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Summary The Volkswagen emissions debacle exemplifies the unpredictable risks (“black swans”) associated with investing in even blue-chip stocks. Avoiding companies with high carbon emissions, as suggested by one author, won’t protect us against the next black swan. For that, we need a black swan-proof portfolio. We note two ways of building a black swan-proof portfolio, detail one of them, and provide an example black swan-proof portfolio. Anticipating The Black Swan Working in the mutual fund industry in the late 1990s, I sat through a number of presentations by fund company economists. They often had question-and-answer sessions, and I’ve forgotten about most of them. But one particular incident stayed with me, as the fund company economist touched on an idea Nassim Nicholas Taleb would later popularize in his 2007 book The Black Swan . The year was in 1999, and if memory serves, the economist was Dr. Bob Froehlich . An investor asked him if we should be worried about Y2K , the widely-anticipated “Year 2000 Problem”, when computer systems programmed to use two digits to record years might get confused by the switchover from “99” to “00”. The economist answered that he wasn’t worried about Y2K, because the electronic debut of the euro as the EU’s currency earlier that year had been a similarly challenging computer problem, and it went smoothly. He then offered a Black Swan-like admonition: If you’ve been hearing a lot about a problem in the news, that means experts are already working on it, so you don’t need to worry about it. Worry about what you haven’t been hearing about. Two Types Of Black Swans Black swans are the crises that you don’t hear about in the news beforehand, and, broadly speaking, there are two types of them: systemic black swans, and stock-specific black swans. An example of a systemic black swan was the freezing of the credit markets during the credit crisis, which affected many companies. An example of a stock-specific black swan is the emissions scandal at Volkswagen ( OTCQX:VLKAY ), which was the subject of John Authers’ “Long View” column in the Financial Times (“Carbon footprints loom for investors after VW scandal”) last weekend. From Blue Chip to Black Swan (click to enlarge) Volkswagen, the blue chip automaker, had once praised itself for its putatively low-emission diesel vehicles by having its engineers sprout angelic wings in an ad campaign, as pictured above (image via this New York Times article on the scandal). In his column, John Authers argued that the VW scandal was a rare case in which the appellation “black swan” was warranted: The phrase “black swan” – meaning an unprecedented low-probability event that prompts markets to overreact – tends to be overused. People will invoke it when really they have simply failed to hedge adequately against obvious risks. But Volkswagen, the German carmaker, produced a true “black swan” this week, as it was revealed that it had for years used complicated software that allowed its diesel-fuelled cars to “cheat” on emissions tests. Drawing The Wrong Lesson Authers went on to suggest that investors use data from MSCI and other index providers to lower their exposure to companies with large carbon footprints. With all due respect to Authers, that’s the wrong lesson to draw from this disaster for Volkswagen shareholders. Authers’ advice is an example of checklist investing, and as we pointed out in a recent article (“A Checklist To Save Your Assets”), those sorts of checklists don’t limit risk. In that article, we recounted the history of a hedge fund manager who developed a 98-question checklist to reduce his error rate, and nevertheless added to a concentrated position in Horsehead Holding Corp. (NASDAQ: ZINC ) at over $12 per share in 2013, and continues to be the largest institutional holder of that stock, which closed under $4 per share on Friday. (click to enlarge) We then noted: Like the margin of safety concept, 98-question checklists may be helpful for security selection. They just don’t limit either of the two kinds of risk associated with stock investing: idiosyncratic risk , the risk of something bad happening to one of the companies you own, and market risk , the risk of your investments suffering due to a decline of the market as a whole. Faulty carbon emissions are in the news now, which means experts are already working to resolve the issue; we need to worry about the next black swan. Of course, by definition, we don’t know what the next black swan will be, or where or when it will strike. But, fortunately, we can build a black swan-proof portfolio without knowing the answers to those questions. Two Ways Of Building A Black Swan-Proof Portfolio A black swan-proof portfolio is one in which both your stock-specific risk and your systemic or market risk are strictly limited. There are two ways to construct one: Use diversification to limit your stock-specific risk, and then use other methods to limit your market risk in according with your risk tolerance. Hedge each position in your portfolio to limit your stock-specific and market risk according to your risk tolerance. In this post, we’ll detail the second method. The beauty of the second method of building a black swan-proof portfolio is that it doesn’t matter what the black swan ends up being: whether it’s financial crisis or a meteor hitting a company’s headquarters, we’re not hedging against a specific event, but the effect of any event on the share price. Whatever happens, our downside will be strictly limited. The hedged portfolio method offers a way to build a black swan-proof portfolio while maximizing your expected return. Below, we’ll run through the process of creating a black swan-proof portfolio using this method, and provide an example using an automated tool. First, we need to note the tradeoff between risk tolerance and expected return. Risk Tolerance, Hedging Cost, And Expected 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”) – the higher his expected return will be. So, for example, an investor willing to risk a decline of 25% would likely have a higher expected return than one willing to risk a decline of only 15%. We’ll split the difference below, and construct a hedged portfolio for an investor who is willing to risk a decline of no more than 20%, and has $500,000 to invest. Constructing A Hedged, Or Black Swan-Proof Portfolio 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 securities with high potential returns For this, you can use Seeking Alpha Pro, among other sources. Seeking Alpha articles often include price targets for long ideas, and you can convert these to percentage returns from current prices. But you’ll need to use the same time frame for each of your expected return calculations to facilitate comparisons of expected returns, hedging costs, and net expected returns. Our method starts with calculations of six-month potential returns. Finding Securities That Are Relatively Inexpensive To Hedge For this step, you’ll need to find hedges for the securities with high potential returns, and then calculate the hedging cost as a percentage of position value for each security. Whatever hedging method you use, for this example, you’d want to make sure that each security is hedged against a greater-than-18% 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. Buying Securities That Score Well On The First Two Criteria To determine which securities these are, 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 sort the securities by their potential returns net of hedging costs, or net potential returns. The securities that come to the top of that sort are the ones you’ll want to consider for your portfolio. Fine-Tuning Portfolio Construction You’ll want to stick with round lots (numbers of shares divisible by 100) to minimize hedging costs. Another fine-tuning step is to minimize cash that’s left over 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 An Expected Return 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 black swan-proof portfolio using the general process described above, facilitated by the automated hedged portfolio construction tool at Portfolio Armor. In the first field below, we’re given the choice of entering our own ticker symbols. Instead, we’ll leave that field blank, and let the site pick its own securities for us. In the second field, we enter the dollar amount of our investor’s portfolio (500,000), and in the third field, the maximum decline he’s willing to risk in percentage terms (20). Next, we clicked the “create” button. A couple of minutes later, we were presented with the hedged portfolio below. The data here is as of Friday’s close: Why These Particular Securities? Portfolio Armor looks at two factors to estimate potential returns: price history, and option market sentiment. Then, it subtracts hedging costs to calculate potential returns net of hedging costs, or net potential returns. The securities included in this portfolio had some of the highest net potential returns in Portfolio Armor’s universe on Friday. Let’s turn our attention now to the portfolio level summary. 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 the hedges expired, the portfolio would decline 19.39%. Negative Hedging Cost Note that, in this case, the total hedging cost for the portfolio was negative, -0.63%, 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. Best-Case Scenario At the portfolio level, the net potential return is 17.27%. 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 6.62% represents a more conservative estimate, based on the historical relationship between our calculated potential returns and actual returns. Each Security Is Hedged Note that in the portfolio above, each underlying security is hedged. Amazon.com (NASDAQ: AMZN ), BofI Holding (NASDAQ: BOFI ), Netflix (NASDAQ: NFLX ), Skechers USA (NYSE: SKX ), Tyler Technologies (NYSE: TYL ), and Under Armour (NYSE: UA ) are hedged with optimal collars with their caps set at their respective potential returns. Celgene (NASDAQ: CELG ) is hedged as a cash substitute, with an optimal collar with its cap set at 1%. Hedging each security according to the investor’s risk tolerance obviates the need for broad diversification, and lets him concentrate his assets in a handful of securities with high potential returns net of their hedging costs. Here’s a closer look at the hedge for one of these positions, UA: As you can see in first part of the image above, UA is hedged with an optimal collar with its cap set at 19.08%, which was the potential return Portfolio Armor calculated for the stock: the idea is to capture the potential return while offsetting the cost of hedging by selling other investors the right to buy UA if it appreciates beyond that over the next six months. The cost of the put leg of this collar was $2,580, or 4.15% of position value, but, as you can see in the image below, the income from the short call leg was $2,100, or 3.37% as percentage of position value. Since the income from the call leg offset some of the cost of the put leg, the net cost of the optimal collar on UA was $480, or 0.77% of position value.[i] Note that, although the cost of the hedge on this position was positive, the hedging cost of this portfolio as a whole was negative . 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 recent instablog post on hedging Tesla (NASDAQ: TSLA ). Hedged Portfolios For More Risk-Averse Investors The hedged portfolio shown above was designed for an investor who could tolerate a decline of as much as 20% over the next six months, but the same process can be used for investors who are even more risk-averse, willing to risk drawdowns of as little as 2%. Notes: [i] To be conservative, the net cost of the collar was calculated using the bid price of the calls and the ask price of the puts. In practice, an investor can often sell the calls for a higher price (some price between the bid and ask) and he can often buy the puts for less than the ask price (again, at some price between the bid and ask). So, in practice, the cost of this collar would likely have been lower. The same is true of the other hedges in this portfolio, the costs of which were also calculated conservatively. 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.