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Record
Title
Predicting Exchange Rate Value-at-Risk and Expected Shortfall: A Neural Network Approach
Type
Student Paper
Publ. year
2019
Author/s
Bijelic, Anna; Ouijjane, Tilila
Department/s
Department of Economics
In LUP since
2019-08-08
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893 108 2
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Sweden 203 (23%)
United States of America 77 (9%)
Germany 54 (6%)
United Kingdom of Great Britain and Northern Ireland 46 (5%)
China 40 (5%)
Unknown 28 (3%)
France 28 (3%)
Pakistan 23 (3%)
Italy 21 (2%)
Canada 20 (2%)
India 18 (2%)
Denmark 17 (2%)
Brazil 15 (2%)
Greece 15 (2%)
Switzerland 15 (2%)
Malaysia 14 (2%)
Norway 14 (2%)
Iran 13 (1%)
Spain 12 (1%)
Hong Kong (China) 12 (1%)
Netherlands (Kingdom of the) 12 (1%)
Viet Nam 10 (1%)
Indonesia 10 (1%)
Poland 9 (1%)
Tunisia 8 (1%)
Taiwan (China) 8 (1%)
Russian Federation 7 (1%)
Turkiye 7 (1%)
South Africa 7 (1%)
Austria 7 (1%)
Hungary 6 (1%)
Romania 6 (1%)
Japan 6 (1%)
Lithuania 6 (1%)
Finland 6 (1%)
Australia 5 (1%)
Portugal 5 (1%)
Algeria 5 (1%)
Serbia 5 (1%)
Belgium 4 (0%)
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Morocco 4 (0%)
Kenya 3 (0%)
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United Arab Emirates 3 (0%)
Singapore 3 (0%)
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Ireland 2 (0%)
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Luxembourg 2 (0%)
Congo 1 (0%)
Sri Lanka 1 (0%)
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Belarus 1 (0%)
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Croatia 1 (0%)
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Lebanon 1 (0%)
Colombia 1 (0%)
Macedonia 1 (0%)
About
The download statistics shown here have been collected since the launch of LUP in October 2007 and are updated every night. Statistics are available for all records with open access fulltexts. Efforts have been made to exclude downloads by robots and track irregular download activities.

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Disclaimer
The information on downloads per country is based on the geolocation of IP addresses and may not be completely accurate. The statistics presented here may also change retroactively when the calculation process is improved to provide more accurate results.

Statistics Last Updated
Thu Jul 11 08:30:05 2024