Tuesday, April 24 , 2018, 2:37 am | Fog/Mist 52º


Dannell Stuart: Mission Wealth Management Helps Couple with Pre-Retirement Makeover, Part III

Monte Carlo Forecasting helps with decision-making in determining the probability of success of a financial plan

[Noozhawk’s note: Third in a series. Click here for the first part. Click here for the second part.]

As we discussed during the past few weeks, Sarah and Logan Green are trying to determine whether they can afford to both retire and remodel their home in the near future. Logan feels burnout sinking in, and at age 59 he’d really like to know if he can retire by 65. Sarah can’t stand their outdated kitchen and bathrooms and feels they should remodel their home now while they’re still working so they can enjoy it even more in retirement.

After thoroughly assessing their resources, we prepared a financial plan. This plan could serve as a road map for the Greens’ future. Unfortunately, based on this plan, it doesn’t look like they can have their cake and eat it, too.

Based on what Logan and Sarah have set aside for retirement, our projections show they can afford to have Logan retire at age 65, but that’s only if they can limit their spending to $10,000 a month. That includes their almost $5,000 monthly mortgage payment. After reviewing their current personal expenses, the Greens realize that $10,000 a month is not realistic, as their current lifestyle is closer to $15,000 a month.

Even with maximized retirement plans, Social Security, and a moderately aggressive portfolio, they could face challenges of longevity and the impact of inflation eating away at the value of their money over time. They feel frustrated that even with more than $2 million in retirement funds, and with saving what feels like a lot into those plans, they still can’t afford to retire at age 65 at their current lifestyle. As we reviewed these retirement projections, it became clear that they couldn’t retire when they want.

Logan and Sarah face some hard decisions. Since it has become apparent that their ideal goal of spending $100,000 on a home remodel, retiring when Logan is 65 and spending $15,000 a month is not feasible, they have to decide what they are willing to give up.

In financial planning we use a tool called Monte Carlo Forecasting* (see below for more information) to help determine the probability of success of a financial plan. Because many unknown variables are involved, such as inflation, investment returns and taxes, we rely on Monte Carlo to run thousands of scenarios to provide an “average probability of success.” With a Monte Carlo of 80 percent or higher, we can feel fairly confident that the client’s retirement savings plan is in line with his or her investment goals and objectives. With a Monte Carlo of less than 80 percent, we usually advise the client that changes need to occur to either the goals or the lifestyle.

We showed Logan and Sarah some alternate scenarios so they could see the impact of potential sacrifices. Their current plan, based on expenses of $10,000 a month, provides a Monte Carlo of 84 percent, but the Greens just don’t think that’s a realistic budget. However, they might enhance their financial situation by paying their mortgage down to a conforming amount with a lower interest rate (thereby saving $755 a month on mortgage payments), having Sarah start saving into her SEP-IRA ($6,000 a year) and repositioning the equity in their condo so it generates more income (a tax-deferred exchange into a more passive investment property that has an approximate 6 percent cash flow). With these changes, the Monte Carlo increases to 86 percent based on a budget of $10,000 a month, or 73 percent based on a budget of $12,000 a month.

The impact of taking $100,000 out of Sarah’s brokerage account to fund the home remodel is surprisingly small. It drops the success probability to 85 percent based on $10,000 monthly spending and 68 percent based on $12,000 monthly spending.

Alternatively, they could forgo the home remodel and Logan could then retire at age 63 with an 80 percent Monte Carlo at $10,000 a month or 60 percent at $12,000 a month. Still, 60 percent is not a very high level of confidence.

Another option would be if Logan could defer his retirement to age 67. They could then afford the home remodel and have an 89 percent Monte Carlo at $10,000 a month or 77 percent at $12,000. Each year Logan delays his retirement, they can add additional funds into their retirement plan, more time to let the funds accumulate and fewer withdrawals from their accounts. They feel much better about the higher success rate of 77 percent, but that doesn’t get Logan into retirement as soon as he’d like, and it’s still not the $15,000 per month they were hoping to spend.

By reviewing these various scenarios, Logan and Sarah learned they have different levers they can experiment with. They understand how changes in spending, retirement date and remodel costs affect their accumulation of retirement funds.

Logan and Sarah are taking some time to mull over this information. They have some difficult conversations ahead regarding what sacrifices they are willing to make. In our next column, we will discuss their conclusions and which action steps they took to implement their financial plan.

* A Monte Carlo simulation generates thousands of probable performance outcomes, called scenarios, that might occur in the future. An investment simulation incorporates economic data such as a range of potential interest rates, inflation rates, tax rates and so on, combined in random order. As a result, it’s designed to account for the uncertainty and performance variations that are always present in financial markets. Many factors determine the actual return on your investment, and your actual investment return may vary greatly from the results offered by this simulation.

Click here for a related article.

— Dannell Stuart CFP, ChFC, CLU, CASL is business development director at Mission Wealth Management. She can be contacted at .(JavaScript must be enabled to view this email address). Click here for more information.

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