ANALYSING THE IMPACT OF FINANCIAL DISTRESS ON THE STOCK PRICE OF NON- FINANCIAL COMPANIES LISTED ON HOCHIMINH STOCK EXCHANGE IN THE CONTEXT OF COVID-19 PANDEMIC IN 2021
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Abstract
The research objective is that analysing the impact of financial distress on stock price of non-financial companies listed on the Hochiminh Stock Exchange (HOSE) in the context of COVID-19 pandemic in 2021. The research sample is 358 non-financial companies listed on HOSE in 2021. The result of research is pointed out that the increase in financial distress of companies made their stock price tends to decrease. The research is also proved that the company’s stock price will continue to increase if its Z-score is smaller than or equal 48.33. In contrast, if the company’s Z-score is larger than 48.33, its stock price will be downward. The result of research is stated that in the COVID-19 period, the companies which have high systematic risk, their stock price is smaller than the stock price of the companies having low systematic risk. Moreover, the significantly positive relationships between size, financial performance of company and its stock price is found in this research.
Keywords
Financial distress, systematic risk, market price per share, listed companies, COVID-19
Article Details
References
Andrade, G., Kaplan, S. (1998). How Costly is Financial (Not Economic) Distress? Evidence from Highly Leveraged Transactions that Became Distressed. The Journal of Finance, 53(5), page 1443-1493
Avramov, D., Chordia., T. and Goyl, A. (2006), Liquidity and autocorrelations in individual stock returns, Journal of Finance, 61(5), page 2365-2394
Asquith, p., Gertner, R., Sharfstein, D. (1994). Anatomy of Financial Distress: An Explanation of Junk Bond Issuers. The Quarterly Journal of Economics, 109, page 625- 658.
Beaver W. (1966), Financial ratios as predictors of failure, Journal of Accounting Research, 4, page 71–111.
Borlea S.N., & Achim M.V. (2014). Assessing bankruptcy risk for Romanian metallurgical companies, Metalurgija, 53(2), page 279–282.
Brown, D., James, C., Mooradian, R. (1993). The Information Content of Distressed Restructurings Involving Public and Private Debt Claims. Journal of Financia
Campbell, J.Y., Hilscher, J.D., Szilagyi, J. (2011), Predicting financial distress and the performance of distressed stocks. Journal of Investment Management, Volume 9(2), page 14-34
Christoforos K. A, Panayiotis C. A, Neophytos L (2021), Financial distress risk and stock price crashes, Journal of Corporate Finance, Volume 67, ISSN 0929-1199, (https://doi.org/10.1016/j.jcorpfin.2020.101870).
Davydenko, S. (2005), When Do Firms Default? A Study of the Default Boundary, Working Paper, London Business School.
Deakin E.B. (1972), A discriminant analysis of predictors of business failure. Journal of Accounting Research, 10(1), page 167–179.
Denis, D., Denis, D. (1995). Causes of Financial Distress Following Leveraged Re-capitalizations. Journal of Financial Economics, 37, page 129-157.
Diamond H.Jr. (1976), Pattern recognition and the detection of corporate failure (PhD dissertation). New York University.
Dichev.D.I (1998), Is the Risk of Bankruptcy a Systematic Risk?, The Journal of Finance, 53 (3), page 1131-1147.
Edmister R. (1972), An empirical test of financial ratio analysis for small business failure prediction. Journal of Financial and Quantitative Analysis, 7(2), page 1477–1493
Gao, P., Parsons, C.A., Shen, J. (2018), Global relation between financial distress and equity returns. The Review of Financial Studies, Volume 31(1), page 239-277
Garlappi, L. & Yan, H. (2011) Financial Distress and the Cross-Section of Equity Returns. Journal of Finance, 66, page 789-822.
Gestel, T., Baesens, B., Suykens, J., Van den Poel, D., Baestaens, D., Willekens, M. (2006). Bayesian Kernel Based Classification for Financial Distress Detection. European Journal of Operational Research, 172(3), page 979-1003.
Ghazali.W.A, Shafie. N.A & Sanusi.Z.M (2015), Earnings Management: An Analysis of Opportunistic Behaviour, Monitoring Mechanism and Financial Distress, Procedia Economics and Finance ,28, page 190-201.
Gilbert, L., Menon, K., Schwartz, K. (1990). Predicting Bankruptcy for Firms in Financial Distress. Journal of Business Finance and Accounting, 17, page 161-171.
Gordon, M. J. (1971), Towards a Theory of Financial Distress, The Journal of Finance, 26 (2), page 347-356.
Graham B., & Dodd D.L. (1934), Security analysis. New York, NY: McGraw-Hill.
Griffin.M.J & Lemmon.L.M (2002), Book-to-Market Equity, Distress Risk, and Stock Returns, The Journal of Finance, 57(5), page 2317-2336.
Koh H. (1987), Prediction of going-concern status: A probit model for the auditors (PhD dissertation), Virginia Polytechnic Institute and State University.
Martin, D. (1977). Early warning of bank failure: a logit regression approach. Journal of Banking & Finance, 1(3), page 249-276
Nguyễn Thị Ánh Ngọc, Dương Nguyễn Thanh Phương và Nguyễn Thanh Tùng (2021), Rủi ro kiệt quệ tài chính của doanh nghiệp niêm yết do COVID-19, Tạp chí Phát triển và Hội nhập, số 58, Trang 24-30.
Ohlson J.A. (1980). Financial ratios and the probabilistic prediction of bankruptcy. Journal of Accounting Research, 18(1), 109–131.
Opler, T., Titman, S. (1994). Financial Distress and Corporate Performance. The Journal of Finance, 49(3), 1015-1040
Platt, H., Platt, M. (2002). Predicting Corporate Financial Distress: Reflections on Choice-Based Sample Bias. Journal of Economics and Finance, 26(2), 184-199
Purnanandam, A. (2005). Financial Distress and Corporate Risk Management: Theory & Evidence. Working Paper, Ross School of Business, University of Michigan
Saji T.H, Financial Distress and Stock Market Failures: Lessons from Indian Realty Sector, Vision, Volume 22 (1), page 50-60
Chu Thị Thu Thuỷ (2019), Financial Distress Prediction on Companies Listed on The Ho Chi Minh Stock Exchange, Review of finance , Volume3, page 26-31.
Lê Thị Phương Vy (2020), Kiệt quệ tài chính và quản trị thu nhập: Bằng chứng thực nghiệm ở các công ty cổ phần niêm yết tại Việt Nam, Tạp chí nghiên cứu và kinh doanh Châu Á, số 2, trang 23-34.