ارائه الگوریتم قاعده محور برای شناسایی رژیم‌ها در بازارهای افتان‌وخیزان

نوع مقاله : علمی - پژوهشی

نویسنده

استادیار، گروه مدیریت مالی، دانشگاه پیام نور، تهران، ایران.

چکیده

پژوهش حاضر ضمن توسعه ادبیات مالی مرتبط با شناسایی رژیم‌های بازارها مالی، شیوه قاعده محور جدیدی را برای انتخاب نقاط تغییر در چرخه‌های کسب‌وکار پیشنهاد می‌کند که در آن ذهنیت‌گرایی را در فرآیند طبقه‌بندی رژیم‌های بازار حذف می‌کند. الگوریتم پیشنهادشده از یک رویکرد اکتشافی برخوردار بوده و هیچ شرطی برای تعیین دوره رژیم‌ها یا دامنه بازدهی آن‌ها اعمال نمی‌شود. همچنین برای مقایسه بین الگوریتم پیشنهادی و الگوریتم‌های پاگان، لیونه از آزمون بوت استرپ وایت در دارایی‌های مختلف شامل شاخص بورس اوراق بهادار تهران، فلزات مس و طلا و کالای نفت از نسبت شارپ به‌عنوان اندازه‌گیری عملکرد در داده‌های برون‌نمونه‌ای استفاده‌ شده است. نتایج حاصل نشان می‌دهد الگوریتم پیشنهادی در شناسایی رژیم‌های برون‌نمونه‌ای به‌خصوص در سری‌های زمانی که متفاوت از داده‌های شاخص بازار سرمایه باشد، عملکردی بهتر یا مساوی با سایر روش‌های شناسایی دارد. نتایج به‌دست‌آمده توفیق الگوریتم پیشنهادی را نسبت به سایر الگوریتم‌ها نشان می‌دهد. ساختار صرفه‌جو الگوریتم پیشنهادی با ارائه روشی مشخص از نوسان‌های بالقوه‌ای که در بهینه‌سازی پارامتر ایجاد می‌شود اجتناب کرده و در شناسایی رژیم‌های متفاوت در مجموعه‌های گوناگونی ازسری‌های زمانی بدون تغییر در پارامترها مفید و کاربردی است.

کلیدواژه‌ها

عنوان مقاله [English]

Designing a Rule-Based Algorithm to Identify Bull and Bear Markets Regimes

نویسنده [English]

  • Seyed Jalal Tabatabaei
Assistant Prof. Department of Financial Management, Payamenoor University, Tehran, Iran
چکیده [English]

To develop the financial literature related to the identification of financial market regimes, the present research proposes a new rule-based method for selecting turning points in business cycles, which eliminates subjectivity in the process of classifying market regimes. The proposed algorithm has a heuristic approach. No conditions are imposed to determine the duration of the regimes or the amplitude of their returns. Also, for the comparison between the proposed algorithm and the algorithms of Pagan, Lunde, White's bootstrap test has been used in various assets, including the Tehran Stock Exchange index, copper and gold metals, and oil commodities, and the Sharpe ratio has been used as a performance measure in out-of-sample data. The results show that the proposed algorithm has better or equal performance with other identification methods in identifying out-of-sample regimes, especially in time series that are different from capital market index data. The obtained results show the success of the proposed algorithm compared to other algorithms. The straightforward structure of the proposed algorithm avoids the potential fluctuations that occur in parameter optimization by providing a specific method and is useful and practical in identifying different regimes in various sets of time series without changing the parameters.

کلیدواژه‌ها [English]

  • Financial Market
  • Market Regimes
  • Financial Cycle
  • Bull Market
  • Bear Market
  • Rule-Based Algorithm

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چشم انداز مدیریت مالی
دوره 13، شماره 43
1402
صفحه 51-78

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