A New Approach for Analyzing Stock Market Stress Based on the Warsaw Stock Exchange in 2005–2019

References

• Anderson, H., and F. Vahid. 1998. “Testing Multiple Equation Systems for Common Nonlinear Components.” Journal of Econometrics 84 (1): 1–36. doi:10.1016/S0304-4076(97)00076-6.
   Web of Science ®Google Scholar
• Beck, K., and P. Stanek. 2019. “Globalization or Regionalization of Stock Markets? the Case of Central and Eastern European Countries.” Eastern European Economics 57 (4): 317–30. doi:10.1080/00128775.2019.1610895.
   Web of Science ®Google Scholar
• Bookstein, F. 1989. “Principal Warps: Thin – Plate Splines and the Decomposition of Deformations.” IEEE Transactions on Pattern Analysis and Machine Intelligence 11 (6): 567–85. doi:10.1109/34.24792.
   Web of Science ®Google Scholar
• Das, D., M. Kannadhasan, A. K. Tiwari, and K. H. Al-Yahyaee. 2018. “Has Co-movement Dynamics in Emerging Stock Markets Changed after Global Financial Crisis? New Evidence from Wavelet Analysis.” Applied Economics Letters 25 (20): 1447–53. doi:10.1080/13504851.2018.1430307.
   Web of Science ®Google Scholar
• Dryden, I. L., and K. V. Mardia. 2016. Statistical Shape Analysis: With Applications in R. 2nd ed. Chichester: John Wiley.
   Google Scholar
• Dua, P., and D. Tuteja. 2016. “Financial Crisis and Dynamic Linkages across International Stock and Currency Markets.” Economic Modelling 59:249–61. doi: 10.1016/j.econmod.2016.07.013.
   Web of Science ®Google Scholar
• Fleurbaey, M., and F. Maniquet. 2011. A Theory of Fairness and Social Welfare. Cambridge: Cambridge University Press.
   Google Scholar
• Galeano, P., D. Pena, and R. S. Tsay. 2006. “Outlier Detection in Multivariate Time Series by Projection Pursuit.” Journal of the American Statistical Association 101 (474): 654–69. doi:10.1198/016214505000001131.
   Web of Science ®Google Scholar
• Goodal, C. R., and K. V. Mardia. 1993. “Multivariate Aspects of Shape Theory.” The Annals of Statistics 21:848–66.
   Web of Science ®Google Scholar
• Görtz, Ch., and J. D. Tsoukalas. 2017. “News and Financial Intermediation in Aggregate Fluctuations.” The Review of Economics and Statistics 99 (3): 514–30. doi:10.1162/REST_a_00612.
   Web of Science ®Google Scholar
• Grabowski, W. 2019. “Givers or Recipients? Co-movements between Stock Markets of CEE-3 and Developed Countries.” Sustainability 11 (22): 6495. doi:10.3390/su11226495.
   Web of Science ®Google Scholar
• Hakkio, C. S., and W. R. Keeton. 2009. “Financial Stress: What Is It, How Can It Be Measured, and Why Does It Matter?” Economic Review 94 (2): 5–50.
   Google Scholar
• Hastie, T., R. Tibshirani, and J. Friedman. 2009. The Elements of Statistical Learning: Data Mining, Inference, and Prediction. New York: Springer.
   Google Scholar
• Huber, P., and E. M. Ronchetti. 2009. Robust Statistics. New York: John Wiley.
   Google Scholar
• Kiani, K. M. 2011. “Fluctuations in Economic and Activity and Stabilization Policies in the CIS.” Computational Economics 37 (2): 193–220. doi:10.1007/s10614-010-9233-z.
   Web of Science ®Google Scholar
• Kiani, K. M., and P. V. Bidarkota. 2004. “On Business Cycle Asymmetries in G7 Countries.” Oxford Bulletin of Economics and Statistics 66 (3): 333–51. doi:10.1111/j.1468-0084.2004.00082.x.
   Web of Science ®Google Scholar
• Klecha, T. 1996a. “Surface Stress Waves in a Nonhomogeneous Elastic Halfspace. Part I. General Results Based on Spectral Analysis. Existence and Analyticity Theorems.” Archives of Mechanics 48 (3): 493–512.
   Google Scholar
• Klecha, T. 1996b. “Surface Stress Waves in Nonhomogeneus Elastic Halfspace. Part II. Existence of Surface Waves for an Arbitrary Variation of Poisson’s Ratio. Approximate Solutions Based on Perturbation Methods.” Archives of Mechanics 48 (3): 513–39.
   Google Scholar
• Klecha, T. 2002. “The Application of a Small Parameter Method to Analysis of the Stress Surface Waves in a Nonhomogeneous Isotropic Halfspace.” The Bulletin of the Polish Academy of Sciences: Technical Sciences 50 (4): 285–285.
   Google Scholar
• Kosiorowski, D. 2006. “Statistical Theory of Shape in Comparative Analysis of Multivariate Economic Phenomena.” PhD diss., Cracow University of Economics.
   Google Scholar
• Kosiorowski, D. 2007. “Nonparametric Equality of Two Shapes Test Based on Multivariate Quantile Functional.” Bulletin of the International Statistical Institute 62:3669–72.
   Google Scholar
• Kosiorowski, D. 2009. “About Robust Estimators of Average Shape and Variance of Shape.” Acta Universitatis Lodziensis, Folia Oeconomica 225:187–96.
   Google Scholar
• Kosiorowski, D., D. Mielczarek, and J. P. Rydlewski. 2020. “A Critical Study of Usefulness of Selected Functional Classifiers in Economics.” Acta Universitatis Lodziensis. Folia Oeconomica 2 (347): 71–90. doi:10.18778/0208-6018.347.05.
   Google Scholar
• Kosiorowski, D., J. P. Rydlewski, and M. Snarska. 2019. “Detecting a Structural Change in Functional Time Series Using Local Wilcoxon Statistic.” Statistical Papers 60 (5): 1677–98. doi:10.1007/s00362-017-0891-y.
   Web of Science ®Google Scholar
• Kosiorowski, D., J. P. Rydlewski, and Z. Zawadzki. 2018. “Functional Outliers Detection by the Example of Air Quality Monitoring.” Statistical Review 65 (1): 81–98.
   Google Scholar
• Kosiorowski, D., and Z. Zawadzki. Forthcoming. “DepthProc: An R Package for Robust Exploration of Multidimensional Economic Phenomena.” Journal of Statistical Software.
   Google Scholar
• Landau, L.D., and E. M. Lifšic. 1959. Theory of Elasticity. Headington Hill Hall: Pergamon Press.
   Google Scholar
• Lee, J. W., and A. Nobi. 2017. “State and Network Structures of Stock Markets around the Global Financial Crisis.” Computational Economics 51 (2): 195–210. doi:10.1007/s10614-017-9672-x.
   Web of Science ®Google Scholar
• Liu, X., Y. Zuo, and Z. Wang. 2013. “Exactly Computing Bivariate Projection Depth Contours and Median.” Computational Statistics and Data Analysis 60:1–11. doi: 10.1016/j.csda.2012.10.016.
   Web of Science ®Google Scholar
• López-Pintado, S., and J. Romo. 2009. “On the Concept of Depth for Functional Data.” Journal of the American Statistical Association 104 (486): 718–34. doi:10.1198/jasa.2009.0108.
   Web of Science ®Google Scholar
• Maronna, R. A., R. D. Martin, and V. J. Yohai. 2006. Robust Statistics - Theory and Methods. Chichester: John Wiley.
   Google Scholar
• Moagar-Poladian, S., D. Clichici, and C. V. Stanciu. 2019. “The Comovement of Exchange Rates and Stock Markets in Central and Eastern Europe.” Sustainability 11 (14): 3985. doi:10.3390/su11143985.
   Web of Science ®Google Scholar
• Ramsay, J., G. Hooker, and S. Graves. 2009. Functional Data Analysis with R and Matlab. New York: Springer.
   Google Scholar
• Romer, D. 2012. Advanced Macroeconomics. New York: McGraw-Hill.
   Google Scholar
• Rydlewski, J. P., and M. Snarska. 2014. “On Geometric Ergodicity of Skewed – SVCHARME Models.” Statistics & Probability Letters 84:192–97. doi: 10.1016/j.spl.2013.10.008.
   Web of Science ®Google Scholar
• Tilfani, O., P. Ferreira, and M. Y. El Boukfaoui. 2019. “Revisiting Stock Market Integration in Central and Eastern European Stock Markets with Dynamic Analysis.” Post-Communist Economies 32 (5): 643–74. doi:10.1080/14631377.2019.1678099.
   Web of Science ®Google Scholar
• Truesdell, C. 1969. Rational Thermodynamics. New York: McGraw-Hill.
   Google Scholar
• Tsay, R. S. 2010. Analysis of Financial Time Series. Chichester: John Wiley.
   Google Scholar
• Tukey, J. W. 1975. “Mathematics and the Picturing of Data.” In Proceeding of the International Congress of Mathematicians, edited by R. D. James, vol. 2, 523–31. Vancouver: Canadian Mathematical Congress.
   Google Scholar
• Youssefmir, M., B. A. Huberman, and T. Hogg. 1998. “Bubbles and Market Crashes.” Computational Economics 12 (2): 97–114. doi:10.1023/A:1008693507721.
   Google Scholar
• Zuo, Y. 2006. “Multidimensional Trimming Based on Projection Depth.” The Annals of Statistics 34 (5): 2211–51. doi:10.1214/009053606000000713.
   Web of Science ®Google Scholar
• Zuo, Y., and R. Serfling. 2000. “General Notions of Statistical Depth Function.” The Annals of Statistics 28 (2): 461–82.
   Web of Science ®Google Scholar