Tag Archives: tlt

Dual ETF Momentum Portfolio – June Update & Backtests

In February I announced a new “Dual ETF Momentum” spreadsheet. The idea was inspired by a paper written by Gary Antonacci and available on Optimal Momentum.

The spreadsheet is available on Scott’s Investment’s here. The objective of the spreadsheet is to track four pairs of ETFs and provide an “Invested” signal for the ETF in each pair with the highest relative 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 bill ETF (a “cash” filter). 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 the cash ETF. This is the absolute momentum filter which is detailed in depth by Antonacci, and has historically helped increase risk-adjusted returns.

I have added an “average” return signal for each ETF 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.

Below are the four portfolios along with current signals.

Return data courtesy of Finviz
Equity  ETF Average of Quarterly/Half/Full Year % Returns Signal based on 1 year returns Signal based on average returns
US Equities VTI 15.67 Invested Invested
International Equities VEU 7.68
Cash SHY 0.04
Credit Risk  ETF Average of Quarterly/Half/Full Year % Returns Signal based on 1 year returns Signal based on average returns
High Yield Bond HYG 3.41 Invested Invested
Interm Credit Bond CIU 0.38
Cash SHY 0.04
Real-Estate Risk  ETF Average of Quarterly/Half/Full Year % Returns Signal based on 1 year returns Signal based on average returns
Equity REIT VNQ 6.51 Invested Invested
Mortgage REIT REM -1.37
Cash SHY 0.04
Economic Stress  ETF Average of Quarterly/Half/Full Year % Returns Signal based on 1 year returns Signal based on average returns
Gold GLD -15.55
Long-term Treasuries TLT -4.95
Cash SHY 0.04 Invested Invested

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.

Using Portfolio123 I backtested a similar strategy using the same portfolios and combined momentum score used above. However, to simplify the screen I did not require an ETF to be ranked above the combined return of SHY; rather, an ETF simply needed the average of its 13 week/26 week/52 week total return to be greater than 0% (the “absolute” momentum filter). Also, the portfolio re-balanced every 4 weeks as opposed to the end of each month.  No considerations were made for taxes or commissions. The test time period was 5/1/08 – 6/10/13 and the benchmark is SPY:

dual momentum test2

A four year test period is short by historical standards but the test is limited to the trading history of ETFs within the portfolio. A more robust, index-based test of the dual momentum strategy can be found on Optimal Momentum.

If you enjoy these free tools, please consider making a donation on the home page of Scott’s Investments using the Paypal link in the upper-right corner!

More on this topic (What's this?)
Cloud M&A: Momentum Adds Twist
Can Cyclicals Breakout And Provide Momentum For Higher Equity Prices?
Read more on Momentum at Wikinvest

Dual ETF Momentum – May Update

In February I announced a new “Dual ETF Momentum” spreadsheet. The idea was inspired by a paper written by Gary Antonacci and available on Optimal Momentum.

The spreadsheet is available on Scott’s Investment’s here. The objective of the spreadsheet is to track four pairs of ETFs and provide an “Invested” signal for the ETF in each pair with the highest relative 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 bill ETF (a “cash” filter). 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 the cash ETF. This is the absolute momentum filter which is detailed in depth by Antonacci, and has historically helped increase risk-adjusted returns.

I have added an “average” return signal for each ETF 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.

Below are the four portfolios along with current signals. As you can see, the 12-month and 3-6-12 signals are the same with the exception of the Real-Estate risk portfolio. REM has  higher 12-month returns than VNQ; however, VNQ has higher 3/6/12 returns than REM.

Return data courtesy of Finviz
Equity ETF Average of 3/6/12 Returns Signal based on 1 year returns Signal based on average returns
US Equities VTI 16.72 Invested Invested
International Equities VEU 13.06
Cash SHY 0.17
Credit Risk ETF Average of 3/6/12 Returns Signal based on 1 year returns Signal based on average returns
High Yield Bond HYG 7.67 Invested Invested
Interm Credit Bond CIU 2.28
Cash SHY 0.17
Real-Estate Risk ETF Average of 3/6/12 Returns Signal based on 1 year returns Signal based on average returns
Equity REIT VNQ 17.17 Invested
Mortgage REIT REM 14.43 Invested
Cash SHY 0.17
Economic Stress ETF Average of 3/6/12 Returns Signal based on 1 year returns Signal based on average returns
Gold GLD -13.42
Long-term Treasuries TLT 0.46 Invested Invested
Cash SHY 0.17

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. Also, the dual momentum strategy has historically had relatively low turnover.

If you enjoy these free tools, please consider making a donation on the home page of Scott’s Investments using the Paypal link in the upper-right corner!

Permanent Portfolio Spreadsheet

I created a Permanent Portfolio Spreadsheet which tracks various investment metrics for four ETFs, the Vanguard Total Stock Market (VTI), iShares Barclays 20+ Year Treasury Bond (TLT), SPDR Gold Trust (GLD), and iShares Barclays 1-3 Year Treasry Bond Fund (SHY).  They were selected to reflect a Harry Browne-esque Permanent Portfolio. The spreadsheet is accessible at the top of the home page.

There are numerous indicators on the sheet, including long-term moving averages  (both 10 month and 200 day), momentum, and absolute momentum (i.e. TLT, VTI, and GLD returns versus SHY). I will probably add to it as time progresses, I don’t yet have a final vision for it but if you have any input let me know.

I realize having anything other than an equal weight flies in the face of Browne’s original Permanent Portfolio strategy of an equal weight allocation. However, I have written several articles on the Permanent Portfolio with some simple twists that have, in some cases, improved historical performance.  Some of those articles are listed below.  And if you need another reason: It is fun creating spreadsheets….

Creating a Permanent ETF Portfolio
Building a Permanent ETF Portfolio, Part 2
Tactical Applications of the Permanent Portfolio
Testing a Harry Browne Permanent ETF Portfolio

Dual ETF Momentum Update

In February I announced a new “Dual ETF Momentum” spreadsheet. The idea was inspired by a paper written by Gary Antonacci and available on Optimal Momentum.

The spreadsheet is available on Scott’s Investment’s here. The objective of the spreadsheet is to track four pairs of ETFs and provide an “Invested” signal for the ETF in each pair with the highest relative 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 bill ETF (a “cash” filter). 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 the cash ETF. This is the absolute momentum filter which is detailed in depth by Antonacci, and has historically helped increase risk-adjusted returns.

I have added an “average” return signal for each ETF 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.

Below are the five portfolios along with current signals. As you can see, the signals are the same with the exception of the Economic Stress portfolio. TLT has slightly higher 12-month returns than SHY. However, TLT and GLD both have lower 3/6/12 returns than SHY:

Equity Representative ETF 1 Year % Total Returns Average of Quarterly/Half/Full Year % Returns Signal based on 1 year returns Signal based on average returns
US Equities VTI 17.93 14.07 Invested Invested
International Equities VEU 11.89 11.57
Cash SHY 0.36 0.14
Credit Risk Representative ETF 1 Year % Total Returns Average of Quarterly/Half/Full Year % Returns Signal based on 1 year returns Signal based on average returns
High Yield Bond HYG 11.22 6.27 Invested Invested
Interm Credit Bond CIU 4.49 1.78
Cash SHY 0.36 0.14
Real-Estate Risk Representative ETF 1 Year % Total Returns Average of Quarterly/Half/Full Year % Returns Signal based on 1 year returns Signal based on average returns
Equity REIT VNQ 18.25 11.29
Mortgage REIT REM 25.16 15.46 Invested Invested
Cash SHY 0.36 0.14
Economic Stress Representative ETF 1 Year % Total Returns Average of Quarterly/Half/Full Year % Returns Signal based on 1 year returns Signal based on average returns
Gold GLD -6.5 -6.8
Long-term Treasuries TLT 0.64 -5.23 Invested
Cash SHY 0.36 0.14 Invested
Return data courtesy of Finviz

As an added bonus, the spreadsheet also has four additional sheets using a dual momentum strategy with broker specific commission-free ETFs. 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. Also, the dual momentum strategy has historically had relatively low turnover.

More on this topic (What's this?) Read more on Momentum, Henders Land Dev at Wikinvest

All-Season ETF Portfolio: Minimum Correlation Allocation

In January I launched an “All-Season ETF Portfolio”. The portfolio began with a static allocation based on a simplistic and unleveraged interpretation of Ray Dalio and Bridgwater Associates “All-Weather” investment strategy. The proposed static allocation is below:

Name Symbol Static Allocation
Vanguard Total Stock Market VTI 18.75%
 PowerShares DB Commodity Index Tracking Fund DBC 7.25%
SPDR Gold Trust GLD 7.25%
 iShares iBoxx $ High Yield Corporate Bond Fund HYG 6.50%
iShares Emerging Markets USD Bond ETF EMB 14.50%
iShares Barclays TIPS Bond Fund TIP 20.75%
iShares Barclays 20+ Year Treasury Bond ETF TLT 12.50%
iShares Barclays Aggregate Bond Fund AGG 12.50%

The proposed allocation is not intended as a one-size-fits-all allocation model, but it does serve as a framework for further study and is based on having allocation to the four different market environments espoused by Bridgewater (full paper here):

I backtested the static allocation using ETFReplay.com – it outperformed the Vanguard 60-40 (VBINX) mutual fund since 2008 on both a total and risk-adjusted basis. The All-Season portfolio has a sharpe ratio of .67 and max drawdown of -21.5% versus a sharpe of.25 and max drawdown of -34.4% for VBINX. Positions were rebalanced annually:

Last week I introduced a basic risk-parity allocation tool for the All-Season ETF portfolio. The risk parity allocation uses the trailing 20-day volatility of the adjusted closing prices of each ETF to calculate a risk-based allocation. The risk parity allocation as of Friday’s close is below:

Name Symbol Risk Parity Weighting (unleveraged)
Vanguard Total Stock Market VTI 5.17%
 PowerShares DB Commodity Index Tracking Fund DBC 7.22%
SPDR Gold Trust GLD 4.32%
 iShares iBoxx $ High Yield Corporate Bond Fund HYG 22.44%
iShares Emerging Markets USD Bond ETF EMB 12.57%
iShares Barclays TIPS Bond Fund TIP 15.62%
iShares Barclays 20+ Year Treasury Bond ETF TLT 5.41%
iShares Barclays Aggregate Bond Fund AGG 27.25%

The All-Season ETF portfolio risk-parity allocation has performed relatively well since 2008, also outperforming VBINX by a wide margin. Risk-parity posted a sharpe ratio of .82 and max drawdown of -16.8%. Positions were rebalanced quarterly:

When researching the All-Weather portfolio I came across David Varadi’s work at CSS Analytics. Varadi, along with Michael Kapler, Corey Rittenhouse, and Henry Bee,  published a paper in September 2012, “The Minimum Correlation Algorithm: A Practical Diversification Tool”.  In the paper they introduce two heuristic algorithms for effective portfolio diversification and passive investment management, which they conclude “is an excellent alternative to Risk Parity, Minimum Variance and Maximum Diversification.”

Their algorithm, in my own words, is an alternative asset allocation model which makes intuitive sense. It uses both the historical volatility and correlation of securities in a portfolio to determine asset allocation. Securities with low correlations and volatility relative to the other securities in the portfolio receive higher weightings. The result is a portfolio allocation which changes over time to reflect the evolving volatility and correlations of the securities in the portfolio.

I was happily surprised to discover David freely provides a downloadable “Mincorr spreadsheet” on his site. The spreadsheet uses the algorithms presented in the paper and allows users to calculate their own minimum correlation allocations.

50 Top Stocks

After downloading the spreadsheet from CSS Analytics, I tweaked it to incorporate eight securities (this took a little more time than anticipated). I then created a template to download daily price data to calculate trailing correlations and volatility for the eight securities in the All-Season portfolio (this took a lot more time than anticipated). Finally, I used the Mincorr spreadsheet framework to calculate a daily “minimum correlation” allocation for the eight securities in the All-Season ETF portfolio and I provide the results on the All-Season ETF spreadsheet.

Backtesting this strategy is more difficult than a simple risk-parity or static asset allocation model. The most comprehensive tests are available in the The Minimum Correlation Algorithm paper, which has tests dating to 1980 for a variety of portfolios. The authors of the paper were kind enough to help me run some tests for the All-Season ETF portfolio. The tests are available in the pdf here: minn corr backtests, with tests being run from December 2007 – February 2013. The “min.corr.excel” results used a formula close to the calculation on my All-Season spreadsheet.

The current Minimum Correlation allocations are below:

Name Symbol Minimum Correlation Weightings
Vanguard Total Stock Market VTI 6.71%
 PowerShares DB Commodity Index Tracking Fund DBC 8.86%
SPDR Gold Trust GLD 3.37%
 iShares iBoxx $ High Yield Corporate Bond Fund HYG 29.37%
iShares Emerging Markets USD Bond ETF EMB 9.76%
iShares Barclays TIPS Bond Fund TIP 14.01%
iShares Barclays 20+ Year Treasury Bond ETF TLT 4.71%
iShares Barclays Aggregate Bond Fund AGG 23.21%

Note: my minimum correlation formula differs slightly from the method in the The Minimum Correlation Algorithm in that I use a 20-day historical volatility & correlation versus the 60-day range used in the paper. Using a shorter time period allows the spreadsheet to load quicker, but I may change the 20-day look-back period in the future.

Any errors or omissions in my Min Corr calculation are my own. I have done my best to review and scrub the data, but I make no warranties. As my programming knowledge evolves I hope to post additional minimum correlation backtests.

Past performance is no guarantee of future results. To learn more about the Minimum Correlation algorithm please take a few minutes to visit CSS Analytics.

If you enjoy these free tools, please consider making a donation on the home page of Scott’s Investments using the Paypal link in the upper-right corner!

More on this topic (What's this?) Read more on Barclays at Wikinvest

All-Season Portfolio: Risk Parity Allocation

Earlier this year I launched an “All-Season” ETF Portfolio. The initial launch of the portfolio provided a static allocation to 8 ETFs.  I have added two dynamic allocations to the All-Season portfolio spreadsheet.

The first is an unleveraged risk-parity asset allocation. The allocations for each ETF are updated daily based on the trailing 20-day volatility of each ETF as calculated using adjusted closing prices. The allocation to each ETF is calculated by taking the inverse of its trailing 20-day volatility and then calculating the percent each ETF contributes to the sum of all the inverse volatilities (for an example of the calculation please visit the spreadsheet). Bottom line: the lower trailing volatility an ETF has relative to the other ETFs in the portfolio, the higher its allocation.

The allocations as of last Friday’s close are below. The 20-day volatility is listed along with the static allocation I proposed in January. While the allocations update daily, I do not personally check the allocations daily nor do I endorse checking allocations daily. The spreadsheet and calculations were created to allow for maximum flexibility; hence, the daily updates:

 

Name Symbol Original Static Allocation Historic 20-Day Volatility of ETF Risk Parity Weighting
Vanguard Total Stock Market VTI 18.75% 12.85% 5.11%
 PowerShares DB Commodity Index Tracking Fund DBC 7.25% 7.01% 9.38%
SPDR Gold Trust GLD 7.25% 14.23% 4.62%
 iShares iBoxx $ High Yield Corporate Bond Fund HYG 6.50% 3.60% 18.27%
iShares Emerging Markets USD Bond ETF EMB 14.50% 4.44% 14.80%
iShares Barclays TIPS Bond Fund TIP 20.75% 4.51% 14.57%
iShares Barclays 20+ Year Treasury Bond ETF TLT 12.50% 12.42% 5.29%
iShares Barclays Aggregate Bond Fund AGG 12.50% 2.35% 27.96%

Stay tuned this week for details on the second dynamic allocation tool, the “minimum correlation” weightings!

If you enjoy these free tools, please consider making a donation on the home page of Scott’s Investments using the Paypal link in the upper-right corner!

Gold – Quarterly Update

AlphaClone posted a fourth quarter 2012  summary of institutional activity in Gold (GLD). Quarter over quarter activity shows an overall decrease in institutional holdings of GLD:

However, as Alphaclone notes there are some very prominent funds with positions in GLD:

For those interested in potential applications of institutional holdings see my tests and post from 2010 here.

GLD remains below its 200 day moving average and there is a clear downward sloping channel, as shown by the Finviz chart below, but GLD did find a bid last week at $152:

From a relative strength perspective GLD is trailing two other major asset classes, US Equities and US Bonds (both long-term Treasuries and Aggregate Bonds). I used ETF Replay to test a relative strength system which went long the one ETF with the highest 6 month relative strength among GLD, SPDR S&P 500 (SPY), iShares Barclays 20+ Treasury (TLT) and iShares Barclays Aggregate Bond (AGG), rebalanced monthly. GLD is currently ranked 4th among the 4 ETFs based on 6 month relative strength (TLT is a close third):

For a contrarian perspective, David Banister of The Market Trend Forecast  predicted a cyclical low in Gold for February 2013 in this article, although gold did surpass his low target price for February. A chart from the article below:

 

More on this topic (What's this?)
Mass Exodus from SPDR Gold Fund
Boston Disaster
Read more on SPDR Gold Trust, Gold at Wikinvest

Combining Multiple Market-Timing Systems

One of my primary focuses on Scott’s Investments is studying and tracking various market-timing, trading, and portfolio strategies.  However, no matter how well a strategy tests historically there is always the possibility a strategy under-performs in the future. One way to mitigate this risk is to diversify strategies within a portfolio, and not just securities.

The tests below were conducted using Stockscreen123 (an off-shoot of Portfolio123).  The tests use a combination of two market timing strategies.

The first timing strategy is a “Equities vs. Fixed Income” strategy, which purchases one core equity ETF, the S&P 500 SPDR (SPY) when conditions are deemed bullish, and a core fixed-income ETF, the iShares Barclay 20-year Treasury ETF (TLT), when conditions are deemed bearish. The timing model assumes conditions are favorable for equity investing if EPS estimates are rising and if valuations are reasonable.

  1. The estimates test is whether the 5-week moving average of the aggregate of the consensus current-year estimates for S&P 500 companies is above the 21-week moving average.
  2. The valuation test is based upon risk premium, specifically, whether the S&P 500 risk premium (earnings yield minus 10-year treasury yield) is above 1%

The second strategy is a simple “technical strategy” using moving averages.  When the 50 day moving average of the S&P 500 is above its 200 day moving average, the strategy goes long SPY.  When these conditions are not met the strategy goes long TLT.

While more often than not both strategies share the same signal (i.e. going long SPY), there are times when mixed signals are sent so the hypothetical portfolio goes long both SPY and TLT simultaneously.

For a free 10 page education trading article from Chris Vermeleun click here (clicking the link will automatically download the pdf).

Below is the results of a 10 year backtest with a  4 week rebalance period, compared to SPY (in blue). Dividends are included but no commissions, taxes, or slippage is assumed:

What if an investor purchased an equal weight portfolio in SPY and TLT 10 years ago and rebalanced annually?  The total returns are lower than the combined market timing system but higher than SPY. Standard deviation and max drawdown of the equal weight SPY/TLT portfolio is lower than the combined market timing system and SPY:

What if we incorporate 0.5% slippage into the combined market timing system? Slippage helps accounts for bid/ask spreads that exist in real-world trading and potential commissions.  Total returns decrease but the results are still solid, which is not surprising given that the system only uses two securities and rebalances every 4 weeks:

Below are the test results in table format. The trading systems by themselves are also included. As you can see, both trading systems test well as a stand-alone system, but the highest sharpe ratio is achieved when combining the two systems:

System Rebalance Period Total Return Annualized Return Max Drawdown Sharpe Ratio Standard Deviation Correlation with SPY
Combined Market Timing 4 weeks 188.27% 11.16% -26.99% 0.47 15.80% 0.32
Combined Market Timing .5% slippage 4 weeks 168.80% 10.39% -26.99% 0.42 15.82% 0.32
SPY/TLT Annual 119.05% 8.15% -23.88% 0.41 10.90% 0.74
SPY N/A 83.86% 6.28% -55.42% 0.11 23.90% 1
Equities vs Fixed Income 4 weeks 203.76% 11.75% -26.99% 0.44 18.42% 0.4
Technical Strategy 4 weeks 167.96% 10.35% -26.99% 0.38 17.55% 0.16
all returns include dividends
Tests 11/24/02 –  11/24/12

The two market timing systems presented here are not intended as optimal timing systems – better options may exist for investors. However, the two systems are easy to implement for an individual investor and as stand-alone systems have strong historical results. When combined into a single portfolio the two strategies have led to even better risk-adjusted returns (as gauged by Sharpe Ratio) even when compared to an equal-weight SPY/TLT portfolio.

ETF Replay Portfolio for September

This month’s ETFReplay.com Relative Strength ETF Portfolio has been updated at Scott’s Investments and includes turnover in three out of four positions.

I previously detailed here and here how an investor can use ETFReplay.com to screen for best performing ETFs based on momentum and volatility.   I select only the top ETFs out of a static basket of 25 ETFs and re-balance the portfolio monthly.

The buy/sell strategy for the portfolio is simple: purchase the top  ETFs based on a combination of their 6 month returns, 3 month returns, and 3 month volatility (lower volatility receives a higher ranking) and the average of  the 3 month return, 20 day return, and 20 day volatility.  I refer to these two different sets as “6/3/3″ and “3/20/20″.  The top 2 ETFs in the 6/3/3 ranking and top 2 in the 3/20/20 ranking are purchased each month.  When there are duplicates in the top 2, I look to the third ranked ETF in the 3/20/20 and, if necessary, the third ranked ETF in the 6/3/3.  The strategy always holds 4 ETFs.

I track this strategy as a public portfolio on Scott’s Investments.  As of the close August 31st the hypothetical portfolio was up 12.25%, since inception on January 1st, 2011. Returns include dividends but exclude commissions and taxes and all trades are hypothetical so real results will differ.  For some backtests on these strategies please see a recent post here.

For August 31st the strategy sold its positions in  iShares iBoxx Invest Grade Bond (LQD) at a gain of 3.30% and an original purchase date of 5/31/12, iShares Barclays Long-Term Treasury (TLT) at a loss of 1.53% and a purchase date of 7/31/12 and U.S. Utilities Sector SPDR (XLU) at a gain of 1.25% and original purchase date of 5/31/12 (individual ETF returns exclude dividends).
Proceeds were used to purchase Vanguard MSCI U.S. REIT (VNQ), Vanguard MSCI U.S. SmallCap Value (VBR) and PowerShares DB Commodity Index (DBC). The portfolio also continues to hold its position in the PowerShares Emerging Markets Bond (PCY) . 
Sign up here for an $8.95 Trial of MarketClub and see their Trade Triangles in Action

Minor fluctuations in rankings may not always justify selling positions each month. For example, if one ETF drops from the second highest rated to the third or fourth highest rated, it may not warrant selling the position. An investor could only sell a position when it drops out of the top 4 or 5 at the end of the month. This type of modification could be used when someone is looking to limit turnover; however, I think it is important to have whatever rule you prefer to use in place prior to making the investment decision in order to avoid discretionary or emotional decision making.

Below are the top 6 ranked ETFs for this month, using both the 6/3/3 and 3/20/20 strategy:

 

6mo/3mo/3mo
PCY PowerShares Emerging Mkts Bond (7-9yr)
VNQ Vanguard MSCI U.S. REIT
PFF iShares S&P US Preferred Stock Index
LQD iShares iBoxx Invest Grade Bond (7-8yr)
RWX SPDR DJ International Real Estate
HYG iShares iBoxx High-Yield Corp Bond (4-5yr)

Follow me on Stocktwits and Twitter!

3mo/20day/20day
DBC PowerShares DB Commodity Index
VBR Vanguard MSCI U.S. SmallCap Value
XLE U.S. Energy Sector SPDR
SPY SPDR S&P 500 Index
DBA PowerShares DB Agricultural Commodities
PFF iShares S&P US Preferred Stock Index

 

Below is a performance graph of the portfolio (green) versus SPY (SPDR S&P 500 ETF) and AOR (S&P Growth Allocation) from the portfolio’s inception until August 31st, 2012. Total returns are similar but a significant drawdown was avoided in 2011:

 

Three Permanent Portfolios for the Long-Run

Last week different tactical approaches (momentum, moving average) to the Permanent Portfolio were detailed here. Harry Browne proposed a “Permanent Portfolio” allocation in his 1998 Fail-Safe Investing: Lifelong Financial Security in 30 Minutes.  The portfolio is an equal-weight portfolio of stocks, long-term bonds, cash, and gold. One approach to replicate the Permanent Portfolio is to hold a stock, long-term bond, cash, and gold position.

Another alternative is to hold a mutual fund or ETF that replicates the entire Permanent Portfolio strategy.  Two “one-stop” options presently exist,  the Permanent Portfolio Mutual Fund (PRPFX) and the Global X Permanent ETF (PERM).

Forbes Special Situation Survey did 4 times better than the S&P 500 over the past 5 years. Subscribe now: save $400 and get 2 free gifts.

PRPFX invests 20% of its assets in Gold, 5% of its assets in Silver, 10% of its assets in Swiss franc assets, 15% of its assets in Stocks of U.S. and foreign real estate and natural resource companies, 15% of its assets in Aggressive growth stocks, and 35% of its assets in Dollar assets. This allocation is similar to the one proposed by Browne, but does differ in its allocation weightings and its exposure to real estate, silver, natural resource companies, and the Swiss franc.

In February Global X Funds launched the Permanent ETF (PERM). This ETF seeks to replicate, net of expenses, the Solactive Permanent Index. The index tracks the performance of four asset class categories that are designed to perform differently across different economic environments. They include stocks, U.S. Treasury bonds (long-term), U.S. Treasury bills and bonds (short-term), and gold and silver.

Since its inception in February, PERM has failed to gather significant assets, with total assets currently listed at less than $15 million. It also has thin volume, with average daily volume less than 15,000 shares and its current expense ratio is .49%. The thin volume makes trading more difficult than more widely held ETFs and could lead to larger bid-ask spreads.

In March I compared the early performance of PERM to an equal-weight portfolio of four ETFs: SPY (SPDR S&P 500 ETF), TLT (iShares Barclays 20+ Year Treasury), SHY (iShares Barclays 1-3 Year Treasury Bond Fund), and GLD (SPDR Gold Trust). Below is an update to the two portfolio’s relative performance. Portfolio A is 100% invested in PERM while Portfolio B uses the four ETF allocation. Returns include dividends (PERM has yet to pay a dividend), data courtesy of ETF Replay:

Since its inception PERM has under-performed a 4 ETF strategy.  The 4 ETF strategy has no exposure to silver, while PERM maintains exposure to silver. As you can below, silver (using the ETF SLV as a proxy) has underperformed gold since February 7th (PERM’s inception date). Date courtesy of Yahoo Finance:

Thus, part of the short-term underperformance of PERM could be related to its silver exposure. The performance difference between gold and silver will fluctuate in the long-term, and at times PERM’s silver exposure could aid its performance.

The expense ratio of PERM is also worth considering when evaluating performance. The expense ratio of .49% compares to the SPY expense ratio of .09%, TLT expense ratio of .15%, GLD expense ratio of .40%, and SHY expense ratio of 15%. In an equal weight portfolio these expense ratios average  .20%. However, additional commissions could be generated when each ETF is bought or sold, while a single Permanent allocation to PERM only creates one transaction.

PRPFX is another viable alternative for investors looking for a Permanent Portfolio strategy. However, as detailed above this mutual fund’s allocation strays further than the Harry Browne allocation. Its performance since February in relation to PERM:

PRPFX has an expense ratio of .84%, higher than its ETF counterpart. However, it may offer an alternative allocation preferred by some investors.

The three Permanent Portfolios detailed here all share similar strategies.  However, as we can see, even small (or in the case of PRPFX, moderate) differences in allocations and expense ratios can lead to differences in performance over a relatively short time period. For the long-term investor, identifying these differences and then allocating accordingly will  impact returns in the long run.