FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2621909493> ?p ?o ?g. }

• W2621909493 endingPage "558" @default.
• W2621909493 startingPage "540" @default.
• W2621909493 abstract "This study introduces a Reverse Adaptive Krill Herd-Locally Weighted Support Vector Regression (RKH-LSVR) model. The Reverse Adaptive Krill Herd (RKH) algorithm is a novel metaheuristic optimization technique inspired by the behavior of krill herds. In RKH-LSVR, the RKH optimizes the locally weighted Support Vector Regression (LSVR) parameters by balancing the search between local and global optima. The proposed model is applied to the task of forecasting and trading six ETF stocks on a daily basis over the period 2010–2015. The RKH-LSVR's efficiency is benchmarked against a set of traditional SVR structures and simple linear and non-linear models. The trading application is designed in order to validate the robustness of the algorithm under study and to provide empirical evidence in favor of or against the Adaptive Market Hypothesis (AMH). In terms of the results, the RKH-LSVR outperforms its counterparts in terms of statistical accuracy and trading efficiency, while the time varying trading performance of the models under study validates the AMH theory." @default.
• W2621909493 created "2017-06-15" @default.
• W2621909493 creator A5060239367 @default.
• W2621909493 creator A5090027748 @default.
• W2621909493 date "2017-12-01" @default.
• W2621909493 modified "2023-10-13" @default.
• W2621909493 title "Reverse adaptive krill herd locally weighted support vector regression for forecasting and trading exchange traded funds" @default.
• W2621909493 cites W1504141014 @default.
• W2621909493 cites W1753270033 @default.
• W2621909493 cites W1966341317 @default.
• W2621909493 cites W1973469161 @default.
• W2621909493 cites W1978996791 @default.
• W2621909493 cites W1981531537 @default.
• W2621909493 cites W1983636075 @default.
• W2621909493 cites W1985460844 @default.
• W2621909493 cites W1988221687 @default.
• W2621909493 cites W1993042967 @default.
• W2621909493 cites W1995652670 @default.
• W2621909493 cites W2002579289 @default.
• W2621909493 cites W2002739427 @default.
• W2621909493 cites W2003961265 @default.
• W2621909493 cites W2005038754 @default.
• W2621909493 cites W2012214132 @default.
• W2621909493 cites W2014341469 @default.
• W2621909493 cites W2015954856 @default.
• W2621909493 cites W2017977879 @default.
• W2621909493 cites W2018389776 @default.
• W2621909493 cites W2022006693 @default.
• W2621909493 cites W2028590934 @default.
• W2621909493 cites W2039935421 @default.
• W2621909493 cites W2042031583 @default.
• W2621909493 cites W2046134594 @default.
• W2621909493 cites W2054337296 @default.
• W2621909493 cites W2064501641 @default.
• W2621909493 cites W2066995518 @default.
• W2621909493 cites W2079615115 @default.
• W2621909493 cites W2089394015 @default.
• W2621909493 cites W2107214544 @default.
• W2621909493 cites W2110485445 @default.
• W2621909493 cites W2119291196 @default.
• W2621909493 cites W2124098825 @default.
• W2621909493 cites W2130980674 @default.
• W2621909493 cites W2131613989 @default.
• W2621909493 cites W2134658143 @default.
• W2621909493 cites W2144317842 @default.
• W2621909493 cites W2145356217 @default.
• W2621909493 cites W2151237529 @default.
• W2621909493 cites W2344279130 @default.
• W2621909493 cites W2508177680 @default.
• W2621909493 cites W2565468692 @default.
• W2621909493 cites W2767186209 @default.
• W2621909493 cites W3021318637 @default.
• W2621909493 cites W3105346980 @default.
• W2621909493 cites W3122305330 @default.
• W2621909493 cites W3125648595 @default.
• W2621909493 doi "https://doi.org/10.1016/j.ejor.2017.06.019" @default.
• W2621909493 hasPublicationYear "2017" @default.
• W2621909493 type Work @default.
• W2621909493 sameAs 2621909493 @default.
• W2621909493 citedByCount "15" @default.
• W2621909493 countsByYear W26219094932017 @default.
• W2621909493 countsByYear W26219094932018 @default.
• W2621909493 countsByYear W26219094932019 @default.
• W2621909493 countsByYear W26219094932020 @default.
• W2621909493 countsByYear W26219094932021 @default.
• W2621909493 countsByYear W26219094932022 @default.
• W2621909493 countsByYear W26219094932023 @default.
• W2621909493 crossrefType "journal-article" @default.
• W2621909493 hasAuthorship W2621909493A5060239367 @default.
• W2621909493 hasAuthorship W2621909493A5090027748 @default.
• W2621909493 hasBestOaLocation W26219094932 @default.
• W2621909493 hasConcept C104317684 @default.
• W2621909493 hasConcept C12267149 @default.
• W2621909493 hasConcept C126255220 @default.
• W2621909493 hasConcept C149782125 @default.
• W2621909493 hasConcept C154945302 @default.
• W2621909493 hasConcept C162324750 @default.
• W2621909493 hasConcept C185592680 @default.
• W2621909493 hasConcept C33923547 @default.
• W2621909493 hasConcept C41008148 @default.
• W2621909493 hasConcept C55493867 @default.
• W2621909493 hasConcept C63479239 @default.
• W2621909493 hasConceptScore W2621909493C104317684 @default.
• W2621909493 hasConceptScore W2621909493C12267149 @default.
• W2621909493 hasConceptScore W2621909493C126255220 @default.
• W2621909493 hasConceptScore W2621909493C149782125 @default.
• W2621909493 hasConceptScore W2621909493C154945302 @default.
• W2621909493 hasConceptScore W2621909493C162324750 @default.
• W2621909493 hasConceptScore W2621909493C185592680 @default.
• W2621909493 hasConceptScore W2621909493C33923547 @default.
• W2621909493 hasConceptScore W2621909493C41008148 @default.
• W2621909493 hasConceptScore W2621909493C55493867 @default.
• W2621909493 hasConceptScore W2621909493C63479239 @default.
• W2621909493 hasIssue "2" @default.
• W2621909493 hasLocation W26219094931 @default.
• W2621909493 hasLocation W26219094932 @default.
• W2621909493 hasLocation W26219094933 @default.
• W2621909493 hasLocation W26219094934 @default.

• next