Friday, April 9, 2021

Short Takes: Investing Simply, Income Tax Issues, and more

A big oversight of mine is that I never subscribed to my own email feed.  Like someone who donates to a charity to feel good about themselves without ever checking if the charity is doing good work, I made my articles available for free by email without ever checking whether the service was working well.  Fortunately, my wife subscribed and told me that sometimes there’s a day delay before an email arrives.  I’ve been working on fixing this.  I’ve now subscribed myself and noticed that the font was kind of small.  So I made it a little bigger.  Hopefully, with some periodic monitoring, I can make the experience better for everyone.

Here are my posts for the past two weeks:

Buy Now Pay Later Apps

Safety-First Retirement Planning

A Life-Long Do-It-Yourself Investing Plan

The Value of Monte Carlo Retirement Analysis

The Dumb Things Smart People Do With Their Money

Here are some short takes and some weekend reading:

Robb Engen makes a strong case for DIY investors to use a single asset-allocation ETF over more complex mixes of ETFs like Justin Bender’s Plaid Portfolio, Ben Felix’s Five Factor Model Portfolio, or my mix of VCN, VTI, VBR, and VXUS.  He’s right that few investors will manage these more complex portfolios successfully.  Complexity builds quickly when you’re managing multiple ETFs over RRSPs, TFSAs, and taxable accounts.  For my portfolio, I estimate my MER and foreign withholding tax (FWT) savings compared to just using VEQT for stocks is currently 0.29% per year.  This isn’t trivial, but you don’t have to mess up the plan much to lose these savings and more.  If I had to manage my portfolio by hand instead of having it automated in an elaborate  spreadsheet, I would gladly trade 0.29% per year for the simplicity of VEQT.  I recommend VEQT to my sons and other family and friends who ask.

The Blunt Bean Counter
is out with his list of common tax issues for the 2020 taxation year.

My Own Advisor makes a weak case that active investors shouldn’t bother benchmarking their portfolios.  I made a decision a while back to read fewer articles related to stock picking, but I still read some.  The main reasons not to benchmark your portfolio are 1) to avoid getting the bad news that your stock picks are losing to the market, and 2) to avoid the work required to figure out your portfolio’s return and to pick a benchmark.  Properly done, benchmarking begins with choosing in advance a mix of passive investments that roughly matches the allocations of your active portfolio.  Then at the end of the year, you can compare your portfolio’s return to that of your benchmark to see over the years whether your active picks are any good.  Most active investors don’t even know their portfolio’s return, so they’d be glad to hear that they don’t need to benchmark.  The few who do calculate their annual returns often find that their skills don’t look very good over the long term compared to a reasonable benchmark, and these investors are even happier to hear that they don’t need to benchmark.  My Own Advisor points to problems with finding a benchmark that matches your goals.  This isn’t actually very hard, but it usually requires blending a few indexes.  The key is to pick this mix in advance so you’re not tempted to choose a mix after the fact that makes your active portfolio look better.  My Own Advisor points to benchmarking being a lagging indicator.  However, the goal isn’t to go back in time and change your investments; it’s to find out whether you should keep picking your own stocks or abandon a losing effort.  It may be disappointing to find your efforts over a decade have lost you money, but it’s better to know the truth.  My Own Advisor suggests focusing on your life, health, and other more important things than benchmarking.  This advice applies much better to reclaiming the time you put into stock picking and just living your life while passive investments do their thing.  People are free to do as they wish with their money, including picking their own stocks and not checking their performance, but it’s not good to advise others to follow this path.

Thursday, April 8, 2021

The Dumb Things Smart People Do With Their Money

Even smart people do some dumb things with their money, according to Jill Schlesinger, a Certified Financial Planner and media personality.  In her book, The Dumb Things Smart People Do With Their Money, she goes over thirteen common costly mistakes.  It’s an easy read that might change your mind about a few things.  The focus is on the U.S., and some detailed parts aren’t relevant to Canadians, but the broad themes are still relevant.

The parts of the book I liked best dealt with buying financial products you don’t understand, buying a house in situations that clearly call for renting, taking on too much risk, indulging yourself too much during your early retirement years, not having a will, and trying to time the market.

On the subject of buying investments we don’t understand, the author says “There just isn't any need to invest in gold,” and “It’s usually a crappy investment.”  On reverse mortgages, some predatory lenders “go to extraordinary (and sometimes illegal) lengths to foreclose on borrowers’ homes,” and “many people take out reverse mortgages without analyzing whether they really should stay in their homes.”

Schlesinger believes strongly in getting advice from fiduciaries.  It’s a mistake to take “financial advice from someone who is trying, first and foremost, to sell you something that will make him or her money, rather than help you.”

In an interesting twist, the author says you don’t need professional advice or a customized plan if “you have consumer debt,” “you aren’t maxing out your retirement contributions (presuming that you are in a high enough tax bracket for that to make sense),” or “you don’t have an emergency account with enough money in it to cover six to twelve months of expenses.”

The section on taking too much risk has an excellent discussion of recency bias.  I see this in myself every time I add new money to my portfolio, take money out, or have to rebalance.  These actions always call for either buying something that has performed poorly recently or selling something that has performed well recently.  I’ve learned to overcome my recency bias in these contexts, but the feeling of wanting to stick with an asset class that has been rising never goes away.  You need “to minimize how many direct investment decisions you make.  The fewer decisions, the less opportunity for your internal biases to wreak havoc.”

Schlesinger devotes an entire chapter to indulging yourself too much early in retirement.  This flies in the face of claims that overspending early in retirement doesn’t meaningfully contribute to the fact that the average retiree spends less with age.

In one section the author links the decision to delay taking Social Security with staying on the job longer.  Maybe that makes sense under U.S. rules, but in Canada, one can certainly benefit by spending savings while delaying CPP and OAS until years after retiring.

The author believes that the amount people can safely draw in retirement is “3 percent or so.”    This makes sense as a starting withdrawal percentage for someone age 60 or younger who pays investment fees above 1% per year.  Higher safe withdrawal amounts are for disciplined low-cost DIY investors or older retirees.

“The insurance industry wants you to think that you need permanent insurance, but most people don’t.”  Well said.

The section on not trying to time the market contains many excellent points.  Unfortunately, at one point the author quotes some DALBAR figures that supposedly illustrate investors’ poor market timing.  The DALBAR methodology for calculating investor returns makes no sense.  It’s true that individual investors aren’t good market timers, but DALBAR penalizes investors who buy into the market with new savings because they didn’t invest the money sooner (i.e., before they even had it).

Overall, this book is an easy read and makes many good points.  One of the downsides of being smart is that you can delude yourself at the same time you persuade others.  This can lead to excessive risk-taking and costly mistakes.

Tuesday, April 6, 2021

The Value of Monte Carlo Retirement Analysis

You may have heard of using Monte Carlo simulators to test your retirement plan.  It sounds impressively scientific to hear that your retirement plan has a 95% chance of success.  However, these simulators necessarily make assumptions about future returns, and the simulator outputs are very sensitive to these assumptions.

The term “Monte Carlo” refers to any algorithm that uses random samples to solve some problem.  Such methods are used widely in engineering, science, finance, and other areas.  In finance, Monte Carlo simulators are used to create many random sets of possible future investment returns, and we can test a retirement plan against these possible futures.  In particular, we can define success in some way, such as not running out of money or not having to cut back too far on spending, and see how often a retirement plan succeeds.

Monte Carlo simulators can work in many different ways.  They can just assume some expected return and volatility for stocks and bonds and generate random returns from what is called a “lognormal distribution.”  Alternatively, they could just start with a collection of past monthly or annual returns and select randomly from this collection.  Some simulators leave out the Monte Carlo part and just use actual return histories starting from various dates.

Unfortunately, the outputs of these simulators are very sensitive to the assumptions built into them.  If you use lognormal returns, you get to choose the expected returns and volatilities of stocks and bonds.  These are just 4 numbers, but they can make the difference between a retirement plan failing 5% of the time or 50% of the time.  

For simulators that use a collection of past returns, we can get very different outcomes depending on what range of historical returns we use.  For example, bond returns from the past 40 years can’t possibly be repeated in the coming 40 years unless interest rates can drop somehow to negative double-digit levels.  A Monte Carlo simulator can easily hide an assumption that we’re headed to interest rates of minus 10%.  Most experts don’t believe future stock returns can match average 20th century returns in the U.S., but a simulator can assume they will.

Another problem most Monte Carlo simulators have is that they assume future returns aren’t correlated to past returns.  We know that when the stock market is high, expected future returns are low and vice-versa.  In a past article I illustrated this effect in pictures.

Yet another problem is that most simulators assume inflation is some low fixed value.  This problem shows itself most with annuities and bonds.  Inflation only has to bump up a little to cut deeply into the value of annuities and long-term bonds.  If a simulator doesn’t allow for the possibility that inflation could tick up a percentage point or two, how can we take its output seriously when it declares a retirement plan successful 95% of the time?

It’s certainly possible for a conscientious and talented financial advisor to take all these facts into account and choose sensible assumptions to build into a Monte Carlo simulator.  However, it’s tempting to tinker with assumptions so that clients can appear to be able to safely spend more during retirement.  Few advisors would admit to doing this, but because experts disagree over what simulator assumptions are sensible, it’s fairly easy to come up with a plausible justification for a wide range of assumptions to build into Monte Carlo simulators.

In the end, simulators can be less of a scientific tool and more of a marketing tool to impress clients and give them comforting answers.  This may sound damning, but comforting clients matters.  It’s not good to misuse a simulator to comfort a client about a bad retirement plan, but it is good to make a client feel safe committing to a good retirement plan.