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Erschienen in: The Journal of Supercomputing 10/2019

22.08.2018

Study on the country risk rating with distributed crawling system

verfasst von: Yuantao Xie, Wen Wang, Yabo Guo, Juan Yang

Erschienen in: The Journal of Supercomputing | Ausgabe 10/2019

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Abstract

This paper built a system containing the Distributed Crawling Module, the Database Module and the Analysis Module to collect a large number of objective data, clean the data and realize the business intelligence representation. The distributed crawling system includes the Distributed Crawling Module building from Hadoop, the Database Module by SQL Server and the Analysis Module by the SAS system. The first two modules support a distributed way to collect and convert non-structural data into structural data for the last module processing. Then, this paper extends research fields from theory to application about B&R, constructs rating system from the perspective of political risk, economic risk, financial risk, business environment risk and legal risk, establishes a 140 rating index, collects 46,200 sample data, and adopts Model of Principal Components Analysis, Analytic Hierarchy Process and Efficacy Function to access “the Belt & Road Initiative” 66 countries for 5 consecutive years of export credit insurance in the country risk rating. This paper also gives a detail explanation on 2015 rating results, showing that, Singapore wins the highest credit rating among the country; the credit rating of Latvia, Estonia, Slovakia, Turkey, Malaysia, Russia, Thailand and other countries is very high; Afghanistan, Ukraine, Laos, Iran, Arabia, Republic of Syria, Iraq, Burma, Republic of Yemen, East Timor and other countries with poor credit ratings. The conclusion is consistent with the domestic and overseas well-known rating agencies.

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Metadaten
Titel
Study on the country risk rating with distributed crawling system
verfasst von
Yuantao Xie
Wen Wang
Yabo Guo
Juan Yang
Publikationsdatum
22.08.2018
Verlag
Springer US
Erschienen in
The Journal of Supercomputing / Ausgabe 10/2019
Print ISSN: 0920-8542
Elektronische ISSN: 1573-0484
DOI
https://doi.org/10.1007/s11227-018-2539-7

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