scholarly journals GDP Development of China and USA in terms of mutual sanctions and COVID-19

2021 ◽  
Vol 92 ◽  
pp. 07061
Author(s):  
Petr Šuleř ◽  
Jaromír Vrbka

Research background: China’s share in the global economy has experienced a swift growth since opening up and reforming the country’s foreign policy in 1978. USA sanction on China has so far concentrated on a heap of issues including China’s enormous exchange shortfall with the U.S., currency control, constrained market access, licensed innovation robbery and security issues identified with Huawei. Also, USA sanction on China has so far lead to a decrease in exports and outflow of FDI, reduce in the inflow trade and investment, and apparently hinders the Chinese GPD growth and diminished its currency exchange rate. Purpose of the article: The aim is to predict the future development of the GDP of the China and the USA and to estimate their further development through the prism of mutual trade sanctions and COVID-19. Methods: The data collection demonstrates the course of a time series of a daily RMB exchange rate development from the beginning of 1992 to June 2020. Furthermore, it represents the time series of a quarterly development of the Chinese GDP for the same time period. Using neural networks, a regression for different variants of the time series delay in connection with the analysis of the USA sanctions is conducted. Findings & Value added: The GDP of both countries has developed over the last two years, as if sanctions had not been imposed. However, the situation is changing with COVID-19. In this case, it is clear that the impact will be more significant. US GDP will stagnate. PRC GDP will fall.

Author(s):  
Hasan Dinçer ◽  
Ümit Hacıoğlu ◽  
Serhat Yüksel

The aim of this study is to identify the determinants of US Dollar/Turkish Lira currency exchange rate for strategic decision making in the global economy. Within this scope, quarterly data for the period between 1988:1 and 2016:2 was used in this study. In addition to this aspect, 10 explanatory variables were considered in order to determine the leading indicators of US Dollar/Turkish Lira currency exchange rate. Moreover, Multivariate Adaptive Regression Splines (MARS) method was used so as to achieve this objective. According to the results of this analysis, it was defined that two different variables affect this exchange rate in Turkey. First of all, it was identified that there is a negative relationship between current account balance and the value of US Dollar/Turkish Lira currency exchange rate. This result shows that in case of current account deficit problem, Turkish Lira experiences depreciation. Furthermore, it was also concluded that when there is an economic growth in Turkey, Turkish Lira increases in comparison with US Dollar. While taking into the consideration of these results, it could be generalized that emerging economies such as Turkey have to decrease current account deficit and investors should focus on higher economic growth in order to prevent the depreciation of the money in the strategic investment decision.


2021 ◽  
Author(s):  
Ting Heng Sheng ◽  
Mohd Saifullah Rusiman ◽  
Norziha Che Him ◽  
Suliadi Firdaus Sufahani ◽  
Efendi Nasibov

2020 ◽  
Vol 21 (4) ◽  
Author(s):  
Kishore Kumar Sahu ◽  
Sarat Chandra Nayak ◽  
Himanshu Sekhar Behera

Exchange rates are highly fluctuating by nature, thus difficult to forecast. Artificial neural networks (ANN) have proved to be better than statistical methods. Inadequate training data may lead the model to reach suboptimal solution resulting, poor accuracy as ANN-based forecasts are data driven. To enhance forecasting accuracy, we suggests a method of enriching training dataset through exploring and incorporating of virtual data points (VDPs) by an evolutionary method called as fireworks algorithm trained functional link artificial neural network (FWA-FLN). The model maintains the correlation between the current and past data, especially at the oscillation point on the time series. The exploring of a VDP and forecast of the succeeding term go consecutively by the FWA-FLN. Real exchange rate time series are used to train and validate the proposed model. The efficiency of the proposed technique is related to other models trained similarly and produces far better prediction accuracy.


Author(s):  
Tim J. Smith ◽  
Kyle T. Westra ◽  
Nathan L. Phipps

AbstractWe extend the normalized approach to constructing profit bridges proffered in a recent paper to examine the impact of currency exchange rate fluctuations within a multinational corporation. In doing so, we describe a profit bridge that would measure corporate performance distinct from that which would measure the performance of business units, including metrics for the impact of volume, price, variable cost, offering mix, and exchange rate changes.


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