Merton’s message: give up on alpha

Nobel Prize winner, Robert Merton, has thrown down the gauntlet. He claims that by focusing on a retirement income goal he can beat any competitor that is managing a 70:30 portfolio that has wealth accumulation as the goal. Do you dare take him on?

The defined contribution pension management industry has it wrong, according to Professor Robert Merton.

“There is so much competition over getting alpha, but everyone has access to the same hedge funds. Give up! That’s not what is important,” Merton says.

Instead the focus should be on goals-based investing, he says. And the right goal for most people is an inflation-protected income at retirement, not wealth accumulation. It’s something Merton talks about with a passion that has supported a 45-year career researching risk and lifecycle investing.

Conventional retirement fund investments focus on wealth accumulation and measure risk as volatility of the portfolio, he says. In this context success looks like maximising the size of each individual’s account balance.

Instead, Merton proposes a new generation defined contribution plan – called Managed DC – which puts retirement income squarely in focus as both the investment goal and as the measure of success. Risk then becomes falling short of achieving the income you need. Managing retirement funds in such a way will provide a much higher degree of certainty of actually succeeding, he argues.

Sponsored Content

“The secret sauce of Managed DC is that if you are willing to agree on a goal, say for example $58,000 per year protected against inflation in retirement, and my competitors and I start with the same Sharpe ratio, but I use dynamic strategies based on the goal versus a 70:30 portfolio, then I promise you I’ll beat them,” he says. “Focusing on the goal is like having 20 per cent more assets.”

Merton, who has spent his entire career writing and researching lifecycle investing first publishing in 1969. These days he is the School of Management Distinguished Professor of Finance at the MIT Sloan School of Management. He is also the University Professor Emeritus at Harvard University,

In his opinion the retirement management industry should change its language, and techniques, to focus on income, and to look at earnings for spending and lifestyle.

“For people outside the financial services industry that is normal, but for the entire history of defined contribution the language is about portfolio returns, not income.”

Most lifecycle products use age as the only trigger for investment allocation differences, but Merton argues income is an essential piece of information.

“Adding income a big step up from age alone,” he says. “For example, a 34-year old woman earning $168,000 is very different to a 34-year old man earning $56,000. Age doesn’t tell you nearly enough to make a sensible asset allocation.

With target date funds the investment mix is such that as you get older you get more conservative because of age alone. That’s wrong. Actually the prime drivers of fund asset allocation are the risk composition of total retirement assets. That includes future contributions and how close you are to fully funding the income goal.”

In this way Merton argues that what drives the asset mix is not age, but the amount of remaining human capital and the funding ratio.

“Although they are correlated why go on a correlation? Go to the primary drivers including income and account balance., Those give you all the answers.”

He believes that defaulted defined contribution funds can get that income information from the administrator, and that getting that information is really important.

Merton who co-founded Long-Term Capital Management, is currently resident scientist at Dimensional Fund Advisors, where he is developing this next-generation, integrated pension-management solution system that addresses the deficiencies associated with traditional defined benefit and defined contribution plans.

He says the motivation for the Managed DC concept came out of the 2000-02 crisis when worldwide stock markets fell and interest rates fell at the same time, an experience repeated in the global financial crisis of 2008-09.

“Traditional DC was not well set up to serve as the core retirement product,” he says, adding in the US defined contribution was originally a supplement to the Employee Retirement Income Security Act (ERISA) as a footnote for higher paid executives motivated by tax.

As corporate funds were struggling with their offering, Merton saw an opportunity.

“What would a CFO rather hear from a manager – a 17 per cent return alongside a 10 per cent fall in the funding ratio, or a 3 per cent return alongside a rise in the funding ratio? The CEO wants to hear that they don’t have to contribute. The funding ratio looks at the income.” Traditionally defined contribution plans only looks at one side of the balance sheet, the asset side. In contrast Merton’s Managed DC borrows some of the elements of defined benefit schemes and takes into account the liabilities side in asset allocation.

To put his ideas into action, Merton chose Dimensional, an independent, transparent firm founded on financial science, something dear to his heart. (Merton received the Alfred Nobel Memorial Prize in Economic Sciences in 1997 for a new method to determine the value of derivatives.)

“For innovating you need the right culture, and Dimensional has the quality people, it’s transparent and has had great success,” he says. “I want to succeed at this, I don’t like the idea of failure, I don’t plan on failing.”

The basic premise of “Managed DC” is income for life adequate for a good retirement, rather than unlimited risk taken in static wealth maximisation strategies. And the investment strategy is the dynamic management of each member’s asset allocation.

“You have to stay live, not fixed, and continuously innovate on a cost benefit basis. It is the art of the science,” he says. “Believe in better not best. It is not realistic to be perfect.”

 

 

 

Robert Merton’s work can be accessed here

 

Leave a Comment

Pension funds confront the question of who owns AI

Pension funds confront the question of who owns AI

As the use of AI within asset owners evolves, organisations are grappling with the governance question of where the strategy and accountability sit. Darcy Song looks at the treatment of AI organisationally within a number of high-profile funds, including OTPP, AustralianSuper, CPP and Norges Bank.

Sort content by

NBIM on AI cultural and organisational integration

By the evening of August 7, the same day GPT-5 was launched by Open AI, NBIM had it available to the entire organisation in a secure and scalable way. Joined on stage by CEO Nicolai Tangen at this year's Arendalsuka, the team behind AI integration explains their aggressive approach.

Responsible AI: Railpen lays out the risks

Much is written extolling the investor opportunities inherent in AI at a time policy makers continue to prioritise deregulation and innovation over safety, but a new report from £34 billion Railpen on the risks AI holds for investors' portfolio companies provides a valuable reality check.

Asset managers can’t have it both ways on sustainability

Asset managers have recently been trying to show that they could cater to all sides, from asset owners that have spent years integrating sustainability into their investment strategies to anti-ESG elected officials in states like Texas. But Hugues Létourneau writes that they can't have it all.

AP4: Why a dynamic, shorter term allocation is paying off

Volatile markets have provided a rich hunting ground and opportunistic best ideas have come thick and fast for AP4’s new five-pronged global allocation made up of systematic equity, currency and rates, asset allocation, hedge funds/external mandates and analysis. Magdalena Högberg explains the risks and opportunities of the best ideas allocation.

Change management in action: CalSTRS lays out how it’s integrating AI

In a recent board meeting, CalSTRS staff outlined how they are integrating AI into the investment process in line with its commitment to be an early adopter of the technology, including writing a set of generative AI policies and guidelines, conducting a cost-benefit analysis and identifying scalable use cases.

Large language models to spark ‘sea change’ in investment analysis

Andrew Lo, finance professor at the MIT Sloan School of Management, believes large language models can bridge the gap between fundamental and quantitative investing in a way that was unfathomable five or 10 years ago, and create ‘quantamental’ investment strategies which would bring together the best of both worlds.

Previous