Even Dimensional Fund Advisors Struggles with Inflation Statistics

Inflation is a risk we have to face in financial planning, particularly in retirement.  We need to measure inflation risk correctly to be able to make reasonable financial plans.  The best guide we have to the future takes into account past inflation statistics.  But the field of statistics is full of subtleties, and even Dimensional Fund Advisors (DFA) can make mistakes.

DFA creates good funds, and their advisors tend to do good work for their clients.  I’d prefer to find errors in the work of a less investor-friendly investment firm, but they provided a clear example to learn from.  They misapplied a statistical rule, and as a result, they misinterpreted the history of inflation over the past century.

I discussed this issue with Larry Swedroe in posts on X.  I respect Larry and have followed his work as he tirelessly explains evidence based investing to the masses.

A Simple Example

To explain the problem, let’s first begin with a simpler example.  Someone might offer the following as a rule: when you add two numbers, you get a total that is larger than either of the numbers you added.  This seems sensible.  After all, when two people put their money together, they end up with more together than either of them had individually.

But what if one of the numbers you add is negative?  Then the rule doesn’t work.  If one person is in debt, merging finances with another person leaves that other person with less money than they started with.  The real rule: for positive numbers, when you add them, you get a total larger than either of the numbers you added.  The qualifier “for positive numbers” is important.

Monthly Inflation Data

The amount of inflation we will get next month is a type of random variable.  This random variable has what is called a standard deviation, which is a measure of how widely the inflation outcome can vary.  The larger the standard deviation, the wider the range of possible values we could get.

Over the past century, monthly U.S. inflation has averaged 0.24% with a standard deviation of 0.52%.  For 77% of the months, inflation was within one standard deviation of its average value, i.e., between 0.24% - 0.52% = -0.28% and 0.24% + 0.52% = 0.76%.

Annual Inflation

We tend to be more interested in annual figures than monthly figures.  It’s not hard to find the average annual inflation over the past century; we just multiply the monthly average of 0.24% by 12 to get 2.9%.  But what about the standard deviation?  It doesn’t get 12 times bigger, because sometimes low inflation months tend to cancel high inflation months.

There is a rule in probability and statistics that when you add independent and identically distributed (IID) random variables, the standard deviation grows as the square root of the number of random variables you added together.  So, if you add 100 months of inflation together, this rule says that the uncertainty (standard deviation) of the total would grow by a factor of 10.  Average total inflation for 100 months would be 0.24% x 100 = 24%, and the standard deviation would be 0.52% x 10 = 5.2%.

DFA started with this rule and the fact that there are 12 months in a year.  Then they multiplied the monthly inflation standard deviation of 0.52% by the square root of 12 (roughly 3.46) to get 1.82% as the annual standard deviation.  This is a fairly low figure, and it indicates that inflation has been fairly predictable.  Unfortunately, this isn’t correct, and inflation has been substantially less predictable than this.

The Error

Recall that the standard deviation rule required that the random variables be “independent.”  This means that knowing the inflation in previous months tells you nothing about next month’s inflation.  However, this isn’t true.

There is a measure of the degree to which one month’s data predicts the next month's data.  It’s called autocorrelation or serial correlation, and is related to the idea of momentum.  The autocorrelation coefficient is a number between -1 and +1.  When random variables are independent, the autocorrelation coefficient is zero.

Monthly U.S. inflation over the past century has had an autocorrelation coefficient of 0.47, which is far too high to treat them as independent.  Knowing last month’s inflation narrows down the uncertainty of next month’s inflation.

When we calculate all the actual annual inflation figures for each of the 100 years and find the standard deviation directly instead of calculating it from monthly figures, the result is 3.7%.  This is more than double the 1.82% figure that DFA calculated.

The author of the DFA report seemed to recognize the potential for a problem.  The following note was attached to the reported annual standard deviation of 1.82%.

“Annualized number is presented as an approximation by multiplying the monthly number by the square root of the number of periods in a year.  Please note that the number computed from annual data may differ materially from this estimate.”

Unfortunately, 1.82% is a terrible “estimate” for 3.7%.  This note didn’t help Larry Swedroe who said in our exchange on X, “Fact is though inflation volatility [is] historically low.”  The DFA report led him to believe that inflation is much more predictable than it really is.

Treating financial numbers over time as independent of each other is pervasive in the financial industry.  
They often do this for stock and bond returns, inflation, and other types of returns.  An exception is the work on momentum in asset prices.  We usually see investment models take into account correlations between asset types, but within an asset type over time, independence is often assumed.  However, we should always check autocorrelation to see whether the independence assumption is justified.  

As Larry observed, inflation is “regime related, and regimes last,” and private equity has high autocorrelation due to “stale prices.”  No doubt there are many other causes of high autocorrelation that make the independence assumption inappropriate.

It Gets Worse

What really matters to a financial plan is how inflation builds over decades, not just one year of inflation.  The autocorrelation coefficient for annual inflation is 0.67, which is even higher than it was for monthly inflation.  This means that uncertainty about inflation over a decade is much higher than we might predict knowing the standard deviation of annual inflation.

There are 120 months in a decade.  If we misapply the standard deviation rule and multiply the monthly standard deviation of 0.52% by the square root of 120, we get 5.7%.  However, when we find the standard deviation of inflation over decades directly, it is 25%, a far cry from only 5.7%.

Putting Decade Standard Deviation of Inflation into Context

Suppose we buy a basket of goods for $100, and we want to know what it will cost in a decade.  If we misapply the standard deviation rule and assume what is called a lognormal distribution of inflation outcomes, we think there is only one chance in a thousand that the basket will cost more than $160 a decade later.  

Within the past century, there are a total of 1081 decade-long periods with one decade starting each month.  When we directly calculate how the price of $100 worth of goods grows during each of these 1081 rolling decades in the past century, we find that 23% of the time it exceeds $160.  That’s not a typo.  Somehow 1 in a thousand in theory became 230 in a thousand in reality.

How Relevant is Old Inflation Data?

Some might argue that old inflation data from 50 to 100 years ago isn’t relevant in today’s world.  There may be some truth to this.  However, if we’re going to discount the standard deviation of inflation to reflect reality in the modern world, we have to start  from the correct figure.  The standard deviation of inflation over decades has been 25%, not 5.7%.  Whatever discounting we do, it should start from 25%.

However, we can’t discount inflation uncertainty too far.  As the recent bout of rising prices we had starting in 2021 showed us, central banks cannot fully control inflation.  Future spikes of inflation are possible, and the models we use to account for inflation in financial planning have to reflect this reality.

Annuities

An annuity is a contract where someone hands a lump sum of money to a bank or insurance company in return for guaranteed payments for life, which provides protection against longevity risk and return risk.  Typically, annuity payments are not inflation protected, but as Larry pointed out, inflation-protected annuities now exist.

Decumulation experts know that investors don’t like annuities, even though simulations show that annuities improve the odds that a financial plan will meet client goals.  They call this the annuity puzzle.  

However, if the problem of not modelling inflation properly is pervasive, then maybe annuities (that don’t have inflation protection) aren’t as helpful in lowering portfolio risk as they appear.  Annuities have not fared well in the simulations I do for my own portfolio, but that is because I model the full “wildness” of inflation.

Implication for Financial Planning

Financial planners often use a tool to run what are called Monte Carlo simulations of a financial plan.  The idea is that the simulator creates many plausible histories of investment returns, and checks how often your plan meets your goals.  You might be told that your plan has, say, a 95% chance of success.

However, if the inflation model the simulator uses is wrong, this success rate will be wrong too.  The main error simulators with bad inflation parameters make is to underestimate the uncertainty in the long-term buying power of fixed income securities, such as medium to long-term bonds and annuities and pensions that don’t have inflation indexing.

I pointed out to Larry that the annual inflation standard deviation has been 3.7% and not 1.8%.  He replied “IMO [this] makes little difference because even if [it] was 1.8 not 3.7 one should still consider left tail risks making the portfolio resilient to that, especially given our fiscal situation and the risk of inflation it creates.”

So Larry is saying that even if the Monte Carlo simulations are wrong, financial planners should be checking financial plans for large shocks known as “left tail risks,” such as high inflation, and these checks will uncover any problems.

I agree that we should check financial plans for left tail risks, but I’m not comfortable with this answer.  Suppose we leave simulators unchanged and continue treating inflation as tame.  Suppose further that a financial planner tells a client that their plan has a 95% chance of meeting their goals and has been checked against left tail risks.  Will the planner go on to say that the 95% figure is not really correct, but not to worry because the left tail check will cover things?  Not likely.  If the planner did bring it up, the client would likely ask how far wrong the success probability is.  The planner wouldn’t know.  The client would wonder what the point of the simulation is if the results are known to be wrong.  If the planner doesn’t tell the client that their probability of success isn’t really 95%, the main purpose of the simulations would be to impress clients rather than inform them; Monte Carlo simulations would be marketing rather than substance.

I’m not sure how much of a difference it will make in Monte Carlo simulations to fix the inflation modelling.  I’ve never run simulations with “tame” inflation, and I’ve never seen others run simulations with “wilder” inflation.  But those who have never modelled inflation properly can’t be sure what difference it will make either.

Conclusion

A well known fact about how to calculate the standard deviation of sums of random variables, such as investment returns or inflation, is widely misused in contexts where it does not apply.  Dimensional Fund Advisors did this with inflation data, and this calls into question the accuracy of financial planners’ simulations of their clients’ financial plans.

Book Review: The Algebra of Wealth

Scott Galloway uses a unique style in his book The Algebra of Wealth: A Simple Formula for Financial Security.  Rather than offer generic advice to choose a career that pays well, Galloway takes the tone of someone telling you privately what he really thinks of various career options, for example.  He takes a similar approach to other topics as well.  Readers may not agree with all of his advice, but they can’t say his opinions weren’t clear.  

The book is divided into chapters on focus, good habits, and avoiding mistakes; choosing a career and developing skills; spending, saving, and budgeting; and investing.  The blunt commentary on choosing a career was the most interesting part of the book.  

For those concerned that this is some sort of math book, it isn’t.  The few formulas in the book are mostly not intended to be taken literally.  For example, “focus + (stoicism x time x diversification),” and “value = (future income + terminal value) x discount rate.”  That latter formula is vaguely close to a value formula, but is unlikely to be helpful to anyone who doesn’t already know the actual formula.

Career choice

Many writers have taken sides on whether to “follow your passion” in picking a career.  Galloway’s take is interesting.  “Don’t follow your passion, follow your talent.” “Passion careers suck,” and “work spoils passion.”  “Focus on mastery; passion will follow.”  I’ve certainly suspected that the reason I had passion for my career and the sports I’ve played is because I was good at them.

Because few entrepreneurial ventures succeed, working for a large organization “offers better risk-adjusted returns.”  “As a society, we romanticize entrepreneurship.” “The defining characteristic of an entrepreneur” is lacking “the skills needed to succeed in a large organization.”  Most entrepreneurs “did not start companies because they could, but because they had no other options.”

Jobs in the trades can be very lucrative, but “We have shamed an entire generation into believing a trades job means things didn’t work out for you.”  Pursuing a college or university degree isn’t the best option for everyone.

Loyalty

These days, employers offer little loyalty to their employees, “and that has made our loyalty to one another, as individuals, even more important.”  “Mike Bloomberg once said, ‘I have always had a policy: If it’s a friend and they get a promotion, I don’t bother to call them; I’ll see them sometime and make a joke about it.  If they get fired, I want to go out for dinner with them that night.  And I want to do it in a public place where everybody can see me.”

Savings Goals

“Ambitious savings goals … can backfire.”  Research shows “people set overambitious goals for savings in the future.”  “Set a goal for saving this month, and you are likely to be realistic and achieve your goal.  Set a goal for saving in six months, and you are likely to set an unrealistic goal and fail to meet it.”  I can’t say I found this to be true for me about saving money, but it’s definitely true for my exercise goals.

Financial planning

“Failing to consider inflation is a common but severe oversight in financial planning.”  Ignoring inflation entirely can be devastating, but assuming it will remain at some fixed low level is dangerous as well.

“You aren’t paying [financial advisers] for investment returns.  Over the long term, nobody beats the market.  And if someone does have the secret to above-market returns, they aren’t going to be sharing it with you for a fixed percentage.  You’re paying an adviser for planning, accountability, and confidence.”

Investing

Invest “in a half dozen low-cost, diversified exchange-traded funds (ETFs) that put the majority of your money in U.S. corporate stocks.”  This is solid advice, but 6 ETFs may be high these days.  There are many good solutions that use 1-3 ETFs.

Galloway’s take on the passive/active investing debate.  Once they get to $10,000 in long-term savings, he tells people to invest $8000 passively, and $2000 actively, and to invest anything past $10,000 passively.  The $2000 “is enough that when you lose, you’ll feel the pain, but it’s not so much that you’re putting your future economic security at unnecessary risk.”  The idea is to learn whether you’re cut out for active investing without risking too much.  Galloway recommends avoiding active funds.

Those who delve into stock picking need to look out for EBITDA.  “CEOs like to emphasize EBITDA [rather than actual profit figures] for the simple reason that it makes their business look more profitable.”  “There has been a trend toward even more aggressive metrics, especially among early stage companies, usually described as ‘adjusted EBITDA.’”  Galloway describes the justification for such metrics as “dubious.”

One short section gives one of the best explanations I’ve seen of what bonds are, why they exist, and what players are involved in bonds.

Options markets are “dominated by sophisticated professionals.”  “Retail investors buying individual [option] contracts are minnows who these big fish swallow up for easy profit.”

Conclusion

This book has interesting takes on a variety of important personal finance topics.  Some of it is specific to Americans (mainly tax matters), but the majority of the book is useful to Canadians as well.  Whether you agree or disagree with the opinions expressed, it will make you think.

Inflation is Much Riskier than Financial Planning Software Makes it out to be

As we’ve learned in recent years, inflation can rise up and make life’s necessities expensive.  Despite the best efforts of central bankers to control inflation through the economic shocks caused by Covid-19, inflation rose significantly for nearly 3 years in both Canada and the U.S.  

Uncertainty about future inflation is an important risk in financial planning, but most financial planning software treats inflation as far less risky than it really is.  This makes projections of the probability of success of a financial plan inaccurate.  Here we analyze the nature of inflation and explain the implications for financial planning.

Historical inflation

Over the past century, inflation has averaged 2.9% per year in both Canada and the U.S.(*)  However, the standard deviation of annual inflation has been 3.6% in Canada and 3.7% in the U.S.  This shows that inflation has been much more volatile than we became used to in the 2 or 3 decades before Covid-19 appeared.  In 22 out of 100 years, inflation in Canada was more than one standard deviation away from the average, i.e., either less than -0.7% or more than 6.5%.(**)  Results were similar in the U.S.

Historical inflation has been far wilder than the tame inflation we experienced from 1992 to 2020.  And the news gets worse.  Within reason, a single year of inflation is not a big deal to a long-term financial plan; what matters is inflation over decades.  It turns out that inflation is wilder over decades than we’d expect by examining just annual figures with the assumption that each year is independent of previous years.

The standard deviation of Canadian inflation over the twenty 5-year periods is 14%, and over the ten decades is 27%.  Based on assuming independent annual inflation amounts, we would have expected these standard deviation figures to be only 8% and 11%.  How could the actual numbers be so much higher?  It turns out that inflation goes in trends.  This year’s inflation is highly correlated with last year’s inflation.  Rather than a correlation of zero, the correlation from one year to the next is 66% in Canada and 67% in the U.S.(***)

Even successive 5-year inflation samples have a correlation of 60% in Canada and 56% in the U.S.  It’s only when we examine successive decades of inflation that correlation drops to 23% in Canada and 21% in the U.S.  This is low enough that we could treat successive decades of inflation as independent, but we can’t reasonably do this for successive years.

How relevant is older inflation data?

Some might argue that old inflation data isn’t relevant; we should use recent inflation data as more representative of what we’ll see in the future.  After all, central banks had a good handle on inflation for a long time.  Let’s test this argument.

From 1992 to 2020, inflation in Canada averaged 1.72% with a standard deviation of 0.94%.  Using this period as a guide, the inflation that followed was shocking.  In the 32 months ending in August 2023, inflation was a total of 15.5%.  Using the 1992 to 2020 period as a model, the probability that the later 32 months could have had such high inflation is absurdly low: about 1 in 10 billion.(****)

It may be that older inflation data is less relevant, but our recent bout of inflation proves that the 1992 to 2020 period cannot reasonably be used as a model for future inflation.  There is room for compromise here, but any reasonable model must allow for the possibility of future bouts of higher inflation.

Implications

It’s important to remember that once a bout of inflation has been tamed, the damage is already done.  Prices have jumped quickly and will start climbing slower from their new high levels.  If there has been 10% excess inflation over some period, all long-term bonds and future annuity payments will be worth 10% less in real purchasing power than our financial plans anticipated.  This is a serious threat to people’s finances.

We often hear that government bonds are risk-free if held to maturity.  This is only true when we measure risk in nominal dollars.  Because spending rises with inflation, our consumption is in real (inflation-adjusted) dollars.  Bonds held to maturity are exposed to the full volatility of inflation.  We need to acknowledge that bonds have significant risk.  Only inflation-protected government bonds are free of risk.

When financial planning software uses a fixed constant for inflation, like 2% or 2.5%, it is understating the risk posed by inflation.  With constant inflation, bonds held to maturity look risk-free when they aren’t.

Most annuities are also exposed to inflation risk.  Annuities are good for removing longevity risk, but future payments are not as stable in real dollars as they appear to be in nominal dollars.

When software performs Monte Carlo simulations to determine the probability that a financial plan will fail, a poor model of inflation overstates the protection offered by bonds and annuities.  The probability that bonds and annuities will fail to perform their main function of providing safety is higher than these simulators estimate.

It’s fairly easy to write software that performs Monte Carlo portfolio simulations.  The challenge is in correctly modelling investment returns and inflation with reasonable parameters.  Unfortunately, software outputs look equally slick whether this modelling is done well or not.  It’s easy to tinker with model parameters to get the success percentage you want for a financial plan, even if you don’t intend to cheat.

Remedies

One way to address inflation risk is to model it better and simulate it along with stock and bond return simulations.  However, stock and bond returns are not independent of inflation.  If a particular simulation run has high inflation, it’s not reasonable to assume that subsequent nominal stock and bond returns are unaffected.

Along with high inflation, we often get interest rate changes, which affects future bond returns.  Businesses typically raise prices in response to inflation, which can raise future nominal stocks returns.  The interplay between inflation and investment returns is complex.

Some financial planners recognize the problem of fixed inflation assumptions and they run their Monte Carlo simulations with different fixed values for future inflation as a further test of a financial plan.  This helps to some degree, but they are punishing the returns from bonds, annuities, and stocks equally, which doesn’t reflect the reality of inflation’s effects on different types of investment returns.

Because we spend real inflation-adjusted dollars, it’s better to model the real returns of stocks, bonds, and other investments directly.  Instead of studying nominal stock returns to create simulation models, we should study and model real stock returns.  The same is true for bonds and other types of investments such as real estate.

We would still need to model inflation to estimate capital gains taxes and anything else that is based on nominal dollars, but directly modelling the real returns of investments tends to make it easier to properly simulate and test a financial plan.

Conclusion

Most financial planning software underestimates the potential for inflation to disrupt a financial plan.  Measuring volatility in nominal terms is fundamentally misguided, and treating inflation as constant implicitly treats nominal and real quantities as having the same volatility.  As a result of this distortion, bonds and annuities are over-valued as a means to control risk.  Inflation-protected bonds are under-valued.  The success percentages that portfolio simulators calculate for financial plans often have little connection to reality.

Footnotes

(*) All figures used here use the logarithm of Consumer Price Index (CPI) ratios.  This is important for good modelling of inflation and investment returns, but makes only a modest difference in the actual figures.  For example, the average logarithm of annual inflation in Canada for the past century is 2.914%, which corresponds to compound average annual inflation of exp(2.914%)-1=2.957%.

(**) For those who expected inflation to be more than one standard deviation from its mean 32% of the time instead of 22%, this is misapplying the normal distribution (also known as the bell curve).  Inflation figures are far from normally distributed.  Financial mathematics is littered with over-application of the normal distribution.

(***) When a random variable is uncorrelated with its past annual values, the standard deviation of a 5-year sum is sqrt(5) times the standard deviation of a single year.  For decades, we multiply by sqrt(10).  With inflation, the actual correlation is not zero; the autocorrelation coefficient is about 2/3.

(****) Assuming that annual inflation samples are independent and lognormal with a mean of 1.72% and standard deviation of 0.94%, our recent 32-month bout of inflation is a 6.4-sigma event, which has probability of about 10^(-10).  So, the distribution assumptions are clearly not true.

How Investing Has Changed Over the Past Century

Benjamin Graham is widely considered to be the “father” of value investing, the process of finding individual stocks whose businesses offer the prospect of future price gains while offering reasonable protection against future losses.  Graham co-founded Graham-Newman Corp. nearly a century ago.  Stock markets have changed drastically since then.

Early in Graham’s investing career, his approach was to buy stock in companies that were out-of-favour and severely undervalued.  He described these methods in his 1934 book Security Analysis.

But Graham’s investment methods were never static.  As Jason Zweig explained in Episode 75 of the Bogleheads on Investing Podcast:

“People criticize Graham all the time for being old-fashioned, for having these formulaic techniques for valuing stocks, … and then people say these things are all out-moded.  Nobody invests like that any more.  Nobody should.  And that completely misses the mark for two reasons.  First, during his lifetime, Graham revised the book [The Intelligent Investor] several times, and every time he revised it he changed all those formulas.  He updated them to reflect the new market realities at the time the new edition of the book was coming out.  … If he were still around today, he would update all those formulas all over again, and they would look nothing like what’s in the books.  … The second objection is much more basic, which is: that’s not Graham’s message.  … Graham’s message is that if you try to play the same game as Wall Street itself, you will lose.”

Graham recognized that markets change over time.  To keep beating the market averages, as he did for many years, his investment methods had to change over time.

However, in Graham’s last version of The Intelligent Investor in 1973, he wrote

“We have some doubt whether a really substantial extra recompense is promised to the active investor under today’s conditions. But next year or the years after may well be different. We shall accordingly continue to devote attention to the possibilities for enterprising investment, as they existed in former periods and may return.”

Graham expressed optimism that conditions might change so that some version of his investment approach might beat the markets.  However, that hasn’t been the trend.  Markets have become ever more competitive with each passing decade.

Another quote from Graham in the same 1973 book:

“Since anyone—by just buying and holding a representative list [a market index]—can equal the performance of the market averages, it would seem a comparatively simple matter to ‘beat the averages’; but as a matter of fact the proportion of smart people who try this and fail is surprisingly large.  Even the majority of investment funds with all their experienced personnel have not performed so well over the years as the general market.”

By 1976, Graham become more pessimistic about beating markets:

“I am no longer an advocate of elaborate techniques of security analysis in order to find superior value opportunities. This was a rewarding activity, say, 40 years ago, when our textbook ‘Graham and Dodd’ was first published; but the situation has changed a great deal since then. In the old days any well-trained security analyst could do a good professional job of selecting undervalued issues through detailed studies; but in the light of the enormous amount of research now being carried on, I doubt whether in most cases such extensive efforts will generate sufficiently superior selections to justify their cost.”

Graham remains a hero to many value investors, despite the fact that 48 years ago he doubted whether analyzing businesses to find good value worked any more.  Graham’s methods worked from 50 to 100 years ago because of the ample dumb money flowing in stock markets.  For superior investors making excess returns to exist, there must be many inferior investors performing worse than market averages.

The proportion of money in stock markets controlled by individual investors has declined steadily over the decades.  Investors who knew little used to buy their own stocks.  Now, many such investors use mutual funds and exchange-traded funds to have their investments controlled by experts.  Dumb money has shrunk as a percentage, and the competition among investment professionals to exploit dumb money has become so sophisticated that few understand it.

Markets have reached the point where many smart investment professionals seem like dumb money when compared to their competition.  In this environment, individual investors have little chance as stock pickers.  In the third edition of The Intelligent Investor, Jason Zweig wrote

“Millions of investors spend their entire lives fooling themselves: taking risks they don’t understand, chasing the phantoms of past performance, selling their winning assets too soon, holding their losers too long, paying outlandish fees in pursuit of the unobtainable, bragging about beating the market without even measuring their returns.”

Markets have changed dramatically over the past century.  Simple methods of beating markets stopped working decades ago.  There may be some brilliant investors, such as Warren Buffett, who can still beat markets, but most investors actively investing their own money are just fooling themselves.  We could make the case that if Graham were around today, he might be a passive index investor.

Passive Investing Exists

Many people like to say that passive investing doesn’t exist.  However, these people make a living from active forms of investing and are just playing semantic games to distract us.  Active fund managers and advisors who recommend active strategies are the main people I see claiming that passive investing doesn’t exist, but what they say isn’t true.

There is a continuum between passive and active investing; they are not absolute properties.  We can reasonably call an investment approach passive even if it involves some decisions, just as we can call a person thin even if their weight isn’t zero.  We may disagree on the exact threshold between passive and active investing, but the concept of passive investing still has meaning.

By “passive investing,” most people mean some form of broadly-diversified index investing with minimal trading.  Although passive investing usually requires substantially less work than active investing, passive investors still have decisions to make.  They need to choose an asset allocation, funds, accumulation strategy, rebalancing strategy, decumulation strategy, etc.  The term “passive” comes from the fact that there is no need for day-to-day or even week-to-week decisions.  It’s possible for passive investment to run on autopilot for a year without adjustment.  In contrast, more active strategies need closer attention.

The rise of passive investing is a threat to active fund management.  Even factor-based investing that leans toward the passive end of the continuum is threatened by more passive forms of investing.  It’s hard to argue against the success of broadly-diversified index investing with minimal trading.  So, rather than trying to argue in favour of more active strategies, it’s easier to meander into a pointless discussion about how passive investing doesn’t really exist.

“Why should I pay your high fees instead of just owning a passive index fund?”  Active fund managers have a very hard time with this question.  A few meet it head on, but most can’t.  Advisors could launch into a discussion of the value of their services beyond portfolio construction, but some find it easier to launch into “well, you know, passive investing doesn’t really exist, because …”.

We could flip the argument against the existence of passive investing to prove that active investing doesn’t exist.  You’re idle for at least part of your day, so no investment strategy is purely active, and all we have is degrees of passive investing.  More absurdly, there is no pure form of red, so all we have is degrees of blue.  We need to see this claim that passive investing doesn’t exist for the distraction it is.

There is nothing wrong with explaining that even passive investors have to make important decisions.  However, phrased this way, active fund managers would have to explain why their products and services help investors make these important decisions.  It’s easier to deny the existence of passive investing and conclude “you see, there’s not much difference between the investment approach you want and what I offer.”  In reality, there are important differences that should be discussed.

Book Review: Simple but not Easy

Richard Oldfield was an investment manager for three decades, and he evaluated and appointed investment managers for a decade.  His book, Simple but not Easy: A Practitioner’s Guide to the Art of Investing, was first published in 2007, and his second edition, that I review here, came out in 2021.  The quality of the writing makes it a pleasure to read, but it comes from a time when “investing” meant stock picking, and few doubted that active investing based on star managers was the best approach.  For those who still think this way, this book offers many useful lessons, but others might see it all as advice on traveling by horse-drawn carriage.

The 2007 edition of the book is left intact with a new preface and a lengthy new afterword added for the second edition.  The new afterword provides interesting commentary on the modern investment landscape, but I still can only recommend this book to those dedicated to trying to beat the market.

Many themes in this book might have been controversial back in 2007, but seem well accepted today, at least by me: active managers are bound to make mistakes, “in aggregate, hedge funds are a con,” “leverage and illiquidity are the kiss of death,” fees drive down returns, investors need to avoid managers who are closet indexers, benchmarks are tricky, a manager’s approach can go in and out of style, forecasts are random at best, and valuations matter.

Some claims are a blast from the past.  Investors “can get almost all the diversification there is to get with a portfolio of as few as 15 stocks.”  No.  The author claims that ignorance and distance from the investing action are advantages for amateur investors.  “Investors in places remote from the City frenzy are arguably at a huge advantage.”  This idea that DIY investors can easily beat the pros used to be very popular, but it isn’t true.

The afterword written in 2021 is more interesting to me.  On bonds, “it is hard to justify using bonds as the counterweight to equities when they now yield almost nothing.”  This would have been written 3 or 4 years ago, and I certainly agreed at that time in the case of long-term bonds.

On electric cars, “there is no obvious reason why the traditional carmakers should not succeed with electric cars.”  To me, the obvious reason is engineering.  Tesla was hugely devoted to advanced engineering, to an extent that traditional car companies have had challenges matching.  U.S. car companies have covered up poor engineering with marketing for decades.  The author’s discussion of safety problems with self-driving cars left out the fact that human-driven cars kill people at a frightening rate.  We don’t need perfection to justify replacing the status quo.  Continued improvement can come later.

On the subject of the rise of passive investing, the author convincingly explains why active managers, on average, must trail passive investment returns by roughly their additional costs.  But he goes on to say “I think that it is possible to choose a group of active managers the majority of whom will outperform for the majority of the time.”  Oldfield’s own arguments make it clear that only a small minority of investors can hope to do this.

“The next ten years could … be a golden decade for active managers because the trend away from them has been too strong and is due for a large dose of reversion to the mean.”  This is just hopeful thinking from a former investment manager.  Active managers can only make up for their costs by exploiting other investors.  If the only other investors to exploit are index investors, the pickings are very slim.  Perhaps if 99% or more of investors were passive, there would be room for active managers to live off these pickings, but the proportion of investor money that is indexed is nowhere near that level yet.

This book is well written, and I would have enjoyed it back in 2007 when the first edition appeared, but now that I’m solidly in the index investing camp, I find its focus on trying to beat the market less compelling.  Investors who are still trying to beat the market with their own stock picks or who seek investment managers who can beat the market are its best target audience.

Indexing of Different Asset Classes

When it comes to stocks, index investing offers many advantages over other investment approaches.  However, these advantages don’t always carry over to other asset classes.  No investment style should be treated like a religion, indexing included.  It pays to think through the reasons for using a given approach to investing.

Stocks

Low-cost broadly-diversified index investing in stocks offers a number of advantages over other investment approaches:

1. Lower costs, including MERs, trading costs within funds, and capital gains taxes
2. Less work for the investor
3. Better diversification leading to lower volatility losses

Choosing actively-managed mutual funds or ETFs definitely has much higher costs.  For investors who just pick some actively-managed funds and stick with them, the amount of work required can be low, but more often the investor stays on the lookout for better funds, which can be a lot of work for questionable benefit.  Many actively-managed funds offer decent diversification.  Ironically, the best diversification comes from closet index funds that charge high fees for doing little.

Investors who pick their own stocks to hold for the long-term, including dividend investors, do well on costs, but typically put in a lot of work and fail to diversify sufficiently.  Those who trade stocks actively on their own tend to suffer from trading losses and poor diversification, and they put in a lot of effort for their poor results.  Things get worse with options.

Despite the advantages of pure index investing in stocks, I make two exceptions.  The first is that I own one ETF of U.S. small value stocks (Vanguard’s VBR) because of the history of small value stocks outperforming market averages.  If this works out poorly for me, it will be because of slightly higher costs and slightly poorer diversification.

One might ask why I don’t make exceptions for other factors shown to have produced excess returns in the past.  The reason is that I have little confidence that they will outperform in the future by enough to cover the higher costs of investing in them.  Popularity tends to drive down future returns.  The same may happen to small value stocks, but they seemed to me to offer enough promise to take the chance.

The second exception I make to pure index investing in stocks is that I tilt slowly toward bonds as the CAPE10 of the world’s stocks grows above 25.  I think of this as easing up on stocks because they have risen substantially, and I have less need to take as much risk to meet my goals.  It also reduces my portfolio’s risk at a time when the odds of a substantial stock market crash are elevated.  But the fact that I think of this measure in terms of risk control doesn’t change the fact that I’m engaged in a modest amount of market timing.

At the CAPE10 peak in late 2021, my allocation to bonds was 7 percentage points higher than it would have been if the CAPE10 had been below 25.  This might seem like a small change, but the shift of dollars from high-flying stocks to bonds got magnified when combined with my normal portfolio rebalancing.

Another thing I do as the CAPE10 of the world’s stocks exceeds 20 is to lower my future return expectations, but this doesn’t include any additional portfolio adjustments.

Bonds

It is easy to treat all bonds as a single asset class and invest in an index of all available bonds, perhaps limited to a particular country.  However, I don’t see bonds this way.  I see corporate bonds as a separate asset class from government bonds, because corporate bonds have the possibility of default.  I prefer to invest slightly more in stocks than to chase yield in corporate bonds.

I don’t know if experts can see conditions when corporate bonds are a good bet based on their risk and the additional yield they offer.  I just know that I can’t do this.  I prefer my bonds to be safe and to leave the risk to my stock holdings.

I also see long-term government bonds as a different asset class from short-term government bonds (less than 5 years).  Central banks are constantly manipulating the bond market through ramping up or down on their holdings of different durations of bonds.  This manipulation makes me uneasy about holding risky long-term bonds.

Another reason I have for avoiding long-term bonds is inflation risk.  Investment professionals are often taught that government bonds are risk-free if held to maturity.  This is only true in nominal terms.  My future financial obligations tend to grow with inflation.  Long-term government bonds look very risky to me when I consider the uncertainty of inflation over decades.  Inflation protected bonds deal with inflation risk, but this still leaves concerns about bond market manipulation by central banks.

Taking bond market manipulation together with inflation risk, I have no interest in long-term bonds.  We even had a time in 2020 when long-term Canadian bonds offered so little yield that their return to maturity was certain to be dismal.  Owning long-term bonds at that time was a bad idea, and I don’t like the odds any other time.

Once we eliminate corporate bonds and long-term government bonds, the idea of indexing doesn’t really apply.  For a given duration, all government bonds in a particular country tend to all have the same yield.  Owning an index of different durations of bonds from 0 to 5 years offers some diversification,  but I tend not to think about this much.  I buy a short-term bond ETF when it’s convenient, and just store cash in a high-interest savings account when that is convenient.

Overall, I’m not convinced that the solid thinking behind stock indexing carries over well to bond investing.  There are those who carve up stocks into sub-classes they like and don’t like, just as I have done with bonds.  However, my view of the resulting stock investing strategies, such as owning only some sub-classes or sector rotation, is that they are inferior to broad-based indexing of stocks.  I don’t see broad-based indexing of bonds the same way.

Real estate

Owning Real-Estate Investment Trusts (REITs) is certainly less risky than owning a property or two.  I’ve chosen to avoid additional real estate investments beyond the house I live in and whatever is held by the companies in my ETFs.  So, I can’t say I know much about REITs.  

However, I don’t think the advantages of indexing that exist with stocks automatically carry over to real estate without checking the details.  Someone would have to examine REITs to see if they can play a positive role in investor portfolios.  Do REITs have hidden costs?  Are other market participants able to exploit REITs when trading properties?  What are the costs of managing passively-owned properties?  Perhaps someone has examined these questions in sufficient detail, but I haven’t seen the analysis.

Some of these problems apply to stock indexing as well.  For example, there are circumstances where traders can exploit the way that index funds respond to changes in the list of stocks making up indexes.  However, major index ETF providers have responded with changes to how they do business that reduce such costs to low levels.  I don’t know if REITs are able to do the same.

Commodities, Hedge Funds, Venture Capital, Collectibles, Cryptocurrencies, other Alternatives

Any time I look at index-style investing in other asset classes, I find more questions than answers.  What answers I do find often keep me away from these asset classes rather than draw me in.  It would take a lot to convince me to make any of these asset classes part of my own portfolio.

Conclusion

I’ll never claim that how I invest is the best way.  I seek reasonable long-term results with a reasonable amount of protection against extreme events, such as stocks market crashes, high inflation, or outright corruption.  In some cases, I stay away from asset classes for well thought out reasons, and in other cases, I stay away out of my own ignorance.  I’m good with that.

Book Review: The Canadian’s Guide to Investing

Authors Tony Martin and Eric Tyson have updated their book, The Canadian’s Guide to Investing, but it certainly does not seem very up-to-date.  Despite a few references to ETFs and some updated examples, most of the text seems decades old and no longer very relevant.  There are some good parts, but there are better choices for investment books.

The book makes reference to many things that used to be true.  Extensive discussion about “funds” is almost exclusively about mutual funds with little about ETFs.  Buying stocks is “costly unless you buy reasonable chunks (100 shares or so) of each stock.”  You can “call the fund company’s toll-free number” and invest by “mailing in a cheque.”  “A great deal of emphasis is placed on who manages a specific fund” – this is mostly a thing of the past.  “Invest in a handful of funds (five to ten).”  There is discussion of real estate “declines in the late 2000s.”

There are repeated references to MERs of 0.5% to 1.5% as being “low.”  Even the ETF discussion on this point says index ETFs “typically have MERs of less than 1 percent.”  I suppose 0.05% is less than 1%.

The authors advise people to avoid limit orders and use market orders when you intend to hold for the long haul.  They seem to consider limit orders as being only for trying to get equities for cheaper than the current ask price.  A good use of limit orders is to offer a price higher than the current ask price (or lower than the current bid price when selling).  This will usually give you the market price, but will prevent the trade from executing if markets move quickly against you just as you’re entering the trade.

The book advises people to rely on credit-rating agencies for bonds, which is interesting in light of the abject ratings failures leading up to the great financial crisis.

On asset allocation, “playing it safe” is to use your age as a bond percentage, “middle of the road” is age minus 10, and “aggressive” is age minus 20.  They go on to break down the stock allocation characterizing owning mostly Canadian stocks as “play-it-safe,” and having half your stock allocation outside of Canada as “aggressive.”  I don’t see anything safe about avoiding U.S. and international stocks.

The authors tell investors “who enjoy the challenge of trying to pick the better [fund] managers and want the potential to earn better than market level returns, don’t use index funds at all.”  Chasing star fund managers is an old and losing game.

At one point, the authors promise to help investors in “spotting a greatly overpriced” market so you can “invest new money elsewhere.”  It turns out that this method uses price-earnings ratios.  Shiller’s CAPE10 measure of U.S. stock market price-earnings has been above 20 since 2010, a period where U.S. stocks have grown by a factor of nearly 6 (including dividends).  This is not a good period to have skipped.

On the positive side, the authors advise against buying expensive cars: “set your sights lower and buy a good used car that you can afford.”  When it comes to index investing, “you can largely ignore the NASDAQ.”  “To find a home that meets your various desires,” taking “six months to a year [to find the right house and neighbourhood] isn’t unusual or slow.”  “Begin your search without [a real estate] agent to avoid … outside pressure.”

The authors have some interesting takes.  “One of the best tactics is to focus only on [retirement saving and paying off your mortgage] and ignore [saving for university or college]” until later.  They also offer extensive advice concerning owning a small business and determining if readers are suited to it.

The authors would need to put extensive work into this book to bring it up to date.  As it is, I can’t recommend it to others.

Tax Rates on RRSP Contributions and Withdrawals

Recent Rational Reminder podcasts (319 and 321) have had a debate about tax rates on RRSP contributions and withdrawals.  Most people agree that when you contribute, you’re lowering your taxes at your marginal tax rate.  The debate concerns withdrawals.  Some say that RRSP withdrawals come at your “average, or effective tax rates, not your marginal tax rate.”  Here, I address this question.

With Canada’s progressive tax system, the first part of your income isn’t taxed at all (or is taxed negatively when you consider income-tested government benefits), then the next part of your income is lightly taxed, and marginal tax rates increase from there as your income rises.

A question that comes up in my own portfolio accumulation and decumulation planning is what order to stack income each year.  Is it CPP and OAS that are taxed lightly and RRSP withdrawals taxed more, or should I stack the income in some other order?  What about other income from non-registered savings?  Maybe everything should be assigned the same average tax rate.

The truth is that this is only a struggle because we’re trying to assign tax rates to one strategy in isolation.  Whether a strategy is good or not cannot be decided in isolation.  It only makes sense to compare two or more strategies.  When we compare strategies, it becomes obvious how to handle tax rates.

Let’s try to create two strategies that isolate the RRSP as the only difference.  Strategy 1: no RRSP.  This strategy might include TFSA contributions or other elements, but it does not use RRSPs.  Strategy 2: everything from strategy 1 plus RRSP contributions while working, and RRSP withdrawals after retiring.

Comparing the two strategies during working years, we should think of RRSP deductions as coming off the highest part of the total income because that is the difference between the two strategies.  If we apply the deduction somewhere in the bottom or middle of the income range, then the other income (that is the same in both strategies) will be taxed differently in the two strategies.  We want to find the net difference between strategies, and that comes from treating the RRSP deduction as coming at the marginal tax rate.

During retirement years, we end up with a similar argument.  Both strategies will have the same income each year, except that Strategy 2 will have additional RRSP withdrawal income.  To isolate the differences in income and taxes between the two strategies, we must think of the RRSP withdrawal as being the last, most highly taxed part of the income.  So, it’s taxed at the marginal rate.

At this point, we should comment on what we mean by marginal rate.  It is usually defined as the tax rate on the last dollar earned.  However, we usually aren’t discussing amounts as trivial as a single dollar.  Larger amounts can easily span multiple marginal tax brackets.  So, it’s possible for your RRSP deduction to give part of its tax savings at one rate and part at a lower rate.  

So, when we say that RRSP contribution tax savings occur at your marginal rate, this might actually be a blended rate, not to be confused with your overall average tax rate.  For example your marginal tax rate might be 43%, your tax savings rate on RRSP contributions might be partly 43% and partly 38% for a blended rate of 40%, and your average tax rate might be 25%.

This effect becomes larger for RRSP withdrawals, because the withdrawals tend to be larger than the contributions.  If your income consists of CPP, OAS, and RRSP withdrawals, your RRSP withdrawals may be the bulk of your income and may span multiple marginal tax brackets.  So, even though we say you pay tax on the RRSP withdrawals at your marginal tax rate, this is actually a blended rate that may not be too much higher than your average tax rate.

So, when comparing the strategies that differ only in RRSP contributions and withdrawals, the argument that RRSP withdrawals come at your average tax rate might be sort of true in the sense that they will likely be at a blended rate, but we get the correct answer when we think of RRSP deductions and income as coming at the top of your income.  We can only answer such questions properly when comparing two or more accumulation and decumulation strategies rather than analyzing one strategy in isolation.

Picking Up Nickels in Front of a Steamroller

Suppose a casino offered the following bet.  You roll six fair dice.  If anything but all sixes shows up, you get $20.  But if all sixes show up, you lose a million dollars.  There are a number of practical problems with this game.  The casino would demand a million dollar deposit in advance, and the odds are way too sensitive to imperfections in the dice and to player skill at not throwing sixes.  But this is a thought experiment designed to shed light on real world financial events.

Initially, few people would play this game, because losing a million dollars is too scary.  But if you watched someone playing, even all day, you’d likely never see a loss.  You’d just see the player collecting $20 every 10 seconds or so building up to many thousands of dollars.  The fear of missing out (FOMO) would set in for some and tempt them to play.

Over the long haul, the casino expects to pay out $933,120 for every million dollars it wins.  So playing this game is good for the casino but a bad idea for the player.  However, it’s easy to forget about the losses if you only see everyone winning $20 every play.  Games like this are referred to as “picking up nickels in front of a steamroller.”  The $20 payoffs are the nickels, and the million-dollar losses are when you get flattened by the steamroller.

The yen carry trade

So what does this have to do with real life?  There are many “games” in real life that resemble this hypothetical game more than people would like to admit.  When interest rates were much lower in Japan than they were in the U.S., it seemed profitable to borrow yen at a low interest rate, convert it to U.S. dollars, and collect high interest on U.S. dollar deposits.

This sounds quite profitable, so why did I say it only “seemed profitable”?  Well, all was well as long as interest rates and the exchange rate between yen and U.S. dollars were stable.  However, a rise in the value of the yen and higher Japanese interest rates (the steamroller) could more than wipe out any profits from the interest rate spread (the nickels).

Unlike the hypothetical dice game where the potential loss of a million dollars is prominent, it’s less obvious with the yen carry trade.  You might convince yourself that the value of the yen and Japanese interest rates would change slowly enough that you could exit your positions profitably.  However, many others would be trying to unwind their positions at the same time, each one trying to be among the first to get out.

Excessive leverage

Rather than just invest a fraction of your wages in stock markets, you could borrow extra money to invest more.  The stock markets may gyrate, but they keep rising.  If you can just wait out the gyrations, you’ll be sure to eventually make more money (the nickels) than if you didn’t borrow.

The problem is that if you borrow too much, and your creditors see that you’re in danger of becoming insolvent, they may demand their money back or impose high interest rates that eliminate your profits.  A sudden stock market crash (steamroller) could wipe you out before you get a chance to wait out the market decline.  Modest leverage can be reasonable, but it takes some skill to determine how much you can borrow safely.

The great financial crisis

Many Wall Street firms made apparent profits selling insurance against mortgage defaults in the form of exotic financial instruments like credit default swaps (CDSs) and collateralized debt obligations (CDOs).  In this case, the nickels were the insurance premiums they collected, and the steamroller was the wave of mortgage defaults across the U.S.

It’s tempting to say that everyone involved was naive or incompetent, but employees of a firm have different interests than the firm itself does.  While the party was ongoing, the apparent profits piled up, and employees collected their share in the form of huge bonuses.  When the steamroller crushed their firms, these employees didn’t have to return their bonuses.  It was like playing the dice game with someone else’s money.  The employees would take a cut of each $20 win, and let others deal with the million dollar loss.

Long-Term Capital Management

The LTCM hedge fund employed Nobel Prize winners to beat the markets, and it seemed to work for a few years.  They used complex models of how markets work to squeeze out profits (the nickels).  Unfortunately for them and their investors, markets eventually stopped working the way the models expected (the steamroller) for long enough to wipe out past profits.

Conclusion

There are many financial schemes in the real world that resemble picking up visible nickels in front of an obscured steamroller.  If you think you've found a way to beat the markets, try to figure out where the steamroller is.

More on My Tesla Model 3 Experience After 5 Years

My post describing my experience with the dual-motor long-range Tesla Model 3 I bought back in April 2019 generated further questions about battery life, recalls, and driving range in winter that I answer here.

Battery life

Recently, I was in a waiting room and couldn’t help overhearing a conversation about electric vehicles.  The two people agreed they wouldn’t consider owning one, and the dominant stated reason was fear of high-cost battery replacements.  It became clear after a while that they mistakenly believed EV batteries would have to be replaced as often as lead-acid batteries in gas cars.  The truth is that Tesla batteries are expected to last longer than the rest of the car.

A few days ago, I was startled to receive a notification on my phone that my car’s battery needed to be replaced.  A few seconds of poking around on the Tesla app eased my worries.  I didn’t realize that my car has a lead-acid battery as well as its large high-tech battery.  So, $164 later, my lead-acid battery has been replaced.  The main battery powering my car is still fine.

Recalls

Tesla has been in the news frequently for having “recalls” of their cars.  This brings to mind images of millions of cars lined up at service stations, but that’s not what’s going on.  Almost all of these recall changes are just folded into the next software update.

Tesla pushes out software updates to cars every month or so.  They mostly contain improvements they’ve made.  Sometimes, they include things regulators want.  In one case, the font size on a warning message was made larger.  Quite the recall.

The only substantive recall item I can remember was something to do with cabling near my trunk.  When I was having a camera realigned for US$34, the technician improved the cabling at no extra charge.

Driving range in winter

Electric vehicle batteries have an optimum temperature.  Heating or cooling them draws battery power, and operating the batteries outside their optimum temperature range is less efficient.  There is nothing the driver has to do about this; the car handles it all itself.  However, the net result is that the car’s range is lower in winter than it is during other seasons.  

The difference in range has been noticeable, but not a problem for me.  One time that I looked at some numbers, the difference in range between a summer day and a below-freezing winter day was close to 15%, but I can’t say whether this is typical.  I suspect the difference depends on how cold it gets and the make of electric car.  To be fair, gas cars burn more gas in winter as well.

Conclusion

My conclusion remains the same: I love my Tesla Model 3’s quiet power and its well-designed features that get improved regularly through software updates.  Most of what I see online about EVs is overblown or doesn’t apply to Teslas.  My car is very cheap to run, but the purchase price was high.  It’s been the best car I’ve owned, but until they become cheaper, I can only recommend them to those who can reasonably afford a luxury car.

Retirement Income for Life (Third Edition)

Actuary Frederick Vettese has a third edition of his excellent book, Retirement Income for Life: Getting More Without Saving More.  He explains methods of making your retirement savings produce more income over your entire retirement.  These methods include controlling investment fees, optimizing the timing of starting CPP and OAS pensions, annuities, Vettese’s free Personal Enhanced Retirement Calculator (PERC), and using reverse mortgages as a backstop if savings run out.

This third edition adds new material about how to deal with higher inflation, CPP expansion, new investment products as potential replacements for annuities, and improvements to Vettese’s retirement calculator PERC.  Rather than repeat material from my review of the second edition, I will focus on specific areas that drew my attention.

Inflation

“We can no longer take low inflation for granted.”  “An annuity does nothing to lessen inflation risk, which should be a greater worry than it was before the pandemic.”  “We could have practically ignored inflation risk before COVID hit but certainly not now.”

It’s true that inflation is a potential concern for the future, but it’s wrong to say that it was okay to ignore inflation in the past.  Not considering the possibility of inflation rising was a mistake many people made in the past.  We were lulled by many years of low inflation into being unprepared for its rise starting in 2021, just as many years of safety in bonds left us unprepared for the battering of long-term bonds when interest rates rose sharply.

Inflation risk is always present, and financial planners who have treated it as a fixed constant were making a mistake before inflation rose, just as they would be wrong to do so now.  This underappreciation of inflation risk is what causes people to say that standard long-term bonds (with no inflation protection) are safe to hold to maturity.  In fact, they are risky because of inflation uncertainty.

People’s future spending obligations are mostly linked to real prices that rise with inflation, not fixed nominal amounts.  The uncertainty in future inflation should be respected just as we respect uncertainty in stock market returns.

Maximizing retirement income

Vettese does a good job of explaining that things like CPP, OAS, and annuities provide more income now because they offer your estate little or nothing after you die.  To make full use of this book, you need to understand this fact, and “you have to commit to the idea that your main objectives are to maximize your retirement income and ensure it lasts a lifetime.”

Spending shocks

Retirees should “set aside somewhere between 3 percent and 5 percent of their spendable income each year, specifically to deal with spending shocks.”  “This reserve might not totally cover all the shocks that people … might encounter, but it will definitely soften their impact.”

It’s easy to plug a smooth future spending pattern into a spreadsheet, but real life is much messier than this.  I’ve seen cases of retirees choosing to spend some safe percentage from their savings while also expecting to be able to dip in anytime something big and unplanned for comes up.  This is a formula for running out of retirement savings early.

Retirement income targets

In this third edition, Vettese assumes that retiree spending will rise with inflation until age 70, then rise one percentage point below inflation during one’s 70s, two percentage points below inflation from age 80 to 84, then 1.8% below at 85, 1.6% below at 86, 1.4% below at 87, 1.2% below at 88, 1% below at 89, and rising with inflation again thereafter.

This plan is based on several academic studies of how retirees spend.  I don’t doubt the results from these studies, but I do have a problem with basing my plan exclusively on the average of what other people do.  The average Canadian smokes two cigarettes a day.  Does that mean I should too?

The academic studies mix together results from retirees who spent sensibly with those who overspent early and were forced to cut back.  I don’t want to base my retirement plan partially on the actions of retirees who made poor choices.  Similarly, I prefer to base my smoking behaviour on those Canadians who don’t smoke.

I suspect that Vettese has already tried to take this into account with his assumed retiree spending reductions, because some studies I’ve read show retiree spending declining earlier than Vettese’s plan.  It’s hard to know what would happen to study results if we excluded early overspenders, but I suspect that spending declines would tend to start later and be less severe than Vettese’s plan.

Part of the reason I believe this comes from the fact that societal spending actually rises faster than inflation; it tends to rise with wage inflation rather than regular (price) inflation.  Wage inflation has averaged about 0.75 percentage points more annually than price inflation.  So, even if your retirement plan assumes your spending will rise with price inflation, your spending will decline relative to your younger neighbours.

In fairness to Vettese, though, his free tool PERC embeds other assumptions that are conservative, so the fact that I find this assumption somewhat aggressive doesn’t diminish the usefulness of PERC.

Monte Carlo simulations

“Monte Carlo simulations might be good at modelling investment returns between the 5th percentile and the 95th percentile, but when you go deeper into the tails of the distribution, it is a different matter.”

This is a good point.  When a simulator says your retirement plan gives you a 97% chance that you won’t run out of money before you die, it sounds wonderfully scientific, but it’s just marketing.  Black swan events make it impossible to make such assessments accurately.  Models of investment returns are never completely accurate, and the further we go toward lower probability outcomes, the worse these models are.

CPP survivor pension

The rules for calculating a surviving spouse’s additional CPP payments after the other spouse dies are quite complex.  Vettese explains them well, except that I think one part is inaccurate, as I explained in detail in an earlier post.  

At one point, Vettese calculates a quantity C that is the difference between the deceased spouse’s basic retirement pension and the surviving spouse’s basic retirement pension.  Information I’ve seen elsewhere says that this should really be the difference between the maximum basic retirement pension and the surviving spouse’s basic retirement pension.

In an example for a couple Susan and Nick, after Nick’s death, “Susan’s CPP pension would be increased to the maximum CPP pension payable to any one individual.”  This is because CPP rules don’t permit Susan’s total CPP to exceed this CPP maximum.  However, my understanding is that this applies to the case where Susan’s CPP pension was started at age 65.  If Susan had started CPP at 70, her own pension would still be 42% higher, and when the survivor pension is added , her total CPP pension would exceed what we think of as the maximum CPP pension.  Similarly, if she had started her CPP at 60, her total pension would be less than what we think of as the maximum CPP pension.

OAS

If you’ve lived at least 40 years in Canada between the ages of 18 and 65, you’re entitled to a full OAS pension (that may be clawed back if your income is high).  However, if you haven’t been in Canada for that long as an adult (but for at least 10 years), your OAS pension “will be reduced in proportion to the number of years of residency … between ages 18 and 65.”

If you delay taking OAS until somewhere between age 65 and 70, the extra years can be used to either increase your years of residency closer to 40, “or to adjust [your] pension upward by 7.2 percent for each year beyond age 65,” but not both.

Deferring CPP

The best reasons for not deferring CPP to age 70 are that either you don’t have enough savings to bridge the retirement gap before age 70, or that your health is severely compromised making an early death certain.  Beyond that, Vettese explains why most other reasons people give are irrational or invalid.

“Deferring CPP pension to age 70 forces you to draw down your [assets] more quickly before age 70, but those same assets last longer because the CPP pension from age 70 and on is so much bigger.”

This is an important point that I find people have a hard time understanding.  They imagine having to spend down their assets, and then imagine a bleak future.  In reality, they will have higher guaranteed CPP income that will insulate them somewhat from stock market gyrations, and their assets will ultimately last longer.

Most of the book’s analyses are based on getting below median investment returns.  In one chapter where Vettese looks at what happens if investment returns are at the median, he concludes that deferring CPP to age 70 “makes eminent sense whether future returns are poor or middle-of-the-road.”

Reverse mortgages

“With a reverse mortgage, you do not have to make any payments while you or your spouse continue to live in the home.  And you cannot be forced to move out.  You do have to maintain the home, however, including paying property taxes and home insurance premiums on a regular basis.”

This is self-contradictory.  You can be forced to move out if you don’t maintain your home or fail to pay property taxes and insurance premiums.  We tend to think of home maintenance as an annoyance, but something we can handle.  However, I’ve known several old people who simply couldn’t maintain a home properly.  Many old people rely on neighbours and family for help with basic maintenance, and many others simply fail to maintain their homes properly.

We are still in the early stages of Canadians taking on reverse mortgages.  Financial institutions are unlikely to deliberately generate bad press while they are trying to make sales.  But in a decade or two, when they have many clients who owe as much as their homes are worth after the cost of selling, the mood will change.  Financial institutions will be incented to force old people out of their homes if the homes are run down.

PERC built-in assumptions

Vettese explains the assumptions built into his free PERC tool, including that “the primary spouse (the one entering the data) is assumed to die at 90 and the surviving spouse at 93.”  However, in an earlier example, “Graham dies at age 85, the default assumption that is built into PERC.”  I’m not sure if this is an error, or if these are somehow built-in assumptions for different types of cases.

For anyone who finds assuming death at 90 or early 90s not to be conservative enough, PERC also assumes that you want to be left with 10% of your assets remaining at this age, which is on the conservative side.  So, depending on what different assumptions the reader might make, these differences might balance out somewhat.

Another thing to keep in mind is that PERC displays income in pre-tax amounts.  I’ve always done my own planning with after-tax amounts, so it takes some work to compare my outputs with those of PERC.

Decumulation strategy

“Retirees are generally better off drawing down assets from multiple sources on an annual basis (in proportion to how much they have of each asset) rather than drawing down taxable assets first and trying to keep their tax-sheltered assets intact for as long as possible.”

This agrees with my own simulations.  However, I’ve found that it’s generally better to draw down taxable assets before drawing down a TFSA, particularly if the taxable assets don’t have large unrealized capital gains.  It’s RRSPs and RRIFs that are best drawn down gradually throughout retirement.

Financial advisors

Controlling investment costs, deferring CPP and OAS, buying annuities, and even planning to rely on a reverse mortgage all cut into financial advisor compensation.  “I know a growing number of financial planners out there who do accept the ideas in this book,” but Vettese also has stories of advisors whose recommendations help themselves rather than their clients.

Conclusion

This is an excellent book about the complex task of decumulating assets in retirement.  The tone of this review may seem negative, but this is because I included every case where I disagreed with the author.  I highly recommend this book to anyone who is either retired or close enough that they need to consider how to create an income from their savings.

Tesla Model 3 Experience After 5 Years

Back in April 2019, I bought a dual-motor long-range Tesla Model 3.  I had some concerns about buying an electric car, but my research showed that none of these concerns were likely to be real problems.  Still, buying the car felt like a leap of faith.  Now that I’ve had it for 5 years and 4 months, I can say that it’s been the best car I’ve owned, even better than my Lexus GS400.

Some concerns I had before I bought the car were its price, the charging network when traveling, home charging, battery reliability, self-driving features, and ongoing costs.  Something I didn’t know about in advance that turned out to be a pleasant surprise is the one-pedal driving.  A negative about owning this car is that somehow EVs have become political.

Price

Compared to other luxury cars, Teslas are reasonably priced.  However, there is no lower end Tesla model suitable for the bulk of car owners.  Teslas are still too expensive for most people.  The lower annual cost of running a Tesla compared to gas cars helps to mitigate this problem somewhat, but isn’t enough to solve it.

Charging network

There is a huge difference between the Tesla and non-Tesla charging networks.  Tesla completed full coverage of the continental U.S. and Canada with chargers a few years before I bought my car.  I’ve never had trouble finding a charger when I needed one.  They’re generally very close to major roads and highways.  About 95% of the time, when I arrive at a charging station, there is a working charger available for me.  The other 5% of the time when the chargers have been busy, I’ve only had to wait 5 or 10 minutes to start charging.

The non-Tesla charging network is a different story.  While much of what you see on social media about EVs is nonsense, the problems with the non-Tesla charging network is real.  Quebec is a notable exception where they’ve gone to a lot of trouble to build a decent network.

When traveling, it’s common to charge from about 20% of battery capacity to about 80%.  Just as with a gas car, you generally don’t run your car to empty.  However, stopping a “fillup” at 80% of battery capacity is different from how we run gas cars.  The reason is that the charging rate slows down a lot as you get nearer full charge.  So, it’s faster to charge up a little more often than it is to charge to the top each time.

On average on long trips, I charge for about 20 minutes every 3 hours.  It was a little slower 5 years ago, but newer Tesla superchargers are faster.  Superchargers are nowhere near as plentiful as gas stations, but my car tells me when to stop and it directs me to the chargers.  

My wife and I are getting older, and we need the 20 minute stops to stretch our legs and find a bathroom.  Extending what would have been a 10-hour trip with a gas car to 11 hours with our EV has been good for our mental and physical well-being.  Others may feel differently.

Home charging

A fact that some people have a hard time wrapping their minds around is that people whose homes have garages hardly ever have to use the charging network.  I had a 220V, 48A charger installed in my garage.  I just leave the car plugged in whenever I’m home, and the car’s fancy software figures out the best way to charge up and stop charging when no more range is needed.

My charger can add about 60 km of range for each hour it’s plugged in, but I rarely notice.  Just as you don’t stand there watching your washing machine spin, there’s no need to watch a car charge.  Each day I wake up to a topped up car.

It’s possible to charge my car with a regular 110V outlet.  At 12A, an hour of charging adds about 7 km of range.  This isn’t much, but plugged in for 10 hours overnight when visiting friends out of town adds about 70 km.  When away from home, I’m often able to stay sufficiently charged for day trips using just a regular 110V outlet.  On a 5-month stay at a rental home in Florida, I only needed superchargers 3 times other than for the long drives between Canada and Florida.

Battery reliability

There’s no question that it would be expensive to replace the batteries in my car, just as replacing a gas car’s engine is expensive.  Fortunately, batteries don’t tend to suddenly fail.  They degrade.  My experience seems to be fairly typical: my range has declined from 500 km to 460 km, or about 8% in a little over 5 years.

This loss of range was faster initially, and is about one percentage point per year now.  If this persists for another 10 years, I can look forward to a 15-year old car that still has a range of 410 km, which is more than usable.  It might work out better or worse than this projection, but the odds are that this car will be scrapped for some other reason before the battery gives out.

Self-driving features

My car can drive itself in most situations with the latest software upgrades, but the truth is that I generally only use these features on highways for now.  Having the car drive itself for long highway stretches greatly reduces mental strain, particularly in the dark.  A day of driving used to leave me wrecked, but not any more.

For short distances I don’t feel the need to use the car’s self-driving features.  When I control the car myself, the safety features are still enabled.  A couple of times now when I’ve needed to make a sudden stop, and the car began braking before I could get my foot to the brake.

The most important features to me are the safety features, keeping the car in its lane, and adaptive cruise control.  Many other EVs and gas cars have these features as well.  Talking to owners of other cars, Tesla’s technology appears to be better, but perhaps there are cars I have no information about that have good self-driving features.

Ongoing Costs

My Tesla has never had or needed regular service.  All my gas cars have needed oil changes and other fluid top-ups a couple of times per year.  Even my brakes last longer because my car usually slows down using regenerative braking.  My brakes haven’t needed any repairs so far.

Apart from replacing tires once and swapping summer and winter tires, the only maintenance I’ve done is new cabin air filters for C$67, a camera realignment for US$34, and windshield washer fluid.  I don’t get charged anything extra for the software updates my car gets every month or so.

However, the big savings come from the low cost of charging vs. the cost of gas.  My car has averaged 0.185 kWh per km driven.  At the 13 cents per kWh I pay on my hydro bill, this works out to only 2.4 cents/km.  Tesla charges double to triple this amount at their superchargers, but I don’t use them enough to make much difference to my overall costs, and supercharging costs still end up being cheaper than gas.  Some hotels offer free EV charging which saves some money on long trips.

If my Model 3 were a gas car, Tesla says that it would get about 30 MPG, or about 7.8L/100km.  I’m guessing that a comparable 350 horsepower gas car would use premium gas.  The current Costco premium gas price in my area is 174.9 cents/L, and my car as a gas car would cost 13.6 cents/km to run.  So, I save 13.6 ‒ 2.4 = 11.2 cents/km.  For the 85,000 km I’ve driven so far, I’ve saved about $9500.

One-pedal driving

I didn’t know about one-pedal driving before I bought my Model 3.  When you ease up on the accelerator, it doesn’t just coast the way a gas car does; the car does some regenerative braking.  So, for most driving, including cornering, you just need to use the accelerator to speed up and slow down.  I only need the brake pedal for panic stops and coming to a final stop after slowing down to about 10 km/h.

It took a few days to get used to one-pedal driving, but now I really like it.  Whenever I drive someone else’s car, I find the going back and forth between pedals annoying.

Politics

Most people seem to find Teslas interesting, and they have questions.  However, a minority react negatively to my car for political or ideological reasons.  This isn’t a problem when it’s just words, but I occasionally get other vehicles doing stupid and dangerous things around me.  Fortunately, this has declined a lot since the first year or so I had the car.

Other people react negatively because they see it as a show off car, like a BMW.  It may be that some others buy Teslas for these reasons, but I don’t even wash mine.  I’ve never seen the point of washing cars.  I tend to think more about practical matters.

Conclusion

I love my Tesla Model 3’s quiet power and its well-designed features that get improved regularly through software updates.  It’s very cheap to run, but the purchase price was high.  Overall, it’s been the best car I’ve owned, but until they become cheaper, I can only recommend them to those who can reasonably afford a luxury car.

Tightwads and Spendthrifts

In his book Tightwads and Spendthrifts, marketing professor Scott Rick promises advice for “financial aspects of intimate relationships.”  What got my attention early is that his guidance “is rooted in rigorous behavioral science.”  Applying the scientific method to human interactions is challenging, but it is generally better than relying on opinions.  The book gives useful insights into how people think about spending money.

The introduction gives a four-question quiz designed to place the reader on a scale from 4 to 26.  Those at the low end of the scale are called tightwads, and those at the other end are spendthrifts.  Roughly half the respondents fell in the middle third of the range and are called “unconflicted consumers.”  Most of the book deals with tightwads, spendthrifts, and their interactions; little is said about unconflicted consumers.

Demographic differences

Extensive surveys revealed some interesting demographic differences between tightwads and spendthrifts. “Tightwads are slightly older than spendthrifts,” but it’s not clear why.  Do people become tighter with money over time (perhaps from getting burned by debt), or are there differences between generations?

“Women were somewhat more likely than men to be spendthrifts, and somewhat less likely than men to be tightwads.  Tightwads were somewhat more likely to be highly educated, and they tended to opt into more mathematical majors, such as engineering, computer science, and natural science.  The most popular college majors among spendthrifts were social work, communication, and humanities.”

How tightwads think

Being a tightwad is not the same as being frugal; “the highly frugal love to save, and tightwads hate to spend.”  “The highly frugal are generally much more at peace in their relationship with money than are tightwads.”

It might seem intuitive that people are the way they are because of how much income they have available to spend, but “in survey after survey, we find no income differences between tightwads and spendthrifts.”  However, “tightwads have far more money in savings and significantly better credit scores than spendthrifts.”

Having higher savings “offers no guarantee that tightwads feel financially comfortable.  Subjective feelings of financial well-being are only loosely related to objective aspects of financial well-being.”  For many tightwads, financial “anxiety stems from economic conditions early in life.”

Tightwads tend to think in terms of opportunity costs when considering spending some money.  In one experiment where some participants had opportunity costs highlighted to them and others didn’t, “spendthrifts were twice as likely to buy the cheaper option” when opportunity costs were highlighted.  “This framing did not influence tightwads.”

While tightwads spend less than spendthrifts in almost every area, “the amount of money both types had donated to charity was the same.”

How spendthrifts think

“Spendthrifts report high susceptibility to shopping momentum and what-the-hell effects.  They commonly report going to buy one thing, then getting carried away.”  “Spendthrifts are significantly more impatient than tightwads.”  Interestingly, spendthrifts tend to understand these facts about themselves, and are not surprised when they later regret their purchases.

“Spendthrifts and compulsive buyers might spend similarly on any given shopping trip, but their underlying psychology differs significantly.  Spendthrifts do not appear or report to be driven by anxiety management or mood repair.”

“Spendthrifts score slightly lower than tightwads on a financial literacy quiz.”  However, Rick says that this is not a defining difference between tightwads and spendthrifts.

Is “spendthrift” an oxymoron?

The word “spendthrift” appears to blend contradictory elements: spending and thriftiness.  However, “thrift here is used as a noun—meaning ‘savings’—as it was in the seventeenth century.  So spendthrifts are traditionally defined as people who recklessly spend their savings.”

Compensating for financial tendencies

Rick offers ways for tightwads and spendthrifts to compensate for their feelings about money.  The first is to change “payment salience.”  The book offers ways for tightwads to feel the pain of paying money less, and for spendthrifts to feel it more (e.g., by using cash more often).

Tightwads can reframe high-end purchases to think of them as a means to get high quality items.  They can add a line item for indulgences into their budgets to make spending a “to-do” item.  They can also reexamine their finances to confirm that all is well and, hopefully, reduce financial anxiety.

Spendthrifts can be mindful of opportunity costs, try to delay spending (e.g., sleep on it), and set saving reminders for themselves.  Interestingly, spendthrifts might understand “better than tightwads” that “the excitement that comes with a new product usually fades over time,” but this knowledge doesn’t appear to help them reduce spending.

Relationships

When we consider marriages among tightwads and spendthrifts, but not including any “unconflicted consumers,” 58% are between a tightwad and a spendthrift, and only 42% are between two people at the same end of the tightwad-spendthrift scale.  “We tend to marry people who share characteristics that we like in ourselves.  However, a key insight about tightwads and spendthrifts is that they do not particularly enjoy being tightwads and spendthrifts.”

Although some prominent people who advise their followers on personal finance topics consider any money secrets between spouses to be “financial infidelity,” Rick thinks there is room for a small amount of secrecy as long as it’s not the cause of financial shortfalls.  How much secrecy is desirable or tolerable probably varies from one couple to the next.

“Latte factor myth”

Rick adds his two cents to the endless debate on whether we should engage in small indulgences by siding with those who say it’s fine to buy expensive coffee.  Like most others, Rick approaches this debate as a binary choice: lattes are either universally good or universally bad.

This is nonsense.  Each person needs to make a decision about small indulgences.  If your latte habit costs $1000 per year, then either they’re worth that much to you or they’re not.  If they’re worth that much to you, then buy lattes all year without guilt.  If they’re not, then stop buying them.  The main thing is to understand the monthly or annual cost of indulgences before making a decision.

I’m not a coffee drinker, so lattes are out for me, but I do enjoy playing softball.  A quick estimate is that I spend about $3300 per year on gear, fees, travel, and post-game indulgences.  This amount is worth it to me, so I keep playing.  Others can make different choices based on their desires and financial circumstances.

Children

Researchers, including this book’s author, “developed a Tightwad-Spendthrift scale for children” and found that “most children were on the tightwad end of the scale.”  They found “no relationship between children’s Tightwad-Spendthrift score and their [parents’ scores].”

However, things are different with adults and their parents.  Adults’ scores are positively correlated with their parents’ scores, and “older adults look more like their parents on the Tightwad-Spendthrift dimension than do younger adults.”

For parents trying to make “family-related Spending decisions,” Rick’s advice is “when you’re debating a material purchase, usually let the tightwad [parent] win.  When you’re debating an experiential purchase, usually let the spendthrift [parent] win.”

Conclusion

This book gives interesting insights into the reasons why people spend, or don’t spend, as they do.  It has the potential to give readers useful insights into their own behaviour, and allow them to make positive changes.  It can also help readers understand the source of financial conflicts between spouses, allowing them to better solve problems.