Maslow Portfolio Selection for Individuals with Low Financial Sustainability

Li, Zongxin; Li, Xinge; Hui, Yi; Wong, Wing‐Keung

doi:10.3390/su10041128

Cited by 32 publications

(31 citation statements)

References 42 publications

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“…To circumvent the limitation, Leung, Ng, and Wong (2012) develop a new estimator for the optimal portfolio return based on an unbiased estimator of the inverse of the covariance matrix and its related terms, and derive explicit formulae for the estimator of the optimal portfolio return. Li, Bai, McAleer, and Wong (2016) (2015), Li, Li, Hui, and Wong (2018) and many others.…”

Section: Portfolio Optimizationmentioning

confidence: 96%

Optimal Solution Techniques in Decision Sciences: A Review

Pho

Tran

et al. 2019

SSRN Journal

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Methods to find the optimization solution are fundamental and extremely crucial for scientists to program computational software to solve optimization problems efficiently and for practitioners to use it efficiently. Thus, it is very essential to know about the idea, origin, and usage of these methods. Although the methods have been used for very long time and the theory has been developed too long, most, if not all, of the authors who develop the theory are unknown and the theory has not been stated clearly and systematically. To bridge the gap in the literature in this area and provide academics and practitioners with an overview of the methods, this paper reviews and discusses the four most commonly used methods to find the optimization solution including the bisection, gradient, Newton-Raphson, and secant methods. We first introduce the origin and idea of the methods and develop all the necessary theorems to prove the existence and convergence of the estimate for each method.We then give two examples to illustrate the approaches. Thereafter, we review the literature of the applications of getting the optimization solutions in some important issues and discuss the advantages and disadvantages of each method. We note that all the theorems developed in our paper could be well-known but, so far, we have not seen any book or paper that discusses all the theorems stated in our paper in detail. Thus, we believe the theorems developed in our paper could still have some contributions to the literature. Our review is useful for academics and practitioners in finding the optimization solutions in their studies.

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Section: Portfolio Optimizationmentioning

confidence: 96%

Optimal Solution Techniques in Decision Sciences: A Review

Pho

Tran

et al. 2019

SSRN Journal

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“…Recently, Li et al (2018) extended Maslow (1943) need hierarchy theory and the two-level optimization approach by developing the framework of the Malsow portfolio selection model (MPSM). The authors were able to do this by solving the two optimization problems to meet the need of individuals with low financial sustainability, who prefer to satisfy their lower-level (safety) need before seeking a higher-level (self-actualization) need to maximize the optimal returns.…”

Section: Portfolio Optimizationmentioning

confidence: 99%

“…For example, Li et al (2018) analyse an investment issue, so that it is related to finance. The paper discusses decision-making for investors with low and high financial sustainability, so the paper is related to management, psychology, and decision-making.…”

Section: Portfolio Optimizationmentioning

confidence: 99%

“…There are strong theoretical links among these areas. For example, we provide a discussion in Section 2.1 that Li et al (2018) is related to finance, economics, management, psychology, decision-making, marketing, big data, and computation science. We note that this paper is not the only research that is related to several different disciplines.…”

Section: Introductionmentioning

confidence: 99%

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Big Data, Computational Science, Economics, Finance, Marketing, Management, and Psychology: Connections

Chang

McAleer

Wong

2018

JRFM

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Abstract:The paper provides a review of the literature that connects Big Data, Computational Science, Economics, Finance, Marketing, Management, and Psychology, and discusses research issues that are related to the various disciplines. Academics could develop theoretical models and subsequent econometric and statistical models to estimate the parameters in the associated models, as well as conduct simulation to examine whether the estimators in their theories on estimation and hypothesis testing have good size and high power. Thereafter, academics and practitioners could apply theory to analyse some interesting issues in the seven disciplines and cognate areas.

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“…Recently, Li, Li, Hui, andWong (2017) extend Maslow's (1943) need hierarchy theory and the two-level optimization approach by developing the framework of the Malsow portfolio selection model (MPSM). The authors solve two optimization problems to meet the needs of individuals with low financial sustainability who prefer to satisfy their lower-level (safety) needs first, and thereafter seek higher-level (self-actualization) needs to maximize the optimal returns.…”

mentioning

confidence: 99%

Decision Sciences, Economics, Finance, Business, Computing, and Big Data: Connections

2018

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This paper provides a review of some connecting literature in Decision Sciences, Economics, Finance, Business, Computing, and Big Data. We then discuss some research that is related to the six cognate disciplines. Academics could develop theoretical models and subsequent econometric and statistical models to estimate the parameters in the associated models. Moreover, they could then conduct simulations to examine whether the estimators or statistics in the new theories on estimation and hypothesis have small size and high power. Thereafter, academics and practitioners could then apply their theories to analyze interesting problems and issues in the six disciplines and other cognate areas. KeywordsDecision sciences, economics, finance, business, computing, and big data, theoretical models, econometric and statistical models, applications. JEL Classification AbstractThis paper provides a review of some connecting literature in Decision Sciences, Economics, Finance, Business, Computing, and Big Data. We then discuss some research that is related to the six cognate disciplines. Academics could develop theoretical models and subsequent econometric and statistical models to estimate the parameters in the associated models. Moreover, they could then conduct simulations to examine whether the estimators or statistics in the new theories on estimation and hypothesis have small size and high power. Thereafter, academics and practitioners could then apply their theories to analyze interesting problems and issues in the six disciplines and other cognate areas.

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Maslow Portfolio Selection for Individuals with Low Financial Sustainability

Cited by 32 publications

References 42 publications

Optimal Solution Techniques in Decision Sciences: A Review

Optimal Solution Techniques in Decision Sciences: A Review

Big Data, Computational Science, Economics, Finance, Marketing, Management, and Psychology: Connections

Decision Sciences, Economics, Finance, Business, Computing, and Big Data: Connections

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