Do investors like to diversify? A study of Markowitz preferences

Egozcue, Martín; García, Luis Fuentes; Wong, Wing‐Keung; Zitikis, Ričardas

doi:10.1016/j.ejor.2011.05.034

Cited by 66 publications

(27 citation statements)

References 14 publications

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“…However, it is well known that the market could have other types of investors (see, for example, Friedman and Savage (1948), Markowitz (1952), Thaler and Johnson (1990), Broll et al (2010) and Egozcue et al (2011) for more discussion). Under the assumption that the market could contain more than one type of investor, such as risk averters, as well as risk seekers, in this situations, academics could apply Theorem 1 to test whether Ω B (η) ≥ Ω A (η) for any η ≥ µ A .…”

Section: Market Efficiency and Rationalitymentioning

confidence: 99%

Stochastic Dominance and Omega Ratio: Measures to Examine Market Efficiency, Arbitrage Opportunity, and Anomaly

2017

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Both stochastic dominance and Omegaratio can be used to examine whether the market is efficient, whether there is any arbitrage opportunity in the market and whether there is any anomaly in the market. In this paper, we first study the relationship between stochastic dominance and the Omega ratio. We find that second-order stochastic dominance (SD) and/or second-order risk-seeking SD (RSD) alone for any two prospects is not sufficient to imply Omega ratio dominance insofar that the Omega ratio of one asset is always greater than that of the other one. We extend the theory of risk measures by proving that the preference of second-order SD implies the preference of the corresponding Omega ratios only when the return threshold is less than the mean of the higher return asset. On the other hand, the preference of the second-order RSD implies the preference of the corresponding Omega ratios only when the return threshold is larger than the mean of the smaller return asset. Nonetheless, first-order SD does imply Omega ratio dominance. Thereafter, we apply the theory developed in this paper to examine the relationship between property size and property investment in the Hong Kong real estate market. We conclude that the Hong Kong real estate market is not efficient and there are expected arbitrage opportunities and anomalies in the Hong Kong real estate market. Our findings are useful for investors and policy makers in real estate.

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Section: Market Efficiency and Rationalitymentioning

confidence: 99%

Stochastic Dominance and Omega Ratio: Measures to Examine Market Efficiency, Arbitrage Opportunity, and Anomaly

2017

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“…However, there are many other types of investors with different kinds of behaviors, for example, risk averters (Markowitz, 1952), risk 20 seekers (Wong and Li, 1999;Wong, 2007;Guo and Wong, 2016), and investors with S-shaped and reversed S-shaped utility functions Levy, 2002, 2004;Wong and Chan, 2008;Broll, et al, 2010;Egozcue, et al, 2011;Bai, et al, 2011). Extension to the study on other behavioral biases should, therefore, be made in the future.…”

Section: Empirical Findingsmentioning

confidence: 99%

Empirical study on conservative and representative heuristics of Hong Kong small investors adopting momentum and contrarian trading strategies

Chow

Hon

Wong

et al. 2018

IJRM

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Abstract:Recently, a new Bayesian approach has been developed to explain some market anomalies. In this paper, we conduct a questionnaire survey to examine whether the theory holds empirically by studying the conservative and representative heuristics by Hong Kong small investors who adopt momentum and/or contrarian trading strategies. In addition, our study provides evidence for the small investors on their time horizon and risk tolerance when facing uncertainty in their investments.Our findings are useful to small investors in their investment decision making and useful to financial advisors in providing service to small investors.

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“…Markowitz (1952), Levy andLevy (2002, 2004), Wong and Chan (2008), among others, suggest investors could follow S-shaped as well as reverse S-shaped utility functions. Broll, Egozcue, Wong, Zitikis (2010), and Egozcue, Fuentes García, Wong, and Zitikis (2011) argue that investment behavior for investors could follow S-shaped as well as reverse S-shaped utility functions. Recently, Guo, Qiao, and Wong (2017) introduce a new utility function for investors that consists of both risk-averse and risk-seeking components to provide a new solution to answer the observation posed by Friedman and Savage (1948) that investors buy insurance and also try their luck with lotteries.…”

Section: Utility Functionsmentioning

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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Do investors like to diversify? A study of Markowitz preferences

Cited by 66 publications

References 14 publications

Stochastic Dominance and Omega Ratio: Measures to Examine Market Efficiency, Arbitrage Opportunity, and Anomaly

Stochastic Dominance and Omega Ratio: Measures to Examine Market Efficiency, Arbitrage Opportunity, and Anomaly

Empirical study on conservative and representative heuristics of Hong Kong small investors adopting momentum and contrarian trading strategies

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

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