Beyond Flatland: When Two Dimensions Are Not Enough

Beyond Flatland: When Two Dimensions Are Not Enough

The conventional method of portfolio analysis has a problem: It’s too flat. Like the universe imagined in Edwin Abbot’s famous essay Flatland, it features just two dimensions: Expected return along one axis and expected volatility along the other.??

In this flat framework, “efficient” portfolios are those that appear to have the potential to deliver the most return for a given level of volatility or the least volatility for a given level of return—depending on the investor’s time horizon and tolerance for risk.?

But, just as the inhabitants of Abbot’s Flatland could only perceive solid objects as lines on a two-dimensional surface, the conventional risk/return approach provides a limited perspective on what is actually a more complex problem. It doesn’t account for the fact that investors may have objectives beyond just maximizing total return or might be worried about risks other than shorter-term volatility.?

These limits become even more confining when the task is evaluating competing retirement income solutions, such as those that might be offered to defined contribution (DC) plan participants.??

As more DC plan sponsors focus on the postretirement spending phase of the investing life cycle, many are finding that the conventional risk/return framework doesn’t cover all the critical factors when selecting a retirement income solution that is aligned with the demographics and preferences of their plan populations.?

To remedy this, our global multi-asset research and retirement strategy teams have developed a patent-pending new approach that covers what we see as the foundational attributes of any retirement income solution. Their methodology has five dimensions:?

  • Longevity risk hedge: How does the solution seek to guard against the risk that retirees might outlive their savings??

  • Level of payments: What level of annual income can investors reasonably expect the solution to support??

  • Volatility of payments: How much could income streams potentially fluctuate from year to year??

  • Liquidity of balance: If the need arose, how much of their savings could investors access quickly without unacceptable loss??

  • Unexpected balance depletion: How high is the risk that the investor’s assets might not last as long as they had planned???

How a retirement income solution addresses these five attributes inevitably requires trade-offs. A solution that prioritizes hedging against longevity risk, for example, might be less effective at supporting a relatively high level of income.?

Drawing on T. Rowe Price’s decades of experience with portfolio design and DC plan administration, our methodology scores proposed solutions on all five dimensions, using a variety of financial metrics. These results are then placed in a single, objective framework for sponsors to consider.??

Two of my colleagues, Senior Quantitative Investment Analyst Berg Cui and Global Retirement Strategist Jessica Sclafani, recently published a paper that describes our five-dimensional approach in more detail. If you’re concerned about retirement income or confused by the many solutions being brought to market, I think it’s worth a read: https://www.troweprice.com/institutional/us/en/insights/articles/2024/q2/a-five-dimensional-framework-for-retirement-income-needs-and-solutions-na.html

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DISCLOSURE?

This material is being furnished for general informational purposes only. The material does not constitute or undertake to give advice of any nature, including fiduciary investment advice, and prospective investors are recommended to seek independent legal, financial and tax advice before making any investment decision.??

Past performance is not a reliable indicator of future performance. The value of an investment and any income from it can go down as well as up. Investors may get back less than the amount invested.?

Information and opinions presented have been obtained or derived from sources believed to be reliable and current; however, we cannot guarantee the sources' accuracy or completeness. There is no guarantee that any forecasts made will come to pass. The views contained herein are as of the date noted on the material and are subject to change without notice; these views may differ from those of other T. Rowe Price group companies and/or associates. Under no circumstances should the material, in whole or in part, be copied or redistributed without consent from T. Rowe Price.?

T. Rowe Price Associates, Inc.?

? 2024 T. Rowe Price. All rights reserved. T. ROWE PRICE, INVEST WITH CONFIDENCE, and the bighorn sheep design are, collectively and/or apart, trademarks or registered trademarks of T. Rowe Price Group, Inc.?

202407—3704650?

Louis Liu, PhD, CFA, ASA, MAAA

Founder and CEO of Coastal Square Asset Allocation Consulting, LLC (CSAA Consulting.) Investment professional with extensive experience in investment, risk management, asset allocation, insurance ALM, pension LDI.

7 个月

This is a very interesting piece, and certainly an extremely important topic. I like the 5 metrics discussed as objectives of DC asset allocation. However, I wouldn’t call them 5 dimensions. To me, it is more of the third dimension (dimension of time) with various objectives. I would call it a multi-horizon DC asset allocation optimization with multiple objectives. The “optimal” AA strategy should maximize a utility function of variables noted in the piece and measured at several future time intervals. It may lead to a similar conclusion…

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David Bell

Executive Director at The Conexus Institute

8 个月

Congratulations Sébastien Page and all the team involved (including Berg Cui, Ph.D., CFA and Jessica Sclafani, CAIA) on this work. It meaningfully progresses the discussions on both retirement preferences and retirement portfolio design.

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Aurèle Storno

Chief Investment Officer Multi Asset at Lombard Odier Investment Managers

8 个月

Interesting, we have approached that optimization using a ??multi-objective optimization?? framework that seeks to compromise between numerous objectives. It use the Pareto Front idea, where you can find portfolios that can’t improve an objective without deteriorating another one. There are other optimization frameworks that can help deal with multiple objectives. I’m interested to understand what your patent will cover, looking forward.

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