Portfolio Strategies to Track and Outperform a Benchmark

Glabadanidis, Paskalis

doi:10.3390/jrfm13080171

Cited by 6 publications

(3 citation statements)

References 24 publications

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“…A real case study is carried out to assess the financial performance of the companies of DJIA between the period 2015 and 2020 using the proposed model. The companies of DJIA have been studied by past researchers in portfolio investment [ 73 , 74 , 75 ].…”

Section: Methodsmentioning

confidence: 99%

Financial Network Analysis on the Performance of Companies Using Integrated Entropy–DEMATEL–TOPSIS Model

Fai

Siew

Lam

2022

Entropy

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In this paper, we propose a multi-criteria decision making (MCDM) model by integrating the entropy–DEMATEL with TOPSIS model to analyze the causal relationship of financial ratios towards the financial performance of the companies. The proposed model is illustrated using the financial data of the companies of Dow Jones Industrial Average (DJIA). The financial network analysis using entropy–DEMATEL shows that the financial ratios such as debt to equity ratio (DER) and return on equity (ROE) are classified into the cause criteria group, whereas current ratio (CR), earnings per share (EPS), return on asset (ROA) and debt to assets ratio (DAR) are categorized into the effect criteria group. The top three most influential financial ratios are ROE, CR and DER. The significance of this paper is to determine the causal relationship of financial network towards the financial performance of the companies with the proposed entropy–DEMATEL–TOPSIS model. The ranking identification of the companies in this study is beneficial to the investors to select the companies with good performance in portfolio investment. The proposed model has been applied and validated in the portfolio investment using a mean-variance model based on the selection of companies with good performance. The results show that the proposed model is able to generate higher mean return than the benchmark DJIA index at minimum risk. However, short sale is not allowed for the applicability of the proposed model in portfolio investment.

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Section: Methodsmentioning

confidence: 99%

Financial Network Analysis on the Performance of Companies Using Integrated Entropy–DEMATEL–TOPSIS Model

Fai

Siew

Lam

2022

Entropy

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“…The MAD model, proposed model and the naive diversification strategy are tested with a numerical example that consists of weekly returns of stocks of the Dow Jones Industrial Average (DJIA), which are listed in the New York Stock Exchange (NYSE), by comparing the performance of the optimal portfolio for the two periods, which are January 2016-December 2019 (before the COVID-19 pandemic period) and January 2020-March 2021 (within the COVID-19 pandemic period). The returns of stocks of the DJIA have been used as data in studies on portfolio optimization by past researchers [27][28][29].…”

Section: Research Developmentmentioning

confidence: 99%

Portfolio Optimization with a Mean–Absolute Deviation–Entropy Multi-Objective Model

Siew

Jaaman

2021

Entropy

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Investors wish to obtain the best trade-off between the return and risk. In portfolio optimization, the mean-absolute deviation model has been used to achieve the target rate of return and minimize the risk. However, the maximization of entropy is not considered in the mean-absolute deviation model according to past studies. In fact, higher entropy values give higher portfolio diversifications, which can reduce portfolio risk. Therefore, this paper aims to propose a multi-objective optimization model, namely a mean-absolute deviation-entropy model for portfolio optimization by incorporating the maximization of entropy. In addition, the proposed model incorporates the optimal value of each objective function using a goal-programming approach. The objective functions of the proposed model are to maximize the mean return, minimize the absolute deviation and maximize the entropy of the portfolio. The proposed model is illustrated using returns of stocks of the Dow Jones Industrial Average that are listed in the New York Stock Exchange. This study will be of significant impact to investors because the results show that the proposed model outperforms the mean-absolute deviation model and the naive diversification strategy by giving higher a performance ratio. Furthermore, the proposed model generates higher portfolio mean returns than the MAD model and the naive diversification strategy. Investors will be able to generate a well-diversified portfolio in order to minimize unsystematic risk with the proposed model.

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“…The well-known passive investment strategy approach was developed based on the invalid assumption that the market is efficient and the price reflects the available information, and, therefore, the future price is predictable (Maneli et al, 2022;Jeremias&Fatih, 2019;Zimon& Robert, 2020). Furthermore, this theory requires no involvement in trading activities and aims to generate a similar return to the market return (Birla, 2012;Glabadanidis, 2020). However, there is no such efficient market, and information available in the market might be limited or possessed by certain parties.…”

Section: Introductionmentioning

confidence: 99%

Factors Affecting Stock Selection and Market Timing Ability Between the Developed Country and Emerging Countries in Asean Markets

Hutabarat,

Sinaga,

Purba

et al. 2023

J. Professional Business Review

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Objective: This research is designed to propose empirical evidence on factors affecting stock selection ability and market timing ability. Theoretical framework: Recent research found that most equity mutual funds underperform the market return due to a lack of stock selection and market timing abilities. However, rarely do they propose evidence of factors affecting the existence of these abilities Method: There are two-panel regression models developed in this research to show evidence of factors affecting stock selection and market timing abilities. The Dumitrescu–Hurlin (DH) test is used to gain a comprehensive understanding of the causality relationship between the variables Results and Conclusion: Based on observation of three ASEAN countries, this research proposes empirical evidence that the growth of fund size, volatility of the fund’s net asset value (NAV), and performance indicators of the underlying assets affect the stock selection ability differently in the respective countries. Similarly, the growth of fund size, volatility of the fund’s NAV, and macroeconomic indicators also affect the market timing ability differently Implications of the research: Therefore, the implementation of investment strategies in the three observed markets considers factors affecting the existence of the two abilities, effectively generating outperforming returns. Originality/value: Recent studies focused more on whether equity mutual funds are managed with stock selection and market timing abilities but not on factors affecting those abilities. This research proposes empirical evidence on factors affecting those abilities in different markets through econometrics analyses on panel data and the Dumitrescu–Hurlincausality test.

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Portfolio Strategies to Track and Outperform a Benchmark

Cited by 6 publications

References 24 publications

Financial Network Analysis on the Performance of Companies Using Integrated Entropy–DEMATEL–TOPSIS Model

Financial Network Analysis on the Performance of Companies Using Integrated Entropy–DEMATEL–TOPSIS Model

Portfolio Optimization with a Mean–Absolute Deviation–Entropy Multi-Objective Model

Factors Affecting Stock Selection and Market Timing Ability Between the Developed Country and Emerging Countries in Asean Markets

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