[
[1] Akgüller, Ö. (2019). A threshold method for financial networks and geometric scattering of agents. Communications in Statistics: Case Studies, Data Analysis and Applications, 5, 3, 230-242.
]Search in Google Scholar
[
[2] Akgüller, Ö., Balcı, M. A. (2018). Geodetic convex boundary curvatures of the communities in stock market networks. Physica A: Statistical Mechanics and its Applications, 505, 569-581.10.1016/j.physa.2018.03.087
]Search in Google Scholar
[
[3] Al-Awadhi, A. M., Al-Saifi, K., Al-Awadhi, A., Alhamadi, S. (2020). Death and contagious infectious diseases: Impact of the COVID–19 virus on stock market returns. Journal of Behavioral and Experimental Finance, 100326.10.1016/j.jbef.2020.100326
]Search in Google Scholar
[
[4] Ashraf, B. N. (2020). Economic impact of government interventions during the COVID–19 pandemic: International evidence from financial markets. Journal of Behavioral and Experimental Finance, 27, 100371.10.1016/j.jbef.2020.100371
]Search in Google Scholar
[
[5] Ashraf, B. N. (2020). Stock markets’ reaction to COVID–19: cases or fatalities? Research in International Business and Finance, 101249.10.1016/j.ribaf.2020.101249
]Search in Google Scholar
[
[6] Baker, S. R., Bloom, N., Davis, S. J., Kost, K., Sammon, M., Viratyosin, T. (2020). The unprecedented stock market reaction to COVID–19. The Review of Asset Pricing Studies. https://doi.org/10.1093/rapstu/raaa00810.1093/rapstu/raaa008
]Search in Google Scholar
[
[7] Balcı, M. A. (2018). Hierarchies in communities of Borsa Istanbul stock exchange. Hacettepe Journal of Mathematics and Statistics, 47, 4, 921-936.
]Search in Google Scholar
[
[8] Balcı, M. A., Akgüller,Ö., Güzel, S. C. (2020). Hierarchies in communities of UK stock market from the perspective of Brexit. Journal of Applied Statistics, 1-19.
]Search in Google Scholar
[
[9] Dashraath, P., et al. (2020). Coronavirus disease 2019 (COVID–19) pandemic and pregnancy. American journal of obstetrics and gynecology.10.1016/j.ajog.2020.03.021
]Search in Google Scholar
[
[10] Gates, B. (2020). Responding to Covid–19 -a once-in-a-century pandemic?. New England Journal of Medicine, 382, 18, 1677-1679.10.1056/NEJMp2003762
]Search in Google Scholar
[
[11] Goodell, J. W. (2020). COVID–19 and finance: Agendas for future research. Finance Research Letters, 101512.10.1016/j.frl.2020.101512
]Search in Google Scholar
[
[12] Guan, W. J., et al. (2020). Clinical characteristics of coronavirus disease 2019 in China. New England journal of medicine, 382, 18, 1708-1720.10.1056/NEJMoa2002032
]Search in Google Scholar
[
[13] Hatipoğlu, V. F. (2017). Application of a New Quantitative Approach to Stock Markets: Minimum Spanning Tree. Alphanumeric Journal, 5, 1, 163-169.
]Search in Google Scholar
[
[14] Holmes, et al. (2020). Multidisciplinary research priorities for the COVID–19 pandemic: a call for action for mental health science. The Lancet Psychiatry.10.1016/S2215-0366(20)30168-1
]Search in Google Scholar
[
[15] Jang, W., Lee, J., Chang, W. (2011). Currency crises and the evolution of foreign exchange market: Evidence from minimum spanning tree, Physica A, 390, 707–718.10.1016/j.physa.2010.10.028
]Search in Google Scholar
[
[16] Kazemilari, M., Mohamadi, A., Mardani, A., Streimikis, J. (2019). Network topology of renewable energy companies: minimal spanning tree and sub-dominant ultrametric for the American stock. Technological and Economic Development of Economy, 25, 2, 168-187.10.3846/tede.2019.7686
]Search in Google Scholar
[
[17] Kwapien, J., Gworek, S., Drozdz, S. (2009). Structure and evolution of the foreign exchange networks, Acta Physica Polonica B, 40, 175–194.
]Search in Google Scholar
[
[18] Li, B., Liao, Z. (2019). Finding changes in the foreign exchange market from the perspective of currency network. Physica A: Statistical Mechanics and its Applications, 545, 123727.
]Search in Google Scholar
[
[19] Liu, Z., Magal, P., Seydi, O., Webb, G. (2020). A COVID–19 epidemic model with latency period. Infectious Disease Modelling, 5, 323-337.10.1016/j.idm.2020.03.003718613432346664
]Search in Google Scholar
[
[20] Lyócsa, Š., Baumohl, E., Vỳrost, T., Molnár, P. (2020). Fear of the coronavirus and the stock markets. Finance research letters, 101735.10.1016/j.frl.2020.101735744877232868975
]Search in Google Scholar
[
[21] Nguyen, Q., Nguyen, N. K. K., Nguyen, L. H. N. (2019). Dynamic topology and allometric scaling behavior on the Vietnamese stock market. Physica A: Statistical Mechanics and its Applications, 514, 235-243.10.1016/j.physa.2018.09.061
]Search in Google Scholar
[
[22] Nguyen, Q., Nguyen, N. K. K. (2019). Composition of the first principal component of a stock index—A comparison between SP500 and VNIndex. Physica A: Statistical Mechanics and its Applications, 536, 120980.
]Search in Google Scholar
[
[23] Nicola, M., et al. (2020). The socio-economic implications of the coronavirus pandemic (COVID–19): A review. International journal of surgery (London, England), 78, 185.10.1016/j.ijsu.2020.04.018716275332305533
]Search in Google Scholar
[
[24] Noraee, S., Bahrol Olom, H. (2020). Responding to Covid–19 -A Once-in-a-Century Pandemic?. Biological Science Promotion, 3, 6, 162-164.
]Search in Google Scholar
[
[25] Petropoulos, F., Makridakis, S. (2020). Forecasting the novel coronavirus COVID–19. PloS one, 15, 3, e0231236.10.1371/journal.pone.0231236710871632231392
]Search in Google Scholar
[
[26] Pfefferbaum, B., North, C. S. (2020). Mental health and the Covid–19 pandemic. New England Journal of Medicine.10.1056/NEJMp200801732283003
]Search in Google Scholar
[
[27] Phan, D. H. B., Narayan, P. K. (2020). Country responses and the reaction of the stock market to COVID–19—A preliminary exposition. Emerging Markets Finance and Trade, 56, 10, 2138-2150.10.1080/1540496X.2020.1784719
]Search in Google Scholar
[
[28] Roosa, K., et al. (2020). Real-time forecasts of the COVID–19 epidemic in China from February 5th to February 24th, 2020. Infectious Disease Modelling, 5, 256-263.10.1016/j.idm.2020.02.002703334832110742
]Search in Google Scholar
[
[29] Saini, R., Kumar, P., Roy, P. P., Pal, U. (2019). Modeling Local and Global Behavior for Trajectory Classification using Graph Based Algorithm. Pattern Recognition Letters.
]Search in Google Scholar
[
[30] Shakil, M. H., Munim, Z. H., Tasnia, M., Sarowar, S. (2020). COVID–19 and the environment: A critical review and research agenda. Science of the Total Environment, 141022.10.1016/j.scitotenv.2020.141022736697032711074
]Search in Google Scholar
[
[31] Topcu, M., Gulal, O. S. (2020). The impact of COVID–19 on emerging stock markets. Finance Research Letters, 101691.10.1016/j.frl.2020.101691734859532837378
]Search in Google Scholar
[
[32] Wagner, A. F. (2020). What the stock market tells us about the post-COVID–19 world. Nature Human Behaviour, 4, 5, 440-440.10.1038/s41562-020-0869-y711495032242087
]Search in Google Scholar
[
[33] Wang, G. J., Xie, C., Han, F., Sun, B. (2012). Similarity measure and topology evolution of foreign exchange markets using dynamic time warping method: Evidence from minimal spanning tree. Physica A: Statistical Mechanics and its Applications, 391, 16, 4136-4146.
]Search in Google Scholar
[
[34] Yue, P., Gizem Korkmaz, A., Zhou, H. (2020). Household financial decision making amidst the COVID–19 pandemic. Emerging Markets Finance and Trade, 56, 10, 2363-2377.10.1080/1540496X.2020.1784717
]Search in Google Scholar
[
[35] Zou H., Yang J., (2019). Dynamic thresholding networks for schizophrenia diagnosis. Artificial intelligence in medicine, 96, 25-32.10.1016/j.artmed.2019.03.00731164208
]Search in Google Scholar
