Sphere-sphere intersection for investment portfolio diversification — A new data-driven cluster analysis

Haddad, Michel Ferreira Cardia

doi:10.1016/j.mex.2019.05.025

Cited by 4 publications

(3 citation statements)

References 11 publications

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“…Higher frequency of occurrence and extremely strong intensity of crises in recent decades have created a demand for the development of suitable methods of clustering in order to distinguish investment alternatives. A new method of clustering presented by Haddad (2019) could help investors when faced with investment decisions, especially during periods of high volatility when stocks tend to become more similar.…”

Section: Impact Of Crises On Risk Diversificationmentioning

confidence: 99%

How Many Stocks Are Sufficient for Equity Portfolio Diversification? A Review of the Literature

Zaimović

Omanovic

Arnaut-Berilo

2021

JRFM

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Using extensive and comprehensive databases to select a subset of research papers, we aim to critically analyze previous empirical studies to identify certain patterns in determining the optimal number of stocks in well-diversified portfolios in different markets, and to compare how the optimal number of stocks has changed over different periods and how it has been affected by market turmoil such as the Global Financial Crisis (GFC) and the current COVID-19 pandemic. The main methods used are bibliometric analysis and systematic literature review. Evaluating the number of assets which lead to optimal diversification is not an easy task as it is impacted by a huge number of different factors: the way systematic risk is measured, the investment universe (size, asset classes and features of the asset classes), the investor’s characteristics, the change over time of the asset features, the model adopted to measure diversification (i.e., equally weighted versus optimal allocation), the frequency of the data that is being used, together with the time horizon, conditions in the market that the study refers to, etc. Our paper provides additional support for the fact that (1) a generalized optimal number of stocks that constitute a well-diversified portfolio does not exist for whichever market, period or investor. Recent studies further suggest that (2) the size of a well-diversified portfolio is larger today than in the past, (3) this number is lower in emerging markets compared to developed financial markets, (4) the higher the stock correlations with the market, the lower the number of stocks required for a well-diversified portfolio for individual investors, and (5) machine learning methods could potentially improve the investment decision process. Our results could be helpful to private and institutional investors in constructing and managing their portfolios and provide a framework for future research.

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Section: Impact Of Crises On Risk Diversificationmentioning

confidence: 99%

How Many Stocks Are Sufficient for Equity Portfolio Diversification? A Review of the Literature

Zaimović

Omanovic

Arnaut-Berilo

2021

JRFM

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“…The SCA method is performed through four subsequent steps, in which each investment alternative * is represented as an 2-sphere in the three-dimensional Euclidean space R 3 . 16 In the first step is performed an analysis over the (i) trajectory of each investment alternative through time based on three variables placed at the axes x, y, and z in R 3 , and (ii) the calculation of the spherical volume variation, termed † as V i|t , in which the correspondent 2-sphere (simply sphere henceforth) dynamic radius ‡ is found. Both (i) and (ii) are based on relevant § variables used as data inputs to compare investment alternatives during a time span.…”

Section: Introductionmentioning

confidence: 99%

“…The main objective of the proposed method in the context of this study is to support financial investors to precisely measure the level of similarity between competing investment alternatives through time. The SCA method is performed through four subsequent steps, in which each investment alternative is represented as an 2‐sphere in the three‐dimensional Euclidean space ℝ 3 . 16 …”

Section: Introductionmentioning

confidence: 99%

Harnessing the power of intersection for pattern recognition: a novel unsupervised learning method and its application to financial engineering

Haddad

2021

Engineering Reports

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In the present paper a data‐driven hard cluster analysis derived from a novel similarity measure is proposed to support financial investors in their portfolio management decision‐making process. The main objective of the proposed method is to provide a less arbitrary learning procedure to quantify similarity levels between investment alternatives (pairwise) as well as revealing clustering patterns (whole sample). This is especially useful during periods of high volatility, when investment alternatives tend to become more similar and, therefore, harder to distinguish between themselves. The method dynamics may be readily interpreted through a clear data visualisation. The advantages and caveats of the proposed method is compared to the most popular class of cluster analysis, applied to the well‐known Fisher's Iris dataset. Such results show a slightly superior performance of the proposed method but, most importantly, through remarkably different clustering allocation approaches. Moreover, further empirical results applied to daily data reflecting a period of 15 years of time series of economies/stock markets of the Group of Seven (G7) illustrate the potential practical usefulness of the proposed unsupervised learning method, particularly, for portfolio strategy, asset allocation, and investment diversification.

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Effects of smart agricultural production investment announcements on shareholder value: Evidence from China

Liu

Long

Wang

et al. 2022

Journal of Management Science and Engineering

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Sphere-sphere intersection for investment portfolio diversification — A new data-driven cluster analysis

Abstract: Graphical abstract

Cited by 4 publications

References 11 publications

How Many Stocks Are Sufficient for Equity Portfolio Diversification? A Review of the Literature

How Many Stocks Are Sufficient for Equity Portfolio Diversification? A Review of the Literature

Harnessing the power of intersection for pattern recognition: a novel unsupervised learning method and its application to financial engineering

Effects of smart agricultural production investment announcements on shareholder value: Evidence from China

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