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Risk-Controlled Multiobjective Portfolio Selection Problem Using a Principle of Compromise
Author(s) -
Takashi Hasuike,
Hideki Katagiri
Publication year - 2014
Publication title -
mathematical problems in engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.262
H-Index - 62
eISSN - 1026-7077
pISSN - 1024-123X
DOI - 10.1155/2014/232375
Subject(s) - portfolio , boom , recession , compromise , selection (genetic algorithm) , portfolio optimization , mathematical optimization , set (abstract data type) , econometrics , modern portfolio theory , computer science , economics , mathematics , actuarial science , financial economics , engineering , artificial intelligence , social science , environmental engineering , sociology , keynesian economics , programming language
This paper proposes a multiobjective portfolio selection problem with most probable random distribution derived from current market data and other random distributions of boom and recession under the risk-controlled parameters determined by an investor. The current market data and information include not only historical data but also interpretations of economists’ oral and linguistic information, and hence, the boom and recession are often caused by these nonnumeric data. Therefore, investors need to consider several situations from most probable condition to boom and recession and to avoid the risk less than the target return in each situation. Furthermore, it is generally difficult to set random distributions of these cases exactly. Therefore, a robust-based approach for portfolio selection problems using the only mean values and variances of securities is proposed as a multiobjective programming problem. In addition, an exact algorithm is developed to obtain an explicit optimal portfolio using a principle of compromise

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