Tag Archives: shy

Dual ETF Momentum April Update

Scott’s Investments provides a free “Dual ETF Momentum” spreadsheet, which was originally created in February 2013. The strategy was inspired by a paper written by Gary Antonacci and available on Optimal Momentum . Antonacci’s book , Dual Momentum Investing: An Innovative Strategy for Higher Returns with Lower Risk, also details Dual Momentum as a total portfolio strategy. My Dual ETF Momentum spreadsheet is available here and the objective is to track four pairs of ETFs and provide an “Invested” signal for the ETF in each pair with the highest relative momentum. Invested signals also require positive absolute momentum, hence the term “Dual Momentum.” Relative momentum is gauged by the 12-month total returns of each ETF. The 12-month total returns of each ETF is also compared to a short-term Treasury ETF (a “cash” filter) in the form of the iShares Barclays 1-3 Treasury Bond ETF (NYSEARCA: SHY ). In order to have an “Invested” signal, the ETF with the highest relative strength must also have 12-month total return greater than the 12-month total returns of SHY. This is the absolute momentum filter, which is detailed in depth by Antonacci, and has historically helped increase risk-adjusted returns. An “average” return signal for each ETF is also available on the spreadsheet. The concept is the same as the 12-month relative momentum. However, the “average” return signal uses the average of the past 3, 6, and 12-month (“3/6/12″) total returns for each ETF. The “invested” signal is based on the ETF with the highest relative momentum for the past 3, 6 and 12 months. The ETF with the highest average relative strength must also have an average 3/6/12 total returns greater than the 3/6/12 total returns of the cash ETF. Portfolio123 was used to test a similar strategy using the same portfolios and combined momentum score (“3/6/12″). The test results were posted in the 2013 Year in Review and the January 2015 Update . Below are the four portfolios along with current signals: Return Data Provided by Finviz Click to enlarge As an added bonus, the spreadsheet also has four additional sheets using a dual momentum strategy with broker specific commission-free ETFs for TD Ameritrade, Charles Schwab, Fidelity, and Vanguard. It is important to note that each broker may have additional trade restrictions and the terms of their commission-free ETFs could change in the future. Disclosure: None

Dual ETF Momentum February Update

Scott’s Investments provides a free “Dual ETF Momentum” spreadsheet which was originally created in February 2013. The strategy was inspired by a paper written by Gary Antonacci and available on Optimal Momentum . Antonacci’s book, Dual Momentum Investing: An Innovative Strategy for Higher Returns with Lower Risk , also details Dual Momentum as a total portfolio strategy. My Dual ETF Momentum spreadsheet is available here and the objective is to track four pairs of ETFs and provide an “Invested” signal for the ETF in each pair with the highest relative momentum. Invested signals also require positive absolute momentum, hence the term “Dual Momentum”. Relative momentum is gauged by the 12 month total returns of each ETF. The 12 month total returns of each ETF is also compared to a short-term Treasury ETF (a “cash” filter) in the form of iShares Barclays 1-3 Treasury Bond ETF (NYSEARCA: SHY ). In order to have an “Invested” signal the ETF with the highest relative strength must also have 12-month total returns greater than the 12-month total returns of SHY. This is the absolute momentum filter which is detailed in depth by Antonacci, and has historically helped increase risk-adjusted returns. An “average” return signal for each ETF is also available on the spreadsheet. The concept is the same as the 12-month relative momentum. However, the “average” return signal uses the average of the past 3, 6, and 12 (“3/6/12″) month total returns for each ETF. The “invested” signal is based on the ETF with the highest relative momentum for the past 3, 6 and 12 months. The ETF with the highest average relative strength must also have an average 3/6/12 total returns greater than the 3/6/12 total returns of the cash ETF. Portfolio123 was used to test a similar strategy using the same portfolios and combined momentum score (“3/6/12″). The test results were posted in the 2013 Year in Review and the January 2015 Update . Below are the four portfolios along with current signals. “Risk-Off” is the current theme among all four portfolios: Return Data Provided by Finviz Click to enlarge As an added bonus, the spreadsheet also has four additional sheets using a dual momentum strategy with broker specific commission-free ETFs for TD Ameritrade, Charles Schwab, Fidelity, and Vanguard. It is important to note that each broker may have additional trade restrictions and the terms of their commission-free ETFs could change in the future. Disclosure: None

Reducing Portfolio Risk With Help From Momentum Model

Reduce portfolio risk by activating momentum model. Reduce portfolio risk based on security volatility. Reduce portfolio risk through the use of stop-loss orders. Controlling portfolio risk is every bit as important as seeking portfolio return, particularly when markets are high and volatile. The following analysis takes readers through a process of controlling portfolio risk with help from a tranche momentum spreadsheet. Main Menu: We begin with the following Main Menu where the basic assumptions are laid out by the portfolio manager. In the following example we are using twelve (12) ETFs plus SHY as the cutoff security. Hence the name, Baker’s Dozen. Many of the ETFs carry low correlations with each other, an important factor to consider when identifying securities to populate a momentum oriented portfolio. In the follow screen-shot we set the number of offset portfolios to 8 and the period between offsets to two (2). What this means is that the securities are ranked multiple times (8) on different dates (separated by 2 days) based on two different look-back periods plus volatility. Using these three metrics, the ETFs are ranked each review period. My preference is to review a portfolio every 33 days so the review is rotated throughout the month. Not only are the ETFs ranked based on current data, but they are ranked two, four, six, eight, and etc. days ago so we know what the rankings looked like up to sixteen (8 x 2) days ago. The look-back periods are 60 and 100 trading days. A 20% weight is assigned to the volatility as we are looking for securities with low volatility. Only two securities are selected for each offset portfolio. This becomes more apparent in the second screen-shot so move down to that slide. (click to enlarge) Tranche Recommendations: Here we have what is called the Tranche Momentum model worksheet. This is the first of three risk reducing mechanisms. The tranche model is designed to reduce the “luck-of-trading-day” as this is a problem inherent in all back-tests as well as real portfolio management. Instead of splitting the portfolio into 50% VNQ and 50% MTUM , as the current offset recommends, we note that offset 3 recommended divisions between VNQ and TLT . Offset portfolio #5 recommended 50% allocation to SHY and 50% to VNQ. Using eight (8) portfolio offsets ends up dividing the portfolio into four securities where the percentages are based on the number of times the ETF shows up in one of the eight rankings. The worksheet permits as many as 12 portfolio offsets, but I tend to favor using eight. The following worksheet ranks the ETFs using both absolute and relative momentum principles. Readers will note that the current portfolio holds 200 shares in VTI, but the tranche momentum model recommends none as VTI is under-performing SHY, our “circuit breaker ETF.” Momentum becomes one of our risk reducing mechanisms as under-performing securities are screened out of the active portfolio. (click to enlarge) Risk Reduction Recommendations: The following worksheet combines recommendations from the above tranche data and adds a volatility factor to come up with a list of recommended ETFs. In the following slide the Maximum Trade Position Risk percentage is set to 2.0% so the total portfolio is not exposed to more than a 6% draw-down until the next review period. The still leaves individual ETFs at unacceptable risk levels which we control in the final screen-shot. Before moving to the final slide, look at the individual recommendations. Shares held in VTI and PCY are sold out of the portfolio as VTI is under-performing SHY and PCY has not shown up as a recommended ETF in any of the last 8 offset portfolios. The recommendations are to hold the following four ETFs. 75 shares of SHY – round up from 74. 300 shares of VNQ – rounded to the nearest 100 shares. 100 shares of TLT – rounded to the nearest 100 shares. 350 shares of MTUM – rounded to nearest 50 shares. (click to enlarge) Manual Risk Reduction Recommendations: For the final risk reduction activity the recommendations from the above worksheet are followed which still leaves a few ETF exposed to excess risk. The final step is to place stop-loss or Trailing Stop Loss Orders (TSLOs) on VNQ and MTUM. VTI is either sold at market or a 6% TSLO is used. While the current portfolio holds $8,000 in cash, the recommendation is to increase it to $32,500. Note that the current portfolio carries a risk of 4.8%, but if the suggested adjustments are made, the risk drops to 3.4%. (click to enlarge) With the aid of the tranche momentum spreadsheet we limit portfolio risk through absolute and relative momentum principles as these keep us out of deep bear markets. Further portfolio risk is controlled by placing stop-loss orders as a way of clamping down on excess draw-downs. Granted, these procedures work when we have an orderly market. Guarding against “flash crashes” is an entirely separate problem.