A Network Approach to Risk Theory and Portfolio Selection

Inspired by the work of Adcock, Landsman, and Shushi (2019) which established the Stein’s lemma for generalized skew-elliptical random vectors, we derive Stein type lemmas for location-scale mixture of generalized skew-elliptical random vectors. Some special cases such as the location-scale mixture of elliptical random vectors, the location-scale mixture of generalized skew-normal random vectors, and the location-scale mixture of normal random vectors are also considered. As an application in risk theory, we give a result for optimal portfolio selection.

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A network approach to portfolio selection

Journal of Empirical Finance ◽

10.1016/j.jempfin.2016.06.003 ◽

2016 ◽

Vol 38 ◽

pp. 157-180 ◽

Cited By ~ 31

Author(s):

Gustavo Peralta ◽

Abalfazl Zareei

Keyword(s):

Portfolio Selection ◽

Network Approach

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A Robust Neural Network Approach for the Portfolio Selection Problem Basing on New Rational Models

Journal of Engineering and Applied Sciences ◽

10.36478/jeasci.2019.675.683 ◽

2019 ◽

Vol 14 (3) ◽

pp. 675-683

Author(s):

Kaoutar Senhaji ◽

Karim El Moutaouakil ◽

Mohamed Ettaouil

Keyword(s):

Neural Network ◽

Portfolio Selection ◽

Selection Problem ◽

Network Approach ◽

Neural Network Approach ◽

Rational Models ◽

Portfolio Selection Problem

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The Collaborative Network Approach: a model for advancing patient-centric research for Castleman disease and other rare diseases

Emerging Topics in Life Sciences ◽

10.1042/etls20180178 ◽

2019 ◽

Vol 3 (1) ◽

pp. 97-105

Author(s):

Mary Zuccato ◽

Dustin Shilling ◽

David C. Fajgenbaum

Keyword(s):

Rare Diseases ◽

Treatment Options ◽

Castleman Disease ◽

High Impact ◽

Collaborative Network ◽

Network Approach ◽

Grant Applications ◽

Research Questions ◽

Novel Strategy ◽

Patient Centric

Abstract There are ∼7000 rare diseases affecting 30 000 000 individuals in the U.S.A. 95% of these rare diseases do not have a single Food and Drug Administration-approved therapy. Relatively, limited progress has been made to develop new or repurpose existing therapies for these disorders, in part because traditional funding models are not as effective when applied to rare diseases. Due to the suboptimal research infrastructure and treatment options for Castleman disease, the Castleman Disease Collaborative Network (CDCN), founded in 2012, spearheaded a novel strategy for advancing biomedical research, the ‘Collaborative Network Approach’. At its heart, the Collaborative Network Approach leverages and integrates the entire community of stakeholders — patients, physicians and researchers — to identify and prioritize high-impact research questions. It then recruits the most qualified researchers to conduct these studies. In parallel, patients are empowered to fight back by supporting research through fundraising and providing their biospecimens and clinical data. This approach democratizes research, allowing the entire community to identify the most clinically relevant and pressing questions; any idea can be translated into a study rather than limiting research to the ideas proposed by researchers in grant applications. Preliminary results from the CDCN and other organizations that have followed its Collaborative Network Approach suggest that this model is generalizable across rare diseases.

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