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THE EFFECT OF FINANCIAL STRESS ON STOCK MARKETS: AN EXAMPLE OF MINT ECONOMIES

Year 2024, Volume: 46 Issue: 2, 452 - 467, 24.10.2024
https://doi.org/10.14780/muiibd.1499394

Abstract

Increasing uncertainties due to developments in financial markets lead to uncontrollable financial behaviors. Financial stress indices are created by taking into account many different financial indicators directly related to the financial system. So, it is important to examine the impact of financial stress indices on stock markets, which have an important share in financial markets. The paper aims to investigate the short and long-term effects of emerging markets' financial stress index (EFSI) and global financial stress indices (GFSI) on the stock markets of MINT (Mexico, Indonesia, Nigeria, and Turkey) economies. For this purpose, analyses were made using the ARDL (Autoregressive Distributed Lag) Bounds Test method using weekly data for the period 10/01/2014-26/04/2024. It has been determined that EFSI and GFSI negatively affected the benchmark stock market indices of all MINT economies in the short term and that the negative effect continued in the long term but it has been significant for only EFSI in all MINT economies, as important results of the analysis. It has been determined that following financial stress indices can be a leading indicator for stock market investors. It is hoped that the results of the paper may be useful for financial market actors who are considering investing in these markets.

References

  • Armah, M., Bossman, A., & Amewu, G. (2023). Information flow between global financial market stress and African equity markets: An EEMD-based transfer entropy analysis. Heliyon, 9(3). https://doi.org/10.1016/j.heliyon.2023.e13899
  • Bouri, E., Gupta, R., Lau, C. K. M., Roubaud, D., & Wang, S. (2018). Bitcoin and global financial stress: A copula-based approach to dependence and causality in the quantiles. The Quarterly Review of Economics and Finance, 69, 297-307. https://doi.org/10.1016/j.qref.2018.04.003
  • Brown, R. L., Durbin, J., & Evans, J. M. (1975). Techniques for testing the constancy of regression relationships over time. Journal of the Royal Statistical Society Series B: Statistical Methodology, 37(2), 149-163. https://doi.org/10.1111/j.2517-6161.1975.tb01532.x
  • Das, D., Kannadhasan, M., & Bhattacharyya, M. (2019). Do the emerging stock markets react to international economic policy uncertainty, geopolitical risk, and financial stress alike?. The North American Journal of Economics and Finance, 48, 1-19. https://doi.org/10.1016/j.najef.2019.01.008
  • Das, D., Kumar, S. B., Tiwari, A. K., Shahbaz, M., & Hasim, H. M. (2018). On the relationship of gold, crude oil, stocks with financial stress: A causality-in-quantiles approach. Finance Research Letters, 27, 169-174. https://doi.org/10.1016/j.frl.2018.02.030
  • Dickey, D. A., & Fuller, W. A. (1981). Likelihood ratio statistics for autoregressive time series with a unit root. Econometrica: journal of the Econometric Society, 1057-1072. https://doi.org/10.2307/1912517 FRED, Federal Reserve Economic Data. St. Louis Fed Financial Stress Index. https://fred.stlouisfed.org/series/STLFSI4
  • Fu, Z., Chen, Z., Sharif, A., & Razi, U. (2022). The role of financial stress, oil, gold, and natural gas prices on clean energy stocks: global evidence from extreme quantile approach. Resources Policy, 78, 102860. https://doi.org/10.1016/j.resourpol.2022.102860
  • Günay, S., Öner, M., & Aybars, A. (2023). Return spillovers between emerging markets’ financial stress and equity markets of BRIC-T countries. Marmara Üniversitesi İktisadi ve İdari Bilimler Dergisi, 45(1), 108-121. https://doi.org/10.14780/muiibd.1317202
  • Gupta, R., Hammoudeh, S., Modise, M. P., & Nguyen, D. K. (2014). Can economic uncertainty, financial stress, and consumer sentiments predict US equity premium?. Journal of International Financial Markets, Institutions and Money, 33, 367-378. https://doi.org/10.1016/j.intfin.2014.09.004
  • Hakkio, C. S., & Keeton, W. R. (2009). Financial stress: What is it, how can it be measured, and why does it matter? Economic Review, 94(2), 5-50.
  • Hollo, D., Kremer, M., & Lo Duca, M. (2012). CISS – A Composite Indicator of Systemic Stress in the Financial System, ECB Working Paper Series, No.1426: 1-49.
  • Illing, M., & Liu, Y. (2003). An index of financial stress for Canada (No. 2003-14). Bank of Canada.
  • Illing, M., & Liu, Y. (2006). Measuring financial stress in a developed country: An application to Canada. Journal of Financial Stability, 2(3), 243-265. https://doi.org/10.1016/j.jfs.2006.06.002 Investing, https://tr.investing.com/
  • Kwiatkowski, D., Phillips, P. C., Schmidt, P., & Shin, Y. (1992). Testing the null hypothesis of stationarity against the alternative of a unit root: How sure are we that economic time series have a unit root?. Journal of Econometrics, 54(1-3), 159-178. https://doi.org/10.1016/0304-4076(92)90104-Y
  • Liang, C., Luo, Q., Li, Y., & Huynh, L. D. T. (2023). Global financial stress index and long-term volatility forecast for international stock markets. Journal of International Financial Markets, Institutions and Money, 88, 101825. https://doi.org/10.1016/j.intfin.2023.101825
  • Monin, P. J. (2019). The OFR financial stress index. Risks, 7(1), 25. https://doi.org/10.3390/risks7010025 OFR, Office of Financial Research. OFR Financial Stress Index. https://www.financialresearch.gov/financial-stress-index/
  • Park, C. Y., & Mercado Jr, R. V. (2014). Determinants of financial stress in emerging market economies. Journal of Banking & Finance, 45, 199-224. https://doi.org/10.1016/j.jbankfin.2013.09.018
  • Pesaran, M. H., & Shin, Y. (1995). An autoregressive distributed lag modeling approach to cointegration analysis (Vol. 9514). Cambridge, UK: Department of Applied Economics, University of Cambridge.
  • Pesaran, M. H., Shin, Y., & Smith, R. J. (2001). Bounds testing approaches to the analysis of level relationships. Journal of Applied Econometrics, 16(3), 289-326. https://doi.org/10.1002/jae.616
  • Xu, Y., Liang, C., & Wang, J. (2023). Financial stress and returns predictability: Fresh evidence from China. Pacific-Basin Finance Journal, 78, 101980. https://doi.org/10.1016/j.pacfin.2023.101980
  • Zhang, D., & Li, B. (2022). What can we learn from financial stress indicator? Finance Research Letters, 50, 103293. https://doi.org/10.1016/j.frl.2022.103293
  • Zivot, E., & Andrews, D. W. K. (1992). Further evidence on the great crash, the oil price shock, and the unit-root hypothesis. Journal of Business & Economic Statistics, 10(3), 25-44.

FİNANSAL STRESİN HİSSE SENEDİ PİYASALARI ÜZERİNDEKİ ETKİSİ: MINT EKONOMİLERİ ÖRNEĞİ

Year 2024, Volume: 46 Issue: 2, 452 - 467, 24.10.2024
https://doi.org/10.14780/muiibd.1499394

Abstract

Finansal piyasalarda yaşanan gelişmeler dolayısıyla artan belirsizlikler kontrol edilemeyen finansal davranışlara yol açmaktadır. Finansal stres endeksleri doğrudan finansal sistem ile ilişkili birçok farklı finansal gösterge dikkate alınarak oluşturulmaktadır. Bu nedenle finansal stres endekslerinin finansal piyasalarda önemli payı olan hisse senedi piyasaları üzerindeki etkisinin incelenmesi önem arz etmektedir. Çalışmada gelişen piyasalar finansal stres endeksi (EFSI) ile küresel finansal stres endekslerinin (GFSI) MINT (Mexico, Indonesia, Nigeria and Türkiye) ekonomilerine ait hisse senedi piyasaları üzerindeki kısa ve uzun dönemli etkilerinin araştırılması amaçlanmıştır. Bu amaçla 10/01/2014-26/04/2024 dönemine ait haftalık veriler kullanılarak ARDL (Autoregressive Distrubited Lag) Sınır Testi methodu ile analizler yapılmıştır. Analizler sonucunda MINT ekonomilerinin tümü için EFSI ve GFSI’nın kısa dönemde ülkelerin gösterge borsa endekslerini negatif etkilediği, uzun dönemde ise bu olumsuz etkinin devam ettiği fakat EFSI için anlamlı olduğu tespit edilmiştir. Finansal stres endekslerini takip etmenin borsa yatırımcıları için öncü bir gösterge olabileceği belirlenmiştir. Çalışma sonuçlarının bu piyasalara yatırım yapma düşüncesindeki piyasa aktörleri için yararlı olabileceği umulmaktadır.

References

  • Armah, M., Bossman, A., & Amewu, G. (2023). Information flow between global financial market stress and African equity markets: An EEMD-based transfer entropy analysis. Heliyon, 9(3). https://doi.org/10.1016/j.heliyon.2023.e13899
  • Bouri, E., Gupta, R., Lau, C. K. M., Roubaud, D., & Wang, S. (2018). Bitcoin and global financial stress: A copula-based approach to dependence and causality in the quantiles. The Quarterly Review of Economics and Finance, 69, 297-307. https://doi.org/10.1016/j.qref.2018.04.003
  • Brown, R. L., Durbin, J., & Evans, J. M. (1975). Techniques for testing the constancy of regression relationships over time. Journal of the Royal Statistical Society Series B: Statistical Methodology, 37(2), 149-163. https://doi.org/10.1111/j.2517-6161.1975.tb01532.x
  • Das, D., Kannadhasan, M., & Bhattacharyya, M. (2019). Do the emerging stock markets react to international economic policy uncertainty, geopolitical risk, and financial stress alike?. The North American Journal of Economics and Finance, 48, 1-19. https://doi.org/10.1016/j.najef.2019.01.008
  • Das, D., Kumar, S. B., Tiwari, A. K., Shahbaz, M., & Hasim, H. M. (2018). On the relationship of gold, crude oil, stocks with financial stress: A causality-in-quantiles approach. Finance Research Letters, 27, 169-174. https://doi.org/10.1016/j.frl.2018.02.030
  • Dickey, D. A., & Fuller, W. A. (1981). Likelihood ratio statistics for autoregressive time series with a unit root. Econometrica: journal of the Econometric Society, 1057-1072. https://doi.org/10.2307/1912517 FRED, Federal Reserve Economic Data. St. Louis Fed Financial Stress Index. https://fred.stlouisfed.org/series/STLFSI4
  • Fu, Z., Chen, Z., Sharif, A., & Razi, U. (2022). The role of financial stress, oil, gold, and natural gas prices on clean energy stocks: global evidence from extreme quantile approach. Resources Policy, 78, 102860. https://doi.org/10.1016/j.resourpol.2022.102860
  • Günay, S., Öner, M., & Aybars, A. (2023). Return spillovers between emerging markets’ financial stress and equity markets of BRIC-T countries. Marmara Üniversitesi İktisadi ve İdari Bilimler Dergisi, 45(1), 108-121. https://doi.org/10.14780/muiibd.1317202
  • Gupta, R., Hammoudeh, S., Modise, M. P., & Nguyen, D. K. (2014). Can economic uncertainty, financial stress, and consumer sentiments predict US equity premium?. Journal of International Financial Markets, Institutions and Money, 33, 367-378. https://doi.org/10.1016/j.intfin.2014.09.004
  • Hakkio, C. S., & Keeton, W. R. (2009). Financial stress: What is it, how can it be measured, and why does it matter? Economic Review, 94(2), 5-50.
  • Hollo, D., Kremer, M., & Lo Duca, M. (2012). CISS – A Composite Indicator of Systemic Stress in the Financial System, ECB Working Paper Series, No.1426: 1-49.
  • Illing, M., & Liu, Y. (2003). An index of financial stress for Canada (No. 2003-14). Bank of Canada.
  • Illing, M., & Liu, Y. (2006). Measuring financial stress in a developed country: An application to Canada. Journal of Financial Stability, 2(3), 243-265. https://doi.org/10.1016/j.jfs.2006.06.002 Investing, https://tr.investing.com/
  • Kwiatkowski, D., Phillips, P. C., Schmidt, P., & Shin, Y. (1992). Testing the null hypothesis of stationarity against the alternative of a unit root: How sure are we that economic time series have a unit root?. Journal of Econometrics, 54(1-3), 159-178. https://doi.org/10.1016/0304-4076(92)90104-Y
  • Liang, C., Luo, Q., Li, Y., & Huynh, L. D. T. (2023). Global financial stress index and long-term volatility forecast for international stock markets. Journal of International Financial Markets, Institutions and Money, 88, 101825. https://doi.org/10.1016/j.intfin.2023.101825
  • Monin, P. J. (2019). The OFR financial stress index. Risks, 7(1), 25. https://doi.org/10.3390/risks7010025 OFR, Office of Financial Research. OFR Financial Stress Index. https://www.financialresearch.gov/financial-stress-index/
  • Park, C. Y., & Mercado Jr, R. V. (2014). Determinants of financial stress in emerging market economies. Journal of Banking & Finance, 45, 199-224. https://doi.org/10.1016/j.jbankfin.2013.09.018
  • Pesaran, M. H., & Shin, Y. (1995). An autoregressive distributed lag modeling approach to cointegration analysis (Vol. 9514). Cambridge, UK: Department of Applied Economics, University of Cambridge.
  • Pesaran, M. H., Shin, Y., & Smith, R. J. (2001). Bounds testing approaches to the analysis of level relationships. Journal of Applied Econometrics, 16(3), 289-326. https://doi.org/10.1002/jae.616
  • Xu, Y., Liang, C., & Wang, J. (2023). Financial stress and returns predictability: Fresh evidence from China. Pacific-Basin Finance Journal, 78, 101980. https://doi.org/10.1016/j.pacfin.2023.101980
  • Zhang, D., & Li, B. (2022). What can we learn from financial stress indicator? Finance Research Letters, 50, 103293. https://doi.org/10.1016/j.frl.2022.103293
  • Zivot, E., & Andrews, D. W. K. (1992). Further evidence on the great crash, the oil price shock, and the unit-root hypothesis. Journal of Business & Economic Statistics, 10(3), 25-44.
There are 22 citations in total.

Details

Primary Language English
Subjects Capital Market, International Finance
Journal Section Makaleler
Authors

Kübra Saka Ilgın 0000-0001-5797-9617

Publication Date October 24, 2024
Submission Date June 11, 2024
Acceptance Date September 6, 2024
Published in Issue Year 2024 Volume: 46 Issue: 2

Cite

APA Saka Ilgın, K. (2024). THE EFFECT OF FINANCIAL STRESS ON STOCK MARKETS: AN EXAMPLE OF MINT ECONOMIES. Marmara Üniversitesi İktisadi Ve İdari Bilimler Dergisi, 46(2), 452-467. https://doi.org/10.14780/muiibd.1499394
AMA Saka Ilgın K. THE EFFECT OF FINANCIAL STRESS ON STOCK MARKETS: AN EXAMPLE OF MINT ECONOMIES. Marmara Üniversitesi İktisadi ve İdari Bilimler Dergisi. October 2024;46(2):452-467. doi:10.14780/muiibd.1499394
Chicago Saka Ilgın, Kübra. “THE EFFECT OF FINANCIAL STRESS ON STOCK MARKETS: AN EXAMPLE OF MINT ECONOMIES”. Marmara Üniversitesi İktisadi Ve İdari Bilimler Dergisi 46, no. 2 (October 2024): 452-67. https://doi.org/10.14780/muiibd.1499394.
EndNote Saka Ilgın K (October 1, 2024) THE EFFECT OF FINANCIAL STRESS ON STOCK MARKETS: AN EXAMPLE OF MINT ECONOMIES. Marmara Üniversitesi İktisadi ve İdari Bilimler Dergisi 46 2 452–467.
IEEE K. Saka Ilgın, “THE EFFECT OF FINANCIAL STRESS ON STOCK MARKETS: AN EXAMPLE OF MINT ECONOMIES”, Marmara Üniversitesi İktisadi ve İdari Bilimler Dergisi, vol. 46, no. 2, pp. 452–467, 2024, doi: 10.14780/muiibd.1499394.
ISNAD Saka Ilgın, Kübra. “THE EFFECT OF FINANCIAL STRESS ON STOCK MARKETS: AN EXAMPLE OF MINT ECONOMIES”. Marmara Üniversitesi İktisadi ve İdari Bilimler Dergisi 46/2 (October 2024), 452-467. https://doi.org/10.14780/muiibd.1499394.
JAMA Saka Ilgın K. THE EFFECT OF FINANCIAL STRESS ON STOCK MARKETS: AN EXAMPLE OF MINT ECONOMIES. Marmara Üniversitesi İktisadi ve İdari Bilimler Dergisi. 2024;46:452–467.
MLA Saka Ilgın, Kübra. “THE EFFECT OF FINANCIAL STRESS ON STOCK MARKETS: AN EXAMPLE OF MINT ECONOMIES”. Marmara Üniversitesi İktisadi Ve İdari Bilimler Dergisi, vol. 46, no. 2, 2024, pp. 452-67, doi:10.14780/muiibd.1499394.
Vancouver Saka Ilgın K. THE EFFECT OF FINANCIAL STRESS ON STOCK MARKETS: AN EXAMPLE OF MINT ECONOMIES. Marmara Üniversitesi İktisadi ve İdari Bilimler Dergisi. 2024;46(2):452-67.