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The Global X FTSE Nordic Region ETF: The Perfect Fit

The fund is concentrated, holding 30 of the region’s top companies. Almost every company held in the fund has a broad global reach. Inclusion in the index requires ample market trading liquidity. European economies get a lot of undeserved bad press. Take the European Union for instance. A few of its economies are indeed lagging like Portugal and Greece, but at the same time several are excelling like the United Kingdom and Germany. The same may be said for the core Eurozone economy. Then there are the Central and Eastern European (CEE) states, several of whom have made remarkable strides within the EU. With a moment’s reflection, an economic comparison can be made with the United States. Some states, like New York, California and Maryland are economic powerhouses, whereas Mississippi, Louisiana and Illinois are still struggling with tough economic times. The same is true of the wider region of North American economies like Canada and Mexico. Some states or provinces do well with natural resources or foreign investment while other must rely on seasonal tourism or agriculture. It takes governments with foresight and courage to forge ahead to establish economic zones while being as inclusive as possible. It is, in fact, the basic purpose of an economic zone: to eliminate economic border constraints and provider opportunity for the weaker entities through unencumbered economic interaction with the stronger entities. It’s different from the investor’s point of view, however. For the investor, it’s always a matter of risk vs reward. The majority of individual retail investors do not have loads of free capital to risk on large scale ‘turn-around’ stories no matter how tempting the total returns might be. The average mid-career investor, saving for retirement or college fund, must look for ways to ‘pick and choose’ the best potential reward with the least possible risk. Those higher reward ventures are best left to the so ‘high rollers’; hedge funds, venture capitalist and the like. (click to enlarge) A good example of a region whose economies are outperforming its neighbors is collectively known as Scandinavia . These are the nations of Sweden, Norway, Finland, Denmark (and sometimes Iceland). The region of Scandinavia is loosely defined and more a matter of cultural and historical relations. However, a word or two needs to be said about their legal economic affiliations. First, Norway is, essentially, an independent economic nation whose primary trading partners are in western Europe most of whom are European Union members. Importantly, Norway uses its own free-float currency the Krone . Sweden is a member of the European Union; it retains the use of its free-float currency, the Krona . Denmark is also a member of the EU and for the time being is using its own currency, the Krone . However, Denmark is in the process of adopting the Euro and must maintain a fixed rate (called a peg) with the Euro before it fully adopts the currency. It should be noted that (about) 7.5 Danish Krone is a virtual Euro. Finland is all in: EU and Euro. Although Iceland is considered a part of Scandinavia, it is not an EU member and uses its traditional Krona. The point of the matter is this: for those investors who wish to pick and choose the best regional ETFs with stability and reasonable returns, the Global X family of funds offers the FTSE Nordic Region ETF (NYSEARCA: GXF ) . Global X seeks to: … provide access to high quality and cost efficient investment solutions… …recognized for its smart core, income, alpha, risk management and access suites of ETFs.. . Indeed this is the case with the Nordic Region Fund. The fund’s tracking index is the FTSE Nordic 30 Index. As for the tracking index itself: … The FTSE Nordic 30 Index is designed to represent the performance of the Danish, Finnish, Norwegian and Swedish Stock Exchanges in real time for the purpose of derivative trading. The index consists of the top 30 companies in the FTSE All-World Index – Nordic Region, ranked by full market capitalization. In order to be eligible for inclusion in the Index, securities (other than new issues) must have a velocity of 40% or more. Velocity is based on the previous six months trading and is defined as the total value of six months exchange turnover annualized and shown as a percentage of the full market capitalization… The description includes the terms “derivatives” and “velocity”, however, don’t be put off. The fund does not involve any derivatives, only common stock. The index is composed of companies whose stocks have high trading volume. This works in favor of the investor. Velocity may be more familiarly expressed as liquidity . Since the velocity measurement is based on the previous six months, this is an indication of a large cap stock, i.e., similar to trading volumes experienced by, for example, GE (NYSE: GE ) , Intel (NASDAQ: INTC ) or Alphabet, (NASDAQ: GOOGL ) here in the U.S. Indeed, this will prove to be the case. The FTSE Nordic 30 includes the four continental nations of Scandinavia. The chart below demonstrates that the sector allocation is, for all intents and purposes, identical. (click to enlarge) Data from FTSE and Global X When the returns are tabulated and compared, again, the fund does reflect the FTSE index. Annualized Returns Comparison Year to Date One Year Three Years Five Years Since Inception 8/17/2009 GXF NAV -2.43% -9.91% 7.76% 5.84% 9.16% GXF Shares -1.86% -9.57% 7.88% 5.88% 9.16% FTSE Nordic 30 Index -3.70% -10.30% 7.45% 5.73% 9.04% Data from Reuters As the index suggests, there are indeed 30 holdings in the fund, plus a small cash position. A quick over view of the fund gives a good indication of its true nature. Since there are so few holdings, they are group together where appropriate. For Example, Financials are only financials, however, the few IT , Tech and Telecom Services holdings are grouped together for conciseness; however, the description will make clear their sub-classifications. Data from Global X The heaviest allocation is the Financial Sector, followed by Industrials and Health Care; 82.51% of the fund. The smaller sectors are Consumer Products, Energy and Materials. Financial 28.90% Ticker Fund Weight Market Cap (in USD Billions) Dividend Yield 5 Year Dividend Growth Rate Total Debt to Equity ROI: ROE: Primary Business Nordea Bank OTCPK:NRBAY 5.80% $44.60 6.01% 19.92% 667.54 NA 12.30 Retail, corporate banking, wealth management Sampo OYJ OTCPK:SAXPY 4.19% $27.72 4.17% 14.29% 21.09 NA 15.50 Property, casualty, life, liability, asset, business, agricultural, insurance SwedBank OTCPK:SWDBY 4.13% $24.88 5.91% NA 791.32 NA 14.74 Savings, brick & mortar, telephone and internet; loans, credit, corporate lending Danske Bank OTCPK:DNSKY 3.33% $26.33 2.99% NA 714.24 NA 4.21 Retail banking, mortgages, insurance, RE, asset mgmt; business & corporate banking Svebska HandelsBanken OTCPK:SVNLY 3.16% $25.34 5.02% 16.95% 1032.5 NA 12.21 Private and Corporate banking, financial services, mortgages, credit cards Investor (Industrial Holding company) OTC:IVSXF 3.07% $28.663 2.72% 17.61% 20.32 5.11 6.23 Minority holdings in Nordic big cap industry; also in EQT and Investor Growth Capital funds Skandinaviska Enskilda OTCPK:SVKEF 2.75% $23.14 4.75% 36.56% 560.83 NA 13.33 Merchant, retail, wealth mgmt, insurance DNB ASA OTCPK:DNHBY 2.47% $20.93 3.40% 16.77% 473.32 NA 13.60 Full range of retail, business, corporate; Offices also in Asia and Americas Averages 3.61% $27.70 4.13% *20.35% 535.15 ROE: 11.515 *x-SWEDa and DANSKE Data from Reuters There are, surprisingly, no REITs. With one exception, they are all big cap, well established banks serving their region, the Baltics Europe including the UK and to a lesser extent, Asia and the Americas. The only unusual position in the sector is Investor , which is not a ‘financial’ per se. Investor , is a holding company, buying minority positions in mostly industrials, but also owns portions of private equity group ‘ EQT’ and venture capital fund ‘ Investor Growth Capital ‘. The holdings do have very high total debt to equity ratios. That’s usually an indication of an aggressive growth strategy. This may not be the case here. The overnight reserve rates in these nations are at, near or below 0 in order to deter ‘safe-haven’ capital inflows, which strengthen the currency, making their exports more expensive. These high ratios may reflect offsetting overnight reserve rate strategies. Health Care 18.20% Ticker Fund Weight Market Cap (in USD Billions) Dividend Yield 5 Year Dividend Growth Rate Total Debt to Equity ROI: ROE: Primary Business Novo-Nordisk NVO 16.77% $113.1 1.39% 27.78% 1.46 75.36 81.73 R&D, manufacturing, marketing of biopharma for diabetes and obesity. Africa, Americas, Europe, Russia, Asia, Coloplast OTCPK:CLPBY 1.43% $16.30 2.20% 44.27% 2.12 13.74 16.36 R&D, manufacturing, marketing of Ostomy, Continence, Urology, Chronic wound care products. Global distribution Averages 9.10% $64.65 1.80% 36.03% 1.79 44.55 49.05 Data from Reuters There are only two holdings for Health Care, but it’s just as good, if not better than a portfolio of several holdings. Novo-Nordisk ranks with the premier global pharmaceutical companies as best in class. Coloplast designs, manufactures, markets and distributes niche personal care products. Together, they cover a significant portion of the sector and contribute to the efficiency of the fund. Industrials 19.73% Ticker Fund Weight Market Cap (in USD Billions) Dividend Yield 5 Year Dividend Growth Rate Total Debt to Equity ROI: ROE: Primary Business Assa Abloy OTCPK:ASAZY 3.54% $22.15 1.18% 12.54% 57.43 12.31 20.46 Ingress and Egress security solutions and components Svenska Cellulosa Aktiebolaget OTCPK:SVCBY 3.03% $25.34 5.02% 7.25% 53.78 5.84 8.36 Sustainable forest products, personal care, hygiene, kitchen paper, bath tissue, packaging Atlas Copco OTC:ATTLF 2.95% $31.90 2.58% 14.87% 50.27 19.11 30.80 Industrial and medical solutions compressors, blowers, filter, vacuum, air, piping; safety, productivity, ergonomics focus Kone OYJ OTCPK:KNYJY 2.90% $19.155 2.98% 13.05% 9.29 36.75 44.34 Elevators, escalators, travelator, auto doors; access control systems Sandvik OTCPK:SDVKY 1.77% $12.61 3.98% 28.47% 121.31 6.53 14.90 Mining and Construction tooling solutions; industrial metal cutting AP Moeller Maersk OTCPK:AMKBF 1.72% $31.54 18.93% NA NA NA International ocean freight and oil shipping; towing and salvage SKF OTCPK:SKFRY 1.25% $7.74 3.70% 9.46% 99.06 7.41 18.86 Lubrication, bearings, seals, services, support, solutions Volvo OTC:VOLAF 2.57% $21.55 3.40% NA 181.72 4.50 11.91 Industrial equipment construction division of Volvo Group Averages 2.47% $21.50 5.22% *14.27% **81.837 **13.20 **21.38 *x- AMKBF, VOLAF **x- AMKBF Data from Reuters There seems to be a common theme among Nordic industrials. They are focused on sustainability, recycling and environmental responsibility. This often gives their industrial sector a more cyclically defensive bias. Two examples from the sector are Svenska Celluosa , a forest product paper and packaging company and Kone , essential a ‘people mover’ designer, manufacturer and service company. Both involve products or services that will be in demand in both good and bad times. Technology 15.68% Ticker Fund Weight Market Cap (in USD Billions) Dividend Yield 5 Year Dividend Growth Rate Total Debt to Equity ROI: ROE: Primary Business Nokia NOK 4.84% $28.92 2.17% -20.87% 31.58 7.44 11.96 Network software, hardware, services; networks, voice, data, global mobile Ericsson ERIC 4.72% $31.676 4.09% 12.34% 18.81 5.84 7.67 Telecom service, software, broadband, cloud services, network infrastructure TeliaSonera OTCPK:TLSNF 2.28% $21.20 7.01% 5.92% 100.11 7.13 13.71 Telecom service, network access, mobile services, broadband and landline services Telenor OTCPK:TELNY 2.20% $26.51 4.75% 23.90% 114.97 7.01 9.16 Mobile telecom services, voice, data, internet, telephony and television, landline Hexagon OTC:HXGBF 1.64% $12.4 1.03% 28.67% 48.70 8.45 13.36 IT operations research services; industrial productivity via sensors, software, workflow data Averages 3.14% $24.14 3.81% 9.99% 62.83 7.17 11.17 Data from Reuters When one thinks of technology in the north countries, Nokia and Ericsson immediately come to mind. The interesting holding is Hexagon which applies real time monitoring and data collection towards improving efficiencies and productivity. This may be concisely described as operations research services. Consumer Products 9.71% Ticker Fund Weight Market Cap (in USD Billions) Dividend Yield 5 Year Dividend Growth Rate Total Debt to Equity ROI: ROE: Primary Business Hennes & Mauritz OTCPK:HNNMY 5.75% $53.4 3.05% 4.04% 0.00 41.57 44.71 Design and manufacture of apparel, sportswear, footwear accessories Pandora OTCPK:PNDZF 2.40% $14.32 1.09% NA 55.17 41.42 55.91 Precious metal jewelry and accessories Carlsberg OTCPK:CABGY 1.56% $12.83 1.53% 20.79% 82.84 -2.20 -5.11 World renowned brewer and soft-drink manufacturer Averages 3.24% $26.85 1.89% 12.42% 46.00 26.93 31.84 Data from Reuters The fund seems well thought out in its construct and the consumer sector exemplifies this. It covers the spectrum of consumer products from the very basics to the very discretionary in just three holdings. Energy 3.57% Ticker Fund Weight Market Cap (in USD Billions) Dividend Yield 5 Year Dividend Growth Rate Total Debt to Equity ROI: ROE: Primary Business StatsOil STO 2.41% $49.24 5.87% 15.63% 77.90 -4.86 -10.32 Global oil and gas exploration, development production Fortum OYJ OTC:FOJCF 1.16% $13.1 9.35% 5.39% 44.15 -8.63 -13.94 Heat and electric production and distribution; plant management services and solutions Averages 1.79% $31.17 7.61% 10.51% 61.03 -6.75 -12.14 Data from Reuters Again, two holdings of best-in-class companies covering the industry from wellhead to home; simple, well founded and concise. Materials 3.31% Ticker Fund Weight Market Cap (in USD Billions) Dividend Yield 5 Year Dividend Growth Rate Total Debt to Equity ROI: ROE: Primary Business Novozymes OTCPK:NVZMY 1.92% $12.36 0.89% 21.14% 12.73 19.15 24.69 Industrial bioengineered enzymes for consumer products; agricultural and feed additives; wastewater treatment Yara International OTCPK:YARIY 1.39% $12.22 3.35% 23.64% 18.32 12.18 14.75 Sustainable fertilizer production, marketing and distribution ammonia, nitrates, nitrogen, phosphorous and potassium Averages 1.66% $12.29 2.12% 22.39% 15.53 15.67 19.72 Data from Reuters Two unique holdings covering the very essence of materials manufacturing products that are less sensitive to business cycle swings: enzymes for household cleaning products, wastewater recycling, agricultural feed, food flavorings, ingredients, and essential fertilizer chemicals all produced with sustainability and environmentally friendly methods. (click to enlarge) A few things need to be said for the fund itself. The expense ratio just a bit higher than average at 0.50%; the distributions are annual. The fund is not large with 30 holdings and roughly $52,249,671.00 in assets. Volume seems reasonable with a three month average daily volume of about 4300 shares/day; more than enough liquidity for a retail position. Smaller, focused ETFs seem to have an advantage over those larger comprehensive funds with hundreds of holdings. Having two or three large funds will most likely result in ‘overlapping positions’ and may have risks not easily noticed among so many holdings. Also, smaller ETFs create the opportunity to piece together the best performers of a region, in a much focused way, and the Global X FTSE Nordic Region ETF is a perfect fit for what an interested retail investor needs to construct an efficient yet diversified portfolio. Lastly, the investor should be aware of a slight currency risk. On December 3rd, the ECB announced a continuation of its weak Euro policy. The non-Eurozone or other European central banks must somehow respond in order to maintain purchasing power parity. Europe, EU or not, has a large, internal trading network so purchasing power parity must be maintained. Hence, when translating back to U.S. Dollars, there may be a short term risk, if any at all; it will present an opportunity if it occurs. One last word about Global X: the website presentation is well thought out and interesting. The link to the GXF page contains a link to a ‘minisite’. The minisite presents an overview of the Scandinavian region: the economies, sovereign credit quality, demographics and culture; a welcome addition to the usual facts & figures presentation. Editor’s Note: This article discusses one or more securities that do not trade on a major U.S. exchange. Please be aware of the risks associated with these stocks.

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