Country Financial Risk and Stock Market Performance: The Case of Latin America

Author(s):  
Ephraim Alois Clark ◽  
Konstantinos Kassimatis
2021 ◽  
Vol 14 (4) ◽  
pp. 177
Author(s):  
Richard C. K. Burdekin ◽  
Samuel Harrison

This paper examines relative stock market performance following the onset of the coronavirus pandemic for a sample of 80 stock markets. Weekly data on coronavirus cases and deaths are employed alongside Oxford indices on each nation’s stringency and government support intensity. The results are broken down both by month and by geographical region. The full sample results show that increased coronavirus cases exert the expected overall effect of worsening relative stock market performance, but with little consistent impact of rising deaths. There is some evidence of significantly negative stock market effects arising from lockdowns as reflected in the Oxford stringency index. There are also positive reactions to government support in March and December in the overall sample—combined with some additional pervasive effects seen in mid-2020 in Latin America.


2022 ◽  
pp. 293-315
Author(s):  
Wookjae Heo ◽  
Eun Jin Kwak ◽  
John E. Grable

The purpose of this chapter is to compare the performance of a deep learning modeling technique to predict market performance compared to conventional prediction modeling techniques. A secondary purpose of this chapter is to describe the degree to which financial risk tolerance can be used to predict future stock market performance. Specifically, the models used in this chapter were developed to test whether aggregate investor financial risk tolerance is of value in establishing risk and return market expectations. Findings from this chapter's examples also provide insights into whether financial risk tolerance is more appropriately conceptualized as a predictor of market returns or as an outcome of returns.


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