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How To Build An Alpha-Rich Portfolio Around Preferred Shares

Summary After taking a look at PFF, I decided it would be worth looking into ways that an investor could use it heavily in a low risk portfolio. The resulting portfolio underperforms SPY in a strong bull market, but does very well at limiting volatility. Looking at the max drawdown shows that over the last 4 years the worst drawdown on the portfolio was only 7.9%. If investors are considering holding cash in their portfolio to reduce the volatility, they may want to consider this style of portfolio instead. After covering the iShares U.S. Preferred Stock ETF (NYSEARCA: PFF ) and noticing that it had some very attractive risk characteristics and a very strong yield at 6%, I decided it was worth looking into the impacts of designing a portfolio for very low volatility at the portfolio level while maintaining a fairly strong yield for investors. I think this is one of the most reasonable ways to incorporate a heavy allocation to PFF in a portfolio. I built a portfolio using only a few tickers so it is reasonably simple to duplicate. Portfolio The Portfolio uses the Schwab U.S. Dividend Equity ETF (NYSEARCA: SCHD ) as the core of the portfolio since it has been noticeably less volatile than whole market ETFs, has a respectable dividend yield with dividends regularly growing, and an expense ratio of only .07%. The next major allocation is a very long duration treasury ETF, the Vanguard Extended Duration Treasury ETF (NYSEARCA: EDV ). The iShares U.S. Preferred Stock ETF gets the same 20% allocation as EDV. The next holding is the iShares MSCI USA Minimum Volatility ETF (NYSEARCA: USMV ) because it has a fairly low beta and fits very well in portfolios designed to minimize total risk at the portfolio level. The final allocation goes to the iShares J.P. Morgan USD Emerging Markets Bond ETF (NYSEARCA: EMB ) with 5% of the portfolio. This is incorporated because it has such unique risk factors that it ends up having only moderate correlations with each other investment while having a yield just over 4.5%. The portfolio is demonstrated below: (click to enlarge) The great thing about this portfolio is that over a sample period of nearly 4 years the annualized volatility is only 6.5% which puts the portfolio volatility at slightly under half of the volatility on the SPDR S&P 500 Trust ETF ( SPY). In other words, an investor holding 50% SPY and 50% cash would have witnessed a higher level of volatility in their portfolio. During the period the worst drawdown was falling 7.9%. All around this is a very resilient portfolio because the risk factors have been so effectively diversified. Alpha Investors may notice that this portfolio has materially underperformed SPY over the sample period, but it is meant to underperform SPY during strong bull markets. When SPY is up almost 77% in less than 4 years, I’m going to call that a strong bull market even if we saw some huge shocks in August. The annual rate of return on SPY is about 16%. The annual rate of return on the portfolio was 11.4%. If investors start from portfolio volatility (rather than beta) for establishing alpha, this portfolio would to create about half of the difference between SPY and the risk free rate. Since the portfolio only underperformed SPY by 4.66% annually during a solid bull market. If we round up the risk on the portfolio to being half of SPY, then we subtract (4.66% * 2) or 9.31% to find the risk free rate necessary to eliminate the entire alpha. The risk free rate that would have neutralized the alpha is 6.73%. I think it is reasonable to say that this portfolio performed very well on a risk adjusted basis relative to investors that were going 100% into SPY or another very similar broad ETF. Correlations A major reason for the strong performance is the correlation within the portfolio. The long term treasury ETF has only a slight positive correlation with the emerging market bond fund, but it is negative with everything else. Both SCHD and USMV have lower levels of volatility than SPY and PFF and EMB have reasonably low levels of annualized volatility combined with moderate correlations to the rest of the portfolio. Conclusion Over the last 4 years this ETF strategy has demonstrated very reasonable returns while being substantially more resilient to periods of weakness. In a prolonged bull market it will fall behind SPY, but on a risk adjusted basis it is still performing very well and if there was a major correction it would be in position to lose substantially less. In my opinion, this kind of strategy is the most reasonable way to incorporate a heavy allocation of PFF into a portfolio. Why would you want to build a portfolio with a heavy allocation to a preferred share ETF? I can think of one solid reason off the top of my head, a dividend yield over 6% at a time when interest rates in much of the economy fail to offer any compelling returns. Disclosure: I am/we are long SCHD. (More…) I wrote this article myself, and it expresses my own opinions. I am not receiving compensation for it (other than from Seeking Alpha). I have no business relationship with any company whose stock is mentioned in this article. Additional disclosure: Information in this article represents the opinion of the analyst. All statements are represented as opinions, rather than facts, and should not be construed as advice to buy or sell a security. Ratings of “outperform” and “underperform” reflect the analyst’s estimation of a divergence between the market value for a security and the price that would be appropriate given the potential for risks and returns relative to other securities. The analyst does not know your particular objectives for returns or constraints upon investing. All investors are encouraged to do their own research before making any investment decision. Information is regularly obtained from Yahoo Finance, Google Finance, and SEC Database. If Yahoo, Google, or the SEC database contained faulty or old information it could be incorporated into my analysis.

Why Comparing Returns Is A Bad Way To Choose An Investment Manager

Summary Short-term or recent returns give little information about future returns, and they increase the odds you’ll make a bad decision. Far too often, investors put significant weight on short-term performance, in many cases by choosing the investment with the highest recent investment return. This tends to actually produce future underperformance. The better way to choose an investment manager is to look at service, fit, and investor returns. The greatest trick the stock market ever pulled was convincing investors that historical returns are predictive. They aren’t. In fact, historical returns not only give you very little information about future returns, but they can also increase the odds you’ll make a bad decision. We often see this bias in investors. Both reporters and prospective customers often ask us, “What are your returns?” I cringe when I hear this. Out of all the questions you should be asking, this one should be low on the list. There are far more informative and useful questions to ask, once you know what’s in our portfolio . To be fair, there are aspects of the answer that can be helpful. Returns can give you an idea of the size of upswings and drawdowns, and how the portfolio relates to other asset classes. But in a passive, index-tracking portfolio, such as Betterment’s, you shouldn’t expect to see market alpha in our performance. When properly benchmarked, we are the benchmark. The other common mistake people make is comparing our portfolio to another over a short period of time. If, after six months, our portfolio has a lower return, they’ll often ask, “Why should I use you if your returns are worse?” Far too often, investors put too much weight on small sample, recent historical performance, choosing the investment with the highest investment return. How deceptive can this be? Our interactive tool below shows that this method leads to astonishingly high odds that they’ll underperform both in absolute and risk-adjusted terms in the future. How the Data Deceives You might not realize it, but when you look at historical returns, you’re doing a statistical analysis. Any set of historical returns comprises a sample of behavior over a certain period. Any inferences you make about what they tell you of the future should be balanced by placing them into context of how variable they are. And when you do that, two clear issues arise. Fooled by Randomness The first is being “fooled by randomness,” a phrase coined by Nicholas Nassim Taleb, a risk analyst and statistician. When you choose the highest returning of two correlated investments using a small sample of historical data, the odds are incredibly high that you picked the wrong fund. The randomness of small samples overwhelms the truth. Let’s work through some examples. We’ll use hypothetical portfolios with return probabilities we know for certain, because we’ve created them through simulation, and see how well the short-term data mimics the long-term truth. These are not Betterment portfolios. Portfolio A will have a mean annual return of 6% and a volatility of 14%. Portfolio B has a mean return of 6.5% and annual volatility of 13%. The portfolios will also have a 0.90 correlation to each other-most stock funds have higher correlations. By both measures of absolute return and risk-adjusted return, Portfolio B is better. Yet over the first randomly simulated six-month period, Portfolio A came out ahead. One 6-Month Simulation (click to enlarge) How often does the worse portfolio come out ahead over a short time period? In this case, we’ll call them C and D, with the same parameters. Let’s look at running 1,000 of such simulations over a six-month period. How often does Portfolio D, who should be the winner, come out ahead? Many Simulations Over 6 Months (click to enlarge) The answer is so close to 50% as to be indistinguishable from it. In fact, we can increase the differences in expected returns and this remains true. Let’s give Portfolio D a mean return of 8% and Portfolio C a mean return of 6%. Both have 14% volatility. The significantly higher return Portfolio D will still lose over 40% of the time over a six-month period. Many Simulations Over 6 Months (click to enlarge) While the odds are just better than 50/50 in the short term, they have big consequences in the long term. Here are the distributions of 20-year outcomes for those same portfolios: Many Simulations Over 20 Years (click to enlarge) The randomness in half-year returns results in choosing the wrong portfolio about half the time, even with large difference in return. You might as well save yourself the time and expense and flip a coin. Over long periods of time (20 years), and with large differences in average returns, the odds of picking the correct choice do increase. But you may be surprised how long it can take. For portfolios with a 1% return difference, by 20 years you still have about a one-in-four chance of picking the portfolio that will have worse underlying returns over even longer periods of time. Chance of Choosing Worse Portfolio Based on Performance Return Difference 3 months 6 months 1 Year 5 Years 10 Years 20 Years 0.50% 49% 48% 48% 42% 40% 37% 1.0% 47% 46% 44% 36% 32% 26% 2.0% 44% 43% 37% 26% 16% 9% Each cell based on 3,000 simulated cumulative returns of better portfolio (8% return) versus a benchmark portfolio with a mean return of 6% and 14% volatility. Correlation of 0.90 between portfolios. To be clear, there are statistical tools you can use to improve your odds of picking the right portfolio, but most investors aren’t professional statisticians. They just go by the cumulative returns over a short period of time. Performance Chasing Is Worse Than Random If the low odds of correctly choosing a better portfolio above didn’t convince you, it’s even worse than that. Empirically, choosing the best funds, a strategy called performance chasing, is likely to reduce your returns. The graph below comes from an excellent research paper from Vanguard. It shows the returns achieved by investing in the best fund in each asset class, compared to a buy-and-hold strategy. Performance chasing-picking investment based on recent performance-produced worse returns of about -2% to -3.5%. Buy-and-Hold Superior to Performance Chasing, 2004-2013 (click to enlarge) If every year, you picked the investment manager with above average returns over the past 12 months, you’d end up underperforming an investor who stuck with the passive index-tracking manager. The Right Things to Consider If recent investment performance is such a poor way to choose an investment manager, how should you select one? Use a set of clear principles that are likely to be true in the future: Monetary Cost: A certain drag on returns, if the service doesn’t deliver value above cost. Consider commissions, trade fees, and assets under management (AUM) fees. Non-Money Costs: How much time and and effort does it take for you to use it well? Does it have a high time or stress cost for you to get the most out of it? Services Offered: Do the services offered make you better off? Does it do things for you which you wouldn’t do yourself? Does it help you make better decisions? Does it make some of those decisions for you, automatically? Experience: Is it easy to use? Do you enjoy using it? Philosophy Fit: Consider its investment philosophy, and if it is parallel to yours. Some funds seek to deviate from the index and cost more, some seek to track it passively. Tax Management: Returns will likely not take into account actual value-adds , such as tax loss harvesting. You won’t have received a comparison tax bill that allows you to compare after-tax returns across services; it will be up to you to compare them. Behavior Management: Does the service have a proven track record of reducing the behavior gap? When choosing an investment manager, the key isn’t to focus on investment performance; it’s to focus on service, fit, and investor returns. Information in this article represents the opinion of the author. No statement in this article should be construed as advice to buy or sell a security. The author does not know your particular objectives for returns or constraints upon investing. All investors are encouraged to do their own research before making any investment decision.

There Is No Margin Of Safety

Summary Value investing’s “margin of safety” is illusory: “50 cent dollars” can turn into “50 cent quarters”, or worse. You can use value investing in security selection, but to protect against stock-specific risk, you need to diversify or hedge. An advantage of hedging is that it let’s you concentrate your assets in a handful of stocks you think will do best, while limiting your downside risk. An additional advantage of hedging is that it protects against market risk, which diversification alone does not. We outline a method for creating a hedged portfolio of value stocks, and provide an example. The Margin of Safety in Value Investing One of key terms used in value investing is ” margin of safety “, which refers to difference between a company’s market price and its ” intrinsic value “, as illustrated by the image below (take from the website of Pratt Capital, LLC) Margin of safety was coined by the putative father of value investing, Benjamin Graham, and perhaps the best way to help explain it is quote one of his famous sayings, “In the short run, the market is a voting machine, but in the long run, it’s a weighing machine”. “Voting”, or investor sentiment, drives the market price in the short term, according to Graham, but “weighing”, or recognition of intrinsic value, drives the stock price in the long term. The idea is, essentially, to buy a stock when it’s trading for less than it’s really worth (its intrinsic value), and sell it at some future date when it’s trading at its intrinsic value or higher. The Margin of Safety in Reality Buying a stock for less than your estimation of its intrinsic value and selling it for more later – value investing, in a nutshell – makes perfect sense. What doesn’t make sense is calling that discount between the market price and your estimation of intrinsic value a “margin of safety”, because it isn’t one. Let’s take the simplest case, what Graham referred to as a ” net-net “, a stock trading for less than its net current assets minus its total liabilities. In Graham’s day, these were more common, but you can still find them occasionally today among very small stocks. A stock trading for 50 cents per share with $1 per share in net current assets minus total liabilities would be a classic “50 cent dollar”. A can’t lose proposition, right? Well, not quite. One problem with a so-called 50 cent dollar is that you really don’t know what the net current assets are now ; you only know what they were as of the date they were reported. What if next time the company reports they have only 50 cents in net current assets per share? All else equal (i.e., the same conditions causing it to sell at discount in the past still applying) the share price will tank. And all else may end up being worse. Diversification versus Margin of Safety Of course, Graham knew this, which is why he advocated buying a basket of net-nets, rather than just a few. The basket — i.e., diversification — was his real downside protection against the stock-specific risk of some of his 50 cent dollars turning out to be a 50 cent half dollars, or, worse, a 50 cent quarters. One could argue that value investors today using more subjective measures of intrinsic value based on estimates of future earnings should be even more concerned about downside protection, particularly after some prominent value investing debacles during the last financial crisis. The Limits of Diversification Although diversification protects against stock-specific risk, it doesn’t protect against market risk. When the market tanks, nearly all stocks tank too. We saw this in miniature last month, as we noted in an article published soon after (“Lessons from Monday’s Market Meltdown”), and of course we saw it in 2008 , when stocks were a sea of red across the globe. What offers protection against market risk is hedging. Hedging Against one Kind of Risk or Both You can use a diversified portfolio to limit your stock-specific risk, and hedge against market risk by buying optimal puts on relevant index ETFs. We offered a step-by-step example of that in a previous post (“Protecting A Million Dollar Portfolio”). Alternatively, you can hedge each security you own; if you do that, you are hedging against both market risk and stock-specific risk, so you’ve obviated the need for broad diversification. That enables you to aim for maximizing your potential return with a concentrated, hedged portfolio. You can still use value investing principles to construct that portfolio, but you won’t be relying on an illusory “margin of safety” to protect it. We demonstrate a way of doing that below. Risk Tolerance and Potential Return All else equal, with a hedged portfolio, the greater an investor’s risk tolerance — the greater the maximum drawdown he is willing to risk (his “threshold”, in our terminology) – the higher his potential return will be. So, we should expect that an investor who is willing to risk a 25% decline will have a chance at higher returns than one who is only willing to risk, say, a 15% drawdown. For the purposes of this example, we’ll split the difference and create a hedged portfolio designed for an investor with $250,000 who is willing to risk a drawdown of no more than 20%. Constructing A Hedged Portfolio We’ll summarize process the hedged portfolio process here, and then explain how you can implement it yourself. Finally, we’ll present an example of a hedged portfolio that was constructed this way with an automated tool. The process, in broad strokes, is this: Find securities with high potential returns (we define potential return as a high-end, bullish estimate of how the security will perform). Find securities that are relatively inexpensive to hedge. Buy a handful of securities that score well on the first two criteria; in other words, buy a handful of securities with high potential returns net of their hedging costs (or, ones with high net potential returns). Hedge them. The potential benefits of this approach are twofold: If you are successful at the first step (finding securities with high potential returns), and you hold a concentrated portfolio of them, your portfolios should generate decent returns over time. If you are hedged, and your return estimates are completely wrong, on occasion — or the market moves against you — your downside will be strictly limited. How to Implement This Approach Finding promising stocks In this case, we’re going to use a large cap value screen from Zack’s Investment Research, but you could also use value stock ideas from Seeking Alpha or Seeking Alpha Pro . To quantify potential returns for these stocks, you can, for example, use analysts’ price targets for them and then convert these to percentage returns from current prices. In general, though, you’ll need to use the same time frame for each of your potential return calculations to facilitate comparisons of potential returns, hedging costs, and net potential returns. Our method starts with calculations of six-month potential returns. Finding inexpensive ways to hedge these securities First, you’ll need to determine whether each of these top holdings are hedgeable. Then, whatever hedging method you use, for this example, you’d want to make sure that each security is hedged against a greater-than-20% decline over the time frame covered by your potential return calculations (our method attempts to find optimal static hedges using collars as well as protective puts going out approximately six months). And you’ll need to calculate your cost of hedging as a percentage of position value. Selecting the securities with highest net potential returns In order to determine which securities these are, out of the list above, you may need to first adjust your potential return calculations by the time frame of your hedges. For example, although our method initially calculates six-month potential returns and aims to find hedges with six months to expiration, in some cases the closest hedge expiration may be five months out. In those cases, we will adjust our potential return calculation down accordingly, because we expect an investor will exit the position shortly before the hedge expires (in general, our method and calculations are based on the assumption that an investor will hold his shares for six months, until shortly before their hedges expire or until they are called away, whichever comes first). Next, you’ll need to subtract the hedging costs you calculated in the previous step from the potential returns you calculated for each position, and exclude any security that has a negative potential return net of hedging costs. Fine-tuning portfolio construction You’ll want to stick with round lots (numbers of shares divisible by 100) to minimize hedging costs, so if you’re going to include a handful of securities from the sort in the previous step and you have a relatively small portfolio, you’ll need to take into account the share prices of the securities. Another fine-tuning step is to minimize cash that’s leftover after you make your initial allocation to round lots of securities and their respective hedges. Because each security is hedged, you won’t need a large cash position to reduce risk. And since returns on cash are so low now, by minimizing cash you can potentially boost returns. In this step, our method searches for what we call a “cash substitute”: that’s a security collared with a tight cap (1% or the current yield on a leading money market fund, whichever is higher) in an attempt to capture a better-than-cash return while keeping the investor’s downside limited according to his specifications. You could use a similar approach, or you could simply allocate leftover cash to one of the securities you selected in the previous step. Calculating Expected Returns While net potential returns are bullish estimates of how well securities will perform, net of their hedging costs, expected returns, in our terminology, are the more likely returns net of hedging costs. In a series of 25,412 backtests over an 11-year time period, we determined two things about our method of calculating potential returns: it generates alpha, and it overstates actual returns. The average actual return over the next six months in those 25,412 tests was 0.3x the average potential return calculated ahead of time. So, we use that empirically derived relationship to calculate our expected returns. An Automated Approach Here we’ll show an example of creating a hedged portfolio starting with value stocks using the general process described above, facilitated by the automated hedged portfolio construction tool at Portfolio Armor . Narrowing Down Our List of Stocks To get a starting list of value stocks, we used the Large Cap Value screen created by Zack’s Investment Research in Fidelity ‘s stock screener. That screen uses these criteria: Market capitalization of $5 billion and above Projected EPS growth (quarter over quarter) of 17% or more Projected EPS growth (year over year) of 17% or more P/E below 12 PEG below 1 Security price above $5 Average volume over 50,000 shares traded daily On Thursday, that screen generated these 11 stocks: American Airlines Group (NASDAQ: AAL ) Citigroup (NYSE: C ) Delta Air Lines (NYSE: DAL ) Ford Motor Co. (NYSE: F ) Gilead Sciences (NASDAQ: GILD ) HollyFrontier Corp (NYSE: HFC ) Lear Corp (NYSE: LEA ) Southwest Airlines (NYSE: LUV ) Tesoro Corp (NYSE: TSO ) United Continental Holdings (NYSE: UAL ) Valero Energy (NYSE: VLO ) Using the Automated Tool In the first step, we enter the eleven ticker symbols in the “Tickers” field, the dollar amount of our investor’s portfolio (250000) in the field below that, and in the third field, the maximum decline he’s willing to risk in percentage terms (20). In the second step, we are given the option of entering our own potential return estimates for each of these securities. Instead, in this case, we’ll let Portfolio Armor supply its own potential returns. Note that the site’s potential returns are calculated based on price history and option market sentiment, so they generally won’t be very high for value stocks. But, again, you can enter your own potential returns in this step if you want. A couple minutes after clicking the “Create” button, we were presented with the hedged portfolio below. The data here is as of Thursday’s close. Why These Particular Securities? The site included all of the entered securities for which it calculated a positive potential return, net of hedging costs. In this case, that turned out to be six of the eleven stocks we entered, DAL, GILD, HFC, LEA, TSO, and VLO. In its fine-tuning step, it added Under Armour (NYSE: UA ) as a cash substitute. Let’s turn our attention now to the portfolio level summary for a moment. Worst-Case Scenario The “Max Drawdown” column in the portfolio level summary shows the worst-case scenario for this hedged portfolio. If every underlying security in it went to zero before their hedges expired, the portfolio would decline 19.8%. Negative Hedging Cost Note that, in this case, the total hedging cost for the portfolio was negative, -2.56%, meaning the investor would receive more income in total from selling the call legs of the collars on his positions than he spent buying the puts. That also means that if the underlying securities returned 0% over the next 6 months, and the hedges expired worthless, the portfolio would return 2.56% (to be prudent, we suggest exiting positions just before their hedges expire instead). Best-Case Scenario At the portfolio level, the net potential return is 6.32% over the next six months. This represents the best-case scenario, if each underlying security in the portfolio meets or exceeds its potential return. A More Likely Scenario The portfolio level expected return of 2.22% represents a conservative estimate, based on the historical relationship between our calculated potential returns and backtested actual returns. By way of comparison, a hedged portfolio created recently using the same decline threshold (20%), but without entering any ticker symbols (i.e., letting Portfolio Armor pick all the securities), had an expected return of 6.1%. You can see that hedged portfolio in a recent article (“Investing While Guarding Against Extensive Vertical Losses”). Each Security Is Hedged Note that each of the above securities is hedged. Under Armour, the cash substitute, is hedged with an optimal collar with its cap set at 1%, and the remaining securities are hedged with optimal collars with their caps set at each underlying security’s potential return, as calculated by the site. Here is a closer look at the hedge for Gilead Sciences: Gilead Sciences is capped here at 10.62%, because that’s the potential return Portfolio Armor calculated for it over the next several months. As you can see at the bottom of the image above, the cost of the put protection in this collar is $464, or 2.08% of position value. But if you look at the image below, you’ll see the income generated from selling the calls is $640, or 2.87% of position value. So, the net cost of this optimal collar is -$176, or -0.79% of position value, meaning the investor would collect more income from selling the calls than he paid to buy the puts.[i] Possibly More Protection Than Promised In some cases, hedges such as the ones in the portfolio above can provide more protection than promised. For an example of that, see this instablog post on hedging the iPath S&P 500 VIX ST Futures ETN (NYSEARCA: VXX ). [i]To be conservative, this optimal collar shows the puts being purchased at their ask price, and the calls being sold at their bid price. In practice, an investor can often buy the puts for less (i.e., at some point between the bid and ask prices) and sell the calls for more (again, at some point between the bid and ask). So the actual cost of opening this collar would have likely been less. That’s true of the other hedges in this portfolio as well. Disclosure: I/we have no positions in any stocks mentioned, and no plans to initiate any positions within the next 72 hours. (More…) I wrote this article myself, and it expresses my own opinions. I am not receiving compensation for it (other than from Seeking Alpha). I have no business relationship with any company whose stock is mentioned in this article.