By Seth J. Masters
Investors have good reasons for their recent net increase in stock fund purchases — and good reasons to remain anxious, in our view. While market volatility has returned to normal, memories of the wild market swings of the past five years loom large. Here’s what we think about the risk of increasing stock exposure now.
First, we think that it’s important to remember that the possibility of big portfolio losses is just one risk; there’s also the risk of running out of money due to insufficient returns or inflation.
Our research suggests that the risk of running out of money is higher than usual today, especially for bond-heavy portfolios, because we project extremely low bond returns and somewhat below-average stock returns for the next 10 years. (For more on our view of current stock-market valuations and our projected returns for stocks and bonds, see “Is It Time to Get Back into Stocks—or Too Late?”)
But our research also suggests that the risk of large losses for stock-heavy allocations is higher than usual, for two reasons. First, there are likely to be more episodes than usual of high volatility in response to any adverse macroeconomic or policy developments. Second, with bond yields so low, bonds are less likely than usual to provide strong returns during a stock-market drop. That is, the potential diversification benefit of bonds has diminished.
It’s important to weigh the risk of running out of money against the risk of loss when considering potential asset mixes. In the display below, you can see how we might approach this balancing act for a hypothetical 65-year-old couple that plans on spending 3.3% of their starting portfolio each year, adjusted for inflation. In this simplified example, we show our forecasts for four portfolio mixes built on globally diversified equities and intermediate-term, diversified municipal bonds.
The first portfolio is invested only in municipal bonds. We estimate that today there’s only a tiny risk that this all-bond portfolio will incur a 20% loss from peak to trough during some period while at least one of the couple, still lives. However, we estimate that holding this portfolio would mean an unacceptable 50% chance that they would run out of money in the same time frame.
By shifting 30% of the portfolio to globally diversified stocks, the odds of a 20% loss at some point would barely increase, but the likelihood of running out of money would fall to just 17%, we estimate. Most retirees I speak to would find this portfolio much more appealing than the all-bond allocation, but would prefer to further reduce their odds of running out of money.
Both the 60%/40% and the 80%/20% stock/bond mixes would cut this couple’s risk of running out of money to just 7% — but at a price. The risk that the portfolio would incur a 20% peak-to-trough loss would rise materially. Of the two stock-heavy allocations, the 60%/40% portfolio would probably be preferable to most investors because the risk of a large short-term loss is lower.
So, either the 30%/70% portfolio or the 60%/40% portfolio, or something in between, may be a reasonable choice for our hypothetical couple. If, like many people, they couldn’t tolerate the higher odds of large losses from a 60%/40% portfolio, they could opt for a 30%/70% portfolio. In that case, they could reduce their odds of running out of money by trimming their spending.
In my next blog post, I will discuss strategies for reducing the unusually high odds of large losses from a 60%/40% stock/bond mix.
Seth J. Masters is Chief Investment Officer of Bernstein Global Wealth Management, a unit of AllianceBernstein, and Chief Investment Officer of Defined Contribution Investments and Asset Allocation at AllianceBernstein.
Disclaimer: The views expressed herein do not constitute research, investment advice or trade recommendations and do not necessarily represent the views of all AllianceBernstein portfolio managers.
The AllianceBernstein Wealth Forecasting System uses a Monte Carlo model that simulates 10,000 plausible paths of return for each asset class and inflation, and produces a probability distribution of outcomes. The model does not draw randomly from a set of historical returns to produce estimates for the future. Instead, the forecasts (1) are based on the building blocks of asset returns, such as inflation, yields, yield spreads, stock earnings and price multiples; (2) incorporate the linkages that exist among the returns of various asset classes; (3) take into account current market conditions at the beginning of the analysis; and (4) factor in a reasonable degree of randomness and unpredictability.