September 19, 2012 (PLANSPONSOR.com) – New research from Morningstar quantifies how much additional retirement income, or “Gamma,” investors can generate by making better financial planning decisions.
Through a series of simulations, the researchers found that a hypothetical retiree may generate approximately 29% more income using a Gamma-efficient retirement income strategy, which is equivalent to an annual arithmetic return increase of 1.82%, compared with the average base case strategy.
The research focused on five fundamental financial planning decisions or techniques for retirees—optimal asset allocation based on total wealth; dynamic withdrawal strategy; product allocation (i.e., guaranteed income products versus traditional investment products); tax-efficient allocation and drawdown; and liability-driven investing. The researchers created a series of portfolios and drawdown strategies that employ these techniques as well as a base case scenario drawn from the practices of average U.S. investors.
Among the five types of Gamma tested, the researchers determined that using a dynamic withdrawal strategy was most important, followed by making tax-efficient allocation decisions.
Morningstar said the results from these simulations, while hypothetical in nature and not actual investment results or guarantees of future results, provide an important look at strategies designed to help retirees reach their goals. Morningstar Associates has implemented these financial planning techniques in Morningstar Retirement Manager, the company's defined contribution advice and managed account service.
“Investors arguably put a lot of time and effort into selecting investment funds or managers they hope will outperform the market—the so called 'Alpha' decision,” said David Blanchett, head of retirement research for the Morningstar Investment Management division. “Unlike traditional Alpha, which can be hard to predict, any investor can achieve Gamma by following an efficient financial planning strategy.” To read the complete research paper, visit http://global.morningstar.com/Gamma.