Managed Risk Investing

• Managed Risk Investing
• TangoETF Asset Allocation Rotation
• TangoETF Growth
• TangoETF Balanced
• TangoETF Endurance
• TangoETF Signal
• Inverse Option
• Long / Short Strategy

TangoETF Asset Allocation Rotation Portfolio (Sample Report)

Today's Holdings

Today's Gains

Next Day's Actions

Portfolio Chart

Portfolio Statistics

Buy/Sell Asset Class Signal 

The Buy/Sell Asset Class Signal measures the risk level in each Asset Class. A Sell Signal indicates a lot of risk in the Asset Class and the probability is greater that the Asset Class will go down rather than go up in the near future. A Buy Signal is just the opposite, indicating less risk in the Asset Class and the probability is greater that the Asset Class will go up rather than down in the near future. The Buy/Sell Asset Class Signal cycle occurs on average 2-3 times a year. These signals will not be shown on the Daily Report.

Bull/Bear State Signal  

The Bear State Signal identifies a Bear Market environment which is the most opportune time to use the Inverse Option (essentially like shorting the market) to profit from a drop in the market. The Bull State Signal identifies a period which is not the opportune time to use the Inverse Option. The Bull/Bear State Signal is the longer term and occurs on average 1 time every 1.5 years.

 The difference between the Asset Class Buy/Sell Signal and the Bull/Bear State Signal is Intermediate Term and Long Term. How do we use these two signals? When the Bull State is in effect, the sample portfolio will trade based on the Buy/Sell Asset Class Signal: Long/Money Market corresponding with the Buy/Sell Asset Class Signal. When the Bear State is in effect, the sample portfolio will trade based on the Asset Class Signal: Long/Inverse(short) corresponding with the Buy/Sell Asset Class Signal.

How They Work Together 

This sample portfolio will use an Inverse trade of 50% Inverse Fund and 50% Money Market. So, during a Asset Class Sell Signal within a Bear State, the sample portfolio will in effect be 50% short the Market by holding an Inverse Fund.

From time to time, the sample portfolio will use different Inverse Funds. The Inverse Fund will be identified in the Daily Report, for example, "Buy MYY" will appear as the Next Days Action, where the portfolio will buy shares equal to approximately 50% of total Asset Class value.

Asset Allocation Rotation Explained

Performance

TangoETF Asset Allocation Rotation (AAR) performance reporting will use the same format as the other TangoETF trading systems. Starting out the results will be from back testing and real time to provide some history. From the beginning a separate Fidelity account will be established to enable tracking of real time performance. When enough real time history has been established we will switch over from the back test/real time to the real time only. Below is a chart of the back test results of AAR. The symbol in the orange for AAR is FBASA. The blue is the S&P500 for reference. This chart shows how powerful Asset Allocation along with Risk Management can be.

The return is 800% greater than the S&P500 with 49% less risk. To good to be true? Not really, but the real time results always come out a little less than back testing even in the most robust trading systems. So expect something less than this.

Theory and Concept Behind Traditional Asset Allocation Investing 

Good parts: Diversification, Less Risk less Volatility, Balanced Investing, Re-balancing (selling part of your winners and buying lagging funds)

Bad Parts: Static Funds Used, Buy and Hold, Large Draw-downs (losses)

The theory and concept of Asset Allocation is widely known. It is a very effective investment technique with some big negatives, it is a BUY and HOLD concept which follows the market and at times has horrendous draw-downs (loses) and volatility which we can not accept or endure. Over a period of 20 years as an example, various fixed mixes of Asset Classes outperform the single component parts and significantly lower risk. A portfolio consisting of one quarter each, Large Cap, Small Cap, Foreign, and US Government Bonds has a higher return and lower risk than the S&P500. It is proven that taking a very risky asset class such as foreign and adding a small amount of low risk bonds will actually increase the performance and lower the risk over the single foreign asset class.

How do you arrive at the Asset Allocation that will provide the best return and least amount of risk? You can't but don't distress, because neither can anyone else. Not even with computer optimisers to select the type and number of Asset Classes and the percentage allocation for each asset class. The basic reason is the performance and risk of various asset classes vary widely over longer periods of time. More on this later.

Part of the concept is periodic re-balancing of your portfolio, in the above example some of the asset classes will outperform others over time. Necessitating re-balancing the asset classes to four equal parts. This forces you to sell a part of your best performers and add a part to your lagging performers, thus selling high and buying low. 

All this sounds great accept for the losses in protracted market downturns, and the Static Funds used. So we set about to solve the negative aspects of Asset Allocation and keep the good aspects in place.

How Asset Allocation Rotation (AAR) was Hatched 

Several things converged to motivate the development of AAR. The terrible Bear Market of 2008, financial sector crisis, and several studies of Asset Allocation we read in the past. The thought of how do we keep the good parts of Asset Allocation and eliminate the bad parts.

For years we have been using Market Risk Management to solve the severe correction and bear market losses. We extended and applied our Risk Management to each separate Asset Class to solve the draw-down losses. The BUY and Hold one fund in each asset class concept was contrary to our philosophy. So we extended and applied our  Risk Adjusted ETF Selection process into each Asset Class. This we know, using Market Managed Risk and Risk Adjusted Ranking will increase performance, lower risk, and lower losses. This allows us to select and hold the best of breed in any one Asset Class during any specific time in the market. This we know will improve performance.

Thus by adding the above Risk Management we are making a Static Asset Allocation process into a Dynamic Computer driven Asset Allocation Rotation (hereafter called AAR) process. Here is a chart showing some alternatives and results. The purple line is a simulation of a typical static buy and hold Asset Allocation investment process. It holds seven asset classes including cash as an asset class. You can see the large draw-down and 6.73% Ann return over 7 years. The green line is applying Tango6x Risk Management signal to the purple line, you can see the reduced draw-down and 11.61% Ann return over 7 years using Risk Management. The orange line is TangoETF AAR with 6 asset classes(we removed the cash asset class), with 19.46% Ann return over 7 years. The light blue line is the S&P500 for reference.

Basic Fundamental Framework of AAR

Number of Asset Classes: We selected six(6) asset classes, we could have selected 8-10-20-or more asset classes. Studies have shown that a few asset classes are most effective, adding a few more asset classes a little better, after that adding more asset classes you are just amusing yourself with a more complex system. Our Asset Class choices were Large Cap, Small Cap, Foreign, Bonds, Real Estate, and Commodities.

Asset Class Fund Selection: The ETF funds in each Asset Class were selected to produce a robust rotational trading system. The ETF's that make up the portfolio mix to be traded in each Asset Class are proprietary.

Asset Class Managed Risk: Each Asset Class's risk will be measured separately and each will have a risk threshold (a line in the sand), that when crossed to the high risk side, that Asset Class will go to cash to reduce exposure to that Asset Class market. At this point that Asset Class has high risk to the downside. The graphic below summarizes the AAR process.

Number of Positions: One position will be held for each separate Asset Class. So the AAR sample portfolio will hold 0 - 6 positions at any given time. No attempt will be made to move cash from one Asset Class that is on a sell and is holding cash to another that is invested in a different Asset Class. This would be contrary to the Asset Allocation concept and reduce diversification.

Re-balancing: Research and testing indicates that the period between re-balancing is not critical to performance. What is critical is that you do re-balance periodically. We will normally re-balance once a year. We will also follow the distortion between the value of each Asset Class. If the distortion is to great before one year we will put out a notice to re-balance and the sample portfolio will be re-balanced at that time. Otherwise the sample portfolio will be re-balanced once a year. We will not specify the re-balancing trades in the Daily Report, we will send out an alert that it is time to re-balance. You can simple re-balance your brokerage account by summing the total amount of cash in the six Asset Classes and divide by six. Then make the trades necessary to bring your position sizing of the six Asset Classes into balance. Experience has shown this does not need to be perfect.

Inverse Option: The Inverse Option that is used in Aggressive, Moderate, and Conservative will be used in the AAR sample portfolio for only three Asset Classes: Large Cap, Small Cap, and Foreign. When in a Bear State and we get a Managed Risk sell signal for one or more of the three Asset Classes, the sample portfolio will buy an Inverse Fund with cash available from the Asset Class on a sell. You can find out more about the Inverse Option. 

The TangoETF Portfolios make trades based on a computer automated trading system and thus the results will differ slightly from the actual brokerage trades made in real-time. The results are slightly different because the automated trading system uses the "End of Day" data and the brokerage trades are made during the day (not at the end of day).

Typically, the actual brokerage trades are made in the early morning but some are made at various times of the day. This makes the prices paid for computer trades and brokerage trades different. Also, the computer trades have no transaction fee expenses and brokerage trades have all the transaction fee expenses charged by the brokerage, this also makes a slight difference in the two different results. The brokerage trades also have a spread cost that the computer trades do not have. 

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