The “bucket approach” to retirement planning has been routinely adopted by financial planners, ever since it was popularized by Harold Evensky. Clients keep several years of assets in safe, liquid investments, while investing the rest of their portfolio more aggressively. But new research shows that this approach actually destroys a portion of clients’ wealth.
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This research comes from Javier Estrada, a professor of financial management at the IESE Business School in Barcelona, Spain. Before we get to Estrada’s research, let’s review how the success and failure of a financial plan is measured using Monte Carlo simulations.
The challenge of measuring failure rates of financial plans
Retiring without sufficient assets to maintain a minimally acceptable lifestyle (which each person defines in their unique way) is an unthinkable outcome. That’s why, when investors are planning for retirement, their most important question is: How much can I plan on withdrawing from my portfolio without having a significant chance of outliving my savings?
The answer generally is expressed in terms of a safe withdrawal rate (SWR) – the percentage of the portfolio you can withdraw the first year with future annual withdrawals adjusted for inflation. While historical returns can provide insight, it’s critical that investors not simply project the past into the future. Current valuation metrics should be used instead.
Another problem that must be considered is that investment returns are not constant, and systematic withdrawals during bear markets cause portfolio values to fall to levels from which they may never recover. Over the 26-year period from 1973 through 1999, the S&P 500 Index provided a nominal return of 13.9% a year and a real return of 8.2% a year. With hindsight, you might think that, given the 8.2% real return, it would have been safe to withdraw 7% a year in real terms (that is, take 7% of the portfolio’s starting value and increase the withdrawal by the inflation rate each year). Unfortunately, had you retired at the end of 1972 and followed that strategy, you would have run out of funds within 10 years, by the end of 1982. This was because of “sequence of returns risk.” Adverse returns in the early stages of retirement are particularly harmful; the S&P 500 Index lost almost 40% in the 1973-1974 bear market.
Additionally, investors must address our limited ability to estimate future returns and the fact that the sequence of returns matters a great deal. The way to solve for these problems is to use a Monte Carlo simulator. Monte Carlo simulations require a set of assumptions regarding time horizon, initial investment levels, asset allocation, withdrawals, rate of inflation and, importantly, the distribution of and correlations between annual returns for various asset classes.
Two numbers determine the expected final wealth distributions in Monte Carlo simulation programs: the average annual return (again, derived from current valuations/yields rather than historical ones) and the standard deviation of the average annual return. The Monte Carlo simulator then randomly selects a return for each year and calculates wealth values over the expected retirement period. This process repeats thousands of times to calculate the likelihood of possible outcomes.
Monte Carlo simulation outputs typically are presented as odds of success. For example, the simulation’s result might show a 90% chance of you not outliving your assets. Said another way, the failure rate, in this case, is an estimated 10%.
Read the full article here by Larry Swedroe, Advisor Perspectives
