As can be inferred from its title, our website is mostly about developing a reasonable spending budget in retirement based on the assets you have (or if you are a Financial Advisor, how much assets your client has). It is my hope that you will manage your finances in retirement by (1) periodically calculating the actuarial budget discussed in this website, (2) periodically comparing your actual spending with this actuarial spending budget and (3) making necessary adjustments to bring the two in line. I know, however, that there are some retirees who don’t want to fuss with a budget and just want to spend $X real dollars each year. Somehow many of these folk got it in their collective mind that there is a Y% (with Y being a fairly high probability) that they can spend this $X per year come hell or high water and not run out of money. The good news for these folk is that they may still find our Actuarial Budget Calculator V 1.0 to be of value. They can use it to solve for the expected period of retirement that they can spend their $X per year and not run out of money. It involves a trial and error process to back into this period, but it can be accomplished fairly easily. The retiree can then compare this expected period with the probability of living this long to see what her probability of ruin (or probability that she will have to change spending in the future) is.
The inspiration for this post comes from a new article from Moshe Milesky, Associate Professor in Finance at the Schulich School of Business and Graduate Faculty in Mathematics and Statistics at York University, Toronto. The article is entitled, “It’s Time to Retire Ruin (Probabilities)” and is scheduled to appear in the March/April issue of Financial Analysts Journal. Thanks to Martin from Maine for pointing me to a pre-release version.
In his article, Mr. Milesky hits the widespread and generally accepted use of Monte Carlo modeling to determine ruin probabilities of specific spending strategies pretty hard. He refers to this approach as a “very trendy metric for wealth management” and expresses his concerns about “how these probabilities are being used (and abused) to simultaneously reassure and scare clients about the viability of their retirement plans.” Many of Mr. Milesky’s remarks echo comments I have made in prior posts about deficiencies of Monte Carlo modeling. In addition, Mr. Milesky advocates the use of fairly low real rates of investment return for planning purposes, so all-in-all I would have to agree with Martin from Maine’s assessment that Mr. Milesky’s article was “right up my alley.” I encourage you to read Mr. Milesky’s brief article.
