This study investigates return and asymmetric volatility spillovers dynamic correlations between the main small medium-sized enterprise (SME) stock markets in Saudi Arabia Egypt for periods before during COVID-19 pandemic. Return are modelled using a VAR-asymmetric BEKK–GARCH (1,1) model, while DCC–GARCH model is employed to conditional these markets, which then used determine explore portfolio...

modern portfolio theories are based on markowitz’s portfolio optimization model that involves the assumption of mean variance behavior and therefore require the asymmetry and normality of returns. this issue also affects the capital asset pricing model that estimates systematic risk and uses it in pricing securities. this article analyzes the various measures of risk. the main purpose of this r...

Selected hedge funds employ trend-following strategies in an attempt to achieve superior risk adjusted returns. We employ a lookback straddle approach for evaluating the return characteristics of a trend following strategy. The strategies can improve investor performance in the context of a multi-period dynamic portfolio model. The gains are achieved by taking advantage of the funds’ high level...

Using a comprehensive and survivor bias-free dataset of US hedge funds, we document the role that inside investment plays in managerial compensation and fund performance. We find that funds with greater investment by insiders outperform funds with less “skin in the game” on a factor-adjusted basis, exhibit greater return persistence, and feature lower fund flow-performance sensitivities. These ...

In this tutorial paper we introduce different approaches to Markowitz portfolio optimization, and we show how to solve such problems in MATLAB, R and Python using the MOSEK optimization toolbox for MATLAB, the Rmosek package, and the MOSEK Python API, respectively. We first consider conic formulations of the basic portfolio selection problem, and we then discuss more advanced models for transac...

In the traditional portfolio model, investors calculate the expected return of assets and the covariance matrix for optimal asset allocation. This paper divides market sentiment period into three states and selectes the securities in the Chinese stock market to construct portfolios. We implement both the Fama-French five-factor model and the robust median covariance matrix approach for predicti...

Portfolio management in finance is more than a mathematical problem of optimizing performance under risk constraints. A critical factor in practical portfolio problems is severe uncertainty – ignorance – due to model uncertainty. In this paper, we show how to find the best portfolios by adapting the standard risk-return criterion for portfolio selection to the case of severe uncertainty, such a...

The success of quantitative approaches to portfolio choice crucially depends on the considered return model. Experts however do not agree on which return model is most appropriate. This controversy about the model specification introduces uncertainty in the optimal portfolio choice. We will not meddle in the discussion on which model specification is most appropriate. Instead we consider the ad...

Researchers have identified hundreds of factors that purport to predict equity returns; we find a half dozen that provide an opportunity to outperform the market. To maximize risk-adjusted returns, diversify across smart beta strategies that access the value, low beta, profitability, investment, momentum, and size factors. Systematic rebalancing to fixed weights—reducing exposure to popular fac...

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...