Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/270022 
Year of Publication: 
2020
Citation: 
[Journal:] Cogent Economics & Finance [ISSN:] 2332-2039 [Volume:] 8 [Issue:] 1 [Article No.:] 1854948 [Year:] 2020 [Pages:] 1-17
Publisher: 
Taylor & Francis, Abingdon
Abstract: 
This paper presents an innovative new approach to investment portfolio design, which applies a discrete, state-based methodology to defining market states and making asset allocation decisions with respect to both current and future state membership. State membership is based on attributes taken from traditional finance and portfolio theory namely expected growth, and covariance. The transitional dynamics of the derived states are modeled as a Markovian process. Asset weighting and portfolio allocation decisions are made through an optimization-based approach coupled with heuristics that account for the probability of state membership and the quality of the state in terms of information provided.
Subjects: 
finance
investment management
Markov
Markowitz
mean-variance
optimization
Portfolio management
regimes
states
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article

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