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  • Search: person:"Shanshan, Ding"
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Year of publication
Subject
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Theorie 2 Theory 2 Black-Litterman 1 CAPM 1 Capital income 1 Capital structure 1 Central dimension folding subspace 1 Central subspace 1 Emissions trading 1 Emissionshandel 1 Erwartungsbildung 1 Expectation formation 1 Expected return 1 Foreign portfolio investment 1 Greenhouse gas emissions 1 Implied return 1 Kapitaleinkommen 1 Kapitalstruktur 1 Leverage constraint 1 Liquidity constraint 1 Liquiditätsbeschränkung 1 Portfolio optimization 1 Portfolio selection 1 Portfolio-Investition 1 Portfolio-Management 1 Sliced inverse regression 1 Sufficient dimension reduction 1 Tensor data 1 Tensor decomposition 1 Treibhausgas-Emissionen 1 USA 1 United States 1 analysis on the effect 1 emission rights trading 1 operation mechanism 1
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Undetermined 3
Type of publication
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Article 3
Type of publication (narrower categories)
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Article in journal 2 Aufsatz in Zeitschrift 2
Language
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English 2 Undetermined 1
Author
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Ding, Shanshan 2 Cook, R. Dennis 1 Jindong, Duan 1 Shanshan, Ding 1 Xin, Leon 1
Published in...
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International journal of economics and finance 1 Journal of Multivariate Analysis 1 The journal of asset management : a major new, international quarterly journal for the financial community 1
Source
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ECONIS (ZBW) 2 RePEc 1
Showing 1 - 3 of 3
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Expected returns with leverage constraints and target returns
Xin, Leon; Ding, Shanshan - In: The journal of asset management : a major new, … 22 (2021) 3, pp. 200-208
Persistent link: https://www.econbiz.de/10012581588
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The operation mechanism of emission right trading and analysis on the operation effect
Shanshan, Ding; Jindong, Duan - In: International journal of economics and finance 9 (2017) 2, pp. 150-158
Persistent link: https://www.econbiz.de/10011618211
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Tensor sliced inverse regression
Ding, Shanshan; Cook, R. Dennis - In: Journal of Multivariate Analysis 133 (2015) C, pp. 216-231
Sliced inverse regression (SIR) is a widely used non-parametric method for supervised dimension reduction. Conventional SIR mainly tackles simple data structure but is inappropriate for data with array (tensor)-valued predictors. Such data are commonly encountered in modern biomedical imaging...
Persistent link: https://www.econbiz.de/10011116235
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