We explore the implications of a potential equity sell-off, where we hypothesize that less-risky, more-profitable firms with more-conservative investment practices prove more resilient than their competitors. 

When investors assess risk, they construct narratives around the data. Investment managers and asset allocators can look to the long history of market sell-offs for context, to better anticipate future drawdowns and prepare portfolios for what the future may hold. 

The MSCI Analytics Summit brought together senior industry experts to explore the evolving landscape of risk management. Participants, including our guests for this episode — Rick Bookstaber and Raina Oberoi — exchanged ideas on how to navigate the complex challenges and opportunities in the market, the importance of integrating a risk culture within investment teams and how best to create a role for risk where it can truly serve to aid decision-making and portfolio resilience.

Attendees at the MSCI Institutional Investor Forums in the U.S. and Canada agreed that the investment megatrends they see underscore the need to centralize risk in investment decision-making, making a total portfolio approach increasingly attractive.

We examine a scenario for how a sudden disruption in credit markets could affect portfolios, especially given indications of the market’s fragility.  

Scenarios are a way of positing the material risks that arise from the combination of events and market vulnerability. The core of understanding risk, the task of building scenarios, is not mechanical and is not trivial. It is alive as a narrative. 

Mean-variance optimization is difficult to customize for a heterogeneous set of clients.  Modern technology can help advisers move from machine-driven optimization to guided rebalancing that respects market realities and client objectives.

Risk management for individuals and other asset owners differs from that of financial institutions. It’s time for a fresh mindset and new tools for these market participants. The authors propose measuring material risk through agent-based models.