Pierpaolo Ferrari’s research while affiliated with Università degli Studi di Brescia and other places

This chapter identifies and investigates the stages of the investment portfolio management, dividing the investment process into the following stages: the identification of the objectives and the constraints of the investment policy; the formalisation of the investment strategy; the implementation of the financial strategy; the periodic rebalancing of the portfolio; the assessment of results and risk control. The starting point for setting up an investment management policy is the identification of the objectives and obligations of the investor. Once the objectives and constraints of the investment policy have been defined, institutional investors need to identify the financial strategy they intend to implement, in order to achieve efficient risk-return combinations from the resources invested during a given period of time. In order to reach these objectives, the investor must identify: the approach underlying the investment policy; financial instruments in which to invest and the associated risks; ex ante constraints to risk exposure; management style adopted; management method, whether internal or delegated, to adopt when such a choice is possible; and organisational division of tasks and responsibilities of the various subjects involved in the investment process. The financial strategy must be subjected to periodical review, in order to assess its effective congruence with the objectives and requirements of the investor. This chapter provides an in-depth analysis of each stage of the investment management policy.

The performance evaluation of an investment portfolio is designed to appraise the quality of the asset manager’s work by analysing the outcomes achieved and the ways in which these results were obtained. This activity involves the identification of: (1) return on the investment portfolio, accounting for alternative calculation methods and selecting the most appropriate one, depending on the objective pursued; (2) portfolio risk, in its various absolute, asymmetric, and relative forms, and the related risk-adjusted performance indicators; (3) the asset manager’s ability to perform effective stock picking by selecting the best stocks on the reference market; (4) the asset manager’s ability to perform profitable market timing through effective tactical asset allocation, by temporarily overweight the sectors and asset classes which will outperform the market and, at the same time, underweight those which will underperform; (5) performance persistence, understood as an evaluation of the continuity and frequency with which the asset manager ranks in the best percentiles of his/her reference peer group.

This chapter looks at the economic, technical, and regulatory issues of asset management products, with particular attention paid to collective investment vehicles. Investment fund classification and the alternative legal structures (common funds, open-end investment companies, unit trusts) for conducting collective portfolio management are examined. Management strategies and the choice between active management and indexed management are also investigated. Restrictions to investment policies, public documentation, and charges of investment funds are explored, assuming the perspective of European Union investors. The final part of the chapter examines other types of asset management products, like individual portfolio management, investment-oriented insurance policies, and structured products, which have a high rate of substitutability with investment funds and represent their natural competitors.

Sustainable investments encompass a set of investment strategies that, when evaluating companies and institutions, integrate financial analysis with environmental, social, and governance criteria (ESG), aiming to create value for investors and society as a whole. Sustainable investments involve a holistic approach that considers not only financial performance but also the broader impact of companies on the environment, society, and governance structures. Specifically, environmental considerations pertain to the challenges of climate change, ecosystem impacts, and related risks; social considerations address issues of inequality, inclusiveness, labour relations, investment in human capital, and improving relations within communities; and governance of public and private institutions relates to the evolution of the corporate governance model and the issues faced by workers and their trade union representatives. This chapter explores strategies for effectively integrating sustainability criteria into the investment process.

The increasing interest of investors in environmental, social, and governance (ESG) issues has prompted asset managers to develop new approaches to strategic asset allocation that can effectively integrate ESG factors into the optimization process. This study reviews the main techniques of the most recent ESG‐efficient portfolio optimization models. Furthermore, this study conducts an empirical investigation to identify the impact of ESG constraints on mean–variance efficient allocations, and extends existing approaches by incorporating a downside risk framework. Our findings reveal that social and combined ESG ratings mitigate the negative skewness of portfolio returns, and that ESG rating, environmental rating, social rating, and combined ESG rating allow the sustainable investor to incur lower transaction costs.

Mean-variance optimization often leads to unreasonable asset allocations. This problem has forced scholars and practitioners alike to introduce portfolio constraints. The scope of our study is to verify which type of constraint is more suitable for achieving efficient performance. We have applied the main techniques developed by the financial community, including classical weight, flexible, norm-based, variance-based, tracking error volatility, and beta constraints. We employed panel data on the monthly returns of the sector indices forming the MSCI All Country World Index from January 1995 to December 2020. The assessment of each strategy was based on out-of-sample performance, measured using a rolling window method with annual rebalancing. We observed that the best strategies are those subject to constraints derived from the equal-weighted model. If the goal is the best compromise between absolute return, efficiency, total risk, economic sustainability, diversification, and ease of implementation, the best solution is a portfolio subject to no short selling and bound either to the equal weighting or to TEV limits. Overall, we found that constrained optimization models represent an efficient alternative to classic investment strategies that provide substantial advantages to investors.

Over recent years, investors' attention on the environment, social responsibility, and governance (ESG) has been growing. At the same time, managers, investors, and regulators are interested in ascertaining whether mutual funds that invest in ESG‐compliant assets perform better than those with a low ESG commitment. The sustainability of funds' portfolios can be measured by ESG ratings, a measure of the financially material ESG factors of the securities held by a fund. Our study therefore aims to verify whether funds with high ESG ratings outperform funds with low ESG ratings, considering the risks taken, including higher moments, and costs borne by investors. Our analysis is carried out on a sample of 634 European mutual funds. By using data envelopment analysis, it provides evidence of the superior efficiency of funds investing in high ESG‐rated securities.

Following the criticism surrounding capitalization-weighting, both academic and practitioner communities have developed alternative approaches to portfolio construction. We analyze one of these approaches, fundamentals-based weighting, which identifies the weights of portfolio constituents on the basis of their market multiples and accounting ratios. Our analysis is carried out on four fundamentals-weighted portfolios (FW) based on four different weighting variants, the capitalization-weighted portfolio (CW), and the equally-weighted (EW) portfolio, from January 2004 to December 2020, and in two subperiods (2004–2011 and 2011–2020). We find that in the first subperiod, the EW portfolio shows the highest risk-adjusted performance, followed by the FW portfolios. In contrast, in the second subperiod and in the period as a whole, the CW portfolio outperforms the other portfolios in terms of risk-adjusted performance. Overall, we conclude that both FW portfolios and the EW portfolio do not exhibit superior results when compared with the classic CW portfolio. Therefore, we have shown that FW and EW techniques provide superior risk-adjusted performance only during a period of exceptional financial turmoil. However, under normal conditions, they cannot be recommended as a rational investment strategy. JEL classification numbers: G11, G14. Keywords: Fundamental weighting, Capitalization weighting, Equal weighting, Value investing, Indexed investing.

In the last decades, risk-based portfolio construction techniques have enjoyed a widespread diffusion in the financial community. This study aims at evaluating how these portfolio construction techniques produce different results depending on whether the segmentation of the stock market investment universe is based on sectorial or geographical criteria. An empirical analysis, applied on the global equity market, is carried out by making use of the typical and most advanced statistical and financial evaluation measures. Geographical segmentation is carried out in relation to the listing market, while sectorial segmentation is made in relation to the productive sectors to which individual companies belong. Our comparative analysis provides substantially coherent results, demonstrating a significant preference for the sectorial criterion compared to the geographic one. In conclusion, this result can be attributed to the subdivision of the investment universe into sectorial indices characterized by greater internal coherence and better external differentiation, in addition to the lower concentration of sectorial segmentation compared to the geographical one.

This study provides an empirical analysis back-testing the implementation of a dispersion trading strategy to verify its profitability. Dispersion trading is an arbitrage-like technique based on the exploitation of the overpricing of index options, especially index puts, relative to individual stock options. The reasons behind this phenomenon have been traced in literature to the correlation risk premium hypothesis (i.e., the hedge of correlations drifts during market crises) and the market inefficiency hypothesis. This study is aimed at evaluating whether dispersion trading can be implemented with success, with a focus on the Standard & Poor’s 100 options. The risk adjusted return of the strategy used in this empirical analysis has beaten a buy-and-hold alternative on the S&P 100 index, providing a significant over-performance and a low correlation with the stock market. The findings, therefore, provide an evidence of inefficiency in the US options market and the presence of a form of “free lunch” available to traders focusing on options mispricing.