Tag: efficient portfolio

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Roth Conversions with Optimal Withdrawals

In our posts from March and April, we discussed several aspects of Roth conversions. We showed that, if tax rates are higher in the future, Roth conversions can have a positive payoff. For tax-deferred assets, like pre-tax assets in a 401(k) or IRA, a retiree may pass some of these assets to an heir. The heir’s income tax rate determines the after-tax value of inheriting tax-deferred assets. This week’s post highlights the most recent software update made to our Optimal Retirement Income Calculator, which now includes Roth conversions and optimal withdrawals simultaneously!

How to model Roth conversions with Optimal Withdrawals

Roth conversions reduce tax-deferred assets by “converting” those assets in any year to a Roth account. Individuals performing a Roth conversion owe income taxes on the amount converted. But, the converted amount increases the individual’s Roth account assets, which a retiree can often access tax-free in retirement. One goal of generating tax-efficient retirement income is for optimal withdrawals to avoid large “spikes” in ordinary income. Our Optimal Retirement Income Calculator does this automatically and considers the tax rate of the heir under three distinct scenarios.

  1. A retiree has insufficient funds to satisfy retirement income
  2. A retiree has sufficient, but not excessive funds
  3. A retiree has excess retirement funds
Roth conversions and optimal withdrawals from Seeking Tax Alpha in Retirement Income
Source: “Seeking Tax Alpha in Retirement Income“, to appear in Financial Service Review (2023)

Excess retirement funds and the importance of your heir(s) tax rate

In scenarios 1 and 2, the top and middle portion of the image above, our calculator already finds the lowest marginal tax rate to efficiently distribute tax-deferred assets.  Consequently, our Optimal Retirement Income Calculator already provides a withdrawal strategy to utilize your tax-deferred assets efficiently. So, no additional tax-alpha is possible with a Roth conversion.  However, this is not the case in scenario 3 or the lower right portion of the image above.

When a retiree’s assets are far beyond what is needed to support their retirement income needs, many of their assets will eventually be passed to an heir. In this case, our Optimal Retirement Income Calculator previously left a significant amount of tax-deferred assets to an heir. With our latest software update, a new Roth Conversion Analysis includes converting tax-deferred assets to a Roth account “using up” the retiree’s tax brackets that are less or equal to those of the heir. For example, if your heir has an expected income tax rate of 25%, scenario 3 would perform a Roth conversion up to the 24% tax bracket. Doing so typically adds about 0.10% tax alpha. We encourage you to use our Optimal Retirement Income Calculator to evaluate possible situations for you or your clients. You can easily see if a Roth conversion with optimal withdrawals provides an additional benefit.

ETFMathGuy is a subscription-based education service for investors interested in using commission-free ETFs in efficient portfolios.
ETFMathGuy is a subscription-based education service for investors interested in tax-efficient investing with ETFs
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Backtesting for 2021 and ETFMathGuy portfolio enhancements

Due to portfolio performance not meeting our recent expectations, we revisited our backtesting results from August 2018 and produced important new insights and portfolio construction enhancements. We discovered that a longer sample period, identified previously, no longer applied. The image below shows that a three-month sample period produced the best returns from January 2020 to August 27, 2021. Each point on this line plot represents annualized backtested performance for 19 monthly portfolios over this testing period.

Backtesting for 2021 to find the optimal sample period (months) for ETFMathGuy Portfolio Construction
Backtesting for 2021 to find the optimal sample period (months) for ETFMathGuy Portfolio Construction

What performance predictions occurred with this shorter sample period?

Using this shorter sample period, we produced the plot below of total return since January of 2020. We chose this time period to include the full pre and post-term effects of the coronavirus on the world economy. In addition, and based on subscriber feedback, we now exclude ETFs that issue K-1 tax forms to investors. We made this decision because these 22 ETFs had a marginal effect on backtested performance that used over 1,000 other ETFs that do not issue K-1s. We also increased our ETF filter threshold of median volume to improve liquidity for future portfolios that will likely have a higher turnover rate. The consequences of these decisions on backtested performance appear below.

Backtested Returns from 2020-2021 of the ETFMathGuy Optimal Portfolios
Backtested Returns from 2020-2021 of the ETFMathGuy Optimal Portfolios

Future ETFMathGuy portfolios

Given the improvement potential identified from this updated backtesting for 2021, all portfolios published in September 2021 and later will follow these updated findings. This update for the September portfolios will likely indicate a significant change from the August portfolios. However, future monthly portfolios will change less significantly. So, we encourage subscribers to log in and see the September ETFMathGuy portfolios that are based on this evidence-based analysis.

ETFMathGuy is a subscription-based education service for investors interested in using commission-free ETFs in efficient portfolios.
ETFMathGuy is a subscription-based education service for investors interested in using commission-free ETFs in efficient portfolios.
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Recap of the first half of 2021

Greeting ETFMathGuy subscribers! This post is a reminder that the latest free and premium optimal portfolios are now available for your review. So, please log in and see how the latest market conditions have affected these ETF portfolios. To begin, we discuss value versus growth ETFs and recent trends in their returns.

Recent returns on value investing leveling off?

A few months ago, we wrote about how value-driven ETFs returned about 5% more in the first quarter than growth ETFs. Revisiting the returns of the ETFs IVV, VUG, and VTV for the first half of 2021 shows this gap has shrunk to 3% after growing to more than 10%. In fact, as the chart here shows, the value ETF is below its early May high, while the growth ETF appears to have begun a new upward trend.

Total returns of value and growth ETFs.
The total return of value and growth ETFs in the first half of 2021. Source: www.ETFReplay.com

Is the relationship between value and growth ETFs typical?

The relationship between two variables can be directly measured using correlation which varies between 1 and -1. So, a correlation of 1 between two investment returns indicates their returns are identical. Traditionally, the correlation between value and growth investments was around 75%. However, as this Wall Street Journal article highlights, the current correlation between growth and value is now below 25%.

Correlation between value and growth returns.
Source: Wall Street Journal, June 28, 2021, by James Mackintosh

Performance of the ETFMathGuy Premium Portfolios

Based on actual investment performance, the risk and return of the moderate and aggressive portfolios over the last 18 months appear below. Consequently, this period includes all of the calendar year 2020, and the first half of 2021.

ModerateAggressiveS&P 500 (IVV)
volatility (risk, annualized)19.5%22.5%21.2%
total return23.9%32.7%36.4%
Annualized risk and total return of the ETFMathGuy portfolios, 2020-2021 (18 months).

We will continue to update our ETFMathGuy portfolios with current market conditions using our updated backtesting calibration results. So, time will tell if value ETF investing continues to outperform growth ETF investing.

ETFMathGuy is a subscription-based education service for investors interested in using commission-free ETFs in efficient portfolios.
ETFMathGuy is a subscription-based education service for investors interested in using commission-free ETFs in efficient portfolios.
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Backtesting ETF portfolios

Backtesting ETF portfolios is a very important part of validating any investment strategy that uses them. At ETFMathGuy, we backtest our optimal portfolio construction strategy periodically. Doing so ensures that our quantitative methodology stays calibrated to the highest performing portfolios. Here, we discuss the key findings from this recent analysis.

Backtesting methodology

Our backtesting methodology follows the same approach we used in our previous backtesting analysis. The key distinction now is our time period begins in 2014 and runs through April of 2021. Also, we focused on one-month holding periods this time. Why? Based on our previous results, we found holding periods between 1-3 months had little impact on returns.

Backtesting ETF results over a longer-term

Firstly, the chart below shows the result of changing the duration of the sampling period on the out-of-sample returns. Note that there are two local maximums, with the first occurring and the 6-9 months, but a second more substantial maximum occurring at about 39 and 45 months.

Annualized returns from backtesting differing sample sizes. Source: ETFMathGuy.com
Annualized returns from backtesting differing sample sizes. Source: ETFMathGuy.com

However, when a risk-adjusted return is considered, we can improve this calibration. In the next figure, we show the annualized return divided by the annualized volatility. Thus, it’s clear that the 39 month sample period is superior with this measure for the moderate and aggressive portfolios. For the conservative portfolios, there is only a slight degradation in risk-adjusted return over these 7+ years of backtesting.

Annualized returns / volatility from backtesting differing sample sizes. Source: ETFMathGuy.com
Risk-adjusted returns from backtesting differing sample sizes. Source: ETFMathGuy.com

Backtesting ETF results over a shorter term

We also backtested our quantitative strategy over a shorter interval of the last 15 months, from January 2020, through April 2021. Ideally, our backtesting results over the long-term, shown above, should agree with this shorter time frame. And, in fact, they generally do.

Annualized returns and risk-adjusted returns from backtesting differing sample sizes. Source: ETFMathGuy.com
Annualized returns and risk-adjusted returns from backtesting differing sample sizes. Source: ETFMathGuy.com

Once again, with the slight exception of the conservative strategy, the 36-39 month sample size provided the largest annualized returns and risk-adjusted returns.

Key takeaways

  • Backtesting provides an estimate on how our quantitative strategy would have performed based on historical time periods.
  • The best calibration for the sample period occurs around 39 months based on both absolute return and risk-adjusted return.
  • Longer-term and shorter-term backtesting provided similar calibration results.
ETFMathGuy is a subscription-based education service for investors interested in using commission-free ETFs in efficient portfolios.
ETFMathGuy is a subscription-based education service for investors interested in using commission-free ETFs in efficient portfolios.
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Risk-seeking investors and the first quarter of 2021

There was plenty of risk-seeking in the first quarter of 2021. So, how did the stock and bond market respond?

A Unique Quarter

This recent Wall Street Journal article summarized this first quarter well. The author identified the following contributors to recent market behavior due to risk-seeking investors.

  1. Meme stocks
  2. Interest rates
  3. Tech rotation

Meme stocks and the Fear Of Missing Out (FOMO)

The most popular “meme” stock was GameStop Corp. for risk-seeking investors. But, what is a meme stock? This source describes it as a stock that exhibits rapid price growth that is popular among millennials. Meme stocks can also be categorized by high volatility, fueled by the so-called Fear Of Missing Out (FOMO) and panic selling. Time will tell if this category of stocks becomes more formalized, as many in the workforce return to their offices, thereby limiting their trading time. Of course, the effect of social media on stock trading isn’t likely to go away anytime soon.

A new trend in interest rates?

The other big news in the first quarter was the increase in interest rates. Long-term bond yields increased in February and March, after starting the year at 0.917%.

U.S. 10 Year Treasury Note Yield in First Quarter of 2021. Source: MarketWatch.com
U.S. 10 Year Treasury Note Yield in First Quarter of 2021. Source: MarketWatch.com

By the end of the first quarter of 2021, the U.S. 10 Year Treasury Note yield rose to 1.745%. As we wrote about before, the price of a bond decreases when yields rise. Consequently, the iShares Core Total US Bond ETF fell, to a year-to-date loss of 3.4%.

Total Return of iShares Core Total US Bond ETF, First Quarter of 2021. Source: ETFReplay.com
Total Return of iShares Core Total US Bond ETF, First Quarter of 2021. Source: ETFReplay.com

Tech Rotation

The first quarter was also characterized by about a 5% return difference between the Dow and Nasdaq indices. For instance, Exxon Mobil Corp. is up 35% this year, while Amazon and Apple have lost 5% and 7.9%, respectively. Of course, no one knows if this rotation out of tech and into energy is a new trend or just a reaction to markets anticipating a future with more energy consumption due to increased commuting. But, these recent changes have been incorporated into our portfolio construction process to produce an update to our free and premium portfolios. We encourage you to log in to see how these ETF portfolios changed due to the latest market dynamics.

ETFMathGuy is a subscription-based education service for investors interested in using commission-free ETFs in efficient portfolios.
ETFMathGuy is a subscription-based education service for investors interested in using commission-free ETFs in efficient portfolios.
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Bond Markets Fell in February 2021

ETFMathGuy optimal portfolios are now available to free and premium subscribers. Please log-in to see them now. In this post, we discuss how the bond markets fell with rising interest rates this past month, and its effect on the stock market and our ETF portfolios.

Bond markets fell. What is happening with interest rates?

The recent reaction of the bond markets appears to be due to investors being less convinced that U.S. Government interest rates will remain low for the long-term. Based on recent Wall Street Journal reporting, demand for the 10-year U.S. Treasury note has been “tepid”. With lesser demand come lower prices to stimulate buying. And, when prices go down in a bond, its interest rate goes up. How so? One simple way to think about this relationship is from the bond seller’s perspective. If the demand for bonds goes up, the bond seller can set a lower fixed interest rate and still find a buyer. Conversely, the bond seller must provide higher fixed interest rates, thereby compensating the bond investor more, if demand is low. If all this sounds confusing, please take a look at the nice visual representation below.

The seesaw relationship between bond prices and interest rates. Source: Securities & Exchange Commission
The seesaw relationship between bond prices and interest rates. Source: Securities & Exchange Commission

Why is demand low for U.S. Government bonds?

The most obvious explanation for the low demand for bonds is the large amount of debt the U.S. Government is expected to sell to fund the ongoing stimulus efforts. One measurable effect of this stimulus is to continue to keep the U.S.’s debt-to-GDP ratio above 100%. Servicing this debt will slowly become more expensive as interest rates rise.

How did ETFMathGuy Premium Portfolios do in February 2021?

Our portfolios gave back some of their gains in January, in part due to the increased chance that interest rates may be on the rise, increasing corporate borrowing costs. The chart below shows the year-to-date returns of stocks, bonds, and ETFMathGuy premium portfolios held at Fidelity and Schwab. Notice how the low demand for bonds has reduced the total return for the iShares Core U.S. Aggregate Bond ETF (ticker: AGG).

Total returns for ETFMathGuy premium portfolios for January and Februrary, 2021

We hope this post provided you with some helpful perspectives on why the bond markets fell, and how the stock market, ETFs, and the overall economy are all dependent on one another.

ETFMathGuy is a subscription-based education service for investors interested in using commission-free ETFs in efficient portfolios.
ETFMathGuy is a subscription-based education service for investors interested in using commission-free ETFs in efficient portfolios.
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Optimal Portfolio Updates for February 2021

ETFMathGuy optimal portfolios are now available to free and premium subscribers. Please log-in to see them now. In this post, we will discuss how the recent GameStop stock prices influenced these portfolios and our portfolio construction process.

Markets in 2021

The 2021 year in the ETF marketplace is already shaping up to be very interesting. The big news recently was the impact of stocks like GameStop’s 500% gain from Jan. 25 through Jan.29. Fortunately, most diversified ETFs saw little impact of this extreme price move. However, this rapid price gain did have a noticeable impact on two ETFs.

What ETFs were impacted most by GameStop?

According to this ETF.com article, two ETFs had their holdings in GameStop jump into double-digits weights. They were the Wedbush ETFMG Video Game Tech ETF (ticker: GAMR) and the SPDR S&P Retail ETF (ticker XRT). In the case of GAMR, this ETF has the largest weighting of GameStop, currently at 26%. Notice, in the image below, that this holding is more than 10-times larger than the next largest one.

Top 10 Holding for the Wedbush ETFMG Video Game Tech ETF (ticker: GAMR). Source: etfmg.com/funds/gamr
Top 10 Holding for the Wedbush ETFMG Video Game Tech ETF (ticker: GAMR). Source: etfmg.com/funds/gamr

Less extreme is the SPDR S&P Retail ETF (ticker: XRT), which currently holds 12% of its assets in GameStop. So, these two ETFs are not as diversified as one might expect.

Did these ETFs impact the ETFMathGuy portfolios?

The short answer to this question is “no”, because of our portfolio construction process begins with a curated list of ETFs. For this month, we chose to intentionally exclude GAMR due to the excessive level of risk associated with holding large amounts of GameStop stock. Fortunately, there were still many ETFs to pick from to build our optimal portfolios, creating plenty of other opportunity for gains. And, gains for 2021 have been good so far. Below is an image showing total returns for stocks (ticker: IVV), bonds (ticker: AGG) and our three premium portfolios invested in real brokerage accounts at Schwab and Fidelity.

Total returns for ETFMathGuy premium portfolios in January, 2021
Total returns for ETFMathGuy premium portfolios in January, 2021

We were happy to see these returns in January, which continues the strong returns from 2020. Please watch for future posts where we will continue our discussion on ETFs, the economy and tax-efficient retirement income.

ETFMathGuy is a subscription-based education service for investors interested in using commission-free ETFs in efficient portfolios.
ETFMathGuy is a subscription-based education service for investors interested in using commission-free ETFs in efficient portfolios.
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Concentrated exposure with thematic ETFs

In our recent post about thematic ETFs, we discussed the growth of so-called “thematic ETFs”. These are ETFs that follow a theme. One of our favorite writers at the WSJ is Jason Zweig, and he also wrote about these ETFs recently. Today, they represent some of the market’s hottest funds by using concentrated exposure.

“Often called thematic ETFs, these funds cut across industries, trying to capitalize on ideas like alternative energy, cloud computing or 3-D printing. Others buy stocks that could benefit as more people work from home, demand gender or racial diversity, or lavish money on their pets.”

Jason Zweig, The Intelligent Investor, Wall Street Journal, January 15, 2021

More Concentrated Exposure

By concentrating on a particular theme, like solar power, robotics or industrial innovation, many of these funds can have very high returns. For example, the Invesco Solar ETF (ticker: TAN) had a 234% return in 2020. Similarly, the ARK Innovation ETF (ticker: ARKK) returned 153%. Of course, these returns didn’t come without their own risks. The volatility of these two thematic ETFs were 55% and 49%, respectively. As a basis of comparison, our typical benchmark for stocks is the iShares Core S&P 500 ETF (ticker: IVV) and bonds is the iShares Core Total US Bond ETF (ticker: AGG). The 2020 return of these ETFs appears below at 18.4% and 7.5%, respectively. Also, note their lower volatility than the thematic ETFs mentioned here.

Risk and Return of Three popular thematic ETFs in 2020. Source: etfreplay.com/charts.aspx
Risk and return of three popular thematic ETFs and two broad-based ETFs in 2020. Source: etfreplay.com/charts.aspx

Higher expenses in thematic ETFs

Expense ratios are often much higher in thematic ETFs than broad-market ETFs like those that track the S&P 500. For instance, the three thematic ETFs from above have expense ratios of 0.69%, 0.95% and 0.75% according to ETF.com. In contrast, our stock and bond benchmark ETFs (tickers IVV and AGG) have expense ratios of 0.04% and 0.06%. So, investors must pay a premium to get unique exposure to these themes. And, until a thematic ETF grows sufficiently, the bid-ask spread on them could be much larger, further degrading returns when they are bought and sold frequently. Nevertheless, we found in 2020 that thematic ETFs, when built into a diversified portfolio, can both manage risk and boost returns.

ETFMathGuy is a subscription-based education service for investors interested in using commission-free ETFs in efficient portfolios.
ETFMathGuy is a subscription-based education service for investors interested in using commission-free ETFs in efficient portfolios.
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2020 Year In Review

Happy New Year from ETFMathGuy! In this post, we conduct a 2020 year in review of stock, bond and ETFMathGuy premium portfolios.

For many, 2020 was an unusual year in the investing world. And, investing in ETFs was no exception. In our first post of 2020, we discussed how we adapted to the new normal of nearly all ETFs trading commission free. That opened our portfolio construction process to consider over 2,000 ETFs. But, as we noted in another post from 2020, we immediately exclude any ETF with under $50 M in assets, which helps an investor avoid ETFs that may soon close, as well as larger bid-ask spreads when traded.

So, how did ETFMathGuy portfolios fare in 2020?

In short, we have been very satisfied with our ETFMathGuy premium portfolios. Our goal was to achieve returns similar to the S&P 500, but at lower risk. We established this goal based on rigorous backtesting all ETFs that were previously commission-free from Fidelity, or slightly less than 500 ETFs. However, in 2020, we expanded into all commission-free ETFs, and the returns from two real accounts at Fidelity appear below.

Total returns for stock market, bond market and two ETFMathGuy portfolios for 2020
Total returns for stock market, bond market and two ETFMathGuy portfolios for 2020

Clearly, we achieved our 1st goal of generating returns “at least as good” as the stock market, which we assume as the S&P 500. These returns were possible thanks to our model’s ability to dynamically adjust to market conditions. For subscribers with free memberships, you can see what these ETFs were by logging into your account, and browsing the 2020 portfolios through June 2020. For example, PALL and ARKK have been consistent components of our optimal portfolios. If you are a current premium subscribers, your January 2021 portfolios and rebalancing calculator are now available for your consideration.

But, what about risk in our 2020 year in review?

The pandemic of 2020 had a substantial impact on market risk. When measured monthly, stock market volatility was 25.8%. Examining the monthly returns for our ETFMathGuy portfolios, we observed an 18.1% and 19.4% and volatility for our moderate and aggressive portfolios, respectively. So, we also achieved our 2nd goal of keeping volatility lower than the stock market. We also revisited our calculation of Alpha and Beta. For the 12-monthly returns in 2020, we found Alpha = 2.48% and Beta = 0.49. Their p-values were 0.09 and 0.02, respectively for the ETFMathGuy aggressive portfolio.  Recall from this post that the smaller the p-values, the greater confidence we have that these are the correct values and have minimal estimation error. So, for those of you “seeking alpha”, these statistics indicate our portfolios likely produced “alpha” in 2020.

Our statistics on 2020 monthly returns indicated that we likely produced "alpha" in our ETFMathGuy aggressive portfolios.
Our statistics on 2020 monthly returns indicated that we likely produced “alpha” in our ETFMathGuy aggressive portfolios.

Forecasting 2021?

We won’t venture a guess at what the markets have in store for investors in 2021. Frankly, there are many, many articles already written on this topic. Instead, we will continue to pursue our goal to construct ETF portfolios that meet or exceed returns like the S&P 500 with lower volatility. If you are interested in accessing the January 2021 premium portfolios, please consider upgrading your membership now at 2020 subscription prices. In the coming weeks, we plan to increase our subscription prices for the new year. Please contact us if you would like a free sample of our latest premium portfolio.

We hope you found this 2020 year in review educational!

ETFMathGuy is a subscription-based education service for investors interested in using commission-free ETFs in efficient portfolios.
ETFMathGuy is a subscription-based education service for investors interested in using commission-free ETFs in efficient portfolios.
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What are Model Portfolios?

Yesterday’s Wall Street Journal had a very interesting article about model portfolios. So, what are these, and why should an individual investor care about them?

A Wall Street Trend

This WSJ article stated that the use of model portfolios is a growing trend, since it helps take the emotion out of investing. So, these portfolios are based on scientific observations and analysis, rather than an investor’s “instincts” or emotional reaction to current market conditions. A growing number of financial advisors are embracing their use too.

Model portfolios take some of the human emotion out of investing. They provide the comfort of science.

Andrew Guillette, Research Director at Broadridge. source: WSJ, December 4, 2020

Thus, these model portfolios are ones that can “dynamically shift the funds it invests in as markets change”. We are advocates of this approach using commission-free ETFs. Our free and premium portfolios do exactly that, as we update them each month based on current market conditions. Please log in to see these portfolios now, which include the latest market shifts through Friday, December 4th. Premium subscribers also have access to a handy web calculator to assist in rebalancing their portfolio.

How have model portfolios performed this year?

Unfortunately, little is published about model portfolio performance. But, we report our model’s performance for ETFMathGuy portfolios on a regular basis. The image below shows the total returns from January through end of November from our investments at our Fidelity brokerage account.

Total returns from January through November of Stocks, Bonds and ETFMathGuy Portfolios

What about risk?

The performance over the last 11 months look very promising, suggesting a scientific approach to rebalancing an ETF portfolio can perform well in volatile markets. But, how much risk did we take with these investments? Using the monthly returns that led to the total returns shown above, the volatility of the stock market (ticker: IVV) was 26.9%. However, the volatility of the moderate risk ETFMathGuy portfolio was only 18.2%. Not surprisingly, the aggressive risk ETFMathGuy portfolio had a higher volatility of 19.0%, as expected for a portfolio seeking more risk. So, these portfolios continue to outperform the stock market, while also taking less risk as measured by volatility.

ETFMathGuy is a subscription-based education service for investors interested in using commission-free ETFs in efficient portfolios.
ETFMathGuy is a subscription-based education service for investors interested in using commission-free ETFs in efficient portfolios.