Using MOEAs To Outperform Stock Benchmarks In The Presence of Typical Investment Constraints

Details Using MOEAs To Outperform Stock Benchmarks In The Presence of Typical Investment Constraints Using MOEAs To Outperform Stock Benchmarks In The Presence of Typical Investment Constraints

2011-09-15

arxiv.org/abs/1109.3488v2

Economy

Quantitative Finance

Portfolio Management

21 pages, Index Terms - multi-objective evolutionary algorithms (MOEA), mean-variance optimization, financial constraints, mul

Scientific paper

Portfolio managers are typically constrained by turnover limits, minimum and maximum stock positions, cardinality, a target market capitalization and sometimes the need to hew to a style (such as growth or value). In addition, portfolio managers often use multifactor stock models to choose stocks based upon their respective fundamental data. We use multiobjective evolutionary algorithms (MOEAs) to satisfy the above real-world constraints. The portfolios generated consistently outperform typical performance benchmarks and have statistically significant asset selection.

Affiliated with

Also associated with

No associations

Rating

Using MOEAs To Outperform Stock Benchmarks In The Presence of Typical Investment Constraints does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Using MOEAs To Outperform Stock Benchmarks In The Presence of Typical Investment Constraints, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Using MOEAs To Outperform Stock Benchmarks In The Presence of Typical Investment Constraints will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-533137