Tag Archives: history

Building A Black Swan-Proof Portfolio

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.

September’s Strong Competitive Wealth-Builder ETF Investment

Summary From a population of some 350 actively-traded, substantial, and growing ETFs, this is a currently attractive addition to a portfolio whose principal objective is wealth accumulation by active investing. We daily evaluate future near-term price gain prospects for quality, market-seasoned ETFs, based on the expectations of market-makers [MMs], drawing on their insights from client order flows. The analysis of our subject ETF’s price prospects is reinforced by parallel MM forecasts for each of the fund’s ten largest holdings. Qualitative appraisals of the forecasts are derived from how well the MMs have foreseen subsequent price behaviors following prior forecasts similar to today’s. The size of prospective gains, the odds of winning transactions, worst-case price drawdowns, and marketability measures are all taken into account. Today’s most attractive ETF… … is the Direxion Daily Healthcare Bull 3X ETF (NYSEARCA: CURE ). The investment seeks daily investment results, before fees and expenses, of 300% of the performance of the Health Care Select Sector Index. The fund creates long positions by investing at least 80% of its assets in the securities that comprise the Health Care Select Sector Index and/or financial instruments that provide leveraged and unleveraged exposure to the index. These financial instruments include: futures contracts; options on securities, indices and futures contracts; equity caps, floors and collars; swap agreements; forward contracts; short positions; reverse repurchase agreements; exchange-traded funds, etc. It is non-diversified. (Source: Yahoo Finance ) The fund currently holds assets of $351 million and has had a YTD price return of +3.95%. Its average daily trading volume of 520,259 produces a complete asset turnover calculation in 21 days at its current price of $31.71. Behavioral analysis of market-maker hedging actions while providing market liquidity for volume block trades in the ETF by interested major investment funds has produced the recent past (6-month) daily history of implied price range forecasts pictured in Figure 1. Figure 1 (used with permission) The vertical lines of Figure 1 are a visual history of forward-looking expectations of coming prices for the subject ETF. They are NOT a backward-in-time look at actual daily price ranges, but the heavy dot in each range is the ending market quote of the day the forecast was made. What is important in the picture is the balance of upside prospects in comparison to downside concerns. That ratio is expressed in the Range Index [RI], whose number tells what percentage of the whole range lies below the then current price. Today’s Range Index is used to evaluate how well prior forecasts of similar RIs for this ETF have previously worked out. The size of that historical sample is given near the right-hand end of the data line below the picture. The current RI’s size in relation to all available RIs of the past 5 years is indicated in the small blue thumbnail distribution at the bottom of Figure 1. The first items in the data line are current information: the current high and low of the forecast range, and the percent change from the market quote to the top of the range, as a sell target. The Range Index is of the current forecast. Other items of data are all derived from the history of prior forecasts. They stem from applying a T ime- E fficient R isk M anagement D iscipline to hypothetical holdings initiated by the MM forecasts. That discipline requires a next-day closing price cost position be held no longer than 63 market days (3 months), unless first encountered by a market close equal to or above the sell target. The net payoffs are the cumulative average simple percent gains of all such forecast positions, including losses. Days held are average market rather than calendar days held in the sample positions. Drawdown exposure indicates the typical worst-case price experience during those holding periods. Win odds tells what percentage proportion of the sample recovered from the drawdowns to produce a gain. The cred(ibility) ratio compares the sell target prospect with the historical net payoff experiences. Figure 2 provides a longer-time perspective by drawing a once-a week look from the Figure 1 source forecasts, back over two years. Figure 2 (used with permission) What does this ETF hold, causing such price expectations? Figure 3 is a table of securities held by the subject ETF, indicating the manner in which a 3X leverage on the healthcare index is accomplished. The ETF’s ratios of current market price to various accounting measures are also shown. Figure 3 (Source: Yahoo Finance) Since the value of the index being leverage-tracked is driven by the intermediate unleveraged ETF, the Health Care Select Sector SPDR ETF (NYSEARCA: XLV ), it is useful to know the concentration of its top ten largest holdings and their percentage of XLV’s total value: Figure 4 (click to enlarge) (Source: Yahoo Finance) XLV concentrates 53% of its assets in its top ten commitments. This provides a responsive measure of the action of market prices of stocks in this essential sector. The major holdings are all established, dominant participants in the healthcare industry. Figure 5 is a table of data lines similar to that contained in Figure 1 for each of the top ten holdings of XLV, plus, for convenience, the XLV and CURE data itself. Figure 5 (click to enlarge) (Source: Peter Way Associates, blockdesk.com) Column (5) contains the upside price change forecasts between current market prices (4) and the upper limit of prices (2) regarded by MMs as being worth paying for price change protection. The average of +7.2% of the top ten XLV holdings is well above the market-average proxy SPDR S&P 500 Trust ETF’s (NYSEARCA: SPY ) +5.3%. Diversification of XLV’s other 47% of holdings damps its overall upside (as MMs see it) to only +5.3%. But in the same stroke, the risk side of the equation in (6) for XLV is brought down to worst-case price drawdowns of -3.2%, below the defensive SPY norm of -3.6%. In an environment many consider imbued with high market risk, XLV may provide a very attractive balance. The ability of XLV holdings to recover from those worst-case drawdowns and achieve profits (8) was shown in 85% of experiences. The equity population only recovered less than two-thirds of the time, and while the SPY experiences were more consistent, the achieved gains were much smaller. SPY has had only +3.1% gains previously from like forecasts of +9.4%. CURE provides an exciting history of price gains derived from the XLV experiences at times (like now) dictated by the MMs expectations for it, as measured by its current Range Index of 18. Each of the rows of data in Figure 5 is a sample of prior forecasts at the same level of RI as today’s in column (7). XLV has a RI of 42, while CURE, because of its leverage, is at a much more extreme low RI level. Instead of having about one and a half times as much upside, it is seen to have nearly triple. The win odds (8) for CURE need to be taken as perhaps a function of their small proportion of the available forecasts (16). But in every prior case, they have been profitable. And the typical holding periods of about two weeks are remarkable. Their size of +12% gains are quite competitive with the 20 best alternatives in the whole population, even should it take seven weeks to achieve. Conclusion CURE provides attractive forecast price gains, supported by its equally appealing largest underlying holdings and 3X operating or structural leverage. Both the ETF and many of its major holdings offer very attractive prospects in near-term price behaviors, demonstrated by previous experiences following prior similar forecasts by market-makers. But it may be considered a defensive commitment in the face of widespread anticipation of further market weakness. The blue summary row of Figure 5 labeled 20 Best-Odds Forecast Price Ranges tells what the current top-ranked wealth-building opportunities are offering, as a comparative competitive norm. YTD in 2015, 2200 of these 20-a-day list members have reached closeouts in an average of 2-month holding periods, providing an annual rate of average price change gains +24% better than SPY. CURE seems to provide an even more superior opportunity. 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.

PCI: High Yield (10.5%), Historic Discount (14.6%), But An Uneven Recent Record

Summary PCI is the largest CEF by market cap in the taxable income category. PCI is paying a distribution yield of 10.5% and is priced at a historically low discount. The fund has suffered along with its category over the past year. Investors might ask if there is now value here. I began this series exploring taxable income CEFs with an overview of 105 CEFs in this category where I showed that the funds had been battered by the market, often well in excess of changes in net asset values. Some funds had cut distributions and the broad data suggest that others may follow. I am following up on that overview with a look at specific funds in the category. First up was the PIMCO Dynamic Income Fund (NYSE: PDI ) which I consider to be the best in the class in today’s skewed market. With this installment, I want to look at its sibling fund, the PIMCO Dynamic Credit Income Fund (NYSE: PCI ), which like many siblings, is fundamentally similar but distinctly different. I refer to the two funds as siblings because they share a similar lineage. They are young funds (May 2012 for PDI, Jan 2013 2013 for PCI) and the most recent additions to the PIMCO CEF line. The funds have similar sounding objectives, but unlike many sibling funds, come have at their objectives quite differently although there are signs that they are coming be more alike as they weather tough times in their category. Where PDI stood out as being at or very near the upper reaches of the group for many key metrics, PCI does not fare nearly as well. This chart shows its percent rank among the funds for various market characteristics. (click to enlarge) Figure 1 . PCI percent rank among 105 taxable, fixed-income CEFs. Liquidity This is an area where PCI outscored PDI but only by minor amounts. It is the category leader for market cap and ranks 3rd of the 105 funds considered for trading volume. But either fund has as much liquidity as one is likely to find among closed end funds. Discount Discount is a second category where PCI turns in a better number than PDI, at least in terms of absolute value. Its discount (-14.64%) ranks 65 of the 105 funds which have a median discount of -13.2%. The fact that a fund can be that deep into discount territory and still be outpaced by 1//3 of the category’s funds shows how difficult times have been for taxable income CEFs. The discount/premium Z-scores show us that this discount is not only deep, it is much deeper than its average value has been over the last 3, 6 or 12 months. (click to enlarge) Figure 2 . PCI Z-Scores for PDI and median values for the category. The discount has been on an expanding trend since early in 2014. Indeed, at its current value, PCI’s discount is at an historic low for the fund. (click to enlarge) Figure 3 . PDI Premium/Discount since inception (end month values). Discounts are without question appealing, and historically low discounts can be especially appealing, but one does not — or, I should say, should not — buy a CEF on the basis of discount alone. Distributions Fixed income CEFs are designed to provide regular income to their shareholders. Most pay out a stable distribution and managers are generally reluctant to reduce those distribution. To a large extend investors value the funds on the basis of those distributions. Here again, PCI is turning in better numbers than PDI. Its distribution at NAV is 8.98% (75% percentile for the category), slightly above PDI’s 8.72%. Its deeper discount pushes the distribution to shareholders well above PDI’s. It is currently paying 10.52% on the basis of its regular distribution; PDI pays 9.53%. The regular distribution currently stands at $ 0.16406/share. It was increased for the September 2015 payment from $ 0.15625/share a value that had been constant from the fund’s inception. This is a 5% increase. PCI has also paid out a special distribution in each of its two years of operation. In 2013 it was $0.36 and for 2014 it was $0.60. If one considers the special distribution, current distribution yield through the past twelve months is 13.14% which would place PCI at the 97%tile of the category. Figure 4. PCI. Regular and special distributions since inception. Of course the difference between the regular distribution at 10.52% and the regular plus full distribution of 13.14% is considerable, but is not predictive for future yield from the fund. The special distributions are special and variable. An investor cannot count on them. One indicator of expectations for a year-end special distribution is undistributed net investment income (UNII). This is where PDI excels, but PCI falls short. Cefconnect list PCI as having -$0.0656 in UNII. Not enough to cause real concern, but it is in negative territory which would indicate that a large year-end special distribution based on excess income will not be forthcoming in 2015. Summing up the distribution situation, PCI has an exceptionally high distribution yield driven in part by its large discount. It looks sustainable at this time. On the surface it is higher than that of PDI but when one considers the history and likelihood of special distributions in the mix, PDI is returning a greater yield. The other significant aspect of UNII is that it is a predictor of distribution stability and sustainability. This is obvious from the recent fall of the PIMCO High Income Fund (NYSE: PHK ) as documented in this recent article on Seeking Alpha . If you are concerned about the stability of distributions for any CEFs you may hold or be researching, I refer you to the cases explored there. Where PDI is at the top of the category for UNII/Distribution, PCI is only at the 37%tile. This has not prevented managers from raising PCI’s distribution, so I’m not inclined to see it as an indicator that the fund’s distribution is in trouble. If I were holding PCI I would be watching this metric carefully in the coming months. Fund Performance Actual return is a interesting facet of CEFs. On one hand there is return to an investor, which is the market return. On the other there is return on NAV which is the true indicator of how a fund is performing. Premium/discount status determines the differences between the two. PCI has outperformed only 38-39% of the category’s funds for total return on market price and NAV for the past year. This is far from an encouraging performance record, particularly when one considers that it has not been a good year for fixed-income. The median fund has a total return on NAV for the trailing twelve months of -0.2% and at market price it’s -5.98%. For PCI 1yr return on price is -7.2%. These returns show make an investor wary of PCI at this time. If tough times persist in fixed income, and there is ample reason to believe they might, declines in price (both at market and NAV) may continue to erode value for the fund’s investors. Add the fact of negative UNII (slight, but negative nonetheless) and PCI’s high yield begins to look much less attractive. I’ve been focused on PCI relative to PDI and the other funds in its category. I’ll now turn attention to PCI itself. What is the fund about. PDI has been operating for a bit over 30 months (inception date: 29 Jan 2013). It has a category-leading total net assets of $2.57B and its effective leverage of 42.44% is higher than all but one fund in the taxable income category. Management fees and other expenses are 1.382% excluding interest expense and 1.501% with interest costs (data from Pimco ). Morningstar compares its performance to Barclays US Aggregate Bond Total Return and its Multisector Bond category. It lists only 2014 and 2015 (YTD) comparisons and the fund underperformed in 2014 but is doing relatively well YTD. Fund Characteristics PCI has a broad investment mandate but is somewhat more focused than PDI. From the sponsor’s website : The fund will normally invest at least 50% of its net assets in corporate income-producing securities of varying maturities issued by U.S. or foreign (non-U.S.) corporations or other business entities, including emerging market issuers. Corporate income-producing securities include fixed-, variable- and floating-rate bonds, debentures, notes and other similar types of corporate debt instruments, such as preferred shares, convertible securities, bank loans and loan participations and assignments, payment-in-kind securities, zero-coupon bonds, bank certificates of deposit, fixed time deposits and bankers’ acceptances, stressed debt securities, structured notes, and other hybrid instruments. As for types of investments: The fund will normally invest at least 80% of its net assets (plus any borrowings for investment purposes) in a portfolio of debt instruments of varying maturities. The fund will normally invest at least 25% of its total assets (i.e., concentrate) in privately issued (commonly known as “non-agency”) mortgage-related securities.: And, “The Fund may normally invest up to 40% of its total assets in securities of issuers economically tied to emerging market countries. This definition is broad and flexible. Its successes or failures will depend on the abilities of management to handle that flexibility. Most of the management team (Daniel Ivascyn, Sai S. Devabhaktuni, Mark Kiesel, Elizabeth O. MacLean and Alfred Murata) has been place since the fund’s inception. Fund documents state that the fund “will normally maintain an average portfolio duration of between zero and eight years.” This is identical to PDI and Morningstar lists effective duration at 2.27 (unadjusted) and 3.91 (adjusted for leverage) which is about a half year longer than comparable durations for PDI. No information is provided on the portfolio’s credit quality. The fund’s holding by sector allocation on market value is (from the PIMCO website): This sector breakdown varies form that of PDI in one important element; PDI has twice as much of its portfolio in mortgage securities. For PDI mortgage securities comprise 2/3 of the portfolio; for PCI it is only 1/3 but that is a substantial increase in the last four months. I last looked at the two funds in May 2015. At that time PCI held only 0.11% in mortgage-back securities. Another change since May is in the geographic distribution of the fund’s portfolio. This chart from the May article shows where PCI was positioned at that time: Figure 5 . PCI. Geographical distribution of the fund’s portfolio in May 2015 (taken from Is It Time To Sell These PIMCO Closed-End Funds? ). Compare this distribution to the current distribution shown in the table below. The current geographical breakdown of the portfolio from Morningstar is: In less than 4 months time the portfolio has been repositioned to strongly favor U.S. bonds, while U.K. and Canada exposure has dropped precipitously from 3/8 of the portfolio to less than 4%. Brazil and Ireland did not even show up in May, now they represent more than 5% of the portfolio. This comparison illustrates the dynamic nature of PCI’s portfolio management. Brazilian bonds are currently the largest holding in the portfolio. With the recent downgrading of Brazil’s sovereign debt to junk status, management’s move into the sector may have been less than timely. The fund’s top 10 holdings sorted from PIMCO’s downloadable spreadsheet are: PCI shares the same risk factors facing PDI in the coming months. Interest rate risk with the on-going anxiety over rising interest rates is primary. The meltdown in emerging markets is also a factor. Each has been weighing on the space for some time. Together they have taken their toll on the fund’s NAV returns and, more severely, on the fund’s returns to investors at market. I do not expect the inevitable uptick in interest rates to be characterized by sudden and markedly disruptive increases. Rather I expect gradual changes that a well managed fund should be able to handle. Indeed, as rates do begin to rise, I would prefer to have my fixed-income allocation positioned to emphasize proven management. PCI’s managers have decreased duration over the past year and “has an outright short on the long-end of the curve” (June 30, 2015 Quarterly Commentary). I have been holding a position in PCI. While I am confident that the fund will continue to deliver excellent income I am concerned about the declines in principal and for the near-term future of the category itself. I am not concerned about the stability or sustainability of the distribution and am encouraged in this view by the small but meaningful increase in that distribution this month. The historically low discount is only of interest to a new buyer, and a new buyer may find value there. To someone holding the fund with no inclination to add to the position, the increasingly deep discount is more of a frustration. In summary, I will continue to hold the fund but if I were considering a new position in a taxable income CEF, I would be more likely to go with PDI, its older sibling, at this time. Disclosure: I am/we are long PCI, PDI. (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: I remind readers that this article does not constitute investment advice. I am passing along the results of my research on the subject. Any investor who finds these results intriguing will certainly want to do all due diligence to determine if any investment mentioned here is suitable for his or her portfolio. As always I welcome your comments and critiques, particularly from those readers who have contrary opinions.