Investigating micro and macro factors affecting business risk in listed companies on the Tehran Stock Exchange

Subject Areas : Journal of Investment Knowledge

samira  olfati ¹ (PhD Student in Financial Engineering, Karaj Branch, Islamic Azad University, Karaj, Iran)
fereidoon  ohadi ² (Assistant Professor , Karaj Branch, Islamic Azad University of Karaj, Karaj, Iran)
hashem  Niko Maram ³ (Full professor, Science and Research Branch, Islamic Azad University, Tehran, Iran)

Received: 2021-06-16 Accepted : 2021-07-04 Published : 2024-09-22

Keywords: Business risk, Company specific features, Industry Features, Macroeconomic variables,

Abstract :

Non-financial data may refer to variables that represent the dimensions of the company's management. Company size and industry are other non-financial dimensions used when assessing business risk. In this regard, the purpose of this study is to explain the effect of micro and macro factors (specific characteristics of the company, industry characteristics, corporate governance, ownership structure and macroeconomic variables) on business risk in listed companies on the Tehran Stock Exchange. In order to achieve this purpose, 1752 firm-year (146 companies for 12 years) observations collected from the annual financial reports of listed companies on the Tehran Stock Exchange during the period 2007 to 2018 have been tested.Findings show that firm size, firm liquidity, firm profitability, firm growth opportunity, firm size, number of firms in industry, board independence, existence of audit committee and management ownership have a negative effect on business risk. while debt ratio and the exchange rate have a positive and significant effect on business risk. The results also show that statistically, firm life, industry decentralization, board size, duality of CEO duties, board financial expertise, audit committee size, audit committee independence, audit committee financial expertise, ownership type, Institutional shareholder ownership, major shareholder ownership, government ownership, interest rates and oil price growth have no effect on business risk.

References:

• ایزدی نیا، ناصر، علینقیان، نسرین (1389). بررسی رابطه خطای پیش‌بینی سود و ریسک مالی و تجاری در شرکت‌های پذیرفته‌شده در بورس اوراق بهادار تهران، تحقیقات حسابداری، شماره 7، صص 18-1.


• خلیلی علی‌آباد، آرزو (1392). بررسی تأثیر ریسک مالی و تجاری بر ساختار ﺳﺮﻣﺎﯾﻪ شرکت‌های پذیرفته‌شده در ﺑﻮرس اوراق ﺑﻬﺎدار ﺗﻬﺮان، پایان نامه کارشناسی ارشد، دانشگاه آزاد اسلامی واحد تهران مرکزی، دانشکده مدیریت.


• راهنمای رودپشتی، فریدون، موسوی ثابت، فرناز (1387). بررسی میزان ارتباط تداوم فعالیت با قیمت سهام، دانش مالی تحلیل اوراق بهادار (مطالعات مالی)، شماره 1، صص 105-79.


• عزتی، کژال (1395). بررسی ارتباط بین توانایی اقلام تعهدی و ریسک غیر سیستماتیک سهام بر مبنای مدل CAPM و مدل فاما و فرنچ در شرکتهای پذیرفته شده در بورس اوراق بهادار تهران، فصلنامه مطالعات مدیریت و حسابداری، دوره 2، شماره 2، صص 267-282.


• میرزائی، حسن؛ ختائی، محمدرضا؛ قنبری، یوسف (1393). بررسی رابطه بین ریسک تجاری و ریسک مالی با عملکرد شرکتهای دارویی پذیرفته شده در بورس اوراق بهادار تهران، فصلنامه حسابداری سلامت، شماره دوم، صص 91-77.


• نوروش، ایرج؛ وفادار، عباس (1378). بررسی سودمندی اطلاعات حسابداری در ارزیابی ریسک بازار شرکت ها در ایران، مجله حسابدار، شماره 135، صص 16-28.


• نیکومرام، هاشم، بادآور نهندی، یونس (1388). تبیین و ارائه الگویی برای تعیین و ارزیابی عوامل موثر بر کیفیت گزارشگری مالی در ایران، فراسوی مدیریت، شماره 8، صص 187-141.


• همت فر، ثقفی، مهدی (1396). بررسی عوامل موثر بر ریسک تجاری در شرکت های پذیرفته شده در بورس اوراق بهادار تهران. مجله بررسی های حسابداری، شماره 17، صص 138-115.


• Abdoh, H. Varela, O.(2017) Product market competition, idiosyncratic and systematic volatility. Journal of Corporate Finance, 43, pp. 500-513.


• Altman, E. I. Iwanicz-Drozdowska, M. Laitinen, E. K. & Suvas, A. (2017). Financial distress prediction in an international context: A review and empirical analysis of Altman's Z-Score model. Journal of International Financial Management and Accounting, 28(2), 131–171.


• Altman, E. I. Sabato, G. & Wilson, N. (2010). The value of non-financial information in small and medium-sized enterprise risk management. Journal of Credit Risk, 2(6), 95–127.


• Altman, E. I. Sabato, G. & Wilson, N. (2010). The value of non-financial information in small and medium-sized enterprise risk management. Journal of Credit Risk, 2(6), 95–127.


• Back, P. (2005). Explaining financial difficulties based on previous payment behavior, management background variables and financial ratios. European Accounting Review, 14(4), 839–868.


• Cultrera, L. & Brédart, X. (2016). Bankruptcy prediction: The case of Belgian SMEs. Review of Accounting and Finance, 15(1), 1–23.


• Doff, R. (2008) “Defining and Measuring Business Risk in an Economic- Capital Framework”. The Journal of Risk Finance, 9 (4): 317-333.


• Hernández-Tinoco, M. & Wilson, N. (2013). Financial distress and bankruptcy prediction among listed companies using accounting, market and macroeconomic variables. International Review of Financial Analysis, 30, 394–419.


• Hillegeist, S. A. Keating, E. K. Cram, D. P. & Lundstedt, K. G. (2004). Assessing the probability of bankruptcy. Review of Accounting Studies, 9(1), 5–34.


• Hopwood, W. McKeown, J. & Mutchler, J. (1989). A test of the incremental explanatory power of opinions qualified for consistency and uncertainty. The Accounting Review, 64(1), 28–48.


• Houmes, R.E. MacArthur, J.B. and Stranahan, H. (2012). “The Operating Leverage Impact on Systematic Risk within a Context of Choice: an Analysis of the US Trucking Industry”. Managerial Finance, 38 (12): 1184-1202.


• Kim, M. Kim, M. & McNiel, R. D. (2008). Predicting survival prospect of corporate restructuring in Korea. Applied Economics Letters, 15(15), 1187–1190.


• Laitinen, E. K. (1999). Predicting a corporate credit analyst's risk estimate by logistic and linear models. International Review of Financial Analysis, 8(2), 97–121.


• Laitinen, E. K. (2013). Financial and non-financial variables in prediction failure of small business reorganization. International Journal of Accounting and Finance, 4(1), 1–34.


• Laitinen, E. K. & Laitinen, T. (2009). Effect of accruals on financial, non-financial, and audit information in payment default prediction. International Journal of Accounting, Auditing and Performance Evaluation, 5(4), 353–383.


• Lensberg, T. Eilifsen, A. & McKee, T. E. (2006). Bankruptcy theory development and classification via genetic programming. European Journal of Operational Research, 169(2), 677–697.


• Lussier, R. N. (1995). A nonfinancial business success versus failure prediction model for young firms. Journal of Small Business Management, 33(1), 8–20.


• McKee, T. E. (2003). Rough sets bankruptcy prediction models versus auditor signaling rates. Journal of Forecasting, 22(8), 569–586.


• Veliyath, R. (1996). “Business Risk and Performance: An Examination of Industry Effects”. Journal of Applied Business Research, 12 (3): 37-47.