Selection of Orthogonal Investment Portfolio Using Evolino RNN Trading Model | Zendy

Nijolė Maknickienė | Zendy

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Selection of Orthogonal Investment Portfolio Using Evolino RNN Trading Model

Author(s) -

Nijolė Maknickienė

Publication year - 2014

Publication title -

procedia - social and behavioral sciences

Language(s) - English

Resource type - Journals

ISSN - 1877-0428

DOI - 10.1016/j.sbspro.2013.12.962

Subject(s) - portfolio , orthogonality , investment strategy , selection (genetic algorithm) , reliability (semiconductor) , financial market , econometrics , portfolio optimization , investment (military) , currency , replicating portfolio , computer science , actuarial science , economics , financial economics , artificial intelligence , mathematics , finance , market liquidity , power (physics) , physics , geometry , quantum mechanics , politics , political science , law , monetary economics

Investing in financial market require the reliable predicting of expecting returns, assessment of risk and reliability. Principle of portfolio orthogonality was using to reduce the risk of the investment. An artificial intelligence system may reveal new opportunities for using this principle. Prediction of recurrent neural networks ensemble is stochastically informative distribution, which is helpful for portfolio selection. Shape and parameters of distribution influence decision making in currency market. Assessment of portfolio riskiness, finding most orthogonal elements of portfolio, influence better results for trading in real market

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