What to do with infected financial plans?
The last couple of weeks have been extremely impactful as a result of the COVID-19 outbreak in all aspects. Not only are several countries taking unprecedented measures to contain the risk of further spreading, they are most importantly taking care of those who are infected. The economic consequences are still very unclear and together with an oil price war, this has generated turbulence and uncertainty on financial markets. Most stock markets are down by 20% or more and interest rates have dropped significantly.
As a result, most financial plans are suffering from an indirect infection by the virus as well. Should we stick to the plan, i.e. do nothing? Or should we instead check on all plans and make sure they are OK and only intervene when necessary? The latter suggestion probably seems like the most reasonable. The question then arises: can we actually do this? Without realistic projections of risk and return and goal monitoring tools, we believe not.
Straight-line growth assumptions
The big caveat we encounter in most planning tools is that the assumption of growth in the underlying investment portfolios is extremely basic. Most of these capital market assumptions are solely based on the historical performance of funds or asset classes. They tend to ignore current market conditions. Several market downturns show that this constant and steady growth assumption is simply not realistic. In the past 20 years, there were several examples such as the dot-com crisis at the end of the millennium, the Global Financial Crisis around 2008 and now the COVID-19 turbulence in 2020. Realistic scenarios are necessary to reflect the client’s experience during his or her investment horizon and manage expectations appropriately.
Plain-vanilla Monte Carlo analysis doesn’t solve the problem either
Some planning tools try to solve this problem by offering a ‘Monte Carlo’ module. A Monte Carlo simulation essentially generates a range of possible outcomes of future scenarios for investment returns. The scenarios represent several thousand “futures” for the portfolio – not a prediction, but a range of possible outcomes. We believe this to be an improvement compared to the ‘straight-line’ growth assumptions.
However, most of these modules provide little added value, due to the basic underlying statistical models used to generate these scenarios. Most Monte Carlo engines use a Normal distribution to provide a range of probability around the same, straight-line, 6% return assumption we mentioned before. The expected result shown from a typical Monte Carlo simulation, which has a 50% probability of success, is essentially the same result as the straight-line return assumption in a deterministic planning. Using these types of Monte Carlo simulations for portfolio projections is like weather forecasting for tomorrow’s temperature solely based on the average daily temperature in the past, ignoring seasonality, current conditions and additional data such as humidity, air pressure, jet stream location etc. In our recent white paper we discuss the properties of realistic projections versus the plain-vanilla Monte Carlo approach.
From projections to monitoring individual goals
Having access to realistic projections of client portfolios is just the start. With these tools at hand, not only can advisors manage expectations for the actual realization of the portfolio. They also have a tool that can recalculate the probability of success of meeting that goal, on a quarterly, monthly or even on a daily basis. When a client would call to figure out what could potentially happen to their plan due to a market downturn, advisors now have the possibility to either reassure the client or discuss options on how to get everything back on track.
No more risk than necessary
In addition, goal monitoring can be used to pro-actively support advisors to reduce the risk that client’s will not achieve their goals. After consecutive years of high returns, advisors may suggest to the client to reduce the risk in the portfolio and decrease the risk of a sudden dropdown. This may reduce the number of client portfolios that contain an unnecessary amount of risk relative to its goal. Looking back on the past couple of years, markets have performed very well. If advisors would have had pro-active tools that signal de-risking opportunities, the hit that a lot of portfolios got last week may have been less severe.