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The 2019 Savvy Investor Awards were announced on December 9th. To celebrate the Awards, Savvy Investor has produced both a digital and print version of the Awards magazine, in which they highlight the Award Winners and also feature papers from the magazine's sponsors.

The four Featured Papers cover several diverse topic areas and include contributions from BNP Paribas, (Factor Investing) Robeco, (Asset Allocation) Invesco, (Quantitative Strategies) and Aviva Investors (ESG).

Savvy Investor has collated all of these papers below.


front page magazine

Private wants, public needs: creating better incentives for tech, pharma and infrastructure (Aviva Investors, 2019)

For compliance reasons, this paper is only accessible in certain geographies

In some instances, the private sector functions more efficiently than the public sector. For example, SpaceX recently began re-using rocket parts, which has driven down the cost of space flight significantly when compared to previous missions undertaken by NASA. In other cases, incentives are not properly aligned to allow the private sector to work towards a particular public good (such as the development of certain antibiotics or using viruses to fight bacteria). Whether the answer comes in the form of tax credits, golden payments for achieving milestones, or guarantees, there are several ways for governmental bodies and other public entities to aid the private sector, or for more than one party to work together towards a common goal. Figuring out better ways to share the costs of large-scale projects, as well as the risks at hand once they are undertaken will be critical aspects of future public-private collaborative partnerships.

Factor Investing in Equities and Corporate Bonds: Neutralising Bias (BNP Paribas AM, 2019)

Factor investing strategies use style factors such as value, quality, momentum or low risk to tilt portfolios in favour of rewarded risk premia. Such an approach is based on strong academic and empirical evidence, which suggests that stocks and corporate bonds exhibiting these characteristics should deliver higher risk-adjusted returns over the long-term. This paper makes the distinction between style factors (which are expected to generate excess return) and unrewarded factors. When building factor exposures it is important to control the exposures to these unrewarded factors, ensuring that the portfolio has no tracking error risk, relative to a benchmark portfolio, resulting from active exposures to them. Instead, the tracking error risk should result from tilting towards desirable style factors. BNP Paribas shows that ‘purifying’ factor exposures in this manner leads to greater information ratios for both equity and debt portfolios.

Global Factor Premiums (Robeco, 2019)

When investigating the existence of factors, most hypothesis testing is performed on U.S. equity market returns, using data sets that stretch back 20 or 30 years. However, the specific factors examined, the sample sizes, and the methodologies are often different. The situation is compounded by the allure of discovering new factors and the pressure to publish research on a popular topic like factor investing. As a result, it is widely thought that many of these ‘newly discovered’ factors may actually be the result of spurious relationships (false positives, a.k.a. type 1 errors). This is a process that statisticians refer to as ‘p-hacking.’ Robeco’s quantitative analysts adopt a more rigorous approach, simultaneously examining the significance of six global return factors across four different asset classes, using over 200 years of data and robust statistical criteria. The results speak for themselves the existence of these particular factors has become very difficult to refute.

Invesco Vision Portfolio Management Decision Support System (2019)

For compliance reasons, this paper is only accessible in certain geographies

Invesco Vision is a portfolio management decision support system. Backed by the BarraOne risk model, Invesco Vision allows for the precise modelling of asset covariances and other inputs related to risk evaluation. It also provides easy access to several portfolio construction and optimization techniques, such as Robust MVO, equal risk portfolios, and minimum variance portfolios. In addition to this, it is capable of running factor decompositions and scenario analysis. The paper concludes with 15 case studies on the application of Invesco Vision to common investment challenges such as risk optimization with respect to a reference portfolio, LDI solutions for DB pensions, and improving risk-adjusted returns using alternative assets.