Portfolio selection problem with liquidity constraints under non-extensive statistical mechanics

Pan, Zhao; Qu, Xiao

doi:10.1016/j.chaos.2015.10.026

Cited by 10 publications

(3 citation statements)

References 20 publications

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“…A variety of portfolio optimization frameworks have explored alternative objective functions utilizing risk measures other than standard volatility (Almahdi and Yang 2017;Bongini et al 2002;Calvo et al 2014;Soleimani et al 2009;Vercher et al 2007). Many authors in the field have taken existing theory and methodologies for the problem of portfolio selection and optimization (Bhansali 2007;Magdon-Ismail et al 2003;Moody and Saffell 2001), including statistical mechanics (Li and Zhang 2021;Zhao and Xiao 2016), clustering (Iorio et al 2018;León et al 2017), fuzzy sets (Ammar and Khalifa 2003;Kocada glı and Keskin 2015;Tanaka et al 2000), graph theory , regularization (Fastrich et al 2014;Li 2015;Pun and Wong 2019) regression trees (Cappelli et al 2021), and multiobjective optimization (Lam et al 2021;Mansour et al 2019). For further details, a review of such techniques for portfolio optimization was conducted by Milhomem and Dantas (2020).…”

Section: Overview Of Portfolio Optimizationmentioning

confidence: 99%

Semi-Metric Portfolio Optimization: A New Algorithm Reducing Simultaneous Asset Shocks

2023

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This paper proposes a new method for financial portfolio optimization based on reducing simultaneous asset shocks across a collection of assets. This may be understood as an alternative approach to risk reduction in a portfolio based on a new mathematical quantity. First, we apply recently introduced semi-metrics between finite sets to determine the distance between time series’ structural breaks. Then, we build on the classical portfolio optimization theory of Markowitz and use this distance between asset structural breaks for our penalty function, rather than portfolio variance. Our experiments are promising: on synthetic data, we show that our proposed method does indeed diversify among time series with highly similar structural breaks and enjoys advantages over existing metrics between sets. On real data, experiments illustrate that our proposed optimization method performs well relative to nine other commonly used options, producing the second-highest returns, the lowest volatility, and second-lowest drawdown. The main implication for this method in portfolio management is reducing simultaneous asset shocks and potentially sharp associated drawdowns during periods of highly similar structural breaks, such as a market crisis. Our method adds to a considerable literature of portfolio optimization techniques in econometrics and could complement these via portfolio averaging.

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Section: Overview Of Portfolio Optimizationmentioning

confidence: 99%

Semi-Metric Portfolio Optimization: A New Algorithm Reducing Simultaneous Asset Shocks

2023

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“…Liquidity: The liquidity of stocks in financial market could be used as an efficient objective or an important constraint in modeling to select appropriate stocks [56][57][58][59][60][61].…”

Section: Conclusion and Research Prospectsmentioning

confidence: 99%

Credibilistic Multi-Period Mean-Entropy Rolling Portfolio Optimization Problem Based on Multi-Stage Scenario Tree

Peykani,

Nouri,

Pishvaee

et al. 2023

Mathematics

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This study considers a time-consistent multi-period rolling portfolio optimization issue in the context of a fuzzy situation. Rolling optimization with a risk aversion component attempts to separate the time periods and psychological effects of one’s investment in a mathematical model. Furthermore, a resilient portfolio selection may be attained by taking into account fuzzy scenarios. Credibilistic entropy of fuzzy returns is used to measure portfolio risk because entropy, as a measure of risk, is not dependent on any certain sort of symmetric membership function of stock returns and may be estimated using nonmetric data. Mathematical modeling is performed to compare the Rolling Model (RM) and the Unified Model (UM). Two empirical studies from the Tehran stock market (10 stocks from April 2017 to April 2019) and the global stock market (20 stocks from April 2021 to April 2023) are utilized to illustrate the applicability of the suggested strategy. The findings reveal that RM can limit the risk of the portfolio at each time, but the portfolio’s return is smaller than that of UM. Furthermore, the suggested models outperform the standard deterministic model.

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“…Different approaches include statistical mechanics [18][19][20], clustering [21][22][23], fuzzy sets [24,25], networks [26], regularisation [27][28][29], Bayesian approaches [30,31] and multiobjective optimisation [32]. For further details, a review of such techniques for portfolio optimisation was conducted by [33].…”

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confidence: 99%

Portfolio diversification with varying investor abilities

James,

Menzies

2024

EPL

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We introduce new mathematical methods to study the optimal portfolio size of investment portfolios over time, considering investors with varying skill levels. First, we explore the benefit of portfolio diversification on an annual basis for poor, average and strong investors defined by the 10th, 50th and 90th percentiles of risk-adjusted returns, respectively. Second, we conduct a thorough regression experiment examining quantiles of risk-adjusted return as a function of portfolio size across investor ability, testing for trends and curvature within these functions. Finally, we study the optimal portfolio size for poor, average and strong investors in a continuously temporal manner using more than 20 years of data. We show that strong investors should hold concentrated portfolios, poor investors should hold diversified portfolios; average investors have a less obvious distribution with the optimal number varying materially over time.

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Portfolio selection problem with liquidity constraints under non-extensive statistical mechanics

Cited by 10 publications

References 20 publications

Semi-Metric Portfolio Optimization: A New Algorithm Reducing Simultaneous Asset Shocks

Semi-Metric Portfolio Optimization: A New Algorithm Reducing Simultaneous Asset Shocks

Credibilistic Multi-Period Mean-Entropy Rolling Portfolio Optimization Problem Based on Multi-Stage Scenario Tree

Portfolio diversification with varying investor abilities

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