022-2030, Available at: https://www.fortunebusinessinsights.com/algorithmic-trading-market-107174 (Accessed 06 May 2023) 26. Moloney, N. (2012). Liability of asset managers: a comment. Capital Markets Law Journal, 7(4), 414-422, available at: https://doi.org/10.1093/cmlj/kms037 (Accessed 06 May 2023) 28.Needed in Algorithmic Decision-making, (2018). 1st May, available at: https://www.utoronto.ca/news/predict-responsibly-fairness-needed-algorithmic-decision-making-u-t-experts-say (Accessed 06 May 2023) 29. Sheridan I. (2017). MiFID II in the context of Financial Technology and Regulatory Technology. Capital Markets Law Journal, 12(4), 417-427, Available at: https://doi.org/10.1093/cmlj/kmx036 30. Sheridan, Iain (2018). Financial Technology and global capital markets—the impact of pro-enterprise regulation and English law. Capital Markets Law Journal, 13(4), 587-599, available at: https://doi.org/10.1093/cmlj/kmy027 31. Wallinga, Marnix (2020). EU Investor Protection Regulation and Liability for Investment Losses; A Comparative Analysis of the Interplay between MiFID & MiFID II and Private Law, Springer. 32. Weiss, Robert M., Ajay K. Mehrotra (2001). Online Dynamic Pricing: Efficiency Equity and the Future of E-Commerce. Virginia Journal of Law and Technology, 6 VA. J.L. & TECH. 11, 1. Available at: https://heinonline.org/HOL/LandingPage?handle=hein.journals/vjolt6&div=14&id=&page= (Accessed 06 May 2023). | ||
|
آمار تعداد مشاهده مقاله: 426 تعداد دریافت فایل اصل مقاله: 1,017 |
||