This paper shows that unexpected stock returns must be associated with changes in expected future dividends or expected future returns A vector autoregressive method is used to break unexpected stock returns into these two components. In U.S. monthly data in 1927-88, one-third of the variance of unexpected returns is attributed to the variance of changing expected dividends, one-third to the va...

the present study is an attempt toward evaluating the performance of portfolios using mean-variance-skewness model with negative data. mean-variance non-linear framework and mean-variance-skewness non- linear framework had been proposed based on data envelopment analysis, which the variance of the assets had been used as an input to the dea and expected return and skewness were the output. conv...

In this analysis of the risk and return of stocks in the United States and global markets, we apply several portfolio construction and optimization techniques to U.S. and global stock universes. We find that (1) mean-variance techniques continue to produce portfolios capable of generating excess returns above transaction costs and statistically significant asset selection, (2) optimization tech...

If investors are more averse to the risk of losses on the downside than of gains on the upside, investors ought to demand greater compensation for holding stocks with greater downside risk. Downside correlations better capture the asymmetric nature of risk than downside betas, since conditional betas exhibit little asymmetry across falling and rising markets. We find that stocks with high downs...

Most conventional Reinforcement Learning (RL) algorithms aim to optimize decisionmaking rules in terms of the expected returns. However, especially for risk management purposes, other risk-sensitive criteria such as the value-at-risk or the expected shortfall are sometimes preferred in real applications. Here, we describe a parametric method for estimating density of the returns, which allows u...

This study presents a stochastic demand multi-product supplier selection model with service level and budget constraints using Genetic Algorithm. Recently, much attention has been given to stochastic demand due to uncertainty in the real world. Conflicting objectives also exist between profit, service level and resource utilization. In this study, the relationship between the expected profit an...

I study how growth affects liquidity of global stock exchanges and how liquidity determines cross-sectional returns on those stock exchange index portfolios. I measure portfolio liquidity by turnover ratio computed as value of shares traded over the market capitalization. I obtain data from FIBV, an association of global stock exchanges. In a multiple regression model for turnover ratio, I find...

In traditional econometrics, the quality of an individual investment – and of the investment portfolio – is characterized by its expected return and its risk (variance). For an individual investment or portfolio, we can estimate the future expected return and a future risk by tracing the returns x1, . . . , xn of this investment (and/or similar investments) over the past years, and computing th...