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
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
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.
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.
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%.
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.
Moderate
Aggressive
S&P 500 (IVV)
volatility (risk, annualized)
19.5%
22.5%
21.2%
total return
23.9%
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.
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
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.
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
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.
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%.
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.
A webinar attended by over 1,800 financial advisors recently featured ETFMathGuy to discuss retirement drawdown strategies. Subsequently, the Retirement Income Journal wrote about this event. In this posting, we will discuss some of the highlights of this webinar. Please click the image below to view the 60-minute webcast. Or, you can browse the slides.
Webcast recording: A Deep Dive Into Retirement Drawdown Strategies.
Webinar highlights
As the title of the webinar indicated, its emphasis was on retirement drawdown strategies. Our host, Steve Parrish discussed some of the recent changes to Required Minimum Distributions (RMDs) that resulted from the SECURE Act, as well as where tax law may go in the future. Steve also wrote a really nice article recently in Forbes entitled “Three Reasons to Take Your RMDs Now“. Joe Elsasser, Founder and President of Covisum, a FinTech company specializing in retirement drawdown strategies, also presented. Joe showed how his firm’s software can identify the so-called “tax torpedo“, and assist retirees on how to plan accordingly.
After that, I discussed two research articles on retirement drawdown strategies. To begin, I quantified the impact of eliminating the stretch IRA for non-spouse heirs, which I highlighted in a previous ETFMathGuy posting. The key takeaway from this peer-reviewed article was that there is still a benefit to an heir to stretch their IRA drawdowns over the 10-years permitted by the SECURE Act. Doing so can increase the heir’s inherited assets by 11-17%, depending on their specific situation.
Emerging Research
I also spent a portion of my presentation to this large group of financial advisors discussing some of my latest research. This recent work builds upon some of my previous publications with Dr. Dan Ostrov at Santa Clara University. In this latest research, I identified the use of the Common Rule as a diagnostic for the next stage of optimal decision making for retirement income. The image below summarizes the preliminary findings for three categories of retirees.
The sensitivity of optimal drawdown strategies for three categories of retirees. Forthcoming research by DiLellio and Simon (2021)
Thank you for your feedback
I would like to thank the many financial advisors who recently tried out my retirement calculator. So, I am logging all these helpful suggestions for improvements. I hope to have this free calculator updated shortly that begins to incorporate many of these suggestions. I will discuss some of the calculator enhancements in a future post.
ETFMathGuy is a subscription-based education service for investors interested in using commission-free ETF efficient portfolios.
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.
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
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
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.
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.
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.
The stock market, measured by the S&P 500, lost about 2.5% in October. But, earlier in the month, the stock market was up over 5%. The chart below shows the roller coaster ride for two ETFs that track the stock and bond markets: iShares Core S&P 500 ETF (ticker IVV), Vanguard Total Bond Market ETF (ticker: BND) So, what’s going on with this market volatility?
Stock and bond returns in October, 2020. Source: finance.yahoo.com
Markets don’t like uncertainty
There are many opinions to describe what caused the financial markets to move like they did in October 2020. We think that the combination of the upcoming election and spike in coronavirus cases is adding to uncertainty. But, this uncertainty, as measured by stock market volatility, is still well below where it was earlier in the year. We used our daily volatility monitor in the plot below.
Stock market volatility as of October 30, 2020. Source: ETFMathGuy.com
As this chart shows, volatility has crept a little higher in October. But, based on the long-term historical norm, this volatility is still slightly elevated in the 75% percentile. Of course, if you are a believer in efficient markets, then you simply don’t know what the future of the market will hold. In more positive news, the WSJ recently reported that the U.S. economy recovered significantly in the 3rd quarter of 2020. Consumer spending for online retail items continue to stay strong, while the travel sector still lags.
How about the ETFMathGuy portfolios and market uncertainty?
Thanks to wide diversification from over 2,000 ETFs we analyze each month, our portfolios continue to perform well. Consequently, the moderate risk portfolio lost 0.6% and the aggressive risk portfolio lost 0.5% in October. The year to date cumulative return of the ETFMathGuy aggressive risk portfolio appears below, along with the S&P 500 and Aggregate Bond Market total return.
ETFMathGuy year to date cumulative returns, versus the S&P 500 and Aggregate Bond Market returns.
Premium subscribers can now access the backtested portfolios for November 2020. Not a premium subscriber yet? Then, just visit the bottom of our “Join Us” page to upgrade your subscription and get immediate access!
ETFMathGuy is a subscription-based education service for investors interested in using commission-free ETFs in efficient portfolios.
Market volatility returned in September 2020. In this post, we discuss this recent surge in the context of long-term historical volatility. We also show how our ETFMathGuy portfolio performed, and elaborate on a source of that performance.
The higher volatility occurring in September did indeed correspond to a loss in the stock and bond markets. The stock market lost 3.7% and the bond market lost 0.1%, based on the ETFs with ticker symbols IVV and AGG. The year to date return of these stock and bond index ETFs were 5.5% and 6.7%, respectively, including dividends. The year to date return of the ETFMathGuy Aggressive Risk Portfolio was 20.8%. This return is the result of trades conducted in a brokerage account at Fidelity Investments, and so includes the bid-ask spread.
Stock and Bond Market YTD Returns compared to the ETFMathGuy Aggressive Risk Portfolio
One ETF that our portfolios have consistently included throughout this year is the Aberdeen Standard Physical Palladium Shares ETF (ticker: PALL). Its 12 month return and volatility appear below next to the S&P 500 ETF (ticker IVV).
The Palladium ETF has higher volatility than the S&P 500, but also has a higher return over the last 12 months. Source: www.ETFreplay.com
Examining these results for PALL confirms the expectation that higher risk can lead to a higher return. Our optimal portfolio construction process creates a portfolio that, along with PALL, finds other ETFs that maximize expected return. This process also keeps the portfolio’s expected risk between the stock and bond markets. Additionally, we backtested this process over a full market cycle. We hope you will consider upgrading your subscription to gain insights into a wider variety of ETFs that appear in our efficient portfolios.
ETFMathGuy is a subscription-based education service for investors interested in using commission-free ETFs in efficient portfolios.
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