Interactive Multiple Objective Asset Allocation

Portfolio efficiency and suitability are two important goals in the asset allocation processing involving a financial advisor and clients. The Analytic Hierarchy Process (AHP) technique is employed as a framework to address an investor's multiple investment objectives. Questionnaires, GAMS (General Algebraic Modelling System) programs and spreadsheet models are developed to facilitate the communications between the financial advisor and investor.

Interactive Multiple Objective Asset Allocation

Portfolio efficiency and suitability are two important goals in the asset allocation processing involving a financial advisor and clients. The Analytic Hierarchy Process (AHP) technique is employed as a framework to address an investor's multiple investment objectives. Questionnaires, GAMS (General Algebraic Modelling System) programs and spreadsheet models are developed to facilitate the communications between the financial advisor and investor.

Board Diversity or Tokenism: A Case for Social Inclusion and an Efficiency Model

This exploratory paper examines the concept of diversity as a dynamic of board effectiveness. The study argues that diversity hardly works without putting in place systems and programmes that promote social inclusion, and, as such, research on board diversity must account for this element in building empirical frameworks and model specifications. The study finds that a great majority of previous studies have ignored this variable of significant importance and, in some instances, conflated it with diversity itself. This represents a material flaw that needs to be addressed. This paper offers guidance on how to measure and account for social inclusion and integration in board diversity research. Finally, a portfolio efficiency frontier model is proposed as a mechanism for differentiating between corporations with efficient board diversity and those that are tokenism based.

Estimation of portfolio efficiency considering social responsibility: Evidence from the multi-horizon diversification DEA

With the introduction of the concept of social responsibility investment/green investment, more and more investors have realized the importance of such investment, which has prompted portfolio managers to more comprehensively consider both financial and non-financial performance of portfolios in different time horizons. DEA (Data Envelopment Analysis), as a data-driven evaluation approach, has been widely used in performance evaluation of portfolios. However, the existing studies are mostly limited to single-horizon problems, and the evaluation indicators are mostly financial indicators, while ignoring the impact of non-financial indicators (e.g., social responsibility indicators). More importantly, the input-output process of portfolios in the multi-horizon framework also needs to be clarified. In this paper, we first define the input-output process of portfolios from the multi-horizon perspective, and then propose the corresponding stochastic output possibility sets based on portfolio returns and social responsibility indicators. We use the expectation and variance measures to derive the deterministic estimation of the above stochastic sets, where the expectations and variances of portfolio returns and social responsibility indicators are all regarded as outputs. We construct the multi-horizon diversification DEA models both with and without social responsibility constraints. Finally, we select the 20 component stocks of China ESG100 index to illustrate the difference between the multi-horizon models and the single-horizon models, and further discuss the impact of social responsibility on the portfolio efficiency and its ranking. The empirical results show that compared with the single-horizon models, the proposed models can provide portfolio managers with an improvement strategy to balance the performance of portfolio returns and social responsibility indicators in different time horizons. Further, we also find that the social responsibility has a greater impact on the portfolio efficiency and its ranking, especially when the portfolio managers pay more attention to the social responsibility performance.

Efficiency Evaluation and Selection Strategies for Green Portfolios under Different Risk Appetites

Since investors have diverse risk motives for green investments, this paper uses data envelopment analysis (DEA) and simulation to accurately evaluate the efficiency of green portfolios from the perspective of investors’ subjective risks and accordingly provide suitable investment selection strategies. On the one hand, the paper integrates investors’ risk preferences with efficiency evaluation models under the framework of behavioral finance, and then constructs a green portfolio efficiency evaluation model based on cumulative prospect theory on the basis of defining green portfolio efficiency. On the other hand, by bringing realistic Chinese stock data into the evaluation model and solving it with the help of large number iteration and DEA, the trends of frontier movements and selection options of green portfolios under the influence of different risk preferences are obtained and analyzed. The empirical simulation reveals that: (1) if investors’ risk aversion at return rises, it will not only reduce the expected prospective value of the green portfolio, but also shift down and flatten the frontier of the green portfolio; indicating that investors will tend to reduce their risk-tolerant attitude and prefer a conservative strategy under the same value condition. (2) If investors increase their risk-seeking in the case of losses, this will raise the expected prospect value of the green portfolio and lead to an inward and steeper green portfolio frontier; suggesting that, given equal value, investors prefer to increase their risk-taking capacity and use aggressive strategies in the hope of turning the profit around. (3) The efficiency results of green portfolios are very sensitive to changes in investors’ risk preferences, suggesting that investors need to select and match green portfolios with their own risk appetite levels. The above findings enrich and expand the risk types and evaluation models in previous green investment studies from the perspective of investors’ subjective risk.

Downside Risk Premium

The purpose of this chapter is to address the main developments and challenges on risk assessment and portfolio management. The former innovation in modern portfolio theory, Markowitz, has been succeeded from linear and non-linear optimization techniques that improve portfolio efficiency. Special emphasis is given on Roy's seminal work on “Safety First Criterion” which advocates that the safety of investments should be prioritized. Thus, an investment should be chosen in a way that it has the lowest probability of falling short of a required threshold of investors. This motivated Markowitz to advocate a downside risk measure based on semivariance. It captures the notion of risk as failure to meet some minimum target. It is influenced by returns below the target rate. It focuses on investors' concern with downside variability and loss reduction. This chapter offers a critical reflection of these recent developments and could be of interest for individual and institutional investors.

The Relationship Between Gold and Stock Markets During the COVID-19 Pandemic

This chapter aims to analyze portfolio diversification in the US, Europe, UK, Hong Kong, China, Japan, and the gold market (XAU) from January 2019 to July 2020. The results indicate that the markets have very significant causalities, which may call into question efficient portfolio diversification strategies. The DFA exponent coefficients suggest that the random walk hypothesis is rejected in certain markets, which has implications for investors, since some returns can be expected, creating opportunities for arbitrage and abnormal profits. These findings also open space for market regulators to take action to ensure better information among international financial markets. In conclusion, the authors believe investors should diversify their portfolios and invest in less risky markets in order to mitigate risk and improve portfolio efficiency.