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Building Risk Parity with Leveraged ETFs

Welcome back. Or, if you are new to Composer and our blog, check out last week’s write-up on the implementation of risk parity. And then, come back to this blog and read the “welcome back” line again. 

Want the TLDR on last week's blog? Risk parity is an investment strategy that weights assets by risk (volatility) instead of dollar amounts (e.g., 60/40). Retail investors face several challenges implementing risk parity, including using leverage, measuring volatility, and updating portfolio allocations. Critics of risk parity point to volatility as an inadequate risk measure and the overweight to bonds as a drag during rising-rate environments. Research from AQR demonstrates that risk parity can outperform over time even through periods of prolonged rising rates. Composer can help investors create and manage risk parity strategies.

Phew. Maybe I should write shorter blogs.

Now that we have a basic understanding of risk parity, let’s have some fun building strategies using the Composer platform. 

Well before that – a quick note. Investors should not underestimate the jump from a simple (unlevered) risk parity portfolio to one that uses 3x leveraged ETFs. The levered portfolio requires a different risk tolerance and willingness to manage a more complex portfolio. 

Leveraged ETFs come with their own risks and nuances. Leveraged ETFs will not be a perfect match to the intended exposure due to daily rebalancing and higher than average fees. The difference in leveraged ETF returns compared to intended exposure may be greater during periods of high volatility. It is always important to DYOR (do your own research) and review ETFs prospectuses and historical performance before investing.

Relatedly, investors need to understand their own, personal risk tolerance…ultimately only you know how strong your stomach is. Ask yourself, what would you do if your portfolio was down 44% (the Max Drawdown for #HFEA). If the answer is panic and sell everything, leveraged ETFs likely aren’t for you. However, what Composer can help with is managing a complex portfolio.

If you are the impatient type, here are the three symphonies discussed in today’s blog:

Risk Parity Dynamic Leverage

Risk Parity Dynamic Asset Allocation

Kyle’s Risk Parity

Building Automated Investment Strategies

Alright, let’s build some stuff. 

One of the things I love about Composer is the playful nature of building portfolios. It is easy to add assets, structure the portfolio, create trading rules, backtest the strategy, and iterate on it. Call me a nerd. That’s fine.

A helpful place to start is modifying an existing symphony. Let’s use Hedgefundie’s Excellent Adventure Refined (#HFEAR), which systematically reduces risk (volatility) by shifting to relatively lower risk assets, like treasuries, gold, TIPs, and corporate bonds when SPY experiences a 10-day Drawdown of 5% or more. What if we took this logic, systematically reducing risk in response to market changes, and evaluated other ways to implement it?

Three approaches to reduce volatility jump to mind: 

  1. Reduce leverage

  2. Shift allocation towards relatively less risky assets

  3. Increase diversification 

Let’s take them in turn, starting with reducing the leverage of the portfolio. Hedgefundie’s Excellent Adventure (#HFEA) symphony holds 3x ETFs in a static allocation while #HFEAR shifts into unlevered ETFs during the Risk Off trade. In the below symphony, I created a strategy that dynamically reduces leverage but not to zero. As with #HFEAR, I have two potential scenarios: a Risk On scenario and a Risk Off scenario. And to keep things simple, I have the same trading logic as #HFEAR – Risk Off is when the 10-day Max Drawdown of SPY is greater than or equal to 5%, otherwise the symphony is Risk On.

Hedgefundie's Excellent Adventure Refined with 2x leveraged ETFs

The symphony shifts from UPRO and TMF (3x leveraged ETFs) to SSO and UBT (2x leveraged ETFs) if SPY experiences a 5% Drawdown in a 10-day period – rebalanced weekly. In a backtest from September 6th 2010 through February 7th, 2022 (longest period we have data), the symphony demonstrates similar characteristics to #HFEAR; however, this dynamic symphony maintains its risk parity position in Risk Off markets. Relative to #HFEAR, this symphony is slightly more volatile (23% vs. 21%) and has a higher Max Drawdown (32% vs. 21%).‍

Hedgefundie's Excellent Adventure Refined investment strategy with reduced leverage performance.

Performance from Sept. 6th 2010 - Feb 7th 2022. Return statistics presented have been generated using historical backtest simulation, which excludes fees and transaction costs which may significantly impact actual relative performance.

Now let’s take the second bullet. What if, instead of adjusting leverage, we shifted asset allocations during Risk Off? Here, I created a symphony that invests 60% in UPRO and 40% in TMF during Risk On and flips the allocation during Risk Off (40% UPRO and 60% TMF). This is the result:‍

Performance of Hedgefundie's Excellent Adventure Refined investment strategy with dynamic asset allocation

Performance from Sept. 6th 2010 - Feb 7th 2022. Return statistics presented have been generated using historical backtest simulation, which excludes fees and transaction costs which may significantly impact actual relative performance.

Looking at the same back test period as before, we see that the dynamic asset allocation symphony falls somewhere between #HFEAR and #HFEA. The shift in asset allocation reduces some of the volatility compared to #HFEA as shown by slightly lower standard deviation and Max Drawdown, but the symphony remains fully invested in UPRO and TMF, creating a much more volatile ride than #HFEAR. As we discussed last week, another way to implement dynamic asset allocation is to use the inverse volatility weighting for UPRO and TMF. 

This is what I love about Composer. I can take investing concepts and put them to the test, quickly comparing symphonies and building on the thinking. ‍

Putting it all together

I had a professor who said during a lecture once, “if we were at [rival school], we’d end the lecture here. But we are not at [rival school], so we will go deeper”. I’ll be honest, that got me a little pumped up for Tax Strategy. School competition aside, I like to think that if you are reading this blog you might also take pride in going deeper. Maybe you weren’t happy with how deep [insert rival retail investing platform] went and that's why you’re here. 

So deeper we go…

Let’s put the concepts of both symphonies together. That means, in the Risk Off environment, we simultaneously reduce leverage and the allocation to equities. And let’s also add some more diversification. We can add additional market coverage through leveraged ETFs for 7-10 year treasuries, small-cap stocks, and mid-cap stocks. Further, we can add 20% of the portfolio to diversifiers which include commodities, TIPs, emerging market bonds, and international stocks. Lastly, for each asset class, we use the inverse volatility weighting to adjust the allocation based on the previous 120-day volatility of each ETF. The symphony is rebalanced on a weekly basis.

This is what the symphony looks like:

A risk parity investment strategy that dynamically adjusts leverage and asset allocation based on market data.

In Risk Off, the risk parity allocation is split 40% equities and 60% fixed income and I use 2x leveraged ETFs (SSO, UBT, UST), except for mid-cap and small-cap equities (IWR, IJR) which are unlevered. My assumption here was that smaller-cap stocks are already more volatile and generally perform worse in down markets. 

In Risk On, we flip the allocation and invest 60% in equities and 40% in fixed income. I use 3x leveraged ETFs (UPRO, TMF, TYD), except for mid-cap and small-cap equities which are leveraged 2x.

A risk parity investment strategy that dynamically adjusts leverage and asset allocation based on market data.

Lastly, here are the diversifiers:

A diversified risk parity investment strategy that dynamically adjusts leverage and asset allocation based on market data.

To summarize the moving parts:‍

Summary of a risk parity investment strategy that dynamically adjusts leverage and asset allocation based on market data.

Within asset classes, ETFs are weighted by their Inverse Volatility. ETFs with higher volatility will receive lower weightings based on the past 120-day volatility.

So what’s the result? Well before we get to that, there are a few things that I like about this symphony. First, it’s based on risk parity which has a strong academic and practical foundation. Second, it adjusts to market environments, seeking to reduce risk during turbulent times, but it maintains its risk parity orientation. Lastly, it pulls in additional asset classes (e.g., commodities, TIPs) and sub-asset classes (e.g., international stocks) for diversification. And yes, I did name this symphony Kyle’s Risk Parity. It’s one of the perks of the job.

The backtested performance of a risk parity investment strategy that dynamically adjusts leverage and asset allocation based on market data.

(Backtest for as long as ETF data is available September 30th, 2015  - February 7th, 2022)‍

My risk parity strategy returns ~19% on an annualized basis compared to 11.3% for the 60-40 portfolio. Please note these performance figures are gross, excluding fees and transaction costs which may significantly impact actual relative performance. The symphony is slightly less volatile than #HFEAR, but experienced a larger Max Drawdown during the period. Over the last three years (February 8th 2019 - February 7th, 2022), risk adjusted returns for this symphony would have been even stronger (Sharpe ratio of 1.32 vs. 1.07 for the 60 40 portfolio).

The takeaway? Play around and experiment in Composer to see what you can build. Take investing concepts you’re interested in and translate them into symphonies. Backtest, iterate, and build up ideas. 

I had fun with this one. I hope you enjoy it too. 

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