Tag Archives: seeking-alpha

4 Portfolio Recipes That Consistently Beat The ‘Lazy Portfolios’

Summary We analyzed several Lazy Portfolios (e.g., static asset allocation portfolios) by running a full set of risk and return metrics. We compared these Lazy Portfolios to over 250 other asset allocation portfolio recipes, both tactical (with dynamic reallocation) and strategic (with a fixed allocation). Four portfolio recipes emerged as winners that consistently beat the Lazy Portfolios. These winners have lower risk and higher return over both the 1-year and 10-year time periods. We recently received a question about the performance of the 8 “Lazy Portfolios” tracked by investment columnist Paul B. Farrell. The term “Lazy Portfolio” refers to a fixed asset allocation that is periodically rebalanced. We like to call this a “strategic portfolio recipe,” but a fixed asset allocation like this can also go by several other names, such as buy-and-hold portfolio, static portfolio, or passive allocation. A strategic portfolio with a fixed allocation can be contrasted with a tactical/dynamic portfolio that changes its allocation over time. Each of the Lazy Portfolios has a backstory or underlying theme, such as modeling the Yale endowment’s asset allocation or copying Ted Aronson’s family portfolio. This article will focus on the overall performance of the 8 portfolios, not their origin stories. Since VizMetrics already tracks over 250 portfolio recipes , we decided to add these 8 Lazy Portfolio recipes to the list of portfolios that we analyze monthly. We were eager to see how these compared to our entire set of strategic and tactical portfolio recipes. The Analysis Process We followed four steps to analyze the risk and return of the Lazy Portfolios and then search for portfolios that outperform the 8 Lazy Portfolios. Create the Lazy Portfolios . We used the exact Vanguard mutual funds and allocations specified for each Lazy Portfolio, and then we backtested their performance using monthly total returns and monthly rebalancing. Our data covered the 10 years ending September 30, 2015. Run the analysis . Then we compared risk and return over the past 1 year and over the past 10 years. We like using the 1-year period since we’ve seen some market turbulence recently, and we like looking at the last 10 years since that period includes the downturn of 2008-2009. If you look at risk vs. return for only a short, upward period, then you can overlook the true risk of the portfolio since the evaluation period doesn’t include much downside variation. Create scatterplots. We plotted risk vs. return for the Lazy Portfolios and all the other portfolios that we track. Filter the results . We found portfolios that beat the Lazy Portfolios, based on both risk and return. Identify the winners . We identified 4 portfolios that beat every Lazy Portfolio over both the 1-year and 10-year periods. The winners included two mutual funds, and two tactical portfolio recipes. Step 1: Create the Lazy Portfolios We created the Lazy Portfolios using Vanguard mutual funds, matching Farrell’s allocations. ETFs could be used instead of mutual funds, but we wanted to remain true to the original portfolio recipes. The Lazy Portfolios are constructed as follows: Lazy Portfolio Name Lazy Portfolio Recipe (ingredients and percentages) Lazy Portfolio: Aronson Family Taxable VEURX =5%, VIPSX =15%, VPACX =15%, VWEHX =5%, VISGX =5%, VISVX =5%, VTSMX =5%, VEIEX =10%, VEXMX =10%, VUSTX =10%, VFINX =15% Lazy Portfolio: Fundadvice Ultimate Buy & Hold VFINX=6%, VFISX =12%, VFITX =20%, VEIEX=6%, VGSIX =6%, NAESX =6%, VISVX =6%, VIVAX =6%, VIPSX=8%, VTMGX =12%, VTRIX =12% Lazy Portfolio: Coffeehouse VFINX=10%, VGSIX=10%, NAESX=10%, VISVX=10%, VIVAX=10%, VGTSX =10%, VBMFX =40% Lazy Portfolio: Margaritaville VIPSX=33%, VGTSX=33%, VTSMX=34% Lazy Portfolio: Dr. Bernstein’s No Brainer VFINX=25%, VEURX=25%, NAESX=25%, VBMFX=25% Lazy Portfolio: Second Grader’s Starter VBMFX=10%, VGTSX=30%, VTSMX=60% Lazy Portfolio: Dr. Bernstein’s Smart Money VEIEX=5%, VEURX=5%, VPACX=5%, VGSIX=5%, NAESX=5%, VISVX=10%, VIVAX=10%, VTSMX=15%, VFSTX =40% Lazy Portfolio: Yale U’s Unconventional VEIEX=5%, VTMGX=15%, VIPSX=15%, VUSTX=15%, VGSIX=20%, VTSMX=30% Step 2: Run the analysis Next we calculated the risk and return metrics for each of the 8 Lazy Portfolios. For the risk measure, we used Maximum Drawdown, which is the maximum percentage that each portfolio lost in value during the period, as measured at the end of each month. We like Maximum Drawdown for measuring risk since it captures quantitatively the “ouch!” that we feel when our portfolio hits the bottom. For the return measure, we used total annual return, which assumes that distributions are reinvested during the period. The Lazy Portfolios showed the following risk and return characteristics, for the period ending September 30, 2015: Lazy Portfolio Name 1-year annual return (%) 1-year maximum drawdown (%) 10-year annual return (%) 10-year maximum drawdown (%) Lazy Portfolio: Aronson Family Taxable -2.8 -9.2 5.9 -41.1 Lazy Portfolio: Fundadvice Ultimate Buy & Hold -2.4 -7.2 5.3 -35.7 Lazy Portfolio: Coffeehouse 0.7 -5.6 6.1 -36.0 Lazy Portfolio: Margaritaville -4.0 -8.5 5.0 -40.5 Lazy Portfolio: Dr. Bernstein’s No Brainer -1.6 -7.8 6.0 -43.3 Lazy Portfolio: Second Grader’s Starter -3.4 -9.6 5.7 -49.2 Lazy Portfolio: Dr. Bernstein’s Smart Money -1.0 -6.3 5.5 -37.6 Lazy Portfolio: Yale U’s Unconventional 0.9 -7.0 6.5 -42.2 Benchmark: The SPDR S&P 500 Trust ETF (NYSEARCA: SPY ) -0.8 -8.5 6.7 -50.8 Note that all the Lazy Portfolios had a maximum drawdown exceeding -35% over the past 10 years, with most worse than -40%. By comparison, the SPDR S&P 500 Trust ETF had a maximum drawdown of -50.8% with a 10-year return of 6.7%. Step 3: Create the scatterplots Now let’s separate the wheat from the chaff using a risk vs. return scatterplot. We plotted the performance of all the Lazy Portfolios along with all the other portfolio recipes in one view. This allows us to visualize two important metrics (risk and return) at the same time. With risk and return shown on the scatterplots below, the best portfolios (with the highest return and lowest risk) appear at the top left. In the plots below, the orange diamonds are the Lazy Portfolios. The blue squares are the portfolio recipes that showed both higher return and lower risk compared to the Lazy Portfolios. The yellow triangles are the additional portfolio recipes tracked by VizMetrics . For a benchmark comparison, we’ve also added SPY, shown as the purple circle. (click to enlarge) The 10-year scatterplot covers the period October 2004 to September 2015. The 1-year scatterplot covers the period October 2014 to September 2015. Step 4: Filter the results You can see that several blue squares are “northwest” (above and to the left) of all the orange Lazy Portfolios. Each blue square represents a portfolio with higher return and lower risk than every one of the Lazy Portfolios. In the 1-year scatterplot, there are 36 blue squares that beat all the Lazy Portfolios. In the 10-year scatterplot, there are 38 blue squares that beat all the Lazy Portfolios. Over the past 10 years, the broad U.S. equity market (represented by an exchange-traded fund, SPY) has generated a higher return than each of the Lazy Portfolios. But this higher return is accompanied by higher volatility. The Lazy Portfolios each have some fixed income exposure and this offers a lower-risk alternative to SPY that some investors may prefer. If we consider both the 1-year and 10-year time period, we find that the following four portfolios beat every Lazy Portfolio based on risk and return: The Four Winners (that outperform all of the Lazy Portfolios) 1-year annual return (%) 1-year maximum drawdown (%) 10-year annual return (%) 10-year maximum drawdown (%) Vanguard Wellesley ( VWINX ) 0.9 -3.2 6.8 -18.8 Vanguard Balanced ( VBIAX ) 1.0 -5.2 6.6 -32.5 Minimum Conditional Value-at-Risk Portfolio ( t.cvar ) 4.1 -4.0 10.0 -11.0 Minimum Drawdown Portfolio ( t.loss ) 8.0 -4.6 9.8 -13.4 Benchmark: S&P 500 ETF -0.8 -8.5 6.7 -50.8 Another portfolio, the “Strategic 60-40 Portfolio” ( s.6040 ) nearly beats all of the Lazy Portfolios, too. This portfolio beats 7 of the 8 Lazy Portfolios (all except “Yale U’s Unconventional”) over the 1-year and 10 year periods. The Strategic 60-40 Portfolio returned 6.4% over 10 years, and “Yale U’s Unconventional” returned 6.5%. Conclusions The 8 Lazy Portfolios do provide some diversification and have shown middle-of-the-pack performance. But there are better choices for investors. If you want a lazy, easy-to-maintain portfolio then either of the Vanguard funds, VWINX or VBIAX, are a better choice. These funds are even lazier than the 8 Lazy Portfolios, since you don’t have to buy and rebalance the ingredients yourself. Importantly, these Vanguard funds also provide better performance with lower risk. That’s a true “no brainer.” Or if you seek higher returns, and if you’re willing to rebalance monthly, you can look at tactical portfolio recipes, such as t.cvar and t.loss . To view the full set of risk and return scatterplots for over 250 portfolio recipes, sign up for a free trial of the VizMetrics Investor subscription. This also includes risk and return analytics for the 1-, 3-, 5-, 7-, and 10-year periods.

Eyeing Q3 Revenue Growth Potential? Try These Sector ETFs

The ETF industry saw height of volatility in the third quarter of 2015 thanks to speculations over Fed tightening, global growth worries, a commodity market crash, horrendous equity sell-off in China and its shockwaves around the world. On the other hand, a strong greenback and a weak energy sector were the other permanent dampeners in the first three quarters of 2015. These evils are also haunting the Q3 earnings season, which has just picked up pace. Though an accommodative Fed and the probability of a delayed rate hike following momentum loss in the U.S. economy charged up stocks to start Q4, issues of the prior quarter will have a significant impact, mostly bad, on the corporate world. Expectations for both earnings and revenue growth remain negative for the quarter. As per the Zacks Earning Trends issued on October 14, 2015, earnings for the S&P 500 are expected to be down 4.9% in Q3 while revenues are likely to decline 5.6%. However, some sectors might surprise, snapping the downtrend and offering decent returns in the ongoing quarter, even if volatility follows through. While looking for these outstanding performers, we would like to highlight those sectors that are likely to post strong revenue gains. This is because; sales are harder to influence an income statement than earnings. A company can land up on decent earnings numbers by adapting cost-cutting or some other measures which do not speak for its core strength. But it is harder for a company to mold its revenue figures. Below, we highlight three lucrative sector ETFs that could be used to book some profits in this whimsical market. Each sector has positive and strong revenue growth estimates for Q3 and offers intriguing fundamentals to protect investors’ portfolios in a dubious global investing backdrop: The Medical or Health Care sector appears the best positioned with an 8.5% revenue growth estimate, the best in the universe of 16 S&P sectors categorized by Zacks. Rise in mergers and acquisitions, the Affordable Care Act, an aging global population and the sector’s non-cyclical nature could earn its some solid gains (read: Obamacare is Here to Stay: 3 ETFs to Buy ). This is especially true as skepticism piles up in the global market. Investors should note that pharma and some biotech companies recently suffered a horrendous sell-off on pricing concerns. On the one hand, the medical device corner showed greater resilience in this tumultuous phase, and on the other hand the sell-off made the entire sector affordable. This should go in its favor. As a result, medical devices ETFs like IHI should log greater gains. XHS is up 2.5% so far this year (as of October 15, 2015) and has a Zacks ETF Rank #1 (Strong Buy) with a Medium risk outlook (read: 2 ETFs Rising to Rank #1 This Earnings Season ). The SPDR S&P Retail ETF (NYSEARCA: XRT ) Though retail sales remained soft lately as evident by the lower-than-expected sales data in September, the revenue growth prospect remains strong. Apart from medical, this is the only sector expected to see revenue growth in high single digits. To add to this, the Fed lift-off talk is now off the table. The Fed is also likely to opt for a slower rate hike trajectory once the step is actually taken, most probably sometime in early 2016. This should favor a cyclical sector like retail. Moreover, the still-subdued oil price is another tailwind for the sector as it would add up to consumers’ fuel price savings and encourage them to buy more discretionary products. However, lackluster job data is undoubtedly a concern for the sector. Retail/Wholesale is projected to register 7.3% revenue growth in Q3, the second best in the pack. XRT is down about 5% so far this year (as of October 15, 2015) and has a Zacks ETF Rank #1 with a Medium risk outlook. The iShares North American Tech ETF (NYSEARCA: IGM ) Tech stocks are giving robust performances of late on higher global IT spending, increased usage of smartphones, tablets or other gadgets, decent valuation and the pile of cash the companies are sitting on. As of now, the Zacks Earnings Trend predicts 3.7% expansion in revenues from tech companies, the third best growth rate. MTK is up about 5% so far this year (as of October 15, 2015). The fund currently has a Zacks ETF Rank #2 (Buy) with a Medium risk outlook. Link to the original post on Zacks.com

How Knowledge Investments Translate Into Superior Profitability

Companies that invest in more knowledge assets, or intangible assets, than their peers leads to a sustainable competitive advantage that manifests itself in superior margins and profitability. Overall, Knowledge Leaders spend about 4x more on intangible investments than Knowledge Follower. The unique capital stock created by knowledge investments enables Knowledge Leaders to command higher margins, keep a more flexible balance sheet, and derive greater profitability than their less knowledge-intensive peers. Regular readers are by now well versed in our belief that companies that invest in more knowledge assets, or intangible assets, than their peers leads to a sustainable competitive advantage that manifests itself in superior margins and profitability. We call these knowledge intensive companies Knowledge Leaders. One of the most important takeaways of the academic literature on knowledge investments is that research shows that knowledge intensive companies end up having higher “future market share, future sales growth and future return on assets” than their less knowledge intensive peers ( Lev, 2005 ). In today’s post, we thought we would illustrate to our readers the statistical differences between Knowledge Leaders and Knowledge Followers. As always, the data we are using Gavekal Capital’s proprietary intangibly-adjusted, USD-based data and we are looking at all mid and large cap companies in the developed world. However, before diving in let me provide a brief overview of how the selection process begins in defining a knowledge leader. The first step of our process is to intangibly-adjust the financial statements of about 3000 companies (2000 in the developed world, 1000 in the emerging markets), going back to 1980 where possible, by removing R&D and a portion of SG&A expense and placing it on the balance sheet as a long-term asset. We carry this new long-term asset, called intellectual property, at historic cost by depreciating the asset and allow the depreciation charge to flow through the statement of cash flows and income statement. The goal here is simply to adhere to the symmetry accounting rule by treating intangible investments as similarly as tangible investments as possible. Once we have an intangible-adjusted set of financial statements, we run the companies through a quantitative screen that looks at seven different variables categorized by: knowledge intensity, financial strength, and profitability. In order for a company to be considered a Knowledge Leader, it must pass the following thresholds: Companies must spend at least 5% of sales on knowledge investments or have at least 5% of assets represented by knowledge. Companies must generate over 20% gross margins. Companies must have less than 3x gross financial leverage. Companies must have less than 50% net debt as a percent of total capital. Companies must have a positive trailing seven year average return on invested capital. Companies must have at least 10% operating cash flow margin on average over the last seven years. Companies must have a positive trailing seven year average free cash flow. For further explanation, please read our three part series on the academic foundation and the real-time application of the Knowledge Effect. Now that we have our foundation in place, let’s begin with the most basic assumption that Knowledge Leaders invest more in intangible assets than Knowledge Followers. Investments in intangible assets fall into two broad categories: research and development (R&D) and firm specific resources. Firm specific resources is a catch-all for other intangible investments such as advertising, brand building, employee training, and codified information. The median Knowledge Leader invests 2.7% of its sales in R&D compared to the median Knowledge Follower which invests just 0.06% of its sales in R&D. The median Knowledge Leader invests 6.9% of its sales in firm specific resources compared to the median Knowledge Follower which invests 2.3% of its sales in firm specific resources. Overall, Knowledge Leaders spend about 4x more on intangible investments than Knowledge Followers. This leads to the median Knowledge Leader having over 7x more intellectual property assets on its balance sheet than the median Knowledge Follower. The median Knowledge Leader has over 15% of its assets in long-term intellectual property. Because investing in knowledge investments creates a unique capital stock, Knowledge Leaders are able command greater profit margins. For those that are familiar with Warren Buffet’s “moat’ concept, a unique capital stock helps to create the moat for a company to maintain its competitive advantages. The median Knowledge Leader has a gross margin of 41.6% while the median Knowledge Follower has a gross margin of just 24.2%. Knowledge Leaders have higher gross margins in nine out of ten sectors. (click to enlarge) Under the archaic accounting rule SFAS #2, knowledge investments must be immediately expensed in the period they occur. This creates a massive distortion on company financial statements as investors have limited information on the innovative activities corporations are undertaking. Because this conservative accounting rule is in place, conservative institutions like banks will not loan money for knowledge investments since there isn’t any physical capital attached to the investment. This leads to a situation where knowledge investments are almost always entirely equity finance and consequently, the balance sheet of Knowledge Leaders is much more liquid and less levered than Knowledge Followers. Knowledge leaders have more cash and less debt as a % of total capital than Knowledge Followers. (click to enlarge) (click to enlarge) (click to enlarge) (click to enlarge) The good news is that Knowledge Leaders are not sacrificing return by having a more liquid, less levered balance sheet either. In fact, the median Knowledge Leader has superior return on assets (ROA), return on equity (ROE) and return on invested capital (NASDAQ: ROIC ). If we break out Knowledge Leaders by sector its very apparent that this profitability superiority is wide and broad based. (click to enlarge) (click to enlarge) (click to enlarge) (click to enlarge) All in all, the unique capital stock created by knowledge investments enables Knowledge Leaders to command higher margins, keep a more flexible balance sheet, and derive greater profitability than their less knowledge intensive peers. The original posting of this article can be found here . All data was created by the author and sourced from Gavekal Capital and FactSet.