Selecting a portfolio with skewness: Recent evidence from US, European, and Latin American equity markets

Prakash, Arun J.; Chang, Chun‐Hao; Pactwa, Therese E.

doi:10.1016/s0378-4266(02)00261-3

Cited by 180 publications

(75 citation statements)

References 19 publications

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“…4 To explain their differences, consider portfolio selection as an example. We assumed a portfolio selection problem with skewness that adopt the Polynomial Goal programming (PGP) method for optimisation, see Lai (1991), Chunhachinda, et al (1997 and Prakash, et al (2003) for more details. In constructing the optimisation, the…”

Section: Risk Measures Of Variance and Below-target Variancementioning

confidence: 99%

The effect of downside risk reduction on UK equity portfolios included with Managed Futures Funds

Tee

2009

International Review of Financial Analysis

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Section: Risk Measures Of Variance and Below-target Variancementioning

confidence: 99%

The effect of downside risk reduction on UK equity portfolios included with Managed Futures Funds

Tee

2009

International Review of Financial Analysis

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“…Stephens and Proffitt (1991) extend the work to develop a generalized performance evaluation model which allows for multiple moments of utility and find that higher moments especially skewness has significant impact on the performance rankings of internationally diversified mutual funds [18]. Lai (1991) [19], Chunhachinda, Dandapanib, Hamidb, Prakash (1997) [20] and Prakash, Chang, Pactwa (2003) [21] explore the portfolio selection with skewness by formulating a goal programming that provides a set of weights for an optimum investment portfolio which satisfy some competing objectives that maximizes both the expected returns and positive skewness, and simultaneously minimize the risk (variance).…”

Section: Previous Literaturementioning

confidence: 99%

Importance of Skewness in Investor Utility: Evidence from the Chinese Stock Markets

Kun¹

2017

JMF

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The goal of this study is to evaluate the importance of skewness in investor utility when predicting stock market return by financial ratio variable. We use the daily time series of four major stock market indices of Shanghai Stock Exchanges and Shenzhen Stock Exchanges. We find evidence of predictability of price-to-earnings ratio and price-to-book ratio on the market returns. Using the evidence of predictability, we find evidence that including skewness leads higher utility. The comparison among different ways to calculate the skewness indicate the calculation method mostly used in popular statistical software may lead to the highest utility.

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“…3. In order to elaborate their differences, we consider a portfolio selection problem along with skewness, which fits Polynomial Goal programming (PGP) framework to optimization; see for more details Chunhachinda et al (1997) and Prakash et al (2003). To make the optimization, the standard statistical moment of distributions are incorporated where investors show a preference on higher values than skewness and mean returns, and detestation on higher values than kurtosis and variance (Scott and Horvath, 1980).…”

Section: Notesmentioning

confidence: 99%

The effects of drawdown risk reduction on the US hedge funds

Baghdadabad

2013

J Deriv Hedge Funds

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We investigate the effects of drawdown risk reduction on the US hedge funds. Despite the existence of numerous evidences on the asymmetric distribution of portfolio returns, the asymmetric risk measures have been extensively applied in risk management during recent years with the considerable applications on the lower partial moment (LPM) methodology. Unlike prior literatures, we use the drawdown risk measure (DRM), which is a special case of LPM, to study the impacts of drawdown risk decrease on management styles of the US hedge funds. The monthly returns are applied for 1720 US hedge funds over the period [2000][2001][2002][2003][2004][2005][2006][2007][2008][2009][2010][2011]. The optimization models in the DRM form are run to optimize the risk measures and investigate the effects of drawdown risk reduction. We find that the potential benefits of funds' diversification may weaken decreases in tolerance levels of drawdown risk. Our findings increase the importance of risk (tolerance) perception, in particular drawdown risk, when making many investment decisions. We find that it can negatively affect portfolio returns. Our findings also show that skewness does not impose any significant problem in the DRM model. The DRM optimization model reduces investors' risk more than the conventional models and can be accommodated with risk-averse investors' approach.

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Selecting a portfolio with skewness: Recent evidence from US, European, and Latin American equity markets

Cited by 180 publications

References 19 publications

The effect of downside risk reduction on UK equity portfolios included with Managed Futures Funds

The effect of downside risk reduction on UK equity portfolios included with Managed Futures Funds

Importance of Skewness in Investor Utility: Evidence from the Chinese Stock Markets

The effects of drawdown risk reduction on the US hedge funds

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