Robust Markowitz mean‐variance portfolio selection under ambiguous covariance matrix

This paper studies a robust continuous‐time Markowitz portfolio selection problem where the model uncertainty affects the covariance matrix of multiple risky assets. This problem is formulated into a min–max mean‐variance problem over a set of nondominated probability measures that is solved by a McKean–Vlasov dynamic programming approach, which allows us to characterize the solution in terms of a Bellman–Isaacs equation in the Wasserstein space of probability measures. We provide explicit solutions for the optimal robust portfolio strategies and illustrate our results in the case of uncertain volatilities and ambiguous correlation between two risky assets. We then derive the robust efficient frontier in closed form, and obtain a lower bound for the Sharpe ratio of any robust efficient portfolio strategy. Finally, we compare the performance of Sharpe ratios for a robust investor and for an investor with a misspecified model.     

Stochastic regularization for the mean-variance allocation scheme

Despite being based on sound principles, the original Markovitz portfolio allocation theory cannot produce sound allocations, and restrictions or modifications need to be imposed from outside the theory in order to obtain meaningful portfolios. This is unsatisfactory, and the reasons for this failure are discussed, in particular, the unavoidable small eigenvalues of the covariance. Within the original principles of risk minimization and return maximization, several modifications of the original theory are introduced. First, the strategic and tactical time horizons are separated. A base long-term allocation is chosen at the strategic time horizon, while the portfolio is optimized at the tactical time horizon using information from the price histories. Second, the tactical portfolio is financed by the strategic one, and a funding operator is introduced. The corresponding optimal allocation (without constraints) has one free parameter fixing the leverage. Third, the transaction costs are taken into account. This includes the current re-allocation cost, but crucially the expected costs of the next reallocation. This last term depends on the sensitivity of the allocation with respect to the covariance, and the expectation introduces another dependency on the (inverse) covariance. The new term regularizes the original minimization problem by modifying the lower part of the spectrum of the covariance, leading to meaningful portfolios. Without constraints, the final Lagrangian can be minimized analytically, with a solution that has a structure similar to the original Markovitz solution, but with the inverse covariance regularized by the expected transaction costs.     

Risk–Return Profiles of Islamic Equities and Commodity Portfolios in Different Market Conditions

Motivated by the recent phenomenal growth in Islamic finance and the financialization of commodities, this study makes an initial attempt to investigate the risk–return profiles of optimized portfolios combining (a) Islamic equities with commodities and (b) conventional equities with commodities during the crises and noncrises periods. The findings tend to indicate that Islamic equity–commodity portfolios provide relatively higher diversification benefits than the conventional equity–commodity portfolios during the 1997 Asian Financial Crisis triggered by the financial sector compared to the 2008 global financial crisis triggered by the real housing sector. The findings further suggest that except for a few cases, commodities in general and gold in particular improve diversification benefits.     

基于我国不同经济周期下基金投资策略的实证研究

基金资产管理的首要问题是资产配置问题。资产配置可以帮助基金经理降低资产价格波动对投资组合的负面影响,通过适应不同类型基金投资者的风险偏好来实现其长期投资目标。针对当前我国基金发展现状和前景,选择证券投资基金在我国不同经济周期背景下的资产配置策略进行分析,运用Markowitz的均值——方差分析方法与双规划模型相结合,为我国基金最优投资组合的构建给出分析和建议。     

引入VaR约束的投资组合模型

通过对Markowitz投资组合模型的简要分析,指出其存在缺陷.VaR是近年来最为流行的风险管理工具.本文将VaR约束引入Markowitz投资组合理论中,建立基于VaR约束下的投资组合模型.     

Art as an investment: risk, return and portfolio diversification in major painting markets

The present paper examines risk, return and the prospects for portfolio diversification among major painting and financial markets over the period 1976–2001. The art markets examined are Contemporary Masters, French Impressionists, Modern European, 19th Century European, Old Masters, Surrealists, 20th Century English and Modern US paintings. The financial markets comprise US Treasury bills, corporate and government bonds and small and large company stocks. In common with the published literature in this area, the present study finds that the returns on paintings are much lower and the risks much higher than conventional investment markets. Moreover, while low correlations of returns suggest that opportunities for portfolio diversification in art works alone and in conjunction with equity markets exist, the construction of Markowitz mean‐variance efficient portfolios indicates that no diversification gains are provided by art in financial asset portfolios. However, diversification benefits in portfolios comprised solely of art works are possible, with Contemporary Masters, 19th Century European, Old Masters and 20th Century English paintings dominating the efficient frontier during the period in question.     

证券投资组合理论在我国的应用及其模型拓展

Markowitz的证券投资组合理论引发了20世纪后半期金融学的第一次革命,为现代金融经济学的崛起奠定了坚实的基础。然而该理论应用在我国这样一个新兴的证券市场却面临着不少问题,有必要对当前我国证券市场的实际情况进行必要的剖析,对Markowitz模型做一些拓展。为了提高资本资产定价模型在我国证券市场的适用性,必须建立一个行之有效的证券市场。     

A semiparametric graphical modelling approach for large-scale equity selection

We propose a new stock selection strategy that exploits rebalancing returns and improves portfolio performance. To effectively harvest rebalancing gains, we apply ideas from elliptical-copula graphical modelling and stability inference to select stocks that are as independent as possible. The proposed elliptical-copula graphical model has a latent Gaussian representation; its structure can be effectively inferred using the regularized rank-based estimators. The resulting algorithm is computationally efficient and scales to large data-sets. To show the efficacy of the proposed method, we apply it to conduct equity selection based on a 16-year health care stock data-set and a large 34-year stock data-set. Empirical tests show that the proposed method is superior to alternative strategies including a principal component analysis-based approach and the classical Markowitz strategy based on the traditional buy-and-hold assumption.     

现阶段我国企业研发结构失衡的动因与破解策略——基于马克维茨投资组合模型的应用及实证检验

如何改善企业研发结构失衡是学界关注的热点问题。首次将马克维茨投资组合模型应用于不同风险研发投资中，从理论上揭示风险收益不平衡是影响企业研发结构失衡的关键因素。政府研发税式支持对风险较小的试验发展具有较强的减税效应，而对风险较大的基础研究减税效应不足。政府“一刀切”的研发税式支持政策抑制了企业研发结构优化。区域异质性分析结果表明，研发加计扣除政策有利于企业研发结构优化，而高新技术企业15%税率式优惠一定程度上加剧了企业研发结构失衡程度。政府在践行创新驱动经济高质量发展战略中，应根据研发支出风险大小，实施不同支持力度的研发财税扶持，间接提升风险较大的研发支出收益率，改变企业研发支出风险收益不匹配状况。     

New Evidence on Optimal Asset Allocation

Brocato and Steed (1998) showed that portfolio rebalancing based on NBER business cycle turning points substantially improves in‐sample Markowitz efficiency. In a similar vein, we investigate potential improvements from rebalancing based on turning points in the monetary cycle. We find that the monetary cycle has greater influence than the business cycle on the variance/covariance structure of multiple asset classes. Furthermore, we find substantial improvements in in‐sample efficiency beyond a buy‐and‐hold strategy and the business‐cycle approach. Importantly, our indicator of monetary cycle turning points has a practical advantage over NBER business cycle turning points, in that it relies only on ex ante information. In out‐of‐sample tests, we continue to find superior portfolio performance after transactions costs using the monetary cycle to time portfolio rebalancing.