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مقایسه مدل هفت عاملی با مدل قیمتگذاری داراییهای سرمایهای و مدل سه عاملی فاما و فرنچ برای پیشبینی بازده مورد انتظار سهام در بورس اوراق بهادار تهران | ||
راهبرد مدیریت مالی | ||
مقاله 1، دوره 10، شماره 4 - شماره پیاپی 39، دی 1401، صفحه 1-30 اصل مقاله (647.22 K) | ||
نوع مقاله: مقاله پژوهشی | ||
شناسه دیجیتال (DOI): 10.22051/jfm.2022.39196.2637 | ||
نویسندگان | ||
سکینه سجودی* 1؛ فاطمه موسوی2 | ||
1استادیار دانشکده اقتصاد و مدیریت دانشگاه تبریز | ||
2کارشناسی ارشد علوم اقتصادی، دانشکده اقتصاد و مدیریت، دانشگاه تبریز | ||
چکیده | ||
درک چرایی و چگونگی افزایش قیمت داراییها، یک نگرانی عمده برای صنایع، سیاستگذاران و سرمایهگذاران است. همین امر موجب جلب توجه محققان به موضوع قیمتگذاری داراییها بخصوص داراییهای پرخطر مانند سهام شده است. مدل قیمتگذاری داراییهای سرمایه ای تک عاملی CAPM)) و مدل سه عاملی فاما و فرنچ (1993) از جمله الگوهای مشهوری هستند که به دنبال توضیح انتظارات سرمایه گذاران برای بازده داراییهای پرخطر میباشند و بسطهای چندعاملی مختلفی از این الگوها ارائه شده است. یکی از آخرین نسخههای این الگوها، مدل هفت عاملی است که انتظار میرود در مقایسه با مدل CAPM و مدل سه عاملی فاما و فرنچ از قدرت توضیح دهندگی بالاتری برخوردار باشد. هدف این مطالعه ارزیابی مدل هفت عاملی در بورس اوراق بهادار تهران و مقایسه آن با مدل CAPM و مدل فاما و فرنچ به منظور پیشبینی بازده مورد انتظار سهام شرکتهای فعال در بخش مالی بورس اوراق بهادار تهران طی دوره 1395:1 تا 1398:12 است. در این مطالعه روش تخمین، الگوی خودتوضیح با وقفههای گسترده (ARDL) است. نتایج مطالعه نشان میدهد که مدل هفت عاملی، نسبت به مدلهای CAPM و فاما و فرنچ برآورد بهتری از بازده مورد انتظار بهدست میدهد. همچنین در مدل هفت عاملی متغیرهای نسبت ارزش دفتری به ارزش بازار، مومنتوم، نسبت گردش نقدینگی و شاخص کالا اثر منفی و معنیداری بر روی بازده مورد انتظار دارند. اما عامل بازار، شاخص اوراق قرضه دولتی و اندازه شرکت تاثیر معنیداری بر روی بازده مورد انتظار ندارد. | ||
کلیدواژهها | ||
بازده مورد انتظار سهام؛ مدل قیمتگذاری داراییهای سرمایهای؛ فاما و فرنچ؛ مدل هفت عاملی؛ بورس اوراق بهادار تهران | ||
عنوان مقاله [English] | ||
Comparison of the Seven-Factor Model with the Capital Assets Pricing Model and the Fama and French Three-Factor Model to Predict the Expected Returns of Stock in the Tehran Stock Exchange | ||
نویسندگان [English] | ||
Sakineh Sojoodi1؛ Fatemeh Mousavi2 | ||
1Assistant Professor, Faculty of Economics and Management, University of Tabriz, | ||
2MA. in Economics,Faculty of Economics and Management University of Tabriz | ||
چکیده [English] | ||
Understanding why and how asset prices rise is a major concern for industry, policymakers and investors. This has attracted the attention of researchers to the issue of asset pricing, especially high-risk assets such as stocks. The single-factor capital asset pricing model (CAPM) and the Fama and French (1993) three-factor model are some of the well-known models that seek to explain investors' expectations for high-risk asset returns, and various multifactorial extensions of these models have been proposed. One of the latest versions of these models is the seven-factor model, which is expected to have a higher explanatory power than the CAPM model and the Fama and French three-factor model. The purpose of this study is to evaluate the seven-factor model in Tehran Stock Exchange and compare it with CAPM model and Fama and French model in order to predict the expected returns of companies operating in the financial sector of Tehran Stock Exchange during the period 2016: 1 to 2019: 12. In this study, the estimation method is the Auto Regressive Distributed Lag (ARDL). The results of the study show that the seven-factor model gives a better estimate of the expected return than the CAPM and Fama and French models. Also in the seven-factor model, the variables of book value to market value ratio, momentum, liquidity turnover ratio and commodity index have a negative and significant effect on expected returns. But market factor, government bond index and company size factors do not have a significant effect on expected returns. | ||
کلیدواژهها [English] | ||
Expected Stock Returns, Capital Asset Pricing Model, Fama and French, Seven Factors Model, Tehran Stock Exchange | ||
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مراجع | ||
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