首页|Findings on Machine Learning Detailed by Investigators at Southwestern Universit y of Finance and Economics (Mean-variance Efficient Large Portfolios: a Simple M achine Learning Heuristic Technique Based On the Two-fund Separation Theorem)

Findings on Machine Learning Detailed by Investigators at Southwestern Universit y of Finance and Economics (Mean-variance Efficient Large Portfolios: a Simple M achine Learning Heuristic Technique Based On the Two-fund Separation Theorem)

扫码查看
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Machine Learning is th e subject of a report. According to news reporting originating in Chengdu, Peopl e’s Republic of China, by NewsRx journalists, research stated, “We revisit in th is article the Two-Fund Separation Theorem as a simple technique for the Mean-Va riance optimization of large portfolios.” The news reporters obtained a quote from the research from the Southwestern Univ ersity of Finance and Economics, “The proposed approach is fast and scalable and provides equivalent results of commonly used ML techniques but, with computing time differences counted in hours (1 min vs. several hours). In the empirical ap plication, we consider three geographic areas (China, US, and French stock marke ts) and show that the Two-Fund Separation Theorem holds exactly when no constrai nts are imposed and is approximately true with (realistic) positive constraints on weights.”

ChengduPeople’s Republic of ChinaAsi aCyborgsEmerging TechnologiesMachine LearningSouthwestern University of Finance and Economics

2024

Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
年,卷(期):2024.(MAY.8)