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Research on regularized mean–variance portfolio selection strategy with modified Roy safety-first principle

Overview of attention for article published in SpringerPlus, June 2016
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (63rd percentile)

Mentioned by

twitter
4 tweeters

Citations

dimensions_citation
7 Dimensions

Readers on

mendeley
5 Mendeley
Title
Research on regularized mean–variance portfolio selection strategy with modified Roy safety-first principle
Published in
SpringerPlus, June 2016
DOI 10.1186/s40064-016-2621-7
Pubmed ID
Authors

Ebenezer Fiifi Emire Atta Mills, Dawen Yan, Bo Yu, Xinyuan Wei

Abstract

We propose a consolidated risk measure based on variance and the safety-first principle in a mean-risk portfolio optimization framework. The safety-first principle to financial portfolio selection strategy is modified and improved. Our proposed models are subjected to norm regularization to seek near-optimal stable and sparse portfolios. We compare the cumulative wealth of our preferred proposed model to a benchmark, S&P 500 index for the same period. Our proposed portfolio strategies have better out-of-sample performance than the selected alternative portfolio rules in literature and control the downside risk of the portfolio returns.

Twitter Demographics

The data shown below were collected from the profiles of 4 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 5 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 5 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 2 40%
Student > Doctoral Student 1 20%
Student > Ph. D. Student 1 20%
Unknown 1 20%
Readers by discipline Count As %
Computer Science 1 20%
Psychology 1 20%
Economics, Econometrics and Finance 1 20%
Social Sciences 1 20%
Unknown 1 20%

Attention Score in Context

This research output has an Altmetric Attention Score of 4. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 20 July 2020.
All research outputs
#5,546,200
of 18,286,759 outputs
Outputs from SpringerPlus
#375
of 1,806 outputs
Outputs of similar age
#105,525
of 290,078 outputs
Outputs of similar age from SpringerPlus
#1
of 1 outputs
Altmetric has tracked 18,286,759 research outputs across all sources so far. This one has received more attention than most of these and is in the 69th percentile.
So far Altmetric has tracked 1,806 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.3. This one has done well, scoring higher than 79% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 290,078 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 63% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them