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A large constrained time‐varying portfolio selection model with DCC‐MIDAS : Evidence from Chinese stock market
Author(s) -
Xu Qifa,
Zuo Junqing,
Jiang Cuixia,
He Yaoyao
Publication year - 2021
Publication title -
international journal of finance and economics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.505
H-Index - 39
eISSN - 1099-1158
pISSN - 1076-9307
DOI - 10.1002/ijfe.1968
Subject(s) - portfolio , economics , stock (firearms) , econometrics , stock exchange , computer science , selection (genetic algorithm) , project portfolio management , mathematical optimization , financial economics , mathematics , finance , engineering , mechanical engineering , artificial intelligence , management , project management
To solve a large portfolio selection, we propose a novel norm constrained time‐varying minimum variance model with DCC‐MIDAS, labelled as NC‐MVP‐DCC‐MIDAS. It applies the DCC‐MIDAS model to improve the estimation of dynamic correlations among financial assets by exploiting rich information contained in mixed frequency data. Additionally, it imposes norm constraints on the minimum variance portfolio with the elastic‐net penalty to pick a reasonable number of assets and prevent extreme positions in the resulting portfolio. Its superiority is illustrated via empirical studies on the construction of optimal sparse and stable portfolios with the constituent stocks in the Shanghai Stock Exchange (SSE) 50 Index of China.