by Lionel Martellini, Director, EDHEC-Risk Institute
Precision medicine, a novel model that proposes the customization of healthcare, with treatments, practices or products being tailored to a subgroup of patients, instead of a one-drug-fits-all model, is widely regarded as a fundamental breakthrough that will mark the start of a whole new era for medical practice. In the same spirit, one could argue that investment management is justified as an industry only to the extent that it can demonstrate a capacity to add value through the design of dedicated and meaningful investor-centric investment solutions, as opposed to one-size-fits-all manager-centric investment products. In this context, and to emphasize the parallel with what we are seeing in the healthcare industry, the term precision investing can be used to describe this trend from generic products to personalized solutions in investment management.
We are witnessing the development of a mass customization approach
Note that while precision medicine refers to the tailoring of medical treatment to the individual characteristics of each patient, it does not literally mean the creation of drugs or medical devices that are unique to a patient. Instead, it is based on the ability to classify individuals into subpopulations that differ in their susceptibility to a particular disease, in the biology or prognosis of the diseases they may develop, or in their response to a specific treatment. Similarly, precision investing does not mean full customization of portfolios tailored to meet the specific needs of each individual or institutional investor. We are instead witnessing the development of a mass customization approach, which relies on the ability to classify investors into separate groups displaying a relatively high degree of homogeneity in terms of their objectives, horizons and constraints.
Liability-driven investing (LDI) in institutional money management and goal-based investing (GBI) in individual money management rely specifically on the proper identification of a set of coherent investment problems, involving an efficient management of market risks, which can be summarized in terms of the investment opportunity set (available menu of assets with their associated risk and return characteristics), and personal risks, which can be summarized in terms of an investor welfare maximization objective for a suitable choice of investor-specific set of objectives and constraints.In liability-driven investing, both definitions of factors are relevant, but they do not apply to the same steps of the process. Factors with a historically robust and economically justified risk premium are clearly good candidates for inclusion in the PSP, where they are expected to improve long-term performance and the risk-return profile, as summarized in the Sharpe ratio, with respect to portfolios traditionally used as benchmarks, like a broad cap-weighted equity index. It is important to emphasize, however, that factor investing is not a free lunch, since the enhanced returns take a long horizon to materialize and because shortfall risk is still present in the short run. As an illustration, our empirical tests show that an equally weighted portfolio of the six traditional US equity factors (size, value, momentum, volatility, investment and profitability) earns on average 11.21% per year between 1972 and 2016, which is well beyond the 10.09% earned by the cap-weighted index, but its maximum drawdown of 52.14% is barely lower than the 53.78% posted by the benchmark.
Recent advances in asset pricing theory suggest that, whatever the context, meeting the complex challenge of investor welfare maximization in the presence of dollar/portfolio/risk constraints requires efficient use of three fundamental sources of added value, each reflecting one particular form of risk management technique.
Precision investing requires an ability and willingness to construct performance portfolios
In this context, fund separation theorems and the LDI/GBI paradigm suggest that there are at least two (non-mutually exclusive) reasons why investors should invest in any particular asset or asset class. On the one hand, the asset class under consideration can be useful if it provides access to excess performance through exposure to a rewarded source of risk. On the other, it can be useful if it provides hedging benefits with respect to risk factors that impact the opportunity set.
Now the fund separation theorem does not imply that investors should not pay attention to the (mis)alignment of risk factor exposures in their performance-seeking versus liability- or goal-hedging portfolios. In fact, it turns out the interaction between performance and hedging motives plays a very important role. In other words, everything else being equal, if given a choice between several candidates portfolios with statistically undistinguishable risk-adjusted performance, it would be rational for an investor to select the performance portfolio with the most attractive consumption and/or income hedging properties (see Deguest et al. (2020)  for a formal analysis of the interaction between performance-seeking and liability-hedging portfolios).
This finding justifies the argument that when considering the problem of constructing a suitable performance-seeking equity or multi-asset portfolio for a given investment solution, one should be willing to analyse conceptual and practical considerations about how to best accommodate the presence of personal risk factors impacting the present value of liabilities. In other words, such equity portfolios are not solely optimized to maximize their risk/return trade-off, but they are optimized to maximize their suitability within the investment solution under consideration. In this context, precision investing requires an ability and willingness to construct performance portfolios that are optimized to be suitable with respect to their use in a context characterized by the need to manage not only market risks but also personal risks.
Regarding the management of personal risks, we argue that more work is needed, in particular for the optimal design of a performance portfolio to be used to efficiently address the investment problem of an individual investor preparing for retirement. The design of such a “retirement-friendly” performance portfolio is expected to encompass analysis and management of interest rate and inflation risk exposures, the main risk factors impacting changes in value of replacement income needs. Besides, the presence of personal constraints such as essential goal levels implies the introduction of a non-linear option-like exposure to the performance-seeking portfolio. In this context where the performance-seeking portfoliois not meant to be used naked but as an underlying for dynamic retirement investment strategy, the standard Sharpe ratio maximization prescription may not be optimal, and it is highly relevant to question what the optimal portfolio strategy should then become.
New avenues of progress are enabled for the most important investment problem: the retirement investment problem
Overall we expect these trends to be stepping stones towards the launch of a new area in the domain of welfare-improving investment solutions. Since it is increasingly recognized that meeting investor needs is the “new alpha” (i.e., the new key source of added value), an ability to produce and distribute suitably designed precision investing performance portfolios adapted to specific investor goals and market risks will likely mark a key step forward from the traditional focus on promoting one-size-fits-all products on the basis of their alleged outperformance. These questions are of substantial practical relevance in delegated portfolio management since there are many situations where the payoff is taken as given, and not necessarily optimal, either because investors do not fully reveal their preferences or because asset managers only have access to a structured set of payoffs.
In this context, we are particularly excited to share the focus of the 2020–2021 EDHEC-Risk Institute/FirstRand Research chair project on Designing and Implementing Welfare-Improving Investment Solutions for Institutions and Individuals. The research will examine the optimal construction of performance portfolios for liability-driven investors seeking downside protection. In this “Precision Investing” sense, the intended result is a growth portfolio specifically shaped to be responsive to the liability context within which it is applied. In so doing, new avenues of progress are enabled for arguably the most important investment problem, namely, the retirement investment problem.
 In this sense insurance is nothing but dynamic hedging, as evidenced by Merton’s (1973) dynamic replicating portfolio interpretation of the option pricing formula derived in Black and Scholes (1973).
 Deguest, R., L. Martellini, and V. Milhau, 2020, From Fund Separation to Fund Interaction Theorems, EDHEC-Risk Publication.