A retirement model that requires no expenditures for long-term care may have a 97 % success rate , but with only a 10 % probability of outcome .
Retirement analysis
Utilizing a Monet Carlo simulation we can model a couple ’ s retirement to determine the probability of success by randomizing the sequence return , in this case 10,000 times . To generate the simulation we utilize the following input : Husband and wife both age 65 $ 500,000 non-qualified assets $ 500,000 qualified assets One of them will live until age 95 Annual retirement spending $ 65,000 ( today ) Annual retirement income $ 40,000 ( today ) Income gap $ 25,000 ( today ) Income tax rate 20 % Inflation rate 3 % Risk averse investing style
• 25 % Domestic Stocks
• 5 % International
• 70 % Bonds Average rate of return 6.0 % Standard deviation 4.3 %
RETIREMENT MODEL
( No Long-term care needed ) 10 % probability of occurrence
The Monte-Carlo simulation is first run based on the couple not needing any Long-Term Care . This is the simulation run by the majority of financial advisors . Unfortunately , a couple only has a 10 % chance that neither of them will need Long-Term Care during retirement .
Out of 10,000 simulations there are only 286 failures which is a 97.1 % success rate . The majority of financial advisors would be comfortable with a retirement strategy predicting a 97 % success rate through age 95 meeting 100 % of the client ’ s spending goal .
The figure on page 38 represents the ending portfolio value based on the 10,000 simulations . The median portfolio value would be $ 418,485 while the 90 % has a value of $ 992,084 and the bottom 10 % would be $ 140,513 .
By all accounts this client can look forward to a very successful and comfortable retirement . The problem is this model neglects to account for the 90 % chance that one or both of them may need Long-Term Care services and the added withdrawals from the portfolio should that need arise .
RETIREMENT MODEL
( Only husband requires long-term care ) 22 % probability of occurrence
The second simulation is based on only the husband needing long-term care . There is a 22 % chance only the husband and not the wife will need long-term care . To model this we use the same input as above , however , we start with a current long-term care monthly cost of $ 5,000 inflated at a rate of 5 %. At the husband ’ s age 80 that will be a monthly cost of $ 10,394 ; the average male will require care for 2.2 years . We now add these expenses to the model starting at age 80 and continuing for 2.2 years .
Out of 10,000 runs there are now 5,407 failures which is only a 45.9 % success rate . This is a far cry from the 97 % success rate when modeled if no care is needed with more than twice the likelihood of occurring . When the plan fails to meet the spending goal 54 % of the time the average spending shortfall is now 14 %.
The ending portfolio value is based on the 10,000 simulations . The median portfolio value would be exhausted at age 94 while the 90 % has a value of $ 357,693 and the bottom 10 % would be exhausted at age 88 .
RETIREMENT MODEL
( Only wife requires long-term care ) 22 % probability of occurrence
The third simulation is based on a 22 % chance of only the wife ; not the husband needing long-term care . To model this we use the same input as above , however , we start with a current long-term care monthly cost of $ 5,000 inflated at a rate of 5 %. At the wife ’ s age 85 that will be a monthly cost of $ 13,266 and the average female will require care for 3.7 years . We now add these expenses to the model starting at age 85 and continuing for 3.7 years .
Out of 10,000 runs , there are now 5,597 failures which is only a 44 % success rate . This is a far cry from the 97 % success rate when modeled if no care is needed with more than twice the likelihood of occurring . When the plan fails to meet the spending goal 56 % of the time the average spending shortfall is now 15 %.
With the ending portfolio value based on the 10,000 simulations , the median portfolio value would be exhausted at age 93 while the 90 % has a value of $ 363,194 . The bottom 10 % would be exhausted at age 87 .
LTC impact on retirement continued on page 38
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