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@article{56901, author = {Horák, Jakub}, article_location = {Basel}, article_number = {1}, doi = {http://dx.doi.org/10.3390/jrfm14010036}, keywords = {artificial neural networks; time series; import; export; restriction; international policy; financial market}, language = {eng}, issn = {1911-8066}, journal = {Journal of Risk and Financial Management}, title = {Sanctions as a Catalyst for Russia's and China's Balance of Trade: Business Opportunity}, url = {http://www.nasemore.com/wp-content/uploads/2018/11/11.-Hlatka-Bartuska.pdf}, volume = {14}, year = {2021} }
TY - JOUR ID - 56901 AU - Horák, Jakub PY - 2021 TI - Sanctions as a Catalyst for Russia's and China's Balance of Trade: Business Opportunity JF - Journal of Risk and Financial Management VL - 14 IS - 1 SP - nestránkováno EP - nestránkováno PB - MDPI SN - 19118066 KW - artificial neural networks KW - time series KW - import KW - export KW - restriction KW - international policy KW - financial market UR - http://www.nasemore.com/wp-content/uploads/2018/11/11.-Hlatka-Bartuska.pdf N2 - The study is based on a highly topical sophisticated model of neural networks, which provides clear results confirming the unintended positive effect. The time series and aggregated data became inputs into multilayer perceptron networks, while the methodology used enabled eliminating of both too large averaging and extreme fluctuations of the equalized time series. Out of 10,000 networks created for each variable and each time lag, five showing the best characteristics given by correlation coefficients and absolute residual sums are retained. ER -
HORÁK, Jakub. Sanctions as a Catalyst for Russia's and China's Balance of Trade: Business Opportunity. \textit{Journal of Risk and Financial Management}. Basel: MDPI, roč.~14, č.~1, s.~nestránkováno, 26 s. ISSN~1911-8066. doi:10.3390/jrfm14010036. 2021.
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