بهبود عملکرد مدل‌های فاما - فرنچ در پیش‌بینی بازده انتظاری با ارائه تعاریف جدید از فاکتورهای ریسک در بورس تهران

محورهای موضوعی : سرمایه‌گذاری

علی محمدنژاداقدم ¹ , علیرضا فضل زاده ² , وحید احمدیان ³ , سجاد نقدی ⁴

1 - گروه اقتصاد و مدیریت، دانشگاه تبریز، تبریز، ایران.
2 - گروه اقتصاد و مدیریت، دانشگاه تبریز، تبریز، ایران.
3 - گروه اقتصاد و مدیریت، دانشگاه تبریز، تبریز، ایران.
4 - گروه اقتصاد و مدیریت، دانشگاه تبریز، تبریز، ایران.

تاریخ دریافت : 1401/05/13 تاریخ پذیرش : 1401/09/20 تاریخ انتشار : 1401/10/01

کلید واژه: بازده انتظاری, فاما - فرنچ, قیمت‌گذاری دارایی‌ها, مدل‌های چندعاملی,

چکیده مقاله :

هدف: در پژوهش حاضر به بررسی امکان بهبود عملکرد مدل‌های فاما - فرنچ در بورس تهران با استفاده از تعریف عوامل ریسک به روش‌های مختلف پرداخته شده است. هدف، تعیین عوامل ریسک با بیش‌ترین قدرت پیش‌بینی‌کنندگی بازده و همچنین شناسایی مدل بهینه بوده است.روش‌شناسی پژوهش: با استفاده از بازدهی ماهیانه شرکت‌های نمونه طی سال‌های 1384 تا 1400، الگوهای بازده غیرعادی سهام بررسی شدند. سپس، از آزمون جی آر اس و رویکرد فاما - مکبث برای بررسی خطای قیمت‌گذاری مدل‌ها و اندازه‌گیری صرف ریسک متغیرهای به‌کاررفته استفاده شد.یافته‌ها: نتایج نشان می‌دهد استفاده از متغیرهای جایگزین در مدل پنج‌عاملی، سبب کاهش خطای قیمت‌گذاری می‌گردد. همچنین، رویکرد فاما - مکبث در برآورد صرف ریسک نشان داد دو ریسک سودآوری و سرمایه‌گذاری در بورس تهران قیمت‌گذاری نشده‌اند؛ اما سبب معنی‌دارتر شدن صرف ریسک عوامل بازار، اندازه و ارزش شدند.اصالت / ارزش‌افزوده علمی: از نتایج پژوهش حاضر می‌توان برای کاهش خطای فرایند قیمت‌گذاری دارایی‌های مالی استفاده کرد. همچنین می‌توان از مدل بهینه معرفی شده در این پژوهش برای پیش‌بینی بازده سهام و طراحی استراتژی‌های سرمایه‌گذاری مبتنی بر آن بهره برد.

چکیده انگلیسی:

Purpose: In this research, the possibility of improving the Fama - French models using new definitions of risk factors in the Tehran Stock Exchange, has been investigated. The goal is to determine the risk factors with the highest predictive power and identify the optimal model.Methodology: Using the monthly returns of the sample firms during the 2006 to 2021 period, the abnormal stock returns were investigated. Then, using the GRS test and the Fama - Macbeth approach, we calculated the mispricing error of the models and the risk premia of each variable. The data used in the study were collected from Rahavard Novin and Codal databases.Findings: The results reveal that including new definitions of risk factors instead of the original ones in the models can reduce the mispricing error in the Fama - French five-factor model. Moreover, Fama - Macbeth regressions showed no profitability and investment effect in the Tehran Stock Exchange, although they strengthen the risk premia of the market, size and value factors.Originality / Value: The results of the present research can be used to reduce the error of the asset pricing process. Also, the optimal model introduced in this research can be utilized to predict stock returns and design investment strategies based on those returns.

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