ارایه‌‌ی مدلی برای انجام معاملات سهام با بسامد بالا، با استفاده از الگوریتم اتوماتای سلولی یادگیرنده و بهینه سازی حدی (CLA-EC-EO )
فصلنامه بورس اوراق بهادار

فصلنامه بورس اوراق بهادار

ارایه‌‌ی مدلی برای انجام معاملات سهام با بسامد بالا، با استفاده از الگوریتم اتوماتای سلولی یادگیرنده و بهینه سازی حدی (CLA-EC-EO )

نوع مقاله : مقاله پژوهشی

نویسندگان
1 دانشیار گروه اقتصاد، واحد تبریز، دانشگاه آزاد اسلامی، تبریز، ایران
2 دانشجوی دکتری مهندسی مالی، گروه اقتصاد، واحد تبریز ، دانشگاه آزاد اسلامی ، تبریز ، ایران
3 دانشیار،گروه حسابداری، واحد تبریز ، دانشگاه آزاد اسلامی ، تبریز، ایران
چکیده
همزمان با افزایش سرعت تبادلات مالی، پیچیدگی‌های زیادی نیز به آن اضافه شده و میزان قابل توجهی نقش بازیگران انسانی در آن کم رنگ گردیده و شیوه معاملات با تواتر بالا پا به عرصه معاملات گذارده است. در این پژوهش مدلی برای معاملات با بسامد بالا ارایه ‌شده است تا علاوه بر کاهش ریسک معاملات، توانایی سازگاری با تغییرات محیطی را بصورت پویا داشته باشد.
روش انجام پژوهش بهره‌گیری از الگوریتم آتوماتای‌ سلولی یادگیرنده و بهینه سازی حدی بوده و از پارامترهای تحلیل بنیادی، اندیکاتورهای تحلیل تکنیکال، متغیرهای اقتصادی و اطلاعات معاملات روزانه سهام به عنوان متغیر استفاده شده و جامعه‌آماری نماد‌های معامله شده در بازار بورس اوراق بهادار تهران از مرداد 1395 الی مرداد 1400 می‌باشد همچنین از الگوی ماتریس درهم ریختگی به منظور ارزیابی الگوی بدست آمده استفاده شده است.
نتایج تحقیق منجر به اصلاح دامنه اثرگذاری متغیرهای تحلیل تکنیکال و نیز متغیراقتصادی برای نمادهای معاملاتی گردید و نیز الگویی پویا برای معاملات بازار سهام ارایه شد که قادر به سازگاری با تغییر شرایط محیطی به منظور کاهش ریسک معاملات می‌باشد.
کلیدواژه‌ها
موضوعات

عنوان مقاله English

A New model for conducting high-frequency Trading Using Collaborative Cellular Learning Automata Algorithm and Extremal Optimization (CLA-EC-EO )

نویسندگان English

seyed ali paytakhti oskooe 1
Seyed Ali Reza Ahmadi 2
Yunes badavar nahandi 3
1 Associate Professor, Department of Economics, Tabriz Branch, Islamic Azad University, Tabriz,
2 Ph.D. Candidate in financial engineering, Faculty of Economics,Tabriz Branch, Islamic Azad University, Tabriz, Iran
3 Associate Professor, Department of Accounting, Tabriz Branch, Islamic Azad university, Tabriz, Iran
چکیده English

Introduction
At the same time as the speed of financial exchanges increases, many complications are also added to it, and the amount of attention paid to the role of human actors in it has faded, and the method of high-frequency trading is over time. In this research, a model for HFT has been presented in order to dynamically adapt to environmental changes in addition to cost reduction.
Methodology
The method of conducting the research is to use the algorithm of colleagues' cellular automata and extermal optimization, and from fundamental analysis books, technical and economic analysis indicators and daily stock information as used and Statistical community of the symbols available in the Tehran Stock Exchange market in August 2016 to August 2021. The confusion matrix model has been used to evaluate the model.
Results
The results of the research led to the modification of the effect range of technical analysis variables as well as economic variables for trading symbols, and a dynamic model for stock market trading was presented, which is able to adapt to changing environmental conditions in order to reduce the trading risk.

کلیدواژه‌ها English

high frequency trading
cellular automata
extermal optimization
confusion matrix
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