The Morpheus ETF Strategy: Combining the Blue Pill and the Red

Home » Blog » Strategy Development » The Morpheus ETF Strategy: Combining the Blue Pill and the Red

A guest post by Tom Gnade.
Are you also interested in sharing your thoughts? Contact us!

Several years ago, the Logical Invest whitepapers first introduced me to rotation investment strategies. After some research, I subscribed to the MYRS (the “Maximum Yield Rotation Strategy“), with good results. It was the first paid investment subscription I had ever used. I moved on to another service to learn options trading, and did well for two years, until a number of sharp setbacks made me come to terms with my investment goals.

After further reflection, here is what really matters to me:

  • Consistency. One must have clear goals and consistent methods for selecting, entering, and exiting positions. Emotions make for very bad decisions.
  • Efficiency. I work two jobs and love spending time with my family. I can’t spend hours each day actively managing investments and assessing risk.
  • Risk management. I need a method that consistently redistributes risk, and that doesn’t rely on my own knowledge or intuition, which are so often flawed. It is too easy to chase gains and too difficult to recoup the inevitable losses.
  • Objectivity. I am not in finance, and I don’t have the knowledge required to manage investments in individual stocks, where risk is difficult to predict at best. Programmatic investing substitutes objective rules for guesswork.
  • Simplicity. I don’t want to manage too many investments at the same time. I like the aesthetic appeal of simplicity, which has the added benefit of limiting transaction costs.
  • Results. I hate drawdowns, especially ones that take a long time to recover. I don’t mind volatility, as long as it slopes up. I love gains. Big gains. Go figure.

So, that’s it. I need a fast, precise, powerful, scientific method shown to perform through thick and thin. Only an automated investment strategy can hope to fulfill these requirements.

In the time since I last used Logical Invest services, they have expanded their offerings to include several different and interesting approaches, and for some time, have been discussing a “strategy of strategies”, which I found very intriguing. After a long wait, they finally released QuantTrader (QT) rather than publishing an SoS solution. This is a far more powerful tool, since it not only provides access to all of their offerings, but also allows for full customization and testing. For example, I’ve been able to build a solution for my company’s 401(k) offerings, which are extremely limited, with acceptable results.

Starting with QuantTrader

I started using QT during a free trial period, during which I learned how to use the software. There isn’t a big learning curve – there are just a few screens used to configure settings, manage symbols, build portfolios, and backtest strategies. It isn’t pretty, and it can be unstable, but that’s typical for new software. The focus isn’t on UI/UX or QA yet. Rather, it is designed with a singular purpose: to build and evaluate rotation strategies, and that it accomplishes well. It’s promising that in 2 months, I’ve already seen 3 releases with bug fixes, and the development team is openly soliciting feedback.

While QT supplies a number of built-in strategies, I immediately set about building my own. Using the existing strategies as a benchmark, I’ve back-tested dozens of combinations in an effort to improve upon them. Most of the time spent with the software is testing various combinations, adjusting parameters, and re-tuning. I’ve invested time over the past 2 months off-and-on with it, and have developed a solution with outstanding results. Even so, I’m still unsure of the meaning of certain settings and parameters. The help documentation is limited, but it is enough to get things started. The dozens of failed experiments help develop a sense for how various combinations and settings will work together. I mostly resorted to brute force, repeatedly backtesting combinations that hold my interest.

Guidelines for Strategy Development

A few general rules are important when developing strategies. You must have a basic understanding of the built-in strategies and ranking algorithms, and use creative combinations. Typically, strategies with dissimilar approaches but similar volatility and returns pair well. Keep the tuning tweaks to a minimum, and only change one at a time. Backtest repeatedly. Look for solutions in the optimization window that are stable, meaning there aren’t large step-changes if you look a few cells in any direction. I tend to avoid overly short or long lookback periods. Sometimes, changing the rebalancing period or volatility limit can have positive results, but usually it’s best to leave those settings alone. Let the optimization choose the lookback period and volatility attenuator for you, but don’t be afraid to choose options with slightly lower performance that are more stable. Change up the ranking method and number of ETFs to test any available combination, as well as the maximum and minimum allocation percent. More recently, I’ve also found it useful to adjust the maximum allocation percent for an individual investment in the Portfolio Manager, or to adjust the volatility multiplier in certain circumstances.

To be honest, none of this needs to be done to achieve an acceptable result. For example, I have very few investment options in my 401(k). Essentially, I can choose SPY, AGG, or cash. By adding the two to a portfolio, and backtesting using the SRRP ranking with no adjustments whatsoever, a 12% CAGR results from 2007 to present, versus 7.2% for SPY, and maximum drawdown is reduced from -55.19% to -15.02%.

The Morpheus Strategy

My current champion strategy, a simple but powerful variant of what is now being referred to as The Beast in the QT forum, rotates monthly between two distinctly different sub-strategies, each of which is a meta-strategy composed of 2-3 different Logical Invest core strategies. Both sub-strategies rotate monthly using the “SR” ranking method, with maximum allocations of 60-70%, so they are always each invested in either 2 or 3 core strategies.

The first sub-strategy, The Blue Pill, offers a lower-volatility baseline. It combines the BRS and GLD-USD core strategies, ranking them by the SR top 2 method, with 60% maximum and 0% minimum allocations. The strategy uses monthly rebalancing and a short lookback period of 24 days. Each of the underlying strategies has also been modified. The BRS strategy uses monthly rebalancing with a 78 day lookback period, SR top 2 ranking with maximum 60% and minimum 40% allocations. The GLD-USD strategy uses monthly rebalancing with a 48 day lookback period, DR top 1 ranking with maximum 100% and minimum 0% allocations. It also uses a -150 mean reversion weight with 4 day mean reversion period. The Blue Pill achieves a 5 year CAGR of 12.4%, Sharpe Ratio of 2.06, volatility 6%, and maximum drawdown of -5%.

The second sub-strategy, The Red Pill, combines 3 aggressive market-risk core strategies, Nasdaq 100 Hedged, MYRS, and UIS SPXL-TMF 3x Leveraged. It ranks them using the SR top 3 method, with 70% maximum and 0% minimum allocation. Each of the underlying strategies has also been modified. The Nasdaq 100 Hedged strategy uses monthly rebalancing with a 26 day lookback period, and ranks the top 2 ETFs using the SR method. The strategy allows 100% maximum allocation and 0% minimum. The  MYRS strategy uses semi-monthly rebalancing with 42 day lookback period. It uses the SR top 2 ranking method with 100% maximum and 0% minimum allocation, and uses a -100 mean reversion weight with 3 day mean reversion period. The UIS SPXL-TMF 3x Leveraged strategy uses monthly rebalancing with 72 day lookback period, and uses the SR top 2 ranking method. It allows 100% maximum and 0% minimum allocation, and uses a -100 mean reversion weight and 4 day mean reversion period. The strategy uses monthly rebalancing and a lookback period of 122 days. The Red Pill achieves a 5 year CAGR of 53%, Sharpe Ratio of 2.7, volatility 19.6%, and maximum drawdown of -12.7%.

Morpheus, the top-level strategy, allocates monthly between The Blue Pill and The Red Pill, ranking them by the SR top 2 method, using a 144 day lookback period. It uses a maximum allocation of 60%, and minimum of 0%. The level of risk exposure can be reduced by choosing a lower maximum allocation percentage, or by applying a volatility limit. At 60% maximum allocation, the strategy achieves a 5 year CAGR of 35.8%, Sharpe Ratio of 2.7, volatility 13.1%, and maximum drawdown of -7%. Its 1 year CAGR is 52.2%, Sharpe Ratio of 4, volatility 13.1%, and maximum drawdown of -4.3%.

I caMorpheus Investment Portfolio VIX Nasdaqll this strategy Morpheus, because he is the Greek God of Dreams, and because he found Neo in the Matrix, and let him choose the blue pill or the red.

“After this, there is no turning back. You take the blue pill—the story ends, you wake up in your bed and believe whatever you want to believe. You take the red pill—you stay in Wonderland, and I show you how deep the rabbit hole goes. Remember: all I’m offering is the truth.”

The Blue Pill combines two very different core strategies, the BRS (Bond Rotation Strategy) and GLD-USD, a clever method to invest in gold. The optimization results are extraordinarily stable. It outperforms BRS in CAGR, volatility, and drawdown, and dramatically outperforms USD-GLD in volatility and drawdown. The strategy is simple, and uses at most 4 concurrent investment symbols, though the symbols do frequently rotate.

The Red Pill combines 3 aggressive market-risk strategies with very dissimilar approaches. The Nasdaq 100 Hedged strategy is the main driver of growth. It invests in the top 4 symbols from the Nasdaq 100 in equal portions, and hedges that investment against TMF, a triple-leveraged 20+ year US Treasuries ETF. The strategy returns astounding results, but has worrisome levels of volatility and drawdown that would shake out all but the most stoic of investors. The second strategy, the MYRS, invests in an inverse volatility ETF that was the subject of Frank Grossman’s first Seeking Alpha article, ZIV. That ETF is also hedged against TMF for results almost as impressive as the Nasdaq strategy. The third strategy, UIS-SPXL-TMF 3x Leveraged, invests in SPXL, a triple-leveraged S&P 500 index ETF, which is also hedged using TMF. The combination of these three different approaches retains most of the CAGR of the Nasdaq 100 strategy, while reducing volatility and drawdown below any of the strategies alone. The Red Pill is slightly more complex than The Blue Pill  it is always invested in 5-7 different symbols. The optimization results are less stable, but are still extremely good, given the underlying volatility.

I have since gone on to develop several improvements to Morpheus that outperform these results, with the most complex implementation called (of course) The Matrix, which achieves a 5-year Sharpe ratio of 3.1. That strategy, however, is for another day.

Morpheus Current Allocations

The Morpheus strategy, then, invests in 9 to 11 symbols that will rotate fairly regularly on a monthly basis. One of the underlying strategies (MYRS) rotates on a semi-monthly basis, and so must be tended to twice as often. The monthly trading costs should be reasonable, but when added to the subscription cost, it sets a floor on the reasonable investment amount you might expect to manage.

The current allocations for this strategy are:

  • The Red Pill: 60%
    • Nasdaq 100 Hedged: 20%
      • Nasdaq 100: 70%
        • CSX: 25%
        • MU: 25%
        • NFLX: 25%
        • WDC: 25%
      • TMF: 30%
    • MYRS: 70%
      • ZIV: 80%
      • TMF: 20%
    • UIS SPXL-TMF: 10%
      • SPXL: 70%
      • TMF: 30%
  • The Blue Pill: 40%
    • BRS: 60%
      • PCY: 40%
      • CWB: 60%
    • GLD-USD: 40%
      • YCS: 30%
      • GLD: 70%

Notice that at each level, the allocations sum to 100%. To find the actual allocation to each market symbol shown in bold, all of the superseding percent allocations must be multiplied together. For example, CSX would be 25% of 70% of 20% of 60%, or 2.1% of the portfolio, while the net TMF investment would be (30% of 20% of 60%) + (20% of 70% of 60%) + (30% of 10% of 60%), or 13.8% of the portfolio. I’ve built a spreadsheet to help me calculate these percentages and determine the buy/sell signals for each symbol, which is proving to be a very useful tool when the time comes to execute the trades. QuantTrader does have integration with Interactive Brokers, and it looks like the trades could be executed through the IB API from QT directly, but I have not yet moved my funds to IB or experimented with those features.

Summing It Up

Overall, I am quite happy with QuantTrader. It allows the rapid prototyping and evaluation of simple investment strategies that can achieve results that would be impossible even for some hedge funds. I look forward to continued experimentation, and to possibly helping shape some of the feature set and improving its stability. It is a democratization of investing, providing a simple, powerful, and inexpensive tool for achieving investing results we might have once only dreamed of.

2017-05-05T12:10:56+00:00 By |25 Comments

About the Author:

I've worked in IT in the energy industry for most of my career. I also teach biology courses at a local community college at night. I have a long-standing interest in investing. Quantitative methods appeal to me, as does the objectivity of rules-based rotation strategies.


  1. Mohamed 04/21/2017 at 3:39 pm - Reply

    Thank you Tom for sharing your great analysis. Can you share your volatility attenuator for the Morpheus strategy and also your optimum lookback days for each of the subgroup and the total strategy. I had difficulty coming up with a clear optimized setting. It would be deeply appreciated if you can link your spreadsheet.

    • Tom Gnade 05/05/2017 at 1:11 am - Reply

      I updated the article with all of the lookback periods and other settings you should need to obtain the same results. If you still have any trouble, I’ll put together a custom .ini file for you. If you’re still interested in the spreadsheet I could share a template of that too.

  2. Derrick 05/06/2017 at 2:52 pm - Reply

    Thank you for your post, this is very interesting. I trade generally the same combination of strategies and get similar results but not quite as good. 20% BRS, 25% MYRS, 10% 3xUIS, 25% NASDAQ, 20% Gold/Currency. CAGR 27% Volatility 11% Sharpe 2.47 MaxDD -7.78% (According to the online portfolio analyzer which goes back to mid 2008). The Max DD was in 2015 when the return was only 5.61%. How did your Morpheus strategy do in 2015? I’m curious too what your thoughts are about whether your process using the Quantrader software may be susceptible to curve-fitting or over-optimization? That being said, simply putting 20% into each of the 5 strategies you use does yield similar results, which I think is a good sign.

    • Tom Gnade 05/08/2017 at 12:41 pm - Reply

      Morpheus returned 17.5% during 2015. The Matrix returned 27.5% during the same period.

      As you point out, a simple SRE 5 (20% fixed allocation) combination of BRS, GLD-USD, UIS, Nasdaq 100 Top 4, and MYRS returns 5-year CAGR 29.6%, Sharpe ratio 2.43, volatility 12.2%, drawdown -9.2%. Morpheus returns 5% more annually, with a much higher Sharpe, slightly higher volatility, and much lower drawdown of a little over 7%. It would, however, incur significant trading cost. The fear I have with an SRE strategy is that it could perform quite poorly during a significant market pullback, because it has no mechanism to reallocate to a safer mix. I feel much safer knowing there is a gearing mechanism involved, even if it costs me in terms of transaction costs. The longer the lookback periods, the less often a rotation strategy will bother with such changes, so that’s one option – combine a simple SRE and an SR variant with long lookback periods, and only use the SR option as a fall-back plan. That’s what I love about this software, I can follow any idea like that and see how it would pan out.

      My biggest concern right now is the lack of sufficient historical data to use when modeling these strategies, something I’m going to deal with in the next month or two by getting a good set of synthetic prices working properly in the software.

      I think any rotation strategy could be called “curve fitting”, but the more consistent the underlying strategies are in terms of volatility and returns over time, the less susceptible to extremely variable returns the top-level rotation strategy will be. I tend to use the longest possible history ranges when choosing lookback optima for that reason, because it represents a long-term “hot spot”. In the end, the historical analysis is just a statistical method to posit future results, and there are of course no guarantees. If a rotation strategy is always invested in several very different underlying mechanisms, then a black swan in any one of them will hopefully not cause the model to break down completely. The best test would use real data back at least prior to the 2000 market events, so both that and the 2009 round trip are taken into account. A stress test could use synthetic “what if” data to model a complete breakdown in one or several of the strategies, and observe how the top-level rules navigate such an event. If, for example, North Korea decided to drop a nuke, there are going to be some very severe and very sudden market moves. Rather than being caught completely off-guard with no plan, however, a rotation strategy will calmly and routinely reanalyze the situation at the next allocation cycle, regardless of the various unbearable losses everyone has suffered.

      • Derrick 05/08/2017 at 2:24 pm - Reply

        Thank you for your reply Tom. You’ve inspired me to want to dig deeper to understand this better. I asked about 2015 because the whipsaws in the traditional SRE mix of strategies was concerning after July/August. I realized how dependent I am on TLT/TMF remaining uncorrelated to equities (in 2011 treasuries worked quite well as a hedge, but 2015 was different). I think you are on to something by trying to find a way to get even more defensive more quickly during market corrections. My hunch is that a majority of the superior returns from your approach over the past 5 years occurred between July-Dec. 2015. Which is precisely the type of market you need these strategies to perform.

  3. vulcan 05/06/2017 at 5:21 pm - Reply

    Can someone provide details on SRRP Ranking formula mentioned in this article?

  4. Mohamed Yosry 05/07/2017 at 10:00 am - Reply

    Excellent work. Tom, you make Logical Invest inspiring. We appreciate sharing your research and we are looking forward to “The Matrix”.
    It ‘d be great if you can link the Spreadsheet and an .ini file because when I run optimization for 10 years, I get slight variations with the lookback period. Do you think optimizing at different dates changes the results?

  5. steve freeman 05/07/2017 at 10:39 am - Reply


    With your experience with the software I was wondering if you could provide a little insight into the calculation of modified sharpe. I’ve seen differing explanations from Alexander and Frank. I initially thought that the volatility attenuator was the only difference between it and regular sharpe. But now it seems as though its calculated like a Z-score. Any clarification would be appreciated.

    • Alexander Horn 05/08/2017 at 3:06 pm - Reply


      I guess you refer to Frank’s statement below in the US Sector Article. We simply normalize / rescale to a 1 scale as Frank mentions to avoid issues with negative values in the ranking, but do not use a Z-Score, which would further involve dividing by the mean return over a certain period.

      Image two assets, both with negative return of -5%, but the first with a volatility of 10%, the second of 15%, assume further a volatility attenuator of 1. Without normalization the first would have a modified sharpe ratio of -0.5, the second of -0.3. So the second would be ranked higher, as being “less negative”, despite having a higher volatility. With the normalization the ranking flip-flops as needed.

      Hope this helps, let´s continue discussion in this forum entry:

      US Sector Article: “We normalize the returns because we want to rank also the SPDR sectors ETFs with negative return. The normal Sharpe calculation (Return/Volatility) can only be used for ETFs with positive return. Normalizing means that we use 1.05 for a +5% performance or 0.97 for a -3% performance. The volatility is normalized the same way.”

  6. jmclean907 05/09/2017 at 12:21 pm - Reply


    I too, was wondering if you could share your .ini file and spreadsheet. I am using a strategy of 25% each of BRS, MYRS, GSRLV and Nasdaq top 4. The results are good, CAGR of 25% and sharpe ratio of 2.31 but not as high as your strategy. That is an interesting use of the GLD strategy. I was wondering if using it could lower the overall volatility of a set of strategies. It looks like you have potentially achieved that. Please feel free to contact me.

  7. Tom Gnade 05/09/2017 at 1:23 pm - Reply

    Spreadsheet for this strategy:
    .ini file for this strategy:

    This .ini file started as the one Frank included with release 315S. I’ve changed a few values in the underlying strategies from the article above, but the end result is similar (5-yr CAGR ~36%, Sharpe 2.8, vol 12.8%, draw -8.1%). After you download the .ini file, save it in your QT folder for future reference and rename it to remove the “.txt” extension. I also always save a copy of the original QT .ini file as “QuantTrader_Original.ini”, so I can easily revert back if needed. Make a copy of the Morpheus .ini and rename it to “QuantTrader.ini” in the same directory as the QT executable. If you make changes that you really want to save before you do further experiments, save a copy of the .ini file with a distinctive name, so you can revert back to it at any time.

    If you have any questions, feel free to ask!

    • Dominick Brunone 05/10/2017 at 10:31 am - Reply

      Great article Tom. I am new to LI, but would love to use this model as a go-by to help me learn the QT capabilities. Would you kindly send the .ini file as well? Thanks in advance.


    • Mohamed Yosry 05/11/2017 at 7:03 pm - Reply

      Thank you Tom and we are looking forward for your future contributions.

    • Dominick Brunone 05/13/2017 at 3:38 pm - Reply

      Thanks much Tom.

      In my QT folder, the .ini file ends with “.ini” but it is still identified as a text document type by Windows. I assume that’s ok. I also renamed the Original as you suggested.

      My problem is how do I get the app to recognize the Morpheus file? It doesn’t show up in the “Portfolio” window drop-down in the upper left-hand corner. I’ve read the getting started directions, but cant seem to find a reference. Thanks in advance.

  8. Mohamed Yosry 05/13/2017 at 5:03 pm - Reply

    If I may answer Dominick, first right click on Tom’s downloaded text file and rename it QuantTrader.ini then create a new folder and move it there. Copy QuantTrader315S.exe and past it in the new folder with the ini file. Then double click on the exe file to run the program and you will find Tom’s Morpheus strategy there. I hope that helps.

  9. Dominick Brunone 05/13/2017 at 7:13 pm - Reply

    Thank you for the reply, Mohamed, and I followed your instructions carefully, but was still not able to get either Portfolio manager or backtester to populate the pulldowns with morpheus.

    I am working on Windows 7 and using Google Chrome. What can I possible be doing wrong?

  10. Mohamed Yosry 05/13/2017 at 10:19 pm - Reply

    It seems you have another ini file in the new folder you created. When you download QuantTrader from this link (make sure you download the latest version which is 315) you end up with 2 files, ini & exe. Copy only the exe file to an empty new folder then put Tom’s ini file there. Make sure that you change name to “QuantTrader.ini”

  11. Dominick Brunone 05/14/2017 at 2:31 pm - Reply

    Mohamed – I really appreciate your patience and willingness to help. I also did what you just said in your latest note.

    However, it appears that even though I change the name of the file, its File Type remains the same.

    In the Portfolio file that is downloaded with QuantTrader, the file type is “Configuration settings (.ini)”

    After the name change that you indicated, Tom’s file type is still “Text Document (.txt)”. I went into the “Details” tab of File Properties, but could not change the file type. Perhaps there is a Windows security issue in play?

    Were you able to do as Tom indicated? Thanks again.


  12. Mohamed Yosry 05/14/2017 at 5:02 pm - Reply

    Here is a link for the renamed file, you can download it directly, put it in a new folder then copy and paste exe file (QuantTrader315S.exe) ONLY to the new folder (so the new folder will contain 2 files only the downloaded ini and the exe). I hope that works.

  13. Dom Brunone 05/14/2017 at 8:12 pm - Reply

    Mohamed – Done. Only 2 files as you say, in the new folder.

    Now when I double click on the 315S.exe to start the program, it asks me whether or not i wish to update the files. But either way I respond, it adds about 300+ files to the same folder. And when I go to the portfolio manager, it doesn’t have the word “Morpheus” as a portfolio name, just “0 LI Strategy of Strategies”. The returns look nothing like what is indicated in the Morpheus article.

    I’m stumped. Thanks for all your help, and I don’t blame you if you wish to give up. If you have any other ideas, or if anyone else wants to chime in, I’m all ears.

    Thanks so much for your efforts.


  14. Mohamed Yosry 05/14/2017 at 9:56 pm - Reply

    Sorry you had to go through all that trouble, but it is there. When you open the program and see the colored graphs, there is drop down menu under Portfolio in the upper left corner ( where you see 0 LI Strategy of Strategies) just click of the arrow and you can see all strategies including “The Blue Pill”, “The red Pill” and “Morpheus”. All you have to do is to click on it. It will be a good idea to watch, or re-watch the tutorial video. I just couldn’t help it to see someone missing on Tom’s great effort creating the Morpheus Strategy.

  15. Dom Brunone 05/14/2017 at 11:15 pm - Reply

    Mohamed – Thank you so very much, upon reloading again, I do see it now, and the returns are now also consistent with the article.

    I really appreciate your helping me through this, I do agree with you that Tom has created a gem here and that it will serve as a go-by to help me get fully up to speed. Your willingness to help me illustrates the value of a Forum like this. I count you as a valued e-friend.


  16. Mohamed Yosry 05/15/2017 at 9:42 am - Reply

    Don, I am glad it worked out. I got myself a lot of help and assistance which emphasizes your point about the quality of the forum. The person who deserves credit is Tom Gnade. He put together a great strategy and was generous sharing it. Although QuantTrader has very good stand-alone starategies, but Tom made a comprehensive integrated one with high return relative to risk. Contrary to “Strategy of strategies” which is impossible to rebalance monthly, “Morpheus” has limited equities to rebalance and surpasses the former in performance.

    • Tom Gnade 05/15/2017 at 1:37 pm - Reply

      Thanks for helping Dom out.

Leave A Comment