Skip to main content Skip to main navigation menu Skip to site footer
BUSINESS & MANAGEMENT STUDIES:
AN INTERNATIONAL JOURNAL
Published: 2020-09-25

EFFECT OF FIRM RISK AND GOVERNANCE QUALITY ON STOCK VOLATILITY: AN APPLICATION WITH PARKINSON VOLATILITY MODEL

Asisst. Prof. Dr., İstanbul Aydın University
Financial markets volatility corporate governance risk

Abstract

LITERATURE
RESEARCH SUBJECT
The concept of volatility refers to the fluctuations in the price of a financial instrument or an index in a given period. The high volatility in financial markets means the expansion of the lower and upper-value range of the asset price. The presence of volatility is indicative of the risk of that asset, as it makes the predictability of the future price of the asset difficult.
Various economic, political and social factors in the markets lead to increased volatility (Karcıoğlu & Özer, 2017). At the firm level, some factors related to the financial structure and debt risk of the firm also affect stock volatility. This issue has been the subject of several studies in the literature (Sheikh & Wang, 2011; Ahmed & Hla, 2018; Aharon & Yagil, 2019).
Besides all these, effective management of firm risk is also related to the governance quality of the firm. In particular, the developments after the 2008 crisis caused corporate governance and early detection of risk and risk management to be handled together (Yaşar, 2016; Erdoğan, 2019). In this framework, this study focused on the impact of both firm risk and corporate governance practices on stock volatility.
RESEARCH PURPOSE AND IMPORTANCE
The purpose of this study is to analyze the effect of firm risk and governance quality on stock volatility. Theoretically, well-governed firms are expected to both manage risks better and be less affected by market fluctuations. This study aims to reveal this through econometric analysis.
CONTRIBUTION of the ARTICLE to the LITERATURE
This study is the first empirical research to analyze the effect of company risk and governance quality on stock volatility according to Parkinson's (1980) model, which aims to detect unobserved volatility. In this respect, it is aimed to contribute to the literature in terms of applying the Parkinson's model to risk and governance areas at the firm level by econometric analysis. Also, the study has proposed a new model for determining governance quality, based on continuity in corporate governance. In this regard, the study is expected to fill an essential gap in the literature.
DESIGN AND METHOD
RESEARCH TYPE
Quantitative research technique was used in the study. The effect of firm risk and governance quality on stock volatility was examined with two econometric models established, and panel data analysis was chosen as the method.
RESEARCH PROBLEMS
The research focuses on two main problems. The first is whether firms that have high debt risk and which place more weight on external resources in their capital structures have higher stock volatility. The second issue is determining the effect of governance quality on stock volatility.
DATA COLLECTION METHOD
The research covers 64 non-financial companies whose shares were continuously traded on Borsa Istanbul between 2008 and 2017. In the research, three different data types are used: stock price data, governance quality data and financial statement data. These data were collected from Borsa Istanbul (BIST), Public Disclosure Platform (KAP) and Corporate Governance Association of Turkey (TKYD). All these data used in the research has available to the public, investors and researchers. No extra information was requested from companies or other institutions.

QUANTITATIVE / QUALITATIVE ANALYSIS
Because the research involves time and horizontal cross-section dimensions, panel data analysis method was preferred. The following factors were also influential in choosing this method:
a) The data set covers ten years, including 2008, when the global financial crisis occurred. Since panel data analysis also takes into account changes over time, it allows both the crisis and post-crisis period to be handled together.
b) The research includes companies of different sizes from various sectors. Panel data analysis helps control the heterogeneity between units, thus preventing biased results (Baltagi, 2005).
c) Panel data analysis is more suitable for investigating the dynamics of change since it deals with repeated cross-sectional observations (Tarı, 2014).
In this research, STATA 14 and EVIEWS 9 programs were used for panel data analysis.
RESEARCH MODEL
The econometric models established for the research are as follows:
Model 1:
〖PRK〗_it= β_0+ 〖β_1 KYE〗_it+ 〖β_2 RISK〗_it+ 〖β_3 lnBUY〗_it+ 〖β_4 AKO〗_it+ ε_it

Model 2:
〖PRK〗_it= β_0+〖β_1 KYK〗_it+ 〖β_2 RISK〗_it+ 〖β_3 lnBUY〗_it+ 〖β_4 AKO〗_it+ ε_it

In the models, "i" represents the firms and "t" the years (between 2008 and 2017).
The stock volatility, which is the dependent variable of the study, was calculated based on the volatility model that was first proposed by Parkinson (1980), which assumes that asset prices follow the Brownian motion. There are two independent variables in the research, and the first one is the firm risk. Governance quality, the second independent variable, was calculated in two different ways and took place in separate models. By the literature, firm size and return on assets (ROA) were added to the models as control variables. Levin, Lin and Chu (LLC) Test, Honda Test and Hausman Test were applied regarding the panel data assumptions before panel data analysis.
RESEARCH HYPOTHESES
In line with the model mentioned above, the main hypotheses of the research are as follows:
H1: Firm risk has an impact on stock volatility.
H2: Governance quality has an impact on stock volatility.
FINDINGS AND DISCUSSION
FINDINGS as a RESULT of ANALYSIS
According to panel data regression analysis results, it was found that firm risk had a statistically positive effect on stock volatility in both models.
Another critical finding obtained from the research is that the governance quality of firms was found to affect stock volatility. In Model 1, the firms in the corporate governance index were determined to be less volatile than firms not included in the index. In Model 2, continuity in governance quality was included as an independent variable, and in this model, governance was found to affect volatility negatively.
HYPOTHESIS TEST RESULTS
Based on the research findings, both hypotheses have been accepted. Accordingly, both firm risk (H1 hypothesis) and governance quality (H2 hypothesis) have an impact on stock volatility.


DISCUSSING the FINDINGS with the LITERATURE
Since stock volatility is calculated according to the Parkinson model in the study, it differs from the studies in the literature. However, the finding that the firm risk obtained in this study increases volatility supports the results of the study found by Aharon and Yagil (2019), which calculates volatility by different methods.
As for the impact of governance quality on volatility, the findings of this research are mostly consistent with the results obtained by Lee, Hooy and Taib (2019). The results of the research also support the findings found by Bayraktaroğlu and Çelik (2015), Şahin, Öncü, and Sakarya (2015) and Güleç, Cergibozan and Çevik (2018). However, it should be noted that those studies were conducted on an index basis, not on a firm level, and volatility measurement methods were different from this study.
CONCLUSION, RECOMMENDATION AND LIMITATIONS
RESULTS of the ARTICLE
Volatility in stock prices is caused by many factors such as economic, social and political developments and trends in the financial markets. A firm cannot change, manage, direct or control all of these. However, there are also several financial and managerial factors affecting stock volatility at the firm level. In this study, firm risk and governance quality, which are among these factors at the firm level, were examined. Research results show that firms with high debt risk have higher stock volatility than in other firms. In another finding, it was found that the high quality of governance reduces stock volatility.
SUGGESTIONS BASED on RESULTS
The results of this research provide various suggestions and different perspectives to companies, regulatory bodies and investors.
Although debt risk and governance quality are analyzed as separate variables in this study, it is suggested that it should also be taken into consideration that they may be interrelated. In this context, it can be said that companies that include corporate governance principles in their business processes manage the risks better and are less affected by volatility. Governance and risk management are handled together in corporate governance codes and legislation in many countries. In this respect, it is recommended that governance quality should not be considered as an abstract concept involving only organizational processes.
LIMITATIONS of the ARTICLE
The most important limitation of the study is that it only covers companies in Turkey. Thus, the results should not be generalized. Future research applying this method for more than one country may provide more substantial evidence of causality behind this approach.

Downloads

Download data is not yet available.

References

  1. Aharon, D. ve Yagil, Y. (2019). The Impact of Financial Leverage on the Variance of Stock Returns. International Journal of Financial Studies, 7(1), 1-18.
  2. Ahmed, Z. ve Hla, D. (2018). Stock Return Volatility and Capital Structure Measures of Non-financial Firms in a Dynamic Panel Model: Evidence from Pakistan. International Journal of Finance & Economics, 1-25.
  3. Aloui, M. ve Jarboui, A. (2018). The Effects of Corporate Governance on the Stock Return Volatility: During the Financial Crisis. International Journal of Law and Management, 60(2), 478-495.
  4. Ararat, M., Black, B. ve Yurtoglu, B. (2017). The Effect of Corporate Governance on Firm Value and Profitability: Time-series Evidence from Turkey. Emerging Markets Review, 30, 113-132.
  5. Azzam, I. (2010). The Impact of Institutional Ownership and Dividend Policy on Stock Returns and Volatility:Evidence from Egypt. International Journal of Business, 15(4), 443-458.
  6. Baele, L. (2005). Volatility Spillover Effects in European Equity Markets. Journal of Financial and Quantitative Analysis, 40(2), 373-401.
  7. Baltagi, B. H. (2005). Econometric Analysis of Panel Data Third Edition. England: John Wiley & Sons.
  8. Baltagi, B. H., Song, S. H. ve Koh, W. (2003). Testing Panel Data Regression Models with Spatial Error Correlation. Journal of Econometrics, 117, 123-150.
  9. Batten, J. ve Lucey, B. (2010). Volatility in the Gold Futures Market. Applied Economics Letters, 17(2), 187-190.
  10. Baxter, N. (1967). Leverage, Risk of Ruin and the Cost of Capital. The Journal of Finance, 22(3), 395-403.
  11. Baykut, E. ve Kula, V. (2018). Borsa İstanbul Pay Endekslerinin Volatilite Yapısı: BİST-50 Örneği (2007-2016 Yılları). Afyon Kocatepe Üniversitesi Sosyal Bilimler Dergisi, 20(1), 279-303.
  12. Bayraktaroğlu, H. ve Çelik, İ. (2015). Kurumsal Yönetim Uygulamalarının Getiri Oynaklığı Üzerine Etkisi:Borsa İstanbul’da Bir Araştırma. Afyon Kocatepe Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 17(1), 97-108.
  13. Bayramoğlu, M. ve Abasız, T. (2017). Gelişmekte Olan Piyasa Endeksleri Arasında Volatilite Yayılım Etkisinin Analizi. Muhasebe ve Finansman Dergisi, 74, 183-200.
  14. Benli, Y. K. ve Yenisu, E. (2017). Doğrudan Yabancı Sermaye Yatırımlarının Ekonomik Büyümeye Etkisi: Türkiye İçin Eşbütünleşme ve Nedensellik Analizi. Gazi İktisat ve İşletme Dergisi, 3(2), 49-71.
  15. Bhandari, L. (1988). Debt/Equity Ratio and Expected Common Stock Returns: Empirical Evidence. The Journal of Finance, 43(2), 507-528.
  16. Breusch, T. ve Pagan, A. (1980). The Lagrange Multiplier Test and its Applications to Model Specification in Econometrics. The Review of Economic Studies, 47(1), Econometrics Issue, 239-253.
  17. Buallay, A., Allam, H. ve Qasim, Z. (2017). Corporate Governance and Firm Performance: Evidence from Saudi Arabia. Australasian Accounting, Business and Finance Journal, 11(1), 78-98.
  18. Cardoso, G., Carr, D. ve Rogers, P. (2019). Does Corporate Governance Matter for Stock Returns Volatility in the Brazilian Context? Corporate Governance, 19(6), 1236-1252.
  19. Chang, C.-L., Hsu, H.-K. ve McAleer, M. (2013). Is Small Beautiful? Size Effects of Volatility Spillovers for Firm Performance and Exchange Rates in Tourism. The North American Journal of Economics and Finance, 26, 519-534.
  20. Chytis, E., Tasios, S. ve Filos, I. (2020). The Effect of Corporate Governance Mechanisms on Tax Planning During Financial Crisis: An Empirical Study of Companies Listed on the Athens Stock Exchange. International Journal of Disclosure and Governance, https://doi.org/10.1057/s41310-020-00072-3.
  21. Corrado, C. ve Truong, C. (2007). Forecasting Stock Index Volatility: Comparing Implied Volatility and the Intraday High-low Price Range. The Journal of Financial Research, 30(2), 201-215.
  22. Dang, C., Li, Z. F. ve Yang, C. (2018). Measuring Firm Size in Empirical Corporate Finance. Journal of Banking & Finance, 86, 159-176.
  23. Danielsson, J., Valenzuela, M. ve Zer, I. (2018). Learning from History: Volatility and Financial Crises. The Review of Financial Studies, 31(7), 2774-2805.
  24. Erdoğan, D. (2019). Firmaların Kurumsal Yönetim Notunu Etkileyen Unsurlar: BİST 100 Örneği. Karabük Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 9(1), 63-79.
  25. Farooq, U. ve Jibran, A. Q. (2017). Firm Size as Moderator to Non-Linear Leverage-Performance Relation: An Emerging Market Review. Binus Business Review, 8(2), 99-106.
  26. Gupta, K., Krishnamurti, C. ve Tourani-Rad, A. (2013). Is Corporate Governance Relevant during the Financial Crisis? Journal of International Financial Markets, Institutions and Money, 23, 85-110.
  27. Güleç, Ö. F., Cergibozan, R. ve Çevik, E. (2018). BİST Endeksleri ile Kurumsal Yönetim Endeksi Arasındaki Volatilite İlişkisinin İncelenmesi. İşletme Araştırmaları Dergisi, 10(1), 17-44.
  28. Güngör, B. ve Güney, G. (2019). Kurumsal Yönetim Performansının Hisse Senedi Getirileri ile İlişkisi: Türkiye Örneği. Atatürk Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 23(1), 37-66.
  29. Hausman, J. (1978). Specification Tests in Econometrics. Econometrica, 46(6), 1251-1271.
  30. Honda, Y. (1985). Testing the Error Components Model with Non-Normal Disturbances. The Review of Economic Studies, 52(4), 681-690.
  31. Karcıoğlu, R. ve Özer, N. (2017). Hisse Senedi Piyasasında Yılın Ayları Anomalilerinin Getiri ve Volatilite Üzerindeki Etkisinin İncelenmesi: Borsa İstanbul Uygulaması. Atatürk Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 21(4), 1571-1596.
  32. Khan, W., Naz, A., Khan, M., Khan, W. ve Ahmad, S. (2013). Impact of Capital Structure and Financial Performance on Stock Returns: 'A Case of Pakistan Textile Industry'. Middle-East Journal of Scientific Research, 16(2), 289-295.
  33. Kula, V. ve Baykut, E. (2017). Borsa İstanbul Kurumsal Yönetim Endeksi (XKURY) İle Korku Endeksi (Chicago Board Options Exchange Volatility Index-VIX) Arasındaki İlişkinin Analizi. Afyon Kocatepe Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 19(2), 27-37.
  34. Laoworapong, M., Supattarakul, S. ve Swierczek, F. (2015). Corporate Governance, Board Effectiveness, and Performance of Thai Listed Firms. AU Journal of Management, 13(1), 25-40.
  35. Lee, S.-N., Hooy, C.-W. ve Taib, F. (2019). The Effect of Corporate Governance on Firm Stock Volatility in Asia. Journal of Asia-Pacific Business, 20(1), 25-47.
  36. Levin, A., Lin, C.-F., & Chu, C.-S. J. (2002). Unit Root Tests in Panel Data:Asymptotic and Finite-sample Properties. Journal of Econometrics, 108(1), 1-24.
  37. Modigliani, F. ve Miller, M. (1958). The Cost of Capital, Corporation Finance and the Theory of Investment. American Economic Review, 48(3), 261-297.
  38. Molnár, P. (2012). Properties of Range-based Volatility Estimators. International Review of Financial Analysis, 23, 20-29.
  39. Parkinson, M. (1980). The Extreme Value Method for Estimating the Variance of the Rate of Return. The Journal of Business, 53(1), 61-65.
  40. Salamat, W. ve Mustafa, H. (2016). The Impact of Capital Structure on Stock Return: Empirical Evidence from Amman Stock Exchange. International Journal of Business and Social Science, 7(9), 183-196.
  41. Sami, H., Wang, J. ve Zhou, H. (2011). Corporate Governance and Operating Performance of Chinese Listed Firms. Journal of International Accounting, Auditing and Taxation, 20(2), 106-114.
  42. Schwert, G. (1990). Stock Market Volatility. Financial Analysts Journal, 46(3), 23-34.
  43. Sharif, S. (2019). The Impact of Capital Structure on Stock Return of Selected Firms in the Pharmaceutical and Chemical Sector in Bangladesh. International Journal of Social Sciences Perspectives, 5(1), 9-21.
  44. Sheikh, N. ve Wang, Z. (2011). Determinants of Capital Structure. An Empirical Study of Firms in Manufacturing Industry of Pakistan. Managerial Finance, 37(2), 117-133.
  45. Şahin, Ö., Öncü, M. A. ve Sakarya, Ş. (2015). Bist 100 ve Kurumsal Yönetim Endeksi Volatilitelerinin Karşılaştırmalı Analizi. Cumhuriyet Üniversitesi İktisadi ve İdari Bilimler Dergisi, 16(2), 107-126.
  46. Tarı, R. (2014). Ekonometri, 10.Baskı. Kocaeli: Umuttepe Yayınları.
  47. Tatoğlu, F. Y. (2016). Panel Veri Ekonometrisi Genişletilmiş 3.Baskı. İstanbul: Beta Basım.
  48. Tatoğlu, F. Y. (2018). Panel Zaman Serileri Analizi Stata Uygulamalı 2.Baskı. İstanbul: Beta Basım.
  49. Torres-Reyna, O. (2007). Panel Data Analysis. Fixed and Random Effects using Stata (v. 4.2). Erişim adresi: https://www.princeton.edu/~otorres/Panel101.pdf
  50. Utami, M. ve Darmawan, A. (2019). Effect of DER, ROA, ROE, EPS and MVA on Stock Prices in Sharia Indonesian Stock Index. Journal of Applied Accounting and Taxation, 4(1), 15-22.
  51. Uyar, U. ve Çağlak, E. (2019). Çimento Sektörü Açısından Sistematik Risk – Finansal Oran İlişkisi: Ana Çimento Üreticisi Ülkeler Karşılaştırması. Muhasebe ve Finansman Dergisi, 81, 231-248.
  52. Vo, X. V. (2015). Foreign Ownership and Stock Return Volatility – Evidence from Vietnam. Journal of Multinational Financial Management, 30, 101-109.
  53. Yaşar, T. (2016). Anonim Şirketlerde Riskin Erken Saptanması ve Yönetimi. Ticaret ve Fikri Mülkiyet Hukuku Dergisi, 2(2), 69-91.
  54. Zakaria, Z., Muhammad, J. ve Zulkifli, A. H. (2012). The Impacy of Dvidend Policy on the Share Price Volatility: Malaysian Construction and Material Companies. International Journal of Economics and Management Sciences, 2(5), 1-8.

How to Cite

LEVENT, C. E. (2020). EFFECT OF FIRM RISK AND GOVERNANCE QUALITY ON STOCK VOLATILITY: AN APPLICATION WITH PARKINSON VOLATILITY MODEL. Business & Management Studies: An International Journal, 8(3), 2992-3020. https://doi.org/10.15295/bmij.v8i3.1537