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Category: ETF research and analysis
Insights from commission-free ETF research & analysis can be very helpful for ETF investors. So, we hope you find these evidence-based insights educational.
ETFMathGuy is a subscription-based education service for investors interested in using commission-free ETFs in efficient portfolios.
In 2022, many long-term trends in asset correlation appear to be changing. In this post, we discuss the longer-term trends in several popular asset class correlations and highlight recent changes that continued from the first half of the year.
Short-Term Correlations and Long-Term Trends
The stock and bond markets continued their downward slide this month. The iShares Core S&P 500 losses for 2022 reached 24%. In addition, the bond markets continue their losses for the year, with the iShares Core U.S. Aggregate Bond Market ETF down about 15%. This latter result is quite surprising, given the long-term correlation between the stock and bond market is 5%, but has recently grown to over 40%. Thus, the stock and bond market returns are more similar than they were in the past, so provide fewer diversification benefits. The chart below shows this upward trend in the correlation between the stock and bond markets in blue. The horizontal dotted line shows the long-term correlation from returns dating back to February 2004.
90-Day Asset Correlation of Total Returns against the S&P 500 Index
Asset Correlation Among Other Sources
The chart above also highlights the diminished effect of other sources on a portfolio’s diversification. For example, international equities are often sought for their diversification benefit. However, the long-term correlation of 88%, which also appears in this figures legend, hasn’t changed much this year. Bitcoin’s long-term correlation is 21%, but this correlation has steadily grown to over 60% this year. The one asset that has performed well this year is a direct investment in the U.S. Dollar ETF, ticker UUP. Long-term, the dollar has an insignificant correlation to the S&P 500. However, in 2022, the dollar’s correlation to the S&P 500 has grown significantly negative, as interest rate rises have increased demand for U.S. dollars. The chart below shows the total return of the five ETFs discussed here.
2022 Total Returns for ETFs associated with the S&P 500, Bonds, International, Bitcoin, and U.S. Dollars.
Given the economic pressures creating these effects on the markets, the remainder of 2022 may continue to surprise investors. In particular, asset classes that formerly had low correlations to the stock market may continue to diverge from their long-term values.
ETFMathGuy is a subscription-based education service for investors interested in tax-efficient investing with ETFs
It has been a very difficult year for cryptocurrency investors. Here, we will discuss the recent trend of cryptocurrency returns. Also, we will highlight the current cost of cryptocurrency mining, and share some thoughts on the future of this asset.
Cryptocurrency returns in 2022
Year-to-date returns of Bitcoin, Ethereum, and the first ETF that tracks bitcoin futures (ticker: BITO) appear below. Like the stock and bond markets, all three of these assets lost value in 2022. Also, in our previous post on the risks of cryptocurrencies, the volatility of all of these cryptocurrency assets was significantly higher than the long-term historical norm of 15-20% for the S&P 500.
Like oil, natural gas, and precious metals, there is a cost to “mine” bitcoin. Economic theory for commodities suggests that, when demand is constant, rising prices should increase production, since even less efficient miners can operate profitably. However, as prices drop, less efficient producers will exit, and less production of a commodity will occur, thereby stabilizing prices. That may be occurring now, as the price to mine one bitcoin is in the $20,000 to $34,000 range. As of July 31, 2022, the price of one bitcoin was within this range, with a value of $23,819.
Bitcoin production cost. Source: TradingView
The Future of Cryptocurrency
The future of cryptocurrency remains uncertain. However, few expect these new innovations in decentralized finance to go away. Instead, we may see longer-term price stabilization, as the investment in mining produces enough cryptocurrency to satisfy demand. Such price stabilization may not entice investors seeking outsize returns but could help cryptocurrency gain wider acceptance if its volatility can also be reduced.
ETFMathGuy is a subscription-based education service for investors interested in tax-efficient investing with ETFs
With the 1st half of 2022 now behind us, we devote this post to a mid-year review of ETFs in a variety of stock sectors. We also highlight some recent research on sectors that have historically held up well during periods of high inflation, and the benefit of time horizon when investing in stocks. We hope you find this mid-year review helpful!
Record-breaking 1st half of 2022
According to this MarketWatch article, the S&P 500 recorded its steepest 1st-half year loss in over 50 years. But, remember that the S&P 500 is a broad-based index consisting of many different companies across a variety of industries. In fact, there are 11 sectors in the S&P 500, which in order of size (and an ETF to represent them) are:
Information Technology (XLK)
Health Care (XLV)
Financials (XLF)
Consumer Discretionary (XLY)
Communication Services (XTL)
Industrials (XLI)
Consumer Staples (XLP)
Energy (XLE)
Utilities (XLU)
Real Estate (IYR)
Materials (XLB)
Mid-year review of best and worst performing sector ETFs
The chart below sorts the total return for the 11 ETFs identified above for 2022. As can be seen here, the biggest gains were among the energy sector (XLE) and the worst in consumer discretionary (XLY). Over this same period, the S&P 500 total return, measured by the iShares Core S&P 500 ETF (ticker: IVV) was -19.2%. Also, note that the energy sector was the only ETF here that saw a positive return, which is not surprising given the war in Ukraine and its impact on supply in the energy sector.
Mid-year review of returns from 11 sector-ETFs in the S&P 500 Index
Where will stocks go from here and what to do about it?
Given the current high inflation rates, Derek Horstmeyer at George Mason University recently showed the following “inflation fighters” in his June 5th Wall Street Journal Article.
Best performing sectors during periods of high inflation. Source: Derek Horstmeyer
Of course, the most prudent course of action may be to simply do nothing based on this mid-year review. Given longer investment horizons, the stock market is less likely to suffer losses. Based on Bank of America research, the chart below supports this fact.
In our last post, we introduced a new calculator to help you forecast your retirement savings. Part of this introduction showed you how the uncertainty in the markets may affect your savings forecast. So here, we summarize the differences between the two simulation options available in our new retirement savings calculator: bootstrapping and geometric Brownian motion.
Simulation of asset prices helps manage savings risks. (The vertical axis is price. The horizontal axis is time.)
Why use simulation?
Simulation, or often termed “Monte Carlo” simulation, is a scientific method to model future uncertainty using a random number generator. In the case of our savings calculator, it models the uncertainty of annual stock and bond returns. By running many simulation trials, each trial can represent one of many possible outcomes for investment returns over your planning horizon. Then, you can see what risk you may be taking in assuming a more pessimistic or optimistic account balance at retirement. For example, using default inputs to our model, a retiree can expect their future tax-deferred account balance to be likely more than $629,047, but likely not more than $1,073,058. (These values are based on default 25th and 75th percentiles. Our calculator allows these levels to be adjusted.)
Simulation provides a range of possible account values and the risk associated with achieving them.
Bootstrapping
The two most common approaches to simulation are bootstrapping and geometric Brownian motion. Bootstrapping uses historical returns of stocks and bonds, and randomly samples from them for each trial to develop simulated returns. For our model, we reconstructed annual returns for an S&P 500 ETF and aggregate bond ETF from 1989 to 2021. We used the same methodology described by DiLellio (2018). Retirees benefit from using bootstrapping since it preserves the historical distribution of stock and bond returns, as well as the correlation of their returns. In particular, extreme market shocks, like the financial crisis of 2008-2009, the dot-com bubble burst of 2001, and the Covid-19 pandemic of 2020 are all included when simulation uses bootstrapping.
One approach to simulating future returns is termed bootstrapping, where we simulate returns by random selection from a set of historical returns. In our calculator, we use annual returns from an S&P 500 and aggregate bond index ETF from 1989 to 2021. This approach has the benefit that it accurately represents the past, including the large market corrections in the financial crisis of 2008-2009, the dot-com bubble bursting in 2001, and the global pandemic in 2020. You can read more about this simulation approach in this peer-reviewed research in DiLellio (2018).
Geometric Brownian Motion
However, what if the future isn’t entirely represented by the past? In this case, we can use the geometric Brownian motion (GBM) stochastic process to simulate future stock and bond prices. Why? Using a GBM permits you to dictate return behavior using a normal distribution of asset returns. This simulation approach gives the retiree complete control over future returns. And, the retiree can select volatility and correlations of stock and bond returns. Lastly, GBM is the foundation for the famous Black-Scholes Option pricing formula. Unfortunately, GBM does not capture extreme events well. The image below from DiLellio (2018) shows how the normal distribution does a fair job, but not a perfect one, of fitting stock and bond returns.
Daily return distribution of stock (top pane) and bond market (bottom pane) indices. Two normal distributions are also shown, with volatility estimates using historical returns from 1989 to 2017. Reducing the volatility appears to provide a slightly improved fit near the center of the distribution, but worsens the fit in the distribution tails. Source: DiLellio (2018) Risk and reward of fractionally leveraged ETFs in a stock/bond portfolio, 27 Financial Services Review.
So, which simulation approach is better?
The short answer is “it depends”. Like any mathematical model, they both have their own strengths and limitations. Fortunately, you can use either of these models to develop your savings plan. In fact, we hope you consider using both, to best understand the risk of achieving your savings goals!
ETFMathGuy is a subscription-based education service for investors interested in tax-efficient investing with ETFs
Inflation hedging continues to be of great interest for investors large and small. In this post, we quantify some possible ways to combat inflation based on a recent article in the WSJ.
Historical Inflation Trend
Inflation is currently around 6%, well above the 2% rate seen recently. The chart below shows how most of this change occurred in 2021. This rate is well above the 2% long-term target set by the Federal Reserve. So, what are some options for investors in this current inflation climate?
Inflation is about 6% in late 2021
Treasury inflation-Protected Securities (TIPS)
TIPS are one of the most obvious places investors look for inflation hedging. The iShares TIPS Bond ETF (ticker: TIP), with over $30 billion in assets, is a popular option. This ETF has performed notably better than a broad bond benchmark, like the iShares Core U.S. Aggregate Bond ETF (ticker: AGG), as the chart below illustrates. Note that while TIP has slightly higher volatility than AGG, it performance in 2021 is noticably better. In fact, according to ETFReplay.com, the 2021 year-to-date return of TIP is 5.4%, versus -1.0% for AGG.
Commodities
There are certainly other options investors can consider. For example, investors often seek commodity investments when inflation rises. This recent study by Vanguard indicated that a 1% rise in inflation could produce a 7-9% rise in commodities. This estimate looks surprisingly accurate, as the ETF DBC (PowerShares DB Commodity Index) should be up 28-36% in 2021, given the inflation rate increase this year from 2% to 6%. In fact, DBC is up 32.7% in 2021, according to ETFReplay.com
Updated optimal portfolios
For subscribers of our ETF optimal portfolios, we encourage you to log in to see the latest updates. Note that, based on our latest backtesting, monthly portfolios change more quickly now to respond to market dynamics.
ETFMathGuy is a subscription-based education service for investors interested in using commission-free ETFs in efficient portfolios.
Investor interest in cryptocurrency and bitcoin remains high. This week, ETF investors may see the first futures-based bitcoin ETFs. Here, we discuss the introduction of bitcoin ETFs, and why they may not perform as ETF investors expect.
According to this ETF.com article, October 18th could be the first effective date that two bitcoin ETFs are set to debut. And, another bitcoin ETF could become available a week later, on October 23rd, and a fourth potentially available on October 25th. But, its important to note that each of these ETFs depend on futures contracts for their bitcoin exposure. Therefore, none of them hold bitcoin to provide direct exposure to the spot market. Instead, the most direct exposure for investors seeking bitcoin remains the Grayscale Bitcoin Trust (GBTC), which typically trades at a premium. In fact, we wrote about the risks and taxation of GBTC earlier this year.
What can happen with futures-based ETFs?
Sadly, futures-based ETFs can often not match the corresponding price performance of the spot market. For example, ETF investors wishing exposure to West Texas Intermediate crude oil price changes could buy the United States Oil Fund ETF (ticker: USO) Unfortunately, a phenomenan called “contango” can occur when the price of the futures contract exceeds the expected future spot price. So, the fund loses money when it replaces expiring contracts with near-term future contracts. Consequently, over time, futures-based ETFs tend to underperform the spot price market.
“These kinds of vehicles are primarily meant to be used by active traders to hedge or short positions. They are not meant as long-term buy and hold vehicles.”
Fortunately, there is some good news about bitcoin ETFs. Greyscale has indicated it may convert its current bitcoin fund into an ETF. If they do, this ETF’s investment returns wouldn’t be subject to contango, and won’t suffer from the return drag of futures-based bitcoin ETFs. However, the Securities and Exchange Commission (SEC) current commissioner has stated he prefers approving ETFs backed by bitcoin futures. So, ETF investors interested in bitcoin may wish to continue to wait or seek alternatives outside the ETF space.
ETFMathGuy is a subscription-based education service for investors interested in using commission-free ETFs in efficient portfolios.
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.
In our post last week, we showed how the risk of cryptocurrencies appears much higher than the risk of stocks and bonds. This week, we will discuss some of the taxes on cryptocurrencies, and how they differ from buying and selling an ETF.
When trading an ETF in a taxable account (e.g. not an IRA or Roth IRA account), trades are generally subject to taxes much like that of a stock. So, gains that are realized after holding for less than a year are taxable as ordinary income. However, to reduce taxes owed on these gains, an investor can offset them with realized losses on other ETFs. Termed tax-loss harvesting, such an approach can have significant economic benefits. But, what if the investor wishes to buy these ETFs they just sold because they anticipate it to appreciate again?
Wash Sale Rules
Selling, then rebuying, an ETF within 30 days violates the Wash Sale Rule. Consequently, such a violation means that the loss on the ETF investment can not be claimed for tax reasons, effectively eliminating the opportunity to tax-loss harvest. But, based on experts cited in this recent CNBC article, wash sale rules do not apply to taxes on cryptocurrencies. The article does caution that some caveats do apply. It suggests that selling a cryptocurrency one day and buying it again the next could still enable tax-loss harvesting. Given the recent wild swings in cryptocurrency prices, and recent gains in some ETFs, investors may wish to consider this tax-loss harvesting approach.
Free and Premium Portfolios Now Available
Lastly, 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.
Note: This post has been prepared for informational purposes only, and is not intended to provide, and should not be relied on for, tax, legal or accounting advice. You should consult your own tax, legal and accounting advisors before engaging in any transaction.
ETFMathGuy is a subscription-based education service for investors interested in using commission-free ETFs in efficient portfolios.
Cryptocurrency risk is well known to be very high for many reasons. However, both individual and institutional investors continue to evaluate it as part of their investment portfolios. This post discusses recent cryptocurrency trends in a diversified portfolio and how the risks of this alternative investment compare to mainstream investments like stocks and bonds.
Volatility estimates
Volatility is one common way of assessing the risk of any investment. For the stock market, we provide a historical perspective, updated daily, to see how volatility changes over time for the stock market. But, how does this volatility compare to investments in cryptocurrency? The chart below shows a 3-month annualized volatility for the last several years of the stock market, measured with the ETF IVV, the bond market, measured by the ETF AGG, and the crypto market, measured by the Grayscale Bitcoin Trust (GBTC). As this chart shows, bond volatility is the lowest, averaging between 3-4%. Stock volatility is higher, averaging between 15 – 20%. Cryptocurrency risk is about five times higher than stocks, with average volatility between 90-100%.
3-Month annualized volatility of the stock, bond, and cryptocurrency markets. Source: ETFMathGuy.com
How much to allocate to cryptocurrency?
This recent WSJ article provided some guidance for individual investors interested in investing in cryptocurrency. While the answers to this question really depend on the individual’s risk tolerance, this article suggested between 1-2%. So, even if the value of the crypto investment hits $0, the investor limits their loss to this original investment amount. But, given the high levels of volatility, more frequent rebalancing may be prudent. Thus, if there is a substantial increase in the price of a crypto investment, the targeted 1-2% allocation would most likely require selling some of the crypto gains.
Unfortunately, selling short-term gains can be “expensive”, especially for those individual investors in a higher income tax bracket. In this case, the use of a Roth IRA may be the best approach. Why? An investor can realize Roth IRA gains tax-free if taken after age 59 1/2 from an account open for more than five years.
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.
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