بررسی عدم تقارن اطلاعات مالی در شرکت‌های دارویی پذیرفته شده در بورس اوراق بهادار تهران و پیش‌بینی بحران مالی آن‌ها با استفاده از شبکه عصبی مصنوعی

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی کارشناسی ارشد، گروه مهندسی صنایع – سیستم‌های مالی، دانشگاه میبد، میبد، ایران.

2 استادیار گروه مهندسی صنایع، دانشگاه میبد، یزد، ایران

3 دانشیار، گروه مهندسی صنایع، دانشگاه میبد، میبد، ایران

چکیده
بر اساس تحقیقات پیشین نسبت‌های مالی توانایی بالایی در پیش‌بینی بحران مالی شرکت‌ها دارند، اما اخیراً تحقیقات مبتنی بر متغیر‌های بازار و متغیر‌های اقتصادی مورد توجه محققین مالی قرارگرفته است. این پژوهش، ابتدا با بررسی مبحث تئوری عدم تقارن اطلاعات مالی شکل گرفته و از آن‌جایی که ذینفعان معمولاً شرایط مالی واقعی شرکت را قبل از وقوع مشکل مالی نمی‌دانند، به پیش‌بینی بحران مالی پرداخته است. هدف این پژوهش این است که بتواند با استفاده از متغیر‌های حسابداری، متغیر‌های کلان اقتصادی و بازار الگوی دقیق‌تری ارائه دهد تا ذینفعان با اتکا به قدرت پیش‌بینی این الگو‌ها، قادر باشند با اطمینان بیشتری تصمیم بگیرند. در این پژوهش با استفاده از داده‌های ۳۰ شرکت دارویی پذیرفته شده در بورس اوراق بهادار تهران در دوره زمانی سال‌های ۱۳۹۷ تا 1400 با استفاده از شبکه عصبی مصنوعی به پیش‌بینی بحران مالی پرداخته شده است. بر اساس نتایج تحقیق، مدل شبکه عصبی با متغیرهای منتخب نسبت بدهی، بازده دارایی، قیمت سهام، اندازه شرکت، شاخص قیمت مصرف کننده و رشد تولید ناخالص داخلی توانایی پیش‌بینی بحران مالی را دارد. برای پیش‌بینی بحران مالی شرکت‌ها، می‌توان از ترکیب متغیر‌های حسابداری، اقتصاد کلان و نیز متغیر‌های بازار استفاده کرد و همچنین تمام متغیر‌های منتخب در تحقیق، بر بحران مالی تأثیرگذارند.

کلیدواژه‌ها


عنوان مقاله English

Investigating financial information asymmetry in pharmaceutical companies listed on Tehran Stock Exchange and prediction their financial crisis using Artificial Neural Network

نویسندگان English

fatemeh heirani 1
najmeh neshat 2
Somayeh Mousavi 3
1 Master's student, Department of Industrial Engineering - Financial Systems, Meybod University, Meybod, Iran.
2 Assistant Professor, Department of Industrial Engineering, Meybod University, Yazd, Iran
3 Associate Professor, Department of Industrial Engineering, University of Meybod, Meybod, Iran
چکیده English

According to previous research, financial ratios have a high ability to predict the financial crisis of companies, but recently, research based on market variables and economic variables have attracted the attention of financial researchers. This research was first formed by examining the theory of asymmetry of financial information and since the stakeholders usually do not know the real financial conditions of the company before the occurrence of financial problems, it has predicted the financial crisis. The aim of this research is to be able to provide a more accurate model by using accounting variables, macroeconomic and market variables, so that stakeholders can make more confident decisions by relying on the predictive power of these models. In this research, using the data of 30 pharmaceutical companies admitted to the Tehran Stock Exchange in the period of 1397 to 1400, Based on the research results, the neural network model with selected variables of debt ratio, asset return, stock price, company size, consumer price index and GDP growth has the ability to predict the financial crisis. To predict the financial crisis of companies, it is possible to use the combination of accounting variables, macroeconomics and market variables, and also all the selected variables in the research affect the financial crisis.

کلیدواژه‌ها English

financial crisis
artificial neural network
financial information asymmetry
pharmaceutical companies
Tehran Stock Exchange
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