In the presence of skewness, portfolio selection requires to consider competing and conflicting objectives. We utilize polynomial goal programming to determine the optimal portfolio from emerging markets industries. The first part of this paper is concerned with an industry level analysis of the effects of portfolio selection when the skewness is taken into account. The second part of the paper...

Tissot indicatrices have provided visual measures of local area and isotropy distortions. Here we show how large scale distortions of flexion (bending) and skewness (lopsidedness) can be measured. Area and isotropy distortions depend on the map projection metric, flexion and skewness, which manifest themselves on continental scales, depend on the first derivatives of the metric. We introduce ne...

While standard models of risky choice account for the first and second statistical moments of reward outcome distributions (mean and variance, respectively), they often ignore the third moment, skewness. Determining a decision-maker's attitude about skewness is useful because it can help constrain process models of the mental steps involved in risky choice. We measured three rhesus monkeys' pre...

OBJECTIVE To determine whether pre-operative perfusion skewness and kurtosis derived from normalized cerebral blood volume (nCBV) histograms are associated with progression-free survival (PFS) of patients after partial resection of newly diagnosed glioblastoma. MATERIALS AND METHODS A total of 135 glioblastoma patients who had undergone partial resection of tumor (resection of < 50% of pre-op...

In this study, a novel neural network-based mean–variance–skewness model for optimal portfolio selection is proposed integrating different forecasts and trading strategies, as well as investors’ risk preference. Based on the Lagrange multiplier theory in optimization and the radial basis function (RBF) neural network, the model seeks to provide solutions satisfying the trade-off conditions of m...

This paper presents a parsimonious approach to estimating conditional skewness and kurtosis, as well as conditional variance, in financial log-returns time series. Using a GARCH formulation of the skew t-distribution (Jones and Faddy, 2003), autoregressive relationships are developed for the conditional skewness and conditional kurtosis. A numerical example indicates that allowing for estimates...

This paper reports the results of an experiment on the revealed preference for skewness in a comparison of continuous return distributions. We find that revealed preferences are highly sensitive to the way asset risks are communicated. While probability density functions lead to a pronounced preference for left-skewed distributions, the opposite is true for cumulative distribution functions. Sy...

A positive Indian Ocean Dipole (IOD) tends to have stronger cold sea surface temperature anomalies (SSTAs) over the eastern Indian Ocean with greater impacts than warm SSTAs that occur during its negative phase. Two feedbacks have been suggested as the cause of positive IOD skewness, a positive Bjerknes feedback and a negative SST-cloud-radiation (SCR) feedback, but their relative importance is...

Engle and Manganelli (2004) propose CAViaR, a class of models suitable for estimating conditional quantiles in dynamic settings. Engle and Manganelli apply their approach to the estimation of Value at Risk, but this is only one of many possible applications. Here we extend CAViaR models to permit joint modeling of multiple quantiles, Multi-Quantile (MQ) CAViaR. We apply our new methods to estim...

Several studies advocating safety first as a major concern to investors propose downside beta risk as an alternative to the traditional systematic riskbeta. Downside measures are concerned with a subset of the data and therefore the results in the studies that consider the downside beta only may be biased. This study addresses this issue by including downside co-skewness risk in addition to the...