Cash Flow and the Optimal Volatility of a Retirement Distribution Portfolio

The complete time horizon for most investors follows a common path; initially, there’s an “accumulation” phase in which positive cash flows are added periodically to their portfolio’s balance, and later, a multiyear “distribution” phase in which cash flows turn negative and withdrawals are made to support the investor’s income needs in retirement.

As the portfolio transitions to the distribution phase, there’s typically a shift in goals as well, from maximizing terminal wealth to preserving the inflation-adjusted value of cash flows received. In line with this new objective, risk profiles should also change, as negative cash flows now expose the investor to the potential of a truly catastrophic outcome—a portfolio value that terminates at zero during the investor’s lifespan. A well-constructed distribution portfolio will address and minimize this possibility, primarily by acknowledging the profound impact that negative cash flows have on the optimal volatility of a distribution portfolio.

Sequence of Returns Risk

It’s well known among financial planners that upon entering the distribution phase, the investor is suddenly exposed to “sequence of returns” risk—poor returns in the earliest years of this phase become particularly detrimental to a retirement plan. In the absence of cash flows, the sequence of returns is largely irrelevant to the terminal value of a portfolio. But a 2008 study from American Funds showed how two distribution portfolios, each with identical risk and return characteristics, could produce vastly different outcomes for a hypothetical investor, simply by scrambling the order that those same returns were experienced. Negative cash flows matter a great deal, because withdrawals from a shrinking portfolio create a smaller base, muting the benefits of subsequent positive returns on the portfolio’s total value.

The lesson for investors from that study and others like it is to limit the risk of a major drawdown in a distribution portfolio, particularly in the earlier years of this phase. Unfortunately, the actual sequence of returns is unknown until the end of a distribution period, and simply estimating the portfolio’s expected return does little to answer the most important question: What are the chances of success or failure? This is where Monte Carlo simulations of portfolio return sequences can be helpful.

Using Monte Carlo Simulations

Borrowing from the collective wisdom of endowments and foundations that face similar periodic spending needs and longevity risk, we know that the target expected return of a distribution portfolio is largely a function of the desired distribution rate. Since it’s critical to maintain the purchasing power of both the portfolio’s corpus and the distributed cash flows, the target return for each simulated distribution portfolio is set at the product of the distribution rate and expected inflation:

In an attempt to determine the impact of volatility on success rates for a distribution portfolio, I’ve simulated portfolio results for a typical 30-year distribution period. The portfolios incorporate distribution rates of 3%, 4%, and 5% and target returns as calculated above. The distributions are inflated at 3% annually, an estimate based roughly on the midpoint between current and historical inflation. Each simulation involves 10,000 separate trials and the results are in Table 1. (Note that this analysis assumes we’re using a “systematic withdrawal” strategy, rather than liquidity segmentation or some other method of cash flow management.)

Table 1

Holding returns constant, we can now see the impact that various levels of volatility have on the odds that a given distribution portfolio will end the full 30-year period with a positive balance (i.e., a “successful” outcome). At a low 3% distribution rate, the portfolios are resilient at most volatility levels, with success rates above 90% at realized rates of volatility up to 11% annually.

At higher distribution rates, however, volatility becomes a major constraint. Success rates above 90% become elusive at the 4% distribution rate unless annual volatility can be restrained to the low 8% range. At a 5% distribution rate, there is an 18.4% chance of failure even at an 8% annual volatility.

Interpreting the Results

The results of Table 1 have broad implications for what reasonably successful asset allocations look like at various distribution rates. As an example, let’s imagine an investor who wants a 90% chance of successfully withdrawing an inflation-adjusted 4% from their portfolio each year for 30 years. From Table 1, we know that volatility needs to be limited to just above 8% while targeting an annual return of about 7.1%. Is that combination of risk and return achievable?

Using the free online tool Portfolio Visualizer, I constructed a simple, moderately balanced portfolio consisting of 30% US equities, 20% global ex-US equities, and 50% short-term US Treasuries. The portfolio was rebalanced annually. That allocation returned 7.3% at a standard deviation of 8.26% over the 30-year period from 1987–2016, remarkably close to the targeted risk and return characteristics. Realistically, there are many combinations of assets that should produce similar results.

What if we simply target a higher rate of return? Unfortunately, this tends to lead to reduced rates of success, because as equities become a higher proportion of the portfolio, volatility rises at a much faster pace than do returns. In the 50/50 portfolio example above, each 5% shift toward equities raises historical returns by roughly 25 basis points, but volatility climbs more than three times as fast (by about 84 bps).

In the accumulation phase, higher volatility is a reasonable price to pay for enhanced returns. But in the distribution phase, negative cash flows change the calculus considerably, particularly at distribution rates of 4% or above. Risk-averse investors entering this phase can take comfort in the fact that a fairly conservative asset allocation may improve their chances of a successful outcome.

About the Author

Robert Fezekas, CFA, works as a financial advisor at Vickery Financial Services, Inc. in Athens, Georgia. Before joining Vickery, he worked as a portfolio manager for Dimensional Fund Advisors in Santa Monica, California, and as a securities analyst with the Principal Financial Group in Des Moines, Iowa. Robert has a B.A. in finance from the University of Iowa and earned his MBA from the University of Chicago Booth School of Business with concentrations in Analytic Finance, Statistics, and Economics. Robert is also a volunteer Board Member for the Athens Area Community Foundation. He writes a monthly investment blog at http://vickeryfinancial.com/resources/.