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Vanguard Capital Preservation Strategy: Effect Of Trade Day And Look-Back Period Length

Further analysis of the Vanguard Capital Preservation (VCP) tactical strategy is presented. The effects of trade day and look-back momentum period on performance and risk are shown. It is shown that the best trade days are end-of-month (EOM) and first day of the next month (EOM+1). Trading on other days reduces performance and increases risk. In a parametric study of look-back periods systematically varied from 10 trade days to 30 trade days, it is shown that the 21-day (one calendar month) look-back period is optimal. The final VCP strategy using a dual momentum approach and backtested to 1988 has a CAGR of 13.0%, a MaxDD of -5.8%, and a MAR of 2.2. This mutual fund strategy can be traded monthly (every 30 days) on the Vanguard platform without any costs. However, a strict schedule must be followed. Introduction to Vanguard Capital Preservation Strategy This article continues the analysis of the Vanguard Capital Preservation [VCP] strategy originally described here . The VCP strategy updates on a monthly schedule and uses a dual momentum approach. In this strategy, there are six Vanguard mutual funds in the basket of funds covering both equity and bond assets, and the two best (highest momentum) funds are selected at the end of each month. The relative strength momentum ranking is based on a one calendar month look-back period. Absolute momentum is used for risk control, i.e. the two funds with the highest relative strength momentum ranking must have returns greater than the money market asset in order to be actually selected. The out-of-market asset is VFIIX (although a money market asset can be used with little decrement in performance). The basket of funds is the following: Vanguard Convertible Securities Fund (MUTF: VCVSX ) Vanguard Health Care Fund (MUTF: VGHCX ) Vanguard High Yield Corporate Fund (MUTF: VWEHX ) Vanguard High Yield Tax-Exempt Fund (MUTF: VWAHX ) Vanguard GNMA Fund (MUTF: VFIIX ) Vanguard Intermediate Term Treasury Fund (MUTF: VFITX ) All of these funds have histories that date back to 1986 except VFITX that only goes back to 1991. To backtest to 1988, the Dreyfus U.S. Treasury Intermediate Fund (MUTF: DRGIX ) is substituted for VFITX. By backtesting to 1988, the strategy shows that it can successfully handle various market conditions including bull markets and bear markets. Please take note that a few of the funds presented in this article are slightly different than those described in the previous article. The other change is that the out-of-market asset is now VFIIX instead of a money market asset. These slight changes were made to improve the overall strategy. Any investor can take the parameters discussed above and insert them into Portfolio Visualizer [PV], a commercially-free backtest software program. PV will backtest the strategy to 1988, plus it will select what funds to select at the end of each month. Results of VCP Strategy The backtested results of the VCP strategy are shown below. The backtest results are produced by Portfolio Visualizer [PV]; the timespan is 1988 – present. Total Return: 1988 – 2015 (click to enlarge) Annual Returns: 1988 – 2015 (click to enlarge) Drawdowns: 1988 – 2015 (with S&P 500 included) (click to enlarge) Drawdowns: 1988 – 2015 (without S&P 500 included) (click to enlarge) Overall Summary: 1988 – 2015 (click to enlarge) It can be seen that the Compounded Annualized Growth Rate [CAGR] is 13.0%, the Standard Deviation [SD] is 6.7%, and the Maximum Drawdown (MaxDD) is -5.8%. This gives a MAR (CAGR/MaxDD) of 2.24. How these numbers compare to a buy & hold strategy (rebalanced annually) and the S&P 500 are presented in the table above. For the buy & hold strategy, the CAGR is 9.0%, the SD is 5.3%, and the MaxDD is -14.3%. This gives a MAR of 0.63. Thus, the tactical strategy is a significant upgrade to the buy & hold strategy. Likewise, the tactical strategy is significantly better that the S&P 500 that has a CAGR of 10.4%, a SD of 14.5%, a MaxDD of -51.0%, and a MAR of 0.20. There are no negative years for the VCP strategy; the worst year has a positive 1.9% return (in 2002). This compares with a worst year of negative 37.0% for the S&P 500 (in 2008) and a worst year of negative 10.3% (in 2008) for the buy & hold strategy. Further Assessment of VCP Strategy In this article, further analysis of the VCP strategy will be presented. In particular, the effect of trade day on backtest results will be assessed, as will the effect of look-back period length. Herbert Haynes has developed a backtester that can be used to study these effects. Haynes’ backtester using dual momentum was set up a little different that the dual momentum approach by PV. In particular, the absolute momentum part of the Haynes’ backtester is slightly different than PV’s absolute momentum test. Haynes followed the conventional absolute momentum technique by Gary Antonacci that uses pure cash or any other asset as the absolute momentum test, and then uses that same asset as the out-of-market asset. In PV, the absolute momentum test is always money market (i.e. 1-month T-Bill returns), and the out-of-market asset can be anything specified by the user. So for the VCP strategy using PV, the absolute momentum test was money market, and the out-of-market asset was VFIIX. For the Haynes’ backtester, the absolute momentum test was VFIIX, and the out-of-market asset was VFIIX. This slight variation between calculations did not cause any significant difference between PV results and Haynes’ backtester results for EOM calculations. First Parametric Study: Trade Day vs. Number of Assets Using the Haynes’ backtester, we first looked at the effect of trade day on performance and risk. For this parametric study, we independently varied the number of assets selected each month (1, 2, and 3) and the trade day. The trade day was varied between EOM-10 trade days and EOM+10 trade days. Heatmap results are shown below. They were skillfully created by Herbert Haynes. Heatmaps are presented for CAGR, MaxDD, and Sharpe Ratio. The colors range from red being worst to blue being best. So cold spots [blue] are desired for each variable. The numbers on the top of each heatmap (-10 to 10) correspond to the trade day. Zero (not actually specified) corresponds to the EOM. The number [-1] stands for EOM-1. The number [1] signified EOM+1. The numbers on the left (1 to 3) correspond to the number of assets selected each month in the VCP strategy. CAGR: Range = 8.5% [red] to 15.3% [blue] (click to enlarge) MaxDD: Range = -27.5% [red] to -6.8% [blue] (click to enlarge) Sharpe Ratio (CAGR/SD): Range = 0.85 [red] to 2.04 [blue] The heatmaps show that the best trading days center around EOM-1 to EOM+1. The optimal number of assets seems to be two when both CAGR and MaxDD are considered. Second Parametric Study: Trade Day vs. Look-back Length The number of assets was set to two, and another parametric was run on Haynes’ backtester. In this parametric study, trade day and look-back length were independently varied. The results are shown below in the form of heatmaps. Heatmaps are presented for CAGR, MaxDD, Volatility (Standard Deviation), and MAR (CAGR/MaxDD). The numbers on the top of each heatmap are the trade days as previously discussed, and the numbers to the left of each heatmap are the look-back trade days for the relative strength momentum. The look-back trade days range from 10 days to 30 days. CAGR: Range = 8.2% [red] to 14.1% [blue] (click to enlarge) MaxDD: Range = -27.3% [red] to -6.3% [blue] (click to enlarge) Volatility [SD]: Range = 6.3% [red] to 8.3% [blue] (click to enlarge) MAR [CAGR/MaxDD]: Range = 0.3 [red] to 2.1 [blue] (click to enlarge) For CAGR, an optimum band is seen going from the upper left corner to the lower right corner. Short look-back periods (11 to 14 days) combined with trading between EOM-8 to EOM-1 seem to be optimal and robust. But the MaxDD results show a different optimal window: look-back periods between 20 – 23 days and trade days between EOM and EOM+2. In terms of volatility, a vertical optimal band is seen that occurs between EOM and EOM+2. The MAR heatmap shows an optimal window between look-back periods of 20 days and 26 days, and trade days between EOM and EOM+2. Overall, the optimal window seems to be around one-month in look-back length, and EOM and EOM+1 in trade days. Conclusions The analysis presented in this article indicates that two assets should be selected in the VCP strategy (from a basket of six assets). The analysis also indicates that the VCP strategy should be traded at EOM or EOM+1. Trading on other days may significantly reduce returns and increase drawdown. The optimal momentum look-back period is one calendar month. Some Practical Issues After further study, it now seems that trading mutual funds on a monthly schedule can only be accomplished using the same family of mutual funds. When different families of funds are used in a monthly strategy, sell and buy trades cannot be executed on the same day. This prevents the execution of a monthly tactical strategy using mutual funds if funds from different families are used. This issue is circumvented when the basket of funds are all in the same family. Then you can sell and buy funds on the same day. That is why only Vanguard funds are used in the actual application of this strategy. This is important because Vanguard blocks the buying of a fund for 30 calendar days after the fund has been redeemed. But this 30-day trade restriction can be accommodated in a monthly schedule if the trade day moves around slightly between EOM and EOM+1. I have presented a trading schedule in my previous article that will satisfy the 30-day trading restriction. It must be followed rigorously, or the trade day will slip downstream. And, as shown, trading on days other than EOM or EOM+1 reduces return and increases risk. The only drawback in this application is that selections must sometimes be made before EOM data are available. In these cases, EOM-1 data must be used to make the selections, with the caveat that there will be some selections that differ from the EOM selections. Going back to 2007, it was seen that EOM-1 selections differed from EOM selections about 17% of the time (averaging 4 selections out of 24 selections each year). This percentage was rather constant over the years. It was also observed that the EOM-1 selections out-performed the EOM selections over the next month about half the time. This seemed to indicate that using EOM-1 data to determine selections is not overly problematic. It is rather easy to use EOM-1 data to come up with fund selections by using StockCharts.com. Using PerfCharts, the list of funds is inserted into the symbol box, and the number of days (that varies each month between 20 days and 24 days) is inserted into the slider box. Set the start date at EOM-1 of the preceding month and the end date at EOM-1 of the current month. The percent return is seen to the right in the resulting figure. As an example, the PerfCharts plot for December selections is shown below. The slider box has 21 days for this month. It can be seen that VCVSX and VWAHX are the selections. And please note that they are both greater than absolute momentum, i.e. zero percent return. (click to enlarge) We have also found another issue in using EOM PV selections that readers need to be aware of. Many investors will look at PV’s selections at EOM and trade accordingly on EOM+1. It turns out that the latest EOM dividend distributions for mutual funds are not usually included in the EOM data feed. This means the adjusted prices are not correct at EOM, and so the selections by PV at EOM may be in error because total returns do not include the latest dividend distribution. The correct adjusted price data are not provided to PV until a number of days after EOM. Thus, the backtest results are correct, but the selections at EOM may be in error using PV. The only way around this challenge is to calculate total returns yourself by using historical data from a data source such as Yahoo. The Yahoo data will also be in error because the dividend distribution at EOM will not be included. Thus, Yahoo adjusted price data must be modified so that the effect of the latest dividend distribution is included. This is very easy to do and could be automated by skilled Excel users.

HACK: Too Much Industry Hype, Too Little Fundamental Support

Summary Cyber-security market top line growth doesn’t necessarily translate to profit growth for companies. Most companies are still spending a large portion of gross profit on R&D for new software/hardware solutions and marketing & selling to boost brand recognition and gain market shares. Until the industry consolidates and SG&A costs stabilize, it’s hard for these companies to retain profits. Recommendation: Sell Although the cybersecurity market is expected to grow at a phenomenal rate, in my opinion it doesn’t necessarily translate to profit growth for companies. Since cybersecurity is a relatively new industry, most companies are still spending a large portion of gross profit on R&D for new software/hardware solutions and marketing & selling to boost brand recognition and gain market shares, resulting in negative bottom line for most companies. Choppy as the cash flow from operation (CFO) growth is, most cybersecurity companies have positive operating cash flow and incur little CapEx. Going forward, keeping up with hacker’s technology requires constant R&D spending on upgrading and updating technology, and large marketing & selling expense to compete for market shares remains a headwind for these companies in this highly fragmented market. Until the industry consolidates and SG&A costs stabilize, it’s hard for these companies to retain profits. ETF Info Price 27.16 52 Wk H 33.91 52 Wk L 18.29 30D Avg Volume 396,270 Market Cap 1,114,917,969 Shares Out 41.05 Return YTD 3.66% Excess Return YTD -1.97% Tracking Error 1.70 Inception Date 11/12/2014 Expense Ratio 0.75% ETF Summary The PureFunds ISE Cyber Security™ ETF (NYSEARCA: HACK ) tracks the price and yield performance of the ISE Cyber Security™ Index, which includes companies or ADRs that are hardware/software developers for cyber security (“Infrastructure Providers”) or non-development service providers (“Service Providers”). The ISE Cyber Security index assigns weights to companies according to category (“Infrastructure providers”/”service providers”) and then is adjusted according to liquidity and market cap. For more information, you can refer to the PureFunds website . Companies Updates When looking at financial statements of the holding companies, other than 6 companies that had negative sales growth for the past year (~-5%), 26 companies had 10%+ sales growth with on average 70% gross margin. A large chunk of gross profit goes to R&D and Selling & Marketing expenses, resulting in negative profit margin for some of the companies. The gap between sales growth and net income growth is largely attributable to SG&A spending. Most of these companies don’t incur much CAPEX and have positive free cash flow when adding back non-cash charges (mostly stock-based compensation and debt amortization). However, the stock-based compensation is a meaningful real expense and will likely to continue due to continuous talent acquisitions. Operating cash flow growths are choppy and unpredictable. These companies have a median forward PE of 22.7x and average forward PE of 40x (vs. S&P 500 average 18.7x forward PE). Among the top 10 holdings, 5 are experiencing fast sales growth for the past several years, 4 have stagnant growth, and 1 had negative growth (shown later in this article). MIN MAX MEDIAN AVERAGE S&P 500 Sales growth (%, FY) -23.2 163.5 8.2 16.1 Net Income growth (%, FY) -2620.1 1865.2 -11.4 -70.9 EBITDA growth (%, FY) -230.5 123.6 5.2 -14.5 CFO growth (%, FY) -122.4 302.8 3.7 21.3 FY Gross margin 9% 95% 76% 67% FY EBITDA margin (adj) -89% 62% 11% 8% FY Operating margin -111% 56% 9% 4% FY Net margin -112% 44% 5% -1% FY CFO/sales -31% 59% 19% 18% FY FCF/sales -47% 56% 14% 14% FY capex -3879.7 -1.4 -14.5 -244.8 FY FCF/capex -2.9 60.7 4.4 8.0 PE(forward) 13.7 312.1 22.7 40.4 18.7 PB 0.9 38.8 5.1 7.5 2.8 *data gathered from yahoo finance and Bloomberg, compiled by author Looking at the table above, the median sales growth is 8%, meaning more than 50% of these companies are doing fine on the top-line. However, median net profit growth is negative, meaning profits for more than 50% of the companies are shrinking. Would you buy into an industry where profits for companies are stagnant or shrinking? Probably not. What worsens the situation is the assigned weights. This ETF is almost as if it’s assigning equal weight to all the companies – the largest holding is 4% and the smallest is

10 Ways To Destroy Your Portfolio

With the increased frequency of heightened volatility, investing has never been as challenging as it is today. However, the importance of investing has never been more crucial either, due to rising life expectancies, corrosive effects of inflation, and the uncertainty surrounding the sustainability of government programs like Social Security, Medicare, and pensions. If you are not wasting enough money from our structurally flawed and loosely regulated investment industry that is inundated with conflicts of interest, here are 10 additional ways to destroy your investment portfolio: #1. Watch and React to Sensationalist News Stories: Typically, strategists and pundits do a wonderful job of parroting the consensus du jour. With the advent of the internet, and 24/7 news cycles, it is difficult to not get caught up in the daily vicissitudes. However, the accuracy of the so-called media experts is no better than weather forecasters’ accuracy in predicting the weather three Saturdays from now at 10:23 a.m. Investors would be better served by listening to and learning from successful, seasoned veterans. #2. Invest for the Short Term and Attempt Market Timing: Investing is a marathon, and not a sprint, yet countless investors have the arrogance to believe they can time the market. A few get lucky and time the proper entry point, but the same investors often fail to time the appropriate exit point. The process works similarly in reverse, which hammers home the idea that you can be 200% wrong when you are constantly switching your portfolio positions. #3. Blindly Invest Without Knowing Fees: Like a dripping faucet, fees, transaction costs, taxes, and other charges may not be noticeable in the short-run, but combined, these portfolio expenses can be devastating in the long run. Whether you or your broker/advisor knowingly or unknowingly is churning your account, the practice should be immediately halted. Passive investment products and strategies like ETFs (Exchange Traded Funds), index funds, and low turnover (long time horizon / tax-efficient) investing strategies are the way to go for investors. #4. Use Technical Analysis as a Primary Strategy: Warren Buffett openly recognizes the problem with technical analysis as evidenced by his statement, “I realized technical analysis didn’t work when I turned the charts upside down and didn’t get a different answer.” Legendary fund manager Peter Lynch adds, “Charts are great for predicting the past.” Most indicators are about as helpful as astrology, but in rare instances some facets can serve as a useful device (like a Lob Wedge in golf). #5. Panic-Sell out of Fear And Panic-Buy out of Greed: Emotions can devastate portfolio returns when investors’ trading activity follows the herd in good times and bad. As the old saying goes, “Following the herd often leads to the slaughterhouse.” Gary Helms rightly identifies the role that overconfidence plays when in investing when he states, “If you have a great thought and write it down, it will look stupid 10 hours later.” The best investment returns are earned by traveling down the less followed path. Or as Rob Arnott describes, “In investing, what is comfortable is rarely profitable.” Get a broad range of opinions and continually test your investment thesis to make sure peer pressure is not driving key investment decisions. #6. Ignore Valuation and Yield: Valuation is like good pitching in baseball…very important. Valuation may not cause all of your investments to win, but this factor should be an integral part of your investment process. Successful investors think about valuation similarly to skilled sports handicappers. Steven Crist summed it up beautifully when he said, “There are no ‘good’ or ‘bad’ horses, just correctly- or incorrectly-priced ones.” The same principle applies to investments. Dividends and yields should not be overlooked – these elements are an essential part of an investor’s long-run total return. #7. Buy and Forget: “Buy-and-hold” is good for stocks that go up in price, and bad for stocks that go flat or decline in value. Wow, how deeply profound. As I have written in the past, there are always reasons of why you should not invest for the long term and instead sell your position, such as: 1) new competition; 2) cost pressures; 3) slowing growth; 4) management change; 5) excessive valuation; 6) change in industry regulation; 7) slowing economy; 8) loss of market share; 9) product obsolescence; 10) etc, etc, etc. You get the idea. #8. Over-Concentrate Your Portfolio: If you own a top-heavy portfolio with large weightings, sleeping at night can be challenging, and also force average investors to make bad decisions at the wrong times (i.e., buy high and sell low). While over-concentration can be risky, over-diversification can eat away at performance as well – owning a 100 different mutual funds is costly and inefficient. #9. Stuff Money Under Your Mattress: With interest rates at the lowest levels in a generation, stuffing money under the mattress in the form of CDs (Certificates of Deposit), money market accounts, and low-yielding Treasuries that are earning next to nothing is counter-productive for many investors. Compounding this problem is inflation, a silent killer that will quietly disintegrate your hard earned investment portfolio. In other words, a penny saved inefficiently will lead to a penny depreciating rapidly. #10. Forget Your Mistakes: Investing is difficult enough without naively repeating the same mistakes. As Albert Einstein said, “Insanity is doing the same thing, over and over again, but expecting different results.” Mistakes will be made and it behooves investors to document them and learn from them. Brushing your mistakes under the carpet may make you temporarily feel better emotionally, but will not help your financial returns. As the year approaches a close, do yourself a favor and evaluate whether you are committing any of these damaging habits. Investing is tough enough already, without adding further ways of destroying your portfolio. Disclosure: Sidoxia Capital Management (SCM) and some of its clients own certain exchange traded funds, but at the time of publishing SCM had no direct position in any other security referenced in this article. No information accessed through the Investing Caffeine (IC) website constitutes investment, financial, legal, tax or other advice nor is to be relied on in making an investment or other decision. Please read disclosure language on IC “Contact” page.