Study of Financial Distress Spillover Effect among Automobile Supply Chain Companies

محورهای موضوعی : Financial Economics

Mirfeiz Fallahshams ¹ , Bita Delnavaz ²

1 - Associate Professor, Department of Business Management, Central Tehran Branch , Islamic Azad University, Tehran, Iran
2 - Finance Department, Management Faculty, Central Tehran Branch, Islamic Azad University, tehran, Iran

تاریخ دریافت : 1398/01/27 تاریخ پذیرش : 1398/10/10 تاریخ انتشار : 1400/10/11

کلید واژه: Supply chain Companies, Key words: Distress Finance, Spillover effect, Multivariate GARCH Model,

چکیده مقاله :

Multiplicity of the companies experiencing financial distress in different countries and as a consequence, their bankruptcy and the impacts on other companies have necessitated conducting research on methods of prediction of such conditions and also their effects on other companies in the market. In this regard, this research has investigated the financial distress spillover in the automobile supply chain companies. For doing so, the methods of default probability time series KMV and the distance from default of four supply chain companies of Iran Khodro and four supply chain companies of SAIPA were calculated. Then, the financial distress spillover in these two major companies was measured in separated models using multivariate GARCH model. The results of the default probability of Iran Khodro companies showed that the default probability with pause of Khodro on the default probability of supply chain companies was significant and negative in 10% level. The results for SAIPA supply chain companies revealed that the default probability with pause of Khaspa had an impact on default probability of Kaspa, Pask and Khazin in significance level of 10%.

منابع و مأخذ:

[1] Helleiner, E., Understanding the 2007–2008 Global Financial Crisis: Lessons for Scholars of International Political Economy, Department of Political Science, University of Waterloo, Waterloo, Ontario N2L 3G1, Canada; 2011, P. 67-87. Doi:10.1146/annurev-polisci-050409-112539.

[2] Giammarino, R., Jan. M., The resolution of financial distress, The Review of Financial Studies, 2010, 2, P. 25-47. Doi:10.1080/1226508X.2010.483834.

[3] Gertner, R., Scharfstein, D., A theory of workouts and the effects of reorganization law, The Journal of Finance 1991, 46, P.1189–1222. Doi:10.1111/i.1540-6261.1991.tb04615.x.

[4] Mooradian, R., The effect of bankruptcy protection on investment: Chapter 11 as a screening device, The Journal of Finance, 1994,49, P. 1403-1430. Doi:10.1111/i.1540-6261.1994.tb02459.x.

[5] Lang, L.H.P., Stulz, R.M., Contagion and competitive intra-industry effects of bankruptcy announcements, journal of financial Economics, 1992, 32, P. 45-60. Doi:10.1016/0304-405x(92)90024-r.

[6] Shoag, D., Veuger, S., Shops and the city: evidence on local externalities and local government policy from big box bankruptcies, Review of Economics and Statistics, 2018, 100, P.440-453.  Doi:10.1162/rest_a_00703.

 [7] Moon, G, W. Yu., Volatility Spillovers between the U.S. and the China Stock Market: Structural Break Test with Symmetric and Asymmetric GARCH Approach, Department of Business Administration, Kyonggi University, 2010, P.129-149. Doi:10.1080/1226508X.2010.483834.

[8] Altman, E. I., Hotchkiss, E., Corporate Financial Distress and Bankruptcy, 3rd edition. New Jersey, Hoboken: J. Wiley and Sons, 2006, P.19-38. Doi:10.4236/ib.2018.101002.

[9] Zhao, L., Huchzermeier, A., Managing supplier Þnancial distress with advance payment discount and purchase order financing, the international journal of management science, Accepted date: 24 October 2018. 3 Reads, Doi:10.1016/j.omega.2018.10.019.

[10] Adams, Z, Füss, R, and Gropp, R., Spillover effects among financial institutions:A state-dependent sensitivity value-at-risk approach, Journal of Financial and Quantitative Analysis, 2014, 49(3), P.575-598.

Doi:10.1017/S0022109014000325.

[11] Bussière, M., Hoerova, M., and Klaus, B., Commonality in hedge fund returns: Driving factors and implications, Journal of Banking and Finance, 2015, 54, P. 266-280.  Doi:10.1016/j.jbankfin.2014.01.039.

[12] Thiele, A., Finanzaufsicht: Der Staat und die Finanzmärkte [Financial supervision: The State and financial markets. Tübingen: Mohr Siebeck.UBS, 2012. Fact Sheet. UBS-ETG HFRX Global Hedge Fund (USD) SF-A. 2014, P.    ISSN: 0941-0503 - Zitiervorschlag: JusPubl.

[13] Arouri, M.E. H., Hammoudeh, S., Lahiani, A., Nguyen, D.K., Long Memory and Structural Breaks in Modeling the Return and Spillover Dynamics of Precious Metals, Quarterly Review of Economics and Finance, 2012, 52(2), P. 207–218. Doi 10.1016/j.qref.2012.04.004.

[14] Izadikhah, M., Farzipoor Saen, R., Ranking sustainable suppliers by context-dependent data envelopment analysis, Ann Oper Res, 2020, 293, P. 607–637, Doi: 10.1007/s10479-019-03370-4

[15] Batten, J.A., Ciner, C., and Lucey, B.M., The Macroeconomic Determinants of Volatility in Precious Metals Markets, Resources Policy, 2010, 35(2), P. 65-71 Doi: 10.1016/j.resourpol.2009.12.002.

[16] Baur, D.G., and Lucey, B.M., IsGold a Hedge or a Safe Haven? An Analysis of Stocks, Bonds and Gold, Financial Review, he Financial Review, 2010, 45, P. 217-229.  Doi: 10.1111/j.1540-6288.2010.00244.x.

[17] Cochran, S.J., Mansur, I., Odusami, B., Volatility Persistence in Metal Returns: a FIGARCH Approach, Journal of Economics and Business, 2012, 64(4), P. 287-305. Doi: 10.1016/j.jeconbus.2012.03.001.

[18] Diamandis, P.F., International Stock Market Linkages: Evidence from Latin America, Global Finance Journal, 2000, 20(1), P.13-30.  Doi:10.1016/j.gfj.2009.03.005.

[19] Engle, R.F., Kraft, D., Kroner, K.F., Multivariate Simultaneous Generalized ARCH, Unpublished manuscript, Department of Economics, University of California, San Diego, CA, USA, 2009, 11(1), P. 122-150.

Doi: 10.1017/S0266466600009036.

[20] Engle, R.F., Kroner, K.F., Multivariate Simultaneous Generalized ARCH, Econometric Theory, 1995, 11(1), P. 122-150.  Doi:10.1017/S0266466600009063.

[21] Wadecki, A.A., Babich, V., Wu, O.Q., Manufacturer competition and subsidies to suppliers, Supply Chain Disruptions. Springer, 27 September 2011, 2012, P. 141-163. Doi: 10.2139/ssrn.1616949

 [22] Adrangi, B., Chatrath, A., The Dynamics of Palladium and Platinum Prices, Computational Economics, 2002, 19(2), P. 179-197. Doi:10,1023/A:1015051912125.

[23] Bernstein, S., Colonnelli, E., Giroud, X., Iverson, B., Bankruptcy spillovers, Journal of Financial Economics, 2019, 133 (3), P. 608-633, Doi: 10.1016/j.jfineco.2018.09.010.

[24] Branch, B., and Min Xu, Hedge Fund Investments in Bankruptcy, The Journal of Alternative Investments, 2014, P. 51-60. Doi:10.3905/jai.2014.16.4.051, 16, 4.

[25] Christie-David, R., Chaudhry, M., and Koch, T.W., Do Macroeconomics News Releases Affect Gold and Silver Prices? Journal of Economics and Business, 2000, 52(5), P. 405-421.  Doi:10.1016/S0148-6195(00)00029-1

[26] Usman, M., Umer, Coskun, M., Kiraci, K., Time-varying Return and Volatility Spillover among EAGLEs Stock Markets: A Multivariate GARCH Analysis, Journal of Finance and Economics Research, 2018, 3(1), P.23-42, Doi:10.20547/jfer1803102.

[27] Bernstein, S., Colonnelli, E., Giroud, X., and Iverson, B., Bankruptcy Spillovers, Journal of Financial Economics, 2019, 133(3), P. 608-633. Doi:10.1016/j.jfineco.2018.09.010.

[28] Hammoudeh, S., Yuan, Y., McAleer, M., Thompson, M., Precious Metals–Exchange Rate Volatility Transmissions and Hedging Strategies, International Review of Economics and Finance, 2010, 19(4), P.633-647.

 Doi: 10.1016/j.iref.2010.02.003.

 [29] Muvingi, J., Nkomo, D., Mazuruse, P., and Mapungwana, P., Default Prediction Models a Comparison between Market Based Models and Accounting Based: Case of the Zimbabwe Stock Exchange 2010-2013, Journal of Finance and Investment Analysis, 2015, 4(1), P. 39-65.

 

[30] Koop, G., Pesaran, M.H., and Potter, S.M., Impulse Response Analysis in Non-Linear Multivariate Models, Journal of Econometrics, 1996, 74(1), P. 119-147.  Doi:10.1016/0304-4076(95)01753-4.