Momentum Strategies With Leveraged Funds
Summary
- Leveraged funds may be successfully included in portfolios managed with momentum strategies.
- Leveraged funds may generate great returns with moderate risk if used during market risk-on periods.
- We compare the performance of three portfolios, two with leveraged funds, the third with the corresponding non-leveraged funds.
Momentum Strategy
In this article we apply a modified version of our dual-momentum strategy to a portfolio made up of three ETFs based on the following US market indexes: S&P500, S&P 400 and Nasdaq 100. We investigate the basic portfolio based on the stocks in the indexes without leverage, as well as portfolios with 2X and 3X leverage. The list of ETFs is given below.
- SPDR S&P 500 ETF Trust (SPY)
- ProShares Ultra S&P 500 (SSO)
- Direxion Daily S&P 500 Bull 3X Shares (SPXL)
- Invesco QQQ Trust (QQQ)
- ProShares Ultra QQQ (QLD)
- ProShares UltraPro QQQ (TQQQ)
- SPDR S&P MIDCAP 400 ETF Trust (MDY)
- ProShares Ultra MidCap 400 (MVV)
- Direxion Daily Mid Cap Bull 3X Shares (MIDU)
We shall use a dual-momentum strategy with two regimes: risk-on and risk-off. During risk-on periods, the strategy allocates to the top two funds based on their relative strength over the previous three months. During risk-off periods, the strategy invests all the funds in one or two Treasury bonds funds.
A topic that received much attention in this work was the choice of factors associated with the transitions between risk-on and risk-off states of the equity markets. Here is the list of funds used to generate signals for market state:
- Invesco DB Base Metals Fund (DBB)
- Invesco DB US Dollar Index Fund (UUP)
- Consumer Discretionary Select Sector SPDR Fund (XLY)
- Consumer Staples Select Sector SPDR Fund (XLP)
In our latest article we used the pair DBB-UUP as an absolute momentum indicator. In that application the return of DBB was compared with the return of the US dollar. In this application we add a new pair: XLY-XLP. The condition that must be satisfied for switching to risk-off allocation is that both pairs indicate a negative return. That happens when the return of DBB is smaller than that of UUP and the return of XLY is lower than the return of XLP over the relative strength evaluation period.
- Following is the list of parameter values used in simulations.
- Initial Balance: $1,000
- Absolute momentum period: 3 months
- Relative strength period: 3 months
- Assets to Hold: 2
The transition from risk-on to risk-off is made the following trading day after the condition for market-off is satisfied. The reverse transition from market-off to market-on is done after a delay of 2 days since the risk-on condition is detected. The allocation is updated at the end of each month during risk-on periods.
Simulation Results
The portfolio for the new strategy was simulated using custom software written in Python. DBB and UUP are used to determine the risk-off periods, while IEF and TLT are used as the safe, "out-of-market assets."
The results for simulations from 1/1/2008 to 3/5/2021 are shown in the table below.
Portfolio | Initial Balance | Final Balance | CAGR | Stdev | Max DD | Sharpe ratio |
[SPY,QQQ,MDY] | $1,000 | $18,496 | 21.98% | 15.28% | -14.98% | 1.39 |
[SSO,QLD,MVV] | $1,000 | $77,115 | 36.00% | 28.08% | -28.86% | 1.23 |
SPY | $1,000 | $3,399 | 9.89% | 20.55% | -51.75% | 0.43 |
A graph of the portfolio balance is shown in Figure 1. The unleveraged portfolio [SPY, QQQ, MDY] is in orange, SPY is in blue, and the 2X leveraged portfolio [SSO, QLD, MVV] is in green.
Figure 1. Equity plots of unleveraged and 2X leveraged portfolio – logarithmic scale.
Source: This chart is based on author computations
It can be seen that both the unleveraged and the leveraged portfolio avoided the huge S&P500 losses during the bear markets of 2008-9 and March 2020.
Since TQQQ data starts in February 2010, we created a table of the portfolios' performance since February 2010 to February 2021. The 3X portfolio invests in [SPXL, TQQQ, MIDU].
Portfolio | Initial Balance | Final Balance | CAGR | Stdev | Max DD | Sharpe ratio |
1X Portfolio | $1,000 | $9,078 | 19.09% | 13.89% | -14.98% | 1.32 |
2X Portfolio | $1,000 | $20,707 | 31.20% | 25.33% | -28.86% | 1.18 |
3X Portfolio | $1,000 | $59,586 | 44.24% | 37.22% | -44.76% | 1.14 |
SPY | $1,000 | $4,137 | 13.76% | 17.27% | -33.72% | 0.75 |
It should be mentioned that leverage was applied only in the risk-on periods. During market risk-off periods, all portfolios were invested in the same Treasury bonds. While there are leveraged Treasury bond funds, we decided not to include them here in order to get a clearer picture of the effect of equity leverage. An analysis of the effects of including leveraged Treasury bonds will be done in a future article.
As one can see from the results, the effect of leverage is consistent with our expectations. More leverage is associated with greater returns, greater volatility, larger drawdowns and smaller Sharpe ratios. The natural conclusion is that leverage may be used safely as a long-term investment vehicle during risk-on periods.
Figure 2. Equity plots of unleveraged and 2X, 3X leveraged portfolios – logarithmic scale.
Source: This chart is based on author computations
The graph in figure 2 shows that momentum strategies outperform buy-and-hold even during strong bull markets. Of course, their advantages are greater during bear markets or deep market corrections.
State of the Equity Markets
First, the indicators used in this article tells us that the market continues to be in risk-on state. The 3-month return of the base metals, DBB, is significantly larger than the corresponding return of the US dollar index, UUP. The return of consumer discretionary sector, XLY, has been negative lately, but its 3-month return is still greater than the return of consumer staples sector, XLP.
The US High Yield Option-Adjusted Spread has increased over the last week, but only marginally, from 3.40 to 3.54. It is still in a downtrend since May 2020. The US Leading Economic Index, LEI, has increased every single month since May 2020.
Nevertheless, there are some reasons to worry about an imminent market correction. Long term interest rates have been in a steady uptrend since August 2020. That has fueled a rise in inflation expectations, a strengthening of the US dollar relative to other major currencies, and increased volatility in equity markets.
The implied volatility index VIX has had some big oscillations lately, but it has retreated for the time being. VIX’s futures do not indicate a market in trouble.
One indicator we used extensively as a signal for market corrections is the return of the total bond market. The 3-month return of the total bond market has been negative since the beginning of the year.
Conclusions
The results of the simulations shown in this article illustrate the advantages and the risks in applying momentum strategies to portfolios made up of leveraged funds. Our main conclusion is that leveraged funds are associated with greater returns as long as they are used only when the market is in uptrends. It is, therefore, of utmost importance to improve the accuracy of the models used to determine the status of the market.
We have added a new set of indicators to assist in our assessment of the market state. We observe that the collection of indicators we use give divergent signals at this time. We plan to address the question of how to aggregate the responses of many indicators in our future research. At this time, we believe that the equity markets are in risk-on state, with some important changes in the sector’s relative strength.
This article was written by
Toma Hentea, PhD. is a University Professor Emeritus with extensive research experience in developing quantitative system models with application to financial markets. His market exposure is varied in accordance to the state of leading US and global economic indicators. Options and leverage are used to enhance the performance of his investments.
Toma leads the investing group Adaptive Momentum Investing, where he applies computational algorithms to evaluate the market state (risk on/off). He uses adaptive momentum strategies to construct robust stock and ETF quant portfolios, aiming at achieving double digit annual returns. Learn more.Analyst’s Disclosure: I am/we are long SPY, MDY. I wrote this article myself, and it expresses my own opinions. I am not receiving compensation for it (other than from Seeking Alpha). I have no business relationship with any company whose stock is mentioned in this article.
Seeking Alpha's Disclosure: Past performance is no guarantee of future results. No recommendation or advice is being given as to whether any investment is suitable for a particular investor. Any views or opinions expressed above may not reflect those of Seeking Alpha as a whole. Seeking Alpha is not a licensed securities dealer, broker or US investment adviser or investment bank. Our analysts are third party authors that include both professional investors and individual investors who may not be licensed or certified by any institute or regulatory body.
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Comments (59)
In the article involving Dow stocks the strategy was in risk-on 61% of the time. In the current article with three broad market ETFs the strategy was in risk-on for 43% of the time.
Your questions are excellent, but I have not done any research on combining bull and bear leveraged funds. My reasoning is that the equity markets are asymmetric, much longer time in uptrends than in downtrends. I prefer going to short term bonds or cash when in risk-off. Using inverse ETFs is harder to manage.
I check some sentiment indicators and have tried including them in simulations. The improvements I get are not significant. I need to do more research in that direction.
Momentum is far and away the best sentiment indicator ever identified. Further research is virtually certain to prove fruitless.
During risk-on periods the strategy is invested equally in the top two funds.
I did try with DOW instead of SPY. The performance was slightly worse with annual gains lower by 1% to 2%.
Drawdowns are the same, Sharpe is higher with SPY.
Unfortunately, the system I use for backtesting does not have access to mutual funds historical data. I consider using a commodity index and the US dollar exchange rates instead. Will write a new comment when I get some results.