FYI: If you just entered the workforce, it’s time to start preparing for retirement. Over the next four decades, you might pull in tens and perhaps hundreds of thousands of dollars every year. An October 2012 Census Bureau study estimates that those with a bachelor’s degree have average lifetime earnings of $2.4 million, figured in today’s dollars.
Of course, it’s lucky you have all that income coming in, because ahead of you lies life’s toughest financial task: amassing enough money so you can retire in comfort. In dry economic terms, your working career is about accumulating enough financial capital, so that one day you’ll no longer need the income from your human capital. This, alas, is a task that most Americans are not good at.
Want to do better? As you ponder how to pay for retirement, it’s helpful to think about your life in three stages—your 20s, 30s and 40s, your 50s and early 60s, and age 65 and beyond—which is how this part of the guide is divvied up.
Regards,
Ted
http://www.humbledollar.com/money-guide/retirement/
Comments
Wow! This assembly of articles by financial writer Johnathan Clements is a real tour-de-force. It touches all the bases that a retiree should consider before retirement, during the decision process, and after retirement. In general, these short pieces yield excellent insights and advice.
But this impressive body of work has a significant shortfall in the area of examining alternate possible financial,scenarios. Based on my earlier submittals, I'm sure many of you can make an accurate guesstimate of what I beleve that area is.
The sequence of investment returns is critical in determining the value and survival of any portfolio during both its accumulation and withdrawal phases. In examining likely financial scenarios, Clements uses the FIRECalc tool kit to explore a limited number of those sequences. I say limited because FIRECalc deploys real historical data with various starting points. This technique generates hundreds of scenarios that have been experienced.
Given the uncertainty of future returns, even hundreds of cases that have been already recorded is simply not enough data when considering all future uncertainties. Thousands and thousands of simulations provide a more complete set of possibities. Projections must be made in terms of likelihoods and odds. Nothing more definitive is possible.
Monte Carlo tools and numerous analyses with those tools are the best way to provide those odds. These tools are readily accessible and easy to use. You need not be a mathematician to productively deploy them. In earlier posts, I have referenced these tools; some are more elegant than others but all serve their basic function well. Here is a Link to a very easy input one:
https://www.portfoliovisualizer.com/monte-carlo-simulation
Another Monte Carlo simulator that requires a few more inputs is listed below:
https://www.portfoliovisualizer.com/monte-carlo-simulation
Sorry for my repeated references, but perhaps some MFOers missed my past postings. Both these tools do good work.
I hope you visit them and try a few cases that represent your special,circumstances. It will be a learning experience that will illuminate some possible dangers if you do a couple of parametric input scenarios. Good luck! Doing these analyses will reduce your need for luck and will help guide your investment and retirement decisions.
Best Wishes
A must have..will bookmark
Like New York, New York, a tool so nice(?) that you named it twice.
He goes on to note that even these tools are best used for educational purposes, not planning:
'For the particular kind of [prostate, breast] cancer you have, the new data show that watchful waiting outcomes are as good in terms of mortality and life quality as treatment, often better, and the number needed to treat is yada yada. Discuss with your doctor whether treatment or monitoring is right for you.'
'Return-sequence risk is always significant and badly down years at the start of your retirement can be deleterious to all of your planning. Discuss with your adviser the consequences of not planning yada yada ...'
And then what? What is the discussion? What can it change besides (dis)comfort level and moves toward drastic preventive actions? How wise is it to have 'just get rid of it' surgery or go to all laddered CDs? In the worst case, plenty wise. So is the discussion necessarily education in likelihood of worst cases?
Thank you for reading my post, but an especial thanks for alerting me to my error in making a double reference. The Portfolio Visualizer website provides an excellent Monte Carlo simulator, but it doesn't merit a double endorsement.
In my initial post, I meant to acknowledge a Monte Carlo simulator that is presented on the MoneyChimp website. It is very simple to use. I have referenced it in earlier postings. Here is the corrected, initial Link:
http://www.moneychimp.com/articles/volatility/retirement.hem
Thanks again for alerting me to my mistake.
When doing any financial analysis, I too am often puzzled over how extensive the data set should be in terms of timespan. The marketplace is in constant change and the relevance of data going back numerous decades is suspect.
Far too much has changed. We have morphed from an agricultural dominated economy to an industrial powerhouse. Market investing is now dominated by institutional agencies and not by individual players. Factors like these should influence the data set selection.
Depending on the scope and purpose of the research, the timeframe for the selected supportive data sets must be prudently chosen. "Garbage In, Garbage Out" applies. For most of the limited analyses that I do, I favor data from after WW II. I recognize the shortfall in numbers that that decision introduces, but I believe these data are more relevant. When doing any statistical analysis, tradeoffs of this kind always must be made. Decisions like these are not always obvious or easy.
To excite some additional responses I'll close,with this decision making quote from Donald Trump: "I have made the tough decisions, always with an eye toward the bottom line. Perhaps it's time America was run like a business."
I anticipate and await acerbic comments.
Best Wishes
There you have it - faith-based investing. You acknowledge that that times change (so that just perhaps the "mean" in mean reversion also changes), but you're stuck in a post WW II industrial past. Maybe that's because that's roughly the period spanning your lifetime, or at least that part of your lifetime when you were aware of your surroundings.
Daniel Bell coined the term post-industrial society all the way back in 1973. The US has moved well beyond the industrial age. It's a service economy now, where fewer people work in industry (even as output increases), just as fewer people work in your agrarian sector even as output increases.
https://www.washingtonpost.com/opinions/robert-jsamuelson-myths-of-post-industrial-america/2013/04/07/775d1062-9fb2-11e2-82bc-511538ae90a4_story.htm
See ag commodity by commodity production graphs (1960 - present) here:
https://www.indexmundi.com/agriculture/?country=us&commodity=milled-rice&graph=production
For earlier data (1900 to 1950), one can wade through this doc:Changes in Agriculture 1900-1950
The decade after WW II was economically unique, as the US was essentially the last economy left standing. Rather than helping to inform investment decisions in today's economy, an argument can be made that that period is no more relevant than the Roaring Twenties.
Geopolitics is another matter. There, WW II is an important starting point. That's when Pax Americana began. But for "the limited analyses that [you] do", this doesn't come into play.
For example, mammograms are not too reliable with dense breast tissue. Here's a page from the American Cancer Society suggesting in that case you talk with your doctor, because on the one hand you might want to also have an MRI. But it also says that MRIs produce false positives leading to more tests and biopsies (which have their own risks).
https://www.cancer.org/cancer/breast-cancer/screening-tests-and-early-detection/mammograms/breast-density-and-your-mammogram-report.html
Similarly, PSA tests are not especially reliable and can lead to biopsies with risks.
A good part of the conversation can simply be an exploration of what's really important to you. In some other thread was a link to an article on how the usual financial planning questions are not helpful, e.g. "would you risk a 20% loss if 2/3 of the time you'd gain 15%?" People don't know what they want or how they'd react if actually (not hypothetically) faced with a 20% loss.
So IMHO talking with a planner at length about what really concerns you and discussing the cost/benefits of different risk mitigators (e.g. immediate annuities, long term care insurance, greater cash allocations, etc.) is a good use of time.
Different people place different values on a given outcome. Worse, most people don't even have a clear idea of how they value each possible outcome.
At one end of the spectrum you have women who will have radical mastectomies because they have a genetic risk of cancer. They choose life, regardless of its quality, over all else. At the other end of the spectrum, you have men who will decline prostate cancer treatment even when faced with certain death, rather than assume any risk of impotence due to treatment.
There are real people like that. I think I can appreciate their perspectives even if I don't agree with them.
Personally, I don't want to go broke, period. In that financial sense, I take an extreme position. A magic number of, say 95% chance of success tells me nothing. I need to know what the 5% of paths look like. Then I can explore possible followup actions that would increase success to 100%.
Likewise with that doctor talk. It's difficult to follow radiation therapy with surgery if the radiation is unsuccessful, while the reverse is much easier. That's a consideration in selecting choice of treatment, if one is willing to live with the much higher likelihood of a degraded quality of life due to multiple therapies.
Knowing not only the odds but the paths of outcomes enables you to plan for dealing with possible failures. And for not doing something just because the expert, whether physician or advisor, felt it was best in his not so humble opinion.
I always wonder what the practical effect is.
One thing that is helpful is hearing oneself have the conversation, and having further on the way home, with oneself or w/ whomever one is with. Letting it sink in, sleeping on it.
So you're a 100%-success 'aimer'?
Assume humility (in advice-giving) on part of expert.
Being an "aimer" is very common. We all have goals. The challenge is how realistic those goals are. What are the odds of achieving those goals? Given market uncertainties, a 100% success goal is very bushy-tailed. But it is achievable if an investor is flexible to changing circumstances.
An early step in that process is to identify the likely odds of success. Monte Carlo simulators provide one useful tool to make those estimates. That tool not only yields the odds for success, but also makes estimates of end wealth, and a timeline for the portfolio failures. If those failure times are well beyond likely life expectancy, the failures are far less significant for planning purposes.
I well understand why only a 95% portfolio survival projection would be troublesome for some folks. It was for me. However, once that estimate is known, an investor could think about adjusting his withdrawal plan to alleviate that possibility.
When planning my retirement, I programmed my own version of a Monte Carlo code. I frequently calculated portfolio survival likelihoods in the mid-90% ranges. What to do? To improve that survival rate, I modified the code to reduce drawdowns by an input value (like 10%) if annual market returns were negative for some specified years. Withdrawals were increased once the markets turned positive in the simulations.
I explored many such portfolio survival issues by using my easily modified Monte Carlo code. Portfolio survival rates of very near 100% could be projected when very modest withdrawal rate flexibility was allowed. Like in so many other life situations, flexibility is a winning strategy.
My Monte Carlo calculations identified the frequency of shortfalls, the magnitudes of any shortfalls, and the timeframe of those shortfalls. These were all useful inputs for my retirement decision. The very modest adjustments needed to alleviate that unacceptable outcome gave great comfort. These additional Monte Carlo simulations cemented my retirement decision.
I believe (alternately, IMHO if you dislike "I believe") that Monte Carlo simulations would help many MFOers when considering their retirement decision.
Thanks for the Kitces reference. Be aware that he has a vested interest in the subject matter of that referenced article. He closes his piece with the following declaration:
"Michael Kitces has a financial interest in the US distribution of the Timeline app."
I have no such vested interest in Monte Carlo codes. I merely advocate that they be included as one tool to support investment decisions. They permit easy multiple sensitivity analyses. Of course, they depend on good input data ranges. They do not stand alone.
Best Wishes
Thank you for reading my posts. I greatly appreciate your long term loyalty. I can assure you that if you continue that loyalty you will not forget the many advantages of Monte Carlo tools since I will continue to strongly advocate them. MFO attracts new visitors who might not be familiar with that tool. I try very hard to make every post useful and devoid of sarcasm.
Best Wishes.
Well done.
Regards,
Ted
Regards,
Ted
As to NIH and HHS telling people that preventive testing is excessive and unnecessary, my guess is that you wouldn't go advising healthy 18 year old women to get mammograms every six months, just in case. We probably agree that at some point preventive testing does become excessive and unnecessary. It's a question of where one draws the line, not whether preventive testing could possibly be excessive.
The ACA generally bases what preventive services be covered at zero cost on USPSTF's guidelines (which say that mammograms offer substantial or moderate benefit starting at age 50, but just small net benefit between 40 and 49). So a specific exception was written into the ACA to include mammograms for women 40 and above.
http://www.factcheck.org/2013/10/aca-doesnt-restrict-mammograms/
I believe it's because of the way the law was written that this exception was going to expire. But for whatever reason, the Health Resources and Services Admin (part of HHS) recently updated its guidelines so that the ACA would continue covering mammograms at age 40.
https://www.kff.org/womens-health-policy/fact-sheet/preventive-services-for-women-covered-by-private-health-plans-under-the-affordable-care-act/
In addition, USPSTF points out that its "'C' [small net benefit] recommendation ... is often misinterpreted as a recommendation against mammography screening or coverage. In the linkage to coverage established by the Patient Protection and Affordable Care Act, the USPSTF's role is limited to evaluating the science to determine the net benefit of a clinical preventive service. [USPSTF's] review of the scientific evidence may be only one of the inputs to determining insurance coverage; often it is the floor to determining minimal coverage, not the ceiling."
https://www.uspreventiveservicestaskforce.org/Page/Document/convergence-and-divergence-around-breast-cancer-screening/breast-cancer-screening1
It is in that gray area of small net benefit (over the whole population) where conversations between patient and doctor may be most productive. Different people place different emphasis on possible outcomes, so what might make sense for one person won't make sense for another.
Here's the Susan G. Komen page on Weighing the Benefits and Risks of Mammography including sections on overdiagnosis and overtreatment.
As noted in a lengthy Mother Jones column: "With so much rhetoric flying back and forth, it can be difficult for women to make truly informed decisions." That makes talking with doctors about the real risks and benefits even more important.
http://www.motherjones.com/politics/2015/10/faulty-research-behind-mammograms-breast-cancer/