In Practice Summary: Managing Sequence Risk to Optimize Retirement Income
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With diligence, expert planning, and a little luck, you arrive at your retirement day with a sizeable retirement fund. But then what?
Some theorize that this is the point when there is the greatest risk of failure in your lifelong savings strategy.
This edition of In Practice summarizes an innovative solution to this dilemma curated from new research from Cass Business School, London.
What’s the investment issue?
Most individuals must decide for themselves the best strategy for yearly withdrawals from their defined contribution retirement funds in order to maximize their post-retirement income.
One important but poorly understood detail that can complicate this decision is sequence risk — the risk of experiencing bad investment outcomes at the wrong time. Basically, it is not just long-term average investment returns, but when those returns are earned that determines a decumulating investor’s wealth. Poor returns in the early phases of decumulation have a more damaging effect on retirement income than those that occur later.
In “Reducing Sequence Risk Using Trend Following and the CAPE Ratio,” published in the CFA Institute Financial Analysts Journal®, authors Andrew Clare, James Seaton, Peter N. Smith, and Stephen Thomas examine the effectiveness of strategies investors with a portfolio of risky assets might use to reduce sequence risk.
How do the authors tackle the issue?
The authors use the concept of a perfect withdrawal rate (PWR) — the proportion of their retirement fund an investor would need to withdraw each year to exhaust the fund at death, assuming the perfect foresight of investment returns, to determine the historical decumulation experience — over a 20-year period — of someone invested in an S&P 500 Index portfolio. The authors acknowledge that this may be an unlikely investment choice in practice, but use it to illustrate their key points.
The hypothesis was that applying a simple monthly trend-following rule to any series of returns would reduce volatility, maintain or increase returns over the long term, and reduce sequence risk. Using real returns from the S&P 500 between 1872 and 2014, the authors calculated — using a Monte Carlo approach — the probability distribution of the PWR for an investor following a buy-and-hold strategy.
Replacing the buy-and-hold investment strategy with an equity strategy that incorporated a trend-following filter, the researchers had their hypothetical investor switch between holding equities and holding cash depending on whether the S&P 500 was above or below its 10-month moving average. Trend following is subtly different from momentum investing, which views price behavior based on technical rules. Trend following also relies on price behavior but orders the past performance of the assets of interest.
The authors also wanted to determine whether other market-timing approaches or valuation indicators, such as the cyclically adjusted price-to-earnings (CAPE) ratio, for example, could provide an “improved” solution.
What are the findings?
Investors who used a buy-and-hold strategy with US equities would have encountered a huge variation in the amount they could withdraw from their retirement pot. Depending on the birth date, the PWR generally varied between 8% and 12%, reaching as low as 4% and as high as 15%.
The 10-month trend-following strategy markedly improved investor outcomes. Around 90% of the time, it produced PWRs greater than the equivalent buy-and-hold equity strategy, and at low levels on the probability distribution, PWRs were almost double.
One clue to explaining these results can be found in the annual real return data: The trend-following strategy produced an average real return of 8.8%, compared with 6.8% from the buy-and-hold strategy. More importantly, the trend-following filter reduced volatility by a third and halved the maximum drawdown. These consequences, in turn, reduced sequence risk and produced higher PWRs in the majority of cases. While the transaction costs of switching between equities and cash would have an effect, the authors found these costs were unlikely to have been high enough to eliminate the benefits of the trend-following approach.
Applying the CAPE ratio produced further improvements in some, but not all, cases. The authors found that in the post-1995 period, with good early returns, a combination of trend following and the CAPE’s predictive power produced a superior retirement experience. When early returns were poor and sequence risk high, trend following alone produced the best withdrawal results.
What are the implications for investors and investment professionals?
The sequence of investment returns can dramatically affect retirement income, for better or for worse. But although asset returns are unpredictable, it suggests that decumulating investors do not have to resign themselves to the accident of their retirement date.
By pursuing a simple trend-following strategy over the past 142 years, investors would have substantially cut sequence risk while maintaining or improving returns. In most cases, they could increase the yearly amount they could sustainably withdraw from their retirement funds. Other market valuation methods, such as the CAPE ratio, might also help guide withdrawal rates when adopted on a regular basis.
Improved ways to visualize sequence risk across time could help retirement planners educate clients when determining and adjusting withdrawal rates.
Readers should keep in mind that other investment strategies to alleviate sequence risk may be better than the method employed here: for example, using multiple asset classes across time rather than equities only.
This article is an In Practice summary of “Reducing Sequence Risk Using Trend Following and the CAPE Ratio,” from the CFA Institute Financial Analysts Journal®.
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All posts are the opinion of the author. As such, they should not be construed as investment advice, nor do the opinions expressed necessarily reflect the views of CFA Institute or the author’s employer.
Image credit: ©Getty Images/ erhui1979
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