Analyzing and managing clients’ portfolio risk is one of the hottest topics for financial advisors today. If we put ourselves to this task, our starting point must be to understand and prioritize a client’s objectives in terms of consumption over time, and then match that against the client’s resources. Only when that framework is in place can the analysis and management of risk really begin.
The relationship of a client’s resources and objectives is embodied in the interaction between risk capacity and risk tolerance. Understanding these entails a complex forecasting effort. Ultimately, every nickel gets spent for some purpose by somebody—it’s just a matter of when. But there are the unknowns, including lifestyle changes, product innovations, inflation, changes in tax regimes and evolving portfolio expectations, and these might extend over decades, even generations. So this foundational step along the path of analyzing and managing a client’s portfolio risk is beset with dynamics and complexity on all sides. People’s resources will change with the vagaries of the market, and their objectives will change with their life experience.
Though the process is complex and fraught with uncertainty, judgment and planning can greatly improve the probability of success.
The True Boundaries Of Risk
Keeping the fundamental uncertainties in mind, we can break risk tolerance and capacity into two stylized cases by looking at the forecast of the ratio of resources to objectives.
If the ratio is greater than 1 (for example, if the client has resources of $1 million and their objectives require $800,000), there is significant capacity for increasing portfolio risk. Whether the client will tolerate increased risk depends on their desire to expand the size or scope of their objectives. Most clients indeed expand their objectives when freed to do so, perhaps by giving some “excess” resources away to family, friends or charity. Relatively few stick strictly to their objectives, but some of those who do will decide to reduce their current level of risk because their unexpanded objectives can be met with a lower risk profile.
If the ratio is less than 1 (say, if the clients’ resources are $800,000 and their objectives require $1 million), they either have to curb their objectives or increase their risk tolerance to try to close the gap. This case is much more common, and it’s where advisors have a very important next step to take. Few clients are eager to curtail their financial objectives, so they are willing to accept (tolerate) a higher level of risk.
This compromise between curtailing objectives and increasing risk is where the advisor plays a crucial role in guiding the client along the difficult path of trade-offs.
As we can see, in both of these cases the ratio of resources to objectives is not constant. Indeed, depending on the path of the markets, and the changing appetites of the client, the ratio might flip back and forth between over- and underfunding over time. So, decisions based on the current ratio would only be misplaced. The astute advisor will understand the client’s tendencies and take these into account rather than simply assuming that the current risk tolerance and objectives will remain static over the course of time.
The time frame looms large in these considerations. It might be more expensive to reach a financial objective over time … or less expensive. The range of expected investment outcomes might either narrow as time reduces the standard deviation of normalized returns or it might expand if the exceptional “black swan” event occurs. And, along the way, a client will likely change objectives or adjust his or her risk appetite in response to intervening events and interim results. Because the client’s capacity for risk and the related tolerance change over time, the advisor’s role never loses its significance. Even if it’s taken for granted in risk assessment tools today, “set and forget” should not be part of the advisor’s lexicon.
Unreliable Input
When advisors use conventional approaches to analyzing clients’ portfolio risk, they fail to account for the full, rich array of key factors involved. Those approaches tend to use static, a priori measurements even though it’s abundantly clear that risk tolerance is dynamic. Only later, in response to real life events, do clients really come to grips with what they can—or must—tolerate in fact. And often they surprise themselves. When you use an a priori risk tolerance input, it fails to account for the fact that this tolerance must be learned. It’s a conclusion, not a premise.