Mando's Risk Parity Strategy [Hedgefundie's EA modification]

[Mando]

Inspired by HEDGEFUNDIE's excellent adventure [HFEA], Siamonds Simulating Returns of Leveraged ETFs, and Uncorrelated's A mean variance framework for portfolio optimization, I decided to create my own risk parity and mean variance approach using leverage. Please head over to these linked posts for more information.

What is your strategy

My strategy follows HFEA as I am a young (mid 20's) investor willing to take on increased risk. But I do not want to hold just 100% stocks or 100% leveraged stocks as that increases risks substantially. I also want to be covered in any sort of economic environment, from rising interest rates, inflation, deflation, etc. To do all of this, I set out to complete the following tasks:

1. Gather monthly data for Stocks (small, mid, large cap), Treasuries, Gold, Commodities, REITS, etc. Any asset that could be added to a portfolio.
2. Estimate leveraged returns for Stocks, Bonds and Gold monthly. See post: Siamonds Simulating Returns of Leveraged ETFs
3. Use Portfolio visualizer to calculate the efficient frontier and geometric efficient frontier of a asset mix using the above assets both leveraged and unleveraged.
4. Optimize asset allocation to reduce long draw downs. Sharpe Ratio, Sortino ratio, ulcer perf. ratio, etc.

1. Gather monthly data

Idealy, I wanted to gather monthly data for as many asset classes back to 1955 as I could. This time was spent scouring this forum, https://fred.stlouisfed.org/, Tyler9000's website Portfolio Charts, and others. I would then backtest what monthly data I collected with an ETF of similar allocation. The data needed to be accurate before leveraging it.

2. Estimate leveraged returns

Next step was estimating what a leveraged return for the specific asset would be. This is where Siamonds Simulating Returns of Leveraged ETFs post was extremely helpful. Using some of these equations, I simulated leveraged (2x & 3x) monthly returns for S&P500, small-cap, mid-cap, LTT's, etc. till 1955. Also, simulated gold back to 1972. Here is the 3x backtest's for S&P500 and LTT compared to relevant ETF's.
S&P500 3x (portfolio 1 is simulated):


LTT 3x (portfolio 1 is simulated):


Here you can see that the simulated leverage LTT's does break from relevant ETF (TMF). Further research is to be done to increase accuracy.

3. Efficient Frontier and mean-variance optimization

Portfolio visualizers historical efficient frontier calculator was then use to plot the difference between an efficient frontier of just 1x assets and an efficient frontier also including 2x/3x assets. Also plotted below is the Geometric Efficient frontier (Kelly Criterion). Both plots only consist of Stocks and bonds, no gold or REITs are used as backtest for gold only went back to 1969 (will be used in section 4.). The "Provided Portfolio" in this plot is Hedgefundies 55UPRO/45TMF Allocation.

Efficient Frontier consisting of Stocks and bonds (1955-2020): Red is 1x Leveraged, Blue is 1x,2x,3x leveraged


Geometric Efficient Frontier consisting of Stocks and bonds (1955-2020): Red is 1x Leveraged, Blue is 1x,2x,3x leveraged


Now I can set my asset allocation to either the max sharpe ratio or anywhere along the curve. So depending on my risk tolerance (standard deviation) or expected return needed, I can select a portfolio that provides that. This is where each individual can select a portfolio allocation based on there specific standard deviation risk tolerance. For the purpose of this post and my own allocation, I have selected to use a portfolio that gives the same return as Hedgfundies strategy during this time frame (17.2% return, 28.2% SD) but with a lower SD. This gives an expected return of 17.2%, SD of 24.6%, and an asset allocation of:

Mando's Portfolio v1[MPv1]: 3x ITT 7-10 yrs - 36%, 3x LTT - 6%, 1x Mid Cap - 18%, 3x Small Cap - 31%, 3x S&P 500 - 9%

Here is the portfolio returns from 1955 till 2020. Portfolio 1 is Mandos Portfolio, Portfolio 2 is HFEA [ 55UPRO/45TMF], Portfolio 3 is 60/40 stocks/bonds


HFEA strategy and this are about equal until 1967 where they split. Around 1975, the basic 60/40 strategy comes close to providing a better return in the short term. Overall, 60/40 unleveraged beats out the other two portfolio's in sharpe ratio during this time frame. Now what really scares me is the 67% and 72% max drawdowns for portfolio 1 (Mando's) and portfolio 2 (HFEA) respectfully.

4. Minimize drawdown

Now this section is optional if you only care about mean-variance optimization. I personally wanted to see if its possible to reduce the max drawdowns without hurting portfolio CAGR by a substantial amount. I stumbled across an interesting paper (PDF) months ago that describes the downsides of only using sharpe ratio as a portfolio metric (See Pg. 9 and 10). It then goes into detail about using the ulcer index and the downsides of just using that(See figure 4 and pg. 14). They then go on to create there own ratio call "Serenity Ratio" and "Pitfall indicator".

As PV does not provide these ratios when simulating returns, I created an excel sheet that would take the monthly returns data from PV and calculate the Serenity Ratio, Ulcer Index, and Pitfall Indicator. I decided to add in bits of gold (1x,2x,3x) and REIT's and by trial and error see if I could reduce the max drawdowns. I also used the solver function in excel coupled with Simba's backtesting spreadsheet with LETF's to help find an allocation of leveraged gold and unleveraged REIT's that would help provide this drawdown protection. This backtest could only go back to 1969 if including gold and 1972 if including REIT's. I would take an equal amount of allocation out of the stocks and bonds and transfer it to leveraged gold or REIT portion of the portfolio. The final result is...

Final Portfolio Allocation - Mando's Portfolio v2[MPv2]: 3x ITT 7-10 yrs - 32%, 3x LTT - 5%, 1x Mid Cap - 16%, 3x Small Cap - 28%, 3x S&P 500 - 8%, 2x Gold - 11%
Rebalanced Annually / Tax Advantaged Roth

Final Backtest (1972-2020): Portfolio 1 - Mando's Portfolio v2, Portfolio 2 - HFEA 55UPRO/45TMF, Portfolio 3 - 60/40 stocks/bonds


Another Backtest (1972-2020): Portfolio 1 - Mando's Portfolio v2, Portfolio 2 - Mando's Portfolio v1, Portfolio 3 - 100% Stocks (S&P 500)


Table of Data/Ratios

The final Mando's portfolio provides better downside protection, Sharpe ratio and Serenity Ratio, compared to HFEA (55UPRO/45TMF) at the same CAGR! It provides a lower Sharpe Ratio than just a 60/40 stock/bond allocation but much higher returns.

Final Thoughts

This portfolio will be useful to anyone that wants to try and capture some of the increased gains that HFEA's allocation does but with better downside protection. I have been allocating a portion of my portfolio to HFEA for the past couple years and plan on continuing that. I will be setting aside an allocation of 5-10%(or more) to this portfolio strategy. I am currently still in the process of optimizing the portfolio like shown in section 4 through my own excel sheets. For now, I have settled on the asset allocation given above.

This portfolio ended up being very close to what I originally hypothesized. That it would end up close to Ray Dalio's All-Weather Portfolio of 40% LTT's, 15% ITT's, 30% Stocks/SP500, 7.5% Gold, 7.5% commodities but leveraged and with a higher allocation to stocks. In my case, I did not have commodities to include so gold ended up becoming 11% of the portfolio.

This will most likely result in a part 2 where I finalize the portfolio allocation. I wanted to open up this thread as a means of getting feedback before I travel down the rabbit hole on this strategy even more!

What I would like to do next

• See if there is any way to model in a Volatility fund(XVZ) or any other volatility hedge

• Add in commodities, international, or utilities as another hedge. The data used is a very US centric approach and during a time period of increased returns of the US market. I would like to allocate a portion to international to hedge against a "lost decade" scenario like Japan in the 90's.

• Discuss and research the issues with using a 3x leveraged Small Cap fund

• Get better accuracy on some of the leveraged returns (3x LTT's) and get additional backtest data until 1955

• Research using options and futures to leverage this strategy instead of 2x and 3x leveraged ETF's

• Use Solver in excel in conjunction with Simba's backtesting spreadsheet including leveraged ETF's to optimize a portfolios Sharpe ratios, Serenity ratios, etc.

Let me know what everyone thinks!

[Callisto]

The over 100 page discussion on HFEA taught me a great deal. This looks pretty thought provoking, hope to see people challenge it.

fwiw I'm nearly 100% in HFEA with my tax advantaged accounts. Definitely interested in exploring this concept.

[Mando]

The over 100 page discussion on HFEA taught me a great deal. This looks pretty thought provoking, hope to see people challenge it.

fwiw I'm nearly 100% in HFEA with my tax advantaged accounts. Definitely interested in exploring this concept.

Yup, that's why I wanted to open up discussion on another similar strategy! I do think that this strategy does have a slight bias toward small cap since it has greater returns since 1955 than the S&P. Might be better off just lumping the stocks into one 3x fund and 1x fund. Then the same for bonds. What you would end up with is HFEA with a bit of gold to help the drawdowns.

[siamond]

Here you can see that the simulated leverage LTT's does break from relevant ETF (TMF). Further research is to be done to increase accuracy.

Draw the same graph, but start in 2011. It should look much prettier. Most leveraged ETFs displayed a weird trajectory compared to their benchmark in their first year of existence. Not sure why, but the Telltale charts are, well, telling. As a side note, I would strongly advise you use Telltale charts instead of Growth charts to analyze trajectories. This is much more informative.

Then TMF is an LETF from Direxion, not from Proshares or Profunds. I am usually quite impressed by the way Proshares and Profunds track their benchmarks. I am definitely LESS impressed by Direxion... As a side note, they closed (or redefined) a good number of their funds in 2020. I find hard to fathom how somebody could follow a long-term strategy with such company.

[RonSea]

Following this -- the strategy requirements you laid out are almost identical to what I've been thinking about lately. This is perfect timing too as I've been considering replacing PSLDX in my ROTH with a lower-risk HEFE strategy. The information you've laid out will definitely help a ton.

As for my initial thoughts:

First, 3X small cap seems.... questionable. The funds have awful volatility decay which likely worsens its performance compared to a leveraged S&P fund (https://www.portfoliovisualizer.com/bac ... 3_2=66.667).

Second, the heavy ITT treasuries over LTT are interesting. Most portfolios I've been playing around with I've included TYD (3x ITT) or SPTI (1x ITT) and I've been surprised at how little support there is in the HEFE thread for them. Especially right now with 10Y interest rates around 1%.

Third, I've been wondering if there is any way to reduce risk in a leveraged strategy by timing an addition of ~5% VXX based on market conditions. I think I saw someone in the HEFE whip-up a strategy that increased CAGR with a higher Sharpe but they mentioned a lack of rigor and simply toyed with variables until one worked. I'm sure many people have tried and failed to develop VIX market timing strategy and have failed spectacularly though.

I stumbled across an interesting paper (PDF) months ago that describes the downsides of only using sharpe ratio as a portfolio metric

Damn I almost feel called out. As a sharpe-chaser that's definitely a paper I'll be reading sometime soon.

[jarjarM]

How often will you be rebalancing? Will you be running this in a tax advantaged account or a taxable? It’s an interesting take so I’ll definitely follow the thread for discussion

[Marseille07]

I think you have too many buckets for all kinds of instruments. There's very little chance 11% Gold, 28% small cap etc etc would remain optimal outside of your backtested period. This is called curve-fitting, and the only way to combat that is to reduce your variables.

[000]

Rising interest rate scenario is still problematic. I wonder if mixing in TIPS or floating rate nominal bonds helps with that scenario.

[Mando]

As for my initial thoughts:

First, 3X small cap seems.... questionable. The funds have awful volatility decay which likely worsens its performance compared to a leveraged S&P fund (https://www.portfoliovisualizer.com/bac ... 3_2=66.667).

Second, the heavy ITT treasuries over LTT are interesting. Most portfolios I've been playing around with I've included TYD (3x ITT) or SPTI (1x ITT) and I've been surprised at how little support there is in the HEFE thread for them. Especially right now with 10Y interest rates around 1%.

Third, I've been wondering if there is any way to reduce risk in a leveraged strategy by timing an addition of ~5% VXX based on market conditions. I think I saw someone in the HEFE whip-up a strategy that increased CAGR with a higher Sharpe but they mentioned a lack of rigor and simply toyed with variables until one worked. I'm sure many people have tried and failed to develop VIX market timing strategy and have failed spectacularly though.

Yeah, I agree with the assessment of the small cap volatility issue. As a way to stay true to the data as I am an engineer , I left it alone and part of the results. It does follow reasonably well to the small cap ETF's. You can see in my original post on the geometric efficient frontier that 3x small cap provides a lower return and higher SD(also pictured below). I used the original efficient frontier in my analysis and not geometric. This might be the cause of the increased small cap exposure. Maybe a better way to capture the required 3x leverage of small caps would be options.



Portfolio 1 - 3x Small Cap, Portfolio 2 - 3x S&P 500


I believe the model selected ITT over LTT for volatility decay reasoning from the 1955-2020 time frame. You can see in the efficient frontier that ITT 7-10 3x provided a better return at a lower SD than either LTT 2x or 3x.

Yup, I have the same suspicions about adding volatility hedges. Check out XVZ too.

[Mando]

How often will you be rebalancing? Will you be running this in a tax advantaged account or a taxable? It’s an interesting take so I’ll definitely follow the thread for discussion

Woops, forgot to add that into original post. I will be rebalancing annually and running in a tax advantaged account (Roth IRA).

I think you have too many buckets for all kinds of instruments. There's very little chance 11% Gold, 28% small cap etc etc would remain optimal outside of your backtested period. This is called curve-fitting, and the only way to combat that is to reduce your variables.

Yeah, that's my thought process too. Later on I will post what happens when using just SP500 3x instead of the 28% small cap and same with removing LTT's and just doing ITT's (or vice versa). I would like to simplify the portfolio some more.

[bluerafters]

This should be a fun thread to follow.

[RonSea]

Yeah, I agree with the assessment of the small cap volatility issue. As a way to stay true to the data as I am an engineer , I left it alone and part of the results. It does follow reasonably well to the small cap ETF's. You can see in my original post on the geometric efficient frontier that 3x small cap provides a lower return and higher SD(also pictured below). I used the original efficient frontier in my analysis and not geometric. This might be the cause of the increased small cap exposure. Maybe a better way to capture the required 3x leverage of small caps would be options.



I believe the model selected ITT over LTT for volatility decay reasoning from the 1955-2020 time frame. You can see in the efficient frontier that ITT 7-10 3x provided a better return at a lower SD than either LTT 2x or 3x.

Yup, I have the same suspicions about adding volatility hedges. Check out XVZ too.

Doesn't an increase in expected volatility [which small caps have relative to the S&P] cause the options premium to increase and result in less profit? I genuinely don't know -- I've never traded options.

My guess is your model also does so well with ITT > LTT because of how high interest rates used to be. I assume with interest rates swinging much more substantially pre-2000 that the volatility of ITTs were more similar to the volatility of LTTs today.

[RonSea]

Mando 2 Portfolio:
111% bonds (96% ITT, 15% LTT)
124% equities (84% small, 16% mid, 24% large)
22% gold

[cos]

Can you post the efficient frontier and geometric efficient frontier transition maps so we know which asset allocations correspond to which standard deviations?

Great work by the way!

[firebirdparts]

Interesting work, nice job!

One thing that worries me about this timeframe, always, is that gold moves just the right way at just the right time, twice. The moves are huge. So in backtesting, you'll always get this fabulous volatility dampening from gold. I may be really wrong, but I think gold is dancing to its own tune and in the future, it may not do such a beautiful job. In fact I think it would be shocking if it did. The past is just too perfect.

[RonSea]

After looking into it more (both from simulations and siamond's thread) I'm pretty impressed by how well the smaller-capped 3x etfs perform. 28% small cap still seems wayyyy too high to be comfortable but I now see the decent argument for including mid or small caps in a risk-parity HEFE portfolio. I guess one reason they're not discussed is because the gains over UPRO are going to be pretty minimal and likely with a greater short-term risk.

[Ramjet]

The over 100 page discussion on HFEA taught me a great deal. This looks pretty thought provoking, hope to see people challenge it.

fwiw I'm nearly 100% in HFEA with my tax advantaged accounts. Definitely interested in exploring this concept.

How much do your tax advantaged accounts make up of your whole portfolio

[cos]

If you pop all of your simulated funds into Portfolio Visualizer's portfolio optimization tool and set the optimization goal to "maximize Kelly criterion", what allocation does it suggest? What if you set the optimization goal to "maximize Sharpe ratio"?

[Callisto]

The over 100 page discussion on HFEA taught me a great deal. This looks pretty thought provoking, hope to see people challenge it.

fwiw I'm nearly 100% in HFEA with my tax advantaged accounts. Definitely interested in exploring this concept.

How much do your tax advantaged accounts make up of your whole portfolio

Its sitting at 24% today. It was a lot lower when I started, but I rolled my 401k in and the strategy did exceptionally last year.

[Mando]

Your analysis also makes a big case for NTSX whose bonds are almost entirely ITTs. It's quite new but performs well (https://www.portfoliovisualizer.com/bac ... ion5_2=-50) and has a low expense ratio (NTSX average duration is 7.3 years, comparison made to IEI / IEF mix with average duration of 7.3 years).

Mando 2 Portfolio:
111% bonds (96% ITT, 15% LTT)
124% equities (84% small, 16% mid, 24% large)
22% gold

NTSX may be able to lower the volatility a bit with:

30% NTSX (27% S&P, 18% ITT)
5% TMF (3x LTT)
10% UGL (2x gold)
25% TYD (3x ITT)
25% TNA (3x small)
5% MIDU (3x midcap)

NTSX-Version Make-up:
108% bonds (93% ITT, 15% LTT)
117% equities (75% small, 15% mid, 27% large)
20% gold

I think NTSX could be especially great for anyone wanting to make a less leveraged HEFE portfolio without holding 3x ETFS in the long run. Some examples: https://www.portfoliovisualizer.com/bac ... tion9_3=10

After looking into it more (both from simulations and siamond's thread) I'm pretty impressed by how well the smaller-capped 3x etfs perform. 28% small cap still seems wayyyy too high to be comfortable but I now see the decent argument for including mid or small caps in a risk-parity HEFE portfolio. I guess one reason they're not discussed is because the gains over UPRO are going to be pretty minimal and likely with a greater short-term risk.

I have been a fan of NTSX(if someone wants to leverage) for this reason, especially in taxable. Later, I will do a full backtest of a simulated NTSX to see if there is any issues that could arise.

I think part of the reason small caps end up backtesting well in this case could have something to do with its volatility. Small caps would be demolished contrary to a large cap allocation before and during a recession. Then when rebalancing occurs the increased volatility helps juice returns.

Can you post the efficient frontier and geometric efficient frontier transition maps so we know which asset allocations correspond to which standard deviations?

Great work by the way!

No problem! Since there's a lot of data to parse through I made a Google Drive folder with both pictures of the different efficient frontiers and related transition maps. Also in the folder is the excel data for the efficient frontier points. I did an original historical run, a robust optimization run, and geometric mean run. The Robust Optimization run does look a little noisy as it shows really small amounts of AA to a specific asset(as expected). It might be useful to use the RO allocation to a specific asset (mid-cap) and leverage to the same percentage. For example, if midcap showed 1x 6%, 2x 3%, 3x 3%. It could just be shown as a 21% allocation to mid cap or 1.75x 12% (done by allocating only to 1x and 2x ETF's).

Interesting work, nice job!

One thing that worries me about this timeframe, always, is that gold moves just the right way at just the right time, twice. The moves are huge. So in backtesting, you'll always get this fabulous volatility dampening from gold. I may be really wrong, but I think gold is dancing to its own tune and in the future, it may not do such a beautiful job. In fact I think it would be shocking if it did. The past is just too perfect.

I agree. Maybe there is some confirmation bias going on. Or it could possibly be that in times of trouble/signs of it, people travel to what they feel is a "safe haven" asset. I would like to extend gold back to 1955 and also include commodities back to then too. Just need to find monthly data for it!

If you pop all of your simulated funds into Portfolio Visualizer's portfolio optimization tool and set the optimization goal to "maximize Kelly criterion", what allocation does it suggest? What if you set the optimization goal to "maximize Sharpe ratio"?

Also, placed this in the Google Drive Folder. Result are interesting for Kelly criterion Portfolio visualizer only goes back to 1972 with the test. It gives an AA of 49% 3x Small Cap, 42% 3x LTT's, and 9% 3x Gold. It shows a lot of volatility during a rising rate environment of the 70's I do think it is best to assume any allocation to small cap(or mid/S&P) should be taken to mean total market. Until I do additional research into the small cap backtests and figure out exactly why it is always showing up in the backtest.

Max Kelly vs. 60/40(20% 7-10 yr ITTs/20% LTTs) Stock/Bonds:



Maximize Sharpe Ratios is very similar to some modern day portfolios. It shows an allocation of 67.5% 1x ITT's 7-10 yr's, 24% 1x Mid Cap, 8.5% 1x Gold.

Max Sharpe vs. 60/40(20% 7-10 yr ITTs/20% LTTs) Stock/Bonds:

[kjm]

I've been tinkering with the HFEA portfolio as well. Here's something to consider...





You're picking two from TQQQ, TNA and TMF each month based on momentum. The two are weighted according to minimum variance. This is pretty risky of course because there are times when the portfolio doesn't have treasuries to hedge. Using TQQQ and TNA (rather than 100% UPRO) offsets this risk somewhat because TQQQ and TNA aren't 100% correlated. You could keep a core TMF position of say 30% and run this momentum approach with the remaining 70%.

Going back further with non-leveraged large-cap growth, small-cap value and long-term treasury funds...



Not sure why my images aren't working, but here are links to images 1, 2, and 3 respectively

https://ibb.co/1z5SmFc

https://ibb.co/SBxmmVN

https://ibb.co/YjSjNvM

[RonSea]

Earlier I mentioned that I could never see TYD be worth holding over EDV because of its expense ratio but after looking into it more I've completely changed my mind. TYD seems to have significant advantages over EDV. Even with the expenses TYD has higher CAGR, lower stdev, and more negative market correlation over most time-frames.

My next question was if EDV is worth holding over TMF. TMF has brought fantastic returns over the past few decades but, going by historic data, it's with significant risk and may be worse in the long-run.

I'm also intrigued by iShares' new ETF -- GOVZ. It's similar to Pimco's ZROZ but with a 0.07 expense ratio and what little data I can find seems to indicate it may have a slightly greater standard deviation.

If that's the case then GOVZ may end up being a decent fund to combine with TYD to reduce risk compared to holding TMF. Unfortunately, as GOVZ is new, its asset total are only 30 million and it lacks historical data. I don't have an answer yet for if EDV / GOVZ are worth holding over TMF but I'm going to keep looking into it a bit.

[Mando]

Earlier I mentioned that I could never see TYD be worth holding over EDV because of its expense ratio but after looking into it more I've completely changed my mind. TYD seems to have significant advantages over EDV. Even with the expenses TYD has higher CAGR, lower stdev, and more negative market correlation over most time-frames.

My next question was if EDV is worth holding over TMF. TMF has brought fantastic returns over the past few decades but, going by historic data, it's with significant risk and may be worse in the long-run.

I'm also intrigued by iShares' new ETF -- GOVZ. It's similar to Pimco's ZROZ but with a 0.07 expense ratio and what little data I can find seems to indicate it may have a slightly greater standard deviation.

If that's the case then GOVZ may end up being a decent fund to combine with TYD to reduce risk compared to holding TMF. Unfortunately, as GOVZ is new, its asset total are only 30 million and it lacks historical data. I don't have an answer yet for if EDV / GOVZ are worth holding over TMF but I'm going to keep looking into it a bit.

Simba's backtesting spreadsheet has a backtest of Long Term treasury STRIPS (EDV) going back to 1871. This is only yearly data though so it can't be input into Portfolio Visualizer. If there was a way to model monthly values and volatility from that, I could include it in my backtest from 1955 to 2020. For now, I simulated the yearly returns by using Simba's backtesting data for EDV and the ITT7-10yr 3x SIM I created. Plotted Below:

[siamond]

Simba's backtesting spreadsheet has a backtest of Long Term treasury STRIPS (EDV) going back to 1871. This is only yearly data though so it can't be input into Portfolio Visualizer. If there was a way to model monthly values and volatility from that, I could include it in my backtest from 1955 to 2020.

I finished updating my LETF monthly model with various improvements to the bond-centric simulation for the first few decades, before daily index data became available. Will publish soon.

I would have to think a bit harder about LT STRIPS. I never played with zero-coupon constructs, but it probably isn't that hard to do. I did assemble yields and returns for a 20-30 regular bond index, so that's a starting point.

[Mando]

I've been tinkering with the HFEA portfolio as well. Here's something to consider...





You're picking two from TQQQ, TNA and TMF each month based on momentum. The two are weighted according to minimum variance. This is pretty risky of course because there are times when the portfolio doesn't have treasuries to hedge. Using TQQQ and TNA (rather than 100% UPRO) offsets this risk somewhat because TQQQ and TNA aren't 100% correlated. You could keep a core TMF position of say 30% and run this momentum approach with the remaining 70%.

Going back further with non-leveraged large-cap growth, small-cap value and long-term treasury funds...



Not sure why my images aren't working, but here are links to images 1, 2, and 3 respectively

https://ibb.co/1z5SmFc

https://ibb.co/SBxmmVN

https://ibb.co/YjSjNvM

I have been interested in the minimum variance strategy that had been presented in HEDGEFUNDIE's thread a few times using portfolio visualizers Adaptive Allocation model. See Here: viewtopic.php?p=5385799#p5385799 and viewtopic.php?p=4678164#p4678164

I still want to look into it more but it could be promising! Let me know your thoughts.