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Trading Inverse Volatility, ETFs and CEFs (US)

Take advantage of 6 different ETF Portfolios based on Volatility, Technical Analysis and Macro Factors. These models explore opportunities and inefficiencies from rolling yield, fundamentals, economic indicators and technical analysis to determine the best ETF to trade for the short term, and long term. 

To add further diversification, this model also offers a portfolio of CEFs (closed-end funds) that are focused on a more conservative adjusted risk return by exposing growth through discounted NAV while investing in more conservative funds.

Please note that this model has been updated on June 6, 2020.  It adds daily timers to 2 models, which introduces immediate notification on signal change.

CEFs were added to this model as a separate portfolio on August 10th, 2019. It trades up to 5 CEFs to provide a more conservative adjusted risk return. The benchmark is a portfolio of half in US equities (SPY) and half of intermediate bonds or treasury (IEF). The model attempts to have lower volatility than the benchmark while having a better capital appreciation due to the CEFs NAV discount. 

This model contains 5 ETF Portfolios and 1 CEF Portfolio.

ETF Portfolio:

There are 5 Portfolios of ETFs:

  1. Based on Inverse Volatility (1 ETF)
  2. Based on Macro Factors (1 ETF)
  3. Based on Technical Factors (1 ETF)
  4. A model combining portoflios 1, 2 and 3 above (3 ETFs)
  5. Low Turnover Investing with ETF (3 ETFs)

 

All portfolios rebalance weekly (except leveraged ETF and based on Technical Anallysis, which are rebalanced daily), which mean buy and sell rules are verified either on a weekly basis or daily basis depending on the model. Each ETF portfolio tracks a different financial idea. Notifications for daily rebalance is always sent after market close, typically in the evening (EST) to be applied on the next business day. Weekly notifications are sent on weekends to be applied on next business day.

The portfolio based on Inverse Volatility attempts to identify when there is a higher probability of the volatility price structure to switch to / remain in contango.  It switches to other ETFs when there is a higher probability that contango momentum might diminish (but still remain bullish) and it switches to bearish / low-equity correlation ETF types when market conditions are bearish. The model uses volatility price structure to calculate rolling yield, as well as market fundamentals, economic indicators and technical analysis to determine the most appropriate signal. This model is rebalanced daily for maximum accuracy. 

This is a mechanical model that chooses what to buy and sell based on a set of rules. Therefore, there will be losing trades from time to time. By no means it reflects a broken strategy. No model can outperform at all times, so it’s paramount to have the proper temperament to stick what a strategy that is aligned to your goals and risk tolerance.

 

Backtests results:

 

Detailed performance simulation and drawdown:

 

Performance stats simulation:

 

Risk Measurement Simulation:

 

The Portfolio based on Macro factors use cyclical seasonality to rotate sectors, and these specific sector ETFs are ranked by momentum. Macro data and guidance is computed monthly, and the model might be long the market, short the market or leveraged the market.

The Portfolio based on Technical factors use price momentum from different timeframes to capture momentum. This model uses daily rebalance for maximum accuracy on signal changes. The model is either long the market (if bullish) or in fixed income (if bearish, for a low correlation with equities). 

 

Trading Inverse Volatility + Macro + Technical Portfolio

Each ETF model provides unique characteristics and ideas. Another alternative is a more balanced portfolio by combining the 3 ETF models, which allows a lower risk / return proposition – and therefore, lower volatility and drawdown when combining all ETF models.  Below is the backtest with the Portfolio of ETFs:

 

Low Turnover ETF Trading Portfolio

Another ETF Portfolio added in 2020 was focused in having 3 ETFs ranked via a balanced mix of momentum and economic indicators like inflation, rate spread, unemployment and other data suggesting that there’s a higher probability of a recession. Those indicators are calculated quarterly, so this portfolio has a very low turnover and high winning rate. It’s designed as a passive portfolio that takes into account macro elements to mitigate risks associated with economic cycles. This portfolio uses 3 ETFs and it’s always invested (no cash position).

Simulated results:

 

 

CEF Portfolio:

This is a medium turnover model. The model rebalances weekly and it trades up to 5 CEFs. The model chooses CEFs from US only, based on a rank that takes NAV discount into account, and favorable momentum from the companies in which these funds are invested on. The benchmark is a portfolio of 50% invested in equities and 50% invested in bonds. Simulation shows that the model had lower drawdown while having superior performance by leveraging NAV CEF discount and momentum from the companies that these funds were invested on.

 

 

Detailed performance and drawdown:

Performance and stats simulation:

 

Risk Measurement Simulation:

 

 

To determine the best ETF to invest for the short term , several components are screened for:

  • Volatility futures help to validate momentum (or anticipate changes) regarding the volatility index, by using concepts from this white paper and a variation of the VRP and rolling yield strategies, described on this white paper;
  • Fundamentals look for earnings guidance and surprise results for the 500 companies of SP500; If earnings results and guidance are improved, volatility are expected to decline (and vice-versa);
  • Economic indicators look for metrics to predict recession and sector rotation that favour different asset allocation;
  • Technical analysis help to identify trends and predict changes based on classical patterns regarding market performance and sector performance to identify sector rotation;
  •  

The ETF portfolios take volatility (ration between 6-months VIX curve and 3-months VIX curve), technical analysis (seasonality and momentum ranked on different timeframes), and macro factors (economic indicators and ratio calculations in a mechanical effort to confirm a recession bias or not).

The CEF portfolio starts with the US CEF Universe and it’s filtered by liquidity and a rank based on CEF NAV Discount. The model trades up to 5 CEFs and a rotation approach is used as the criteria to when to buy and sell. Many investors looking for short-term gains are tempted to ride recent winners, identified either through ad-hoc observation or an objective trading system. Interestingly, though, it may be preferable to latch onto recent losers under the assumption that such shares may be ready for a bounce – the CEF NAV discount is a good indicator for that. In other words, we may do better with funds that have just experienced corrections or taken a breather. The idea of choosing recent losers instead of winners is emotionally challenging to many, however logically, it makes sense. No asset (equity or fixed income) can go up forever without consolidation phases, so the strongest among the recent winners may be the ones most vulnerable. This is a trading, rather than investing approach. Accordingly, it’s often better to rebalance lists created using this approach on a weekly, rather than, say, on a monthly basis. This particular rotational ranking system is based mainly on asset performance change over the past five trading days with weaker being better. To help tilt the balance toward stronger CEF experiencing a pause, rather than a deteriorating CEF continuing a downtrend, the model also looks at asset price change over the past 120 trading days and the 1-year Sharpe ratio (stronger being better in both cases). Furthermore, the model takes into account NAV gap, NAV growth (to attempt establishing momentum) and technical analysis of the underneath assets to justify the choice.

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2nd model 10% discount (applied to the 2nd model)
3rd model 20% discount (applied to the 3rd model)
4th model 30% discount (applied to the 4th model)
5th model 40% discount (applied to the 5th model)
6th model 50% discount (applied to the 6th model)
7th model 60% discount (applied to the 7th model)
8th model 70% discount (applied to the 8th model)

 

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ETF model based on Inverse Volatility and Leveraged Indexing

Performance Info:

(last updated on July 12, 2020)

 

 

Stats Info:

(last updated on July 12, 2020)

 

 

Risk Info:

(last updated on July 12, 2020)

 

ETF model based on Macro Analysis

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(last updated on July 12, 2020)

 

 

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(last updated on July 12, 2020)

 

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(last updated on July 12, 2020)

ETF model based on Technical Analysis

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(last updated on July 12, 2020)

 

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(last updated on July 12, 2020)

 

 

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last updated on July 12, 2020)

3 ETF portfolios above combined

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(last updated on July 12, 2020)

 

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(last updated on July 12, 2020)

 

 

 

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(last updated on July 12, 2020)

 

Asset Correlation Info:

(last updated on July 12, 2020)

Low Turnover ETF Investing

Performance Info:

(last updated on July 12, 2020)

 

 

Stats Info:

(last updated on July 12, 2020)

 

 

Risk Info:

(last updated on July 12, 2020)

 

 

5 CEFs

Performance Info:

(last updated on July 12, 2020)

 

Stats Info:

(last updated on July 12, 2020)

 

 

Risk Info:

(last updated on July 12, 2020)

 

Cost of this model:  $33 / month. Cancel anytime.  

This model includes 5 Portfolio signals:

One for each ETF (case one wants to trade it individually) + one portfolio of all 3 ETFs combined + one portfolio of 5 CEFs.

Interested in subscribing to multiple models? Discounts are available when subscribing to 2 or more models. Simply subscribe to your first model and then let us know which model you want to subscribe next, and we’ll send you a discount coupon.

Discount rates:

1st model full price
2nd model 10% discount (applied to the 2nd model)
3rd model 20% discount (applied to the 3rd model)
4th model 30% discount (applied to the 4th model)
5th model 40% discount (applied to the 5th model)
6th model 50% discount (applied to the 6th model)
7th model 60% discount (applied to the 7th model)
8th model 70% discount (applied to the 8th model)

Got questions?  Check our Frequently Asked Questions for Premium models or contact us.

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5 Comments

  1. Fouracle

    Is the model busted?

    Reply
    • Rod [Boost Your Income]

      No, the model continues to work. The model dropped more than the market due to the nature of leveraged ETFs, but it was not invested in inverse volatility products, since the VIX price structure is in backwardation since January 26th. The model takes that into account, and would only consider to buy an inverse volatility ETF (SVXY) if the VIX price structure is in contango. This is obviously a very volatile model, but you can’t outperform the market without volatility – any high beta model will do better than the market when going up and worse than the market when going down. Different simulation shows a max drawdown similar to the market (-50%), so the model continues to behave as expected.

      Reply
  2. Matt

    Hi
    Is this model available for subscription?

    Reply
    • Rod [Boost Your Income]

      Given the high performance on backtests, this model is on “incubation” phase to validate out-of-sample performance. I expect to launch it for subscription in March. If you click on the Subscribe tab, you can add your email to be notified when the model is available.

      Thanks!

      Reply

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