طراحی و تبیین مدل ارزیابی ریسک‌پذیری بانک‌ها از شرایط عدم اطمینان سیاست پولی
محورهای موضوعی : مالی اسلامینفیسه وطن‌چی 1 , میرفیض فلاح شمس لیالستانی 2 * , غلامرضا زمردیان 3
1 - گروه مدیریت مالی، واحد تهران مرکزی، دانشگاه آزاد اسلامی، تهران، ایران.
2 - گروه مدیریت مالی، واحد تهران مرکزی، دانشگاه آزاد اسلامی، تهران، ایران.
3 - گروه مدیریت مالی واحد تهران مرکزی، دانشگاه آزاد اسلامی، تهران، ایران.
کلید واژه: ریسک‌پذیری بانک‌ها, عدم قطعیت سیاست پولی,
چکیده مقاله :
هدف: هدف کلی این مطالعه طراحی و تبیین مدل ارزیابی ریسک‌پذیری بانک‌ها از شرایط عدم اطمینان سیاست پولی میباشد.
روش‌شناسی پژوهش: این پژوهش بر اساس هدف، کاربردی است. به این منظور، سؤال پژوهش بر مبنای یک نمونة آماری متشکل از 9 بانک فعال در بورس اوراق بهادار تهران در بازه زمانی سالهای 1390 الی 1399 به‌صورت میان‌دوره‌ای مورد تحلیل و بررسی قرارگرفته است. نااطمینانی شاخصهای سیاست پولی با استفاده از روش واریانس شرطی خود رگرسیون تعمیم‌یافته نمایی و مدل نهایی با استفاده از روش پنل دیتا برآورد گردیده است.
یافته‌ها: نتایج حاصل از برآورد مدل بیانگر آن است که نااطمینانی سیاست پولی رابطه مثبت و معنادار با ریسک‌پذیری بانک‌های موردمطالعه دارد.
اصالت / ارزش‌افزوده علمی: باتوجه‌به اینکه در چند سال اخیر پس از بحران مالی سال 2008، سیاستهای پولی از طریق کانال جدیدی به نام کانال ریسک‌پذیری فعالان بخش پولی و مالی به‌ویژه بانک‌ها، بر فعالیت‌های واقعی اقتصاد مؤثر بوده است، لذا ارائه‌ی مدلی مبتنی بر ارزیابی ریسک‌پذیری بانک‌ها از شرایط عدم اطمینان سیاست پولی میتواند منجر به ارائه راهکارهای تجربی مناسب برای بانک‌ها و سیاست‌گذاران کشور گردد.
Objective: The main purpose of this study is to design and explain a model for assessing banks' risk-taking behavior under monetary policy uncertainty conditions.
Research Methodology: This research is application-oriented based on its objective. To this end, the research question was analyzed using a statistical sample comprising 9 banks listed on the Tehran Stock Exchange during the period from 2011 to 2020 on an interim basis. The uncertainty of monetary policy indicators was estimated using the Exponential Generalized Autoregressive Conditional Heteroskedasticity (EGARCH) method, and the final model was estimated using panel data methodology.
Findings: The results from the model estimation indicate that monetary policy uncertainty has a positive and significant relationship with the risk-taking behavior of the studied banks.
Originality/Scientific Value: Considering that in recent years following the 2008 financial crisis, monetary policies have affected real economic activities through a new channel called the risk-taking channel of monetary and financial sector participants, particularly banks, presenting a model based on assessing banks' risk-taking behavior under monetary policy uncertainty conditions can lead to appropriate empirical solutions for banks and national policymakers.
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