Мақола

Efficient Portfolios Computed via Moment-Based Bounding-approximations: Part I - EB

Steftcho DokovSchool of Computer and Information Engineering, INHA University in Tashkent, Tashkent, UzbekistanIvilina PopovaDepartment of Finance & Economics McCoy College of Business, Texas State University, San Marcos, TX, USADavid P. MortonDepartment of Industrial Engineering and Management Sciences, Northwestern University, Evanston, IL, USA

2019 International Conference on Information Science and Communications Technologies (ICISCT)conference2019en

ABI

Аннотация

We develop and analyze mean-variance efficient portfolios. Each portfolio comes as a solution of an optimization problem, which approximates the expected value of a utility function. The approximation is an upper bound on the expected value of the utility function. The bound is based on the first two probability moments and cross-moments of the portfolio”s random return. We prove that the optimal solution of the approximate optimization problem yields a mean-variance efficient portfolio. We illustrate how to use the resulting portfolio in practice by designing a daily trading strategy with stocks traded on the New York Stock Exchange (NYSE). The approximate optimization model is solved once every day. Out-of-sample numerical results are presented for 27 years of daily trading for 24 stocks from NYSE.

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Мавзулар

Risk and Portfolio Optimization Stochastic processes and financial applications Financial Markets and Investment Strategies

Идентификаторлар

DOI: 10.1109/icisct47635.2019.9011994

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