A Weighted Portfolio Optimization Model Based on the Trend Ratio, Emotion Index, and ANGQTS

Chou, Yao-Hsin; Jiang, Yu-Chi; Hsu, Yi-Rui; Kuo, Shu-Yu; Kuo, Sy‐Yen

doi:10.1109/tetci.2021.3118041

Cited by 16 publications

(3 citation statements)

References 41 publications

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“…The model took into account the volatility of the portfolio comprehensively and automatically constructs them through quantum non-gates. The results showed that the algorithm had high accuracy and efficiency [19].…”

Section: Related Workmentioning

confidence: 97%

Optimizing Enterprise Marketing Project Portfolios Using Fuzzy Ant Colony Optimization

Mao

2024

INT J COMPUT COMMUN, Int. J. Comput. Commun. Control

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Enterprise marketing project portfolio optimization is important for business competitiveness, but involves multiple uncertain factors. An integrated model using fuzzy rules was proposed in this paper to enhance ant colony optimization. The fuzzy ant colony algorithm effectively handled ambiguity in project costs, returns, and risks when selecting an optimal portfolio of marketing initiatives. Experiments demonstrated the algorithm efficiency in converging towards high-quality solutions. Case studies indicated the model helped boost customer loyalty and profits through tailored marketing strategies, outperforming conventional approaches. The fuzzy optimization provides an effective decision-making framework for enterprises to maximize marketing effectiveness.

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Section: Related Workmentioning

confidence: 97%

Optimizing Enterprise Marketing Project Portfolios Using Fuzzy Ant Colony Optimization

Mao

2024

INT J COMPUT COMMUN, Int. J. Comput. Commun. Control

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“…Next, they compute a scoring function that takes into account fundamental factors such as the net profit margin and the cash flow ratio. Alternative stock evaluation and scoring strategies encompass the use of clustering to find groups of similar stocks [ 11 ], genetic algorithms [ 24 ] or swarm intelligence methodologies [ 25 – 27 ] to deal with portfolio optimization, and itemset mining to generate candidate portfolios satisfying global constraints on the expected portfolio returns [ 14 ]. [ 14 ] perform a greedy selection of the candidate portfolios based on a set of a user-specified constraints related to portfolio size and diversification level.…”

Section: Literature Reviewmentioning

confidence: 99%

Early portfolio pruning: a scalable approach to hybrid portfolio selection

2023

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Driving the decisions of stock market investors is among the most challenging financial research problems. Markowitz’s approach to portfolio selection models stock profitability and risk level through a mean–variance model, which involves estimating a very large number of parameters. In addition to requiring considerable computational effort, this raises serious concerns about the reliability of the model in real-world scenarios. This paper presents a hybrid approach that combines itemset extraction with portfolio selection. We propose to adapt Markowitz’s model logic to deal with sets of candidate portfolios rather than with single stocks. We overcome some of the known issues of the Markovitz model as follows: (i) Complexity: we reduce the model complexity, in terms of parameter estimation, by studying the interactions among stocks within a shortlist of candidate stock portfolios previously selected by an itemset mining algorithm. (ii) Portfolio-level constraints: we not only perform stock-level selection, but also support the enforcement of arbitrary constraints at the portfolio level, including the properties of diversification and the fundamental indicators. (iii) Usability: we simplify the decision-maker’s work by proposing a decision support system that enables flexible use of domain knowledge and human-in-the-loop feedback. The experimental results, achieved on the US stock market, confirm the proposed approach’s flexibility, effectiveness, and scalability.

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“…Yang and Huang (2022) showed that mutual funds with a higher proportion of actively managed funds outperform peer funds with a low percentage of actively managed funds over year 1993 to 2015 [6]. Besides, according to Chou et al ( 2022), an increasing number of people treat investments not only to enhance their own wealth but also to hedge against the risk of inflation [7]. Therefore, the most urgent affair is to decide an actively managed portfolio to help investors handling their money.…”

Section: Introductionmentioning

confidence: 99%

Portfolio Selection Based on a Four-Dimensional Weighted Scoring Model

Yuan¹

2023

BCPBM

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Although factor investment approaches are currently receiving a lot of attention, active investment strategies rarely apply the combination of different factors. This paper's major goal is to utilise a clearly defined model to assess if the portfolio chosen by the model offers superior total returns compared to standard indexes (S&P 100 is taken as an example in this article). The author constructs a weighted scoring model combing different indicators to well demonstrate four factors based on the identification of valuation, profitability, growth and pay-out. This paper collects data of high-capitalization corporates in US during the period from 2015 to 2021 to illustrate that an active management portfolio well designed by the weighted scoring model can outperform competing index strategies. The reported results illustrate that combined precisely weighted indicators deliver significant outcome of selected stocks, especially in the long-term condition. The 5-year return of the selected portfolio, which is determined by the model constructed, delivers the outstanding performance with returns of up to about 180%.

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A Weighted Portfolio Optimization Model Based on the Trend Ratio, Emotion Index, and ANGQTS

Cited by 16 publications

References 41 publications

Optimizing Enterprise Marketing Project Portfolios Using Fuzzy Ant Colony Optimization

Optimizing Enterprise Marketing Project Portfolios Using Fuzzy Ant Colony Optimization

Early portfolio pruning: a scalable approach to hybrid portfolio selection

Portfolio Selection Based on a Four-Dimensional Weighted Scoring Model

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