@inproceedings{6cd10bc3fd5744df90d24808ea50fcac,
title = "Efficient Portfolios Computed via Moment-Based Bounding-approximations: Part i - EB",
abstract = "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.",
keywords = "Concave Increasing Utility Function, Efficient Portfolio, Mean-Variance Efficient Frontier, Trading Strategy",
author = "Steftcho Dokov and Ivilina Popova and Morton, {David P.}",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 2019 International Conference on Information Science and Communications Technologies, ICISCT 2019 ; Conference date: 04-11-2019 Through 06-11-2019",
year = "2019",
month = nov,
doi = "10.1109/ICISCT47635.2019.9011994",
language = "English (US)",
series = "International Conference on Information Science and Communications Technologies: Applications, Trends and Opportunities, ICISCT 2019",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "International Conference on Information Science and Communications Technologies",
address = "United States",
}