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  • Search: subject:"Clustering technique"
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Year of publication
Subject
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Asset Allocation 1 Autoregressive models 1 Clustering Technique 1 Clustering technique 1 Evolutionary Approach 1 Heuristic Optimization 1 Mean square forecast error 1 Pooled series 1 Sharpe Ratio 1 moving thresholds 1 national systems of innovation 1 super-paramagnetic clustering technique 1
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Online availability
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Free 3
Type of publication
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Book / Working Paper 3
Language
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English 3
Author
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Albuquerque, Eduardo da Motta e 1 Bernardes, Américo Tristão 1 Inder, B. 1 Marahaj, E.A. 1 Maringer, Dietmar 1 Ribeiro, Leonardo Costa 1 Ruiz, Ricardo Machado 1 Zhang, Jin 1
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Institution
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COMISEF 1 Centro de Desenvolvimento e Planejamento Regional (Cedeplar), Universidade Federal de Minas Gerais 1 Department of Econometrics and Business Statistics, Monash Business School 1
Published in...
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Monash Econometrics and Business Statistics Working Papers 1 Textos para Discussão Cedeplar-UFMG 1 Working Papers / COMISEF 1
Source
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RePEc 3
Showing 1 - 3 of 3
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Asset Allocation under Hierarchical Clustering
Zhang, Jin; Maringer, Dietmar - COMISEF - 2010
This paper proposes a clustering asset allocation scheme which provides better risk-adjusted portfolio performance than those obtained from traditional asset allocation approaches such as the equal weight strategy and the Markowitz minimum variance allocation. The clustering criterion used,...
Persistent link: https://www.econbiz.de/10008506027
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The curse of technological race: the red queen effect
Ribeiro, Leonardo Costa; Ruiz, Ricardo Machado; … - Centro de Desenvolvimento e Planejamento Regional … - 2006
thirty years (1974 to 2003) and applied a super-paramagnetic clustering technique on them, finding nations divided in three …
Persistent link: https://www.econbiz.de/10005029964
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Forecasting Time Series from Clusters.
Marahaj, E.A.; Inder, B. - Department of Econometrics and Business Statistics, … - 1999
Forecasting large numbers of time series is a costly and time-consuming exercise. Before forecasting a large number of series that are logically connected in some way, the authors can first cluster them into groups of similar series. In this paper they investigate forecasting the series in each...
Persistent link: https://www.econbiz.de/10005149049
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