Tag Archives: author

Finding Bargains Among High Income CEFs Selling At Historic Discounts

Summary The discounts associated with CEFs are at historic highs, with many discounts over 2 standard deviations from the mean. The highly discounted CEFs have been significantly more volatile than high yield bonds. MGU and GLO had the best risk-adjusted performance among the CEFs analyzed. As an income focused investor, I was a fan of high distribution Closed End Funds (CEFs). Many of these funds have been hit hard by the Fed’s plans to increase interest rates. As the prices deteriorated, the discounts of these CEFs have widened to historically large levels. This is evidenced by their Z-score, a statistic popularized by Morningstar to measure how far a discount (or premium) is from the mean discount (or premium). The Z-score is computed in terms of standard deviations from the mean so it can be used to rank CEFs. A good source for Z-scores is the CEFAnalysis website . (Thanks to SA author, Left Bank, for his article on where to find Z-scores). A Z-score more negative than minus 2 is relatively rare, occurring less than 2.25% of the time. However, in today’s environment, there are over 150 CEFs that have one year Z-scores more negative than minus 2, which illustrates the current lack of demand for these CEFs. There were too many CEFs to analyze so I reduced the sample size by using the following selection criteria: A Z-score more negative than minus 2.9. This will occur (assuming a normal distribution) less than 0.2% of the time. A history that includes October 12, 2007 (the beginning of the 2008 bear market) A daily average volume greater than 100,000 shares A market cap of at least $100 million. A distribution of 6% or higher The following CEFs satisfy all these criteria. Clough Global Opportunities Fund (NYSEMKT: GLO ). The CEF sells at a discount of 16.7% and has a Z-score of negative 3.59. This CEF has a “go anywhere” philosophy and has a portfolio of 167 securities, with 60% allocated to the equities, 28% to cash alternatives, and 7% to bonds. The fund may also use an option strategy to increase income. The fund uses a high leverage of 52% and has an expense ratio of 2.2%. The distribution is 10.7%, consisting primarily of gains and Return of Capital (ROC). Over the past year, ROC has been used 50% of the time, with the amount of ROC ranging from 30% to 100%. Invesco Credit Opportunities Fund (NYSE: VTA ). This CEF sells at a discount of 15.3% and has a Z-score of negative 3.59. It has a portfolio of 610 securities invested primarily in senior loans (76%) and high yield bonds (18%). The fund uses 33% leverage and has an expense ratio of 2.5%. The distribution is 8.2% with no ROC. Madison Covered Call and Equity Strategy Fund (NYSE: MCN ). This CEF sells at a discount of 15.1% and has a Z-score of negative 3.3. The portfolio consists of 47 securities, with 78% in equities and 20% in short-term debt. The fund does not use leverage and has an expense ratio of 0.8%. The distribution is 9.7% with no ROC. LMP Corporate Loan Fund (NYSE: TLI ). This CEF sells for a discount of 13% and has a Z-score of negative 3.25. The portfolio consists of 268 securities invested primarily in senior loans (87%) and high yield bonds (8%). The fund uses 33% leverage and has an expense ratio of 1.8%. The distribution is 8.4% with no ROC. Macquarie Global Infrastructure Total Return Fund (NYSE: MGU ). This CEF sells for a discount of 16.9% and has a Z-score of negative 3.09. The fund is concentrated with 51 holdings in infrastructure companies (89%) and 6% in master limited partnerships. The fund uses 30% leverage and has an expense ratio of 2.2%. The distribution is 7%, paid from income and capital gains with no ROC. Calamos Convertible Opportunities and Income Fund (NASDAQ: CHI ). This CEF sells at a discount of 11.2% and has a Z-score of negative 3.04. The portfolio consists of 287 securities, with 57% in convertible bonds and 38% in high yield bonds. The fund uses 28% leverage and has an expense ratio of 1.5%. The distribution is 10.8% with 2 months of ROC during the past year. MS Emerging Markets Debt Fund (NYSE: MSD ). This CEF sells for a discount of 18.3% and has a Z-score of negative 2.95. The portfolio consists of 115 emerging market holdings, with 41% investment grade bonds and the rest in high yield bonds. The fund uses only 8% leverage and has an expense ratio of 3.5%. The distribution is 6.6% with no ROC. GDL Fund (NYSE: GDL ). This CEF sells for a discount of 18.1% and has a Z-score of negative 2.9. The fund seeks total return by using arbitrage transactions and investing in reorganizations and spinoffs. It has 159 holdings, with 75% in equity and 21% in Government bonds. It uses 35% leverage and has an expense ratio of 3%. The distribution is 6.5% with only a small amount of ROC over the past year (the distribution for one quarter had 25% ROC). Based on the Z-score, these high income CEFs appear to be bargains, but Z-score is only one metric to consider. I also like to look at the reward-versus-risk over different time frames. In my mind, the best fund is the one that delivers the highest reward for a given level of risk. This article will analyze these CEFs in terms of risk-versus-reward to help you determine which may be right for your portfolio. To assess the performance of the selected CEFs, I plotted the annualized rate of return in excess of the risk free rate (called Excess Mu in the charts) versus the volatility of each of the component funds over the past bear-bull cycle (from October 12, 2007 to August 28, 2015). The risk free rate was set at 0% so that performance could be easily assessed. This plot is shown in Figure 1. Note that the rate of return is based on price, not Net Asset Value (NAV). I used the iShares iBoxx $ High Yield Corporate Bond ETF (NYSEARCA: HYG ) as a reference. (click to enlarge) Figure 1. Risk versus Reward over the bear-bull cycle The plot illustrates that these CEFs have booked a wide range of returns. To better assess the relative performance of these funds, I calculated the Sharpe Ratio. The Sharpe Ratio is a metric, developed by Nobel laureate William Sharpe that measures risk-adjusted performance. It is calculated as the ratio of the excess return over the volatility. This reward-to-risk ratio (assuming that risk is measured by volatility) is a good way to compare peers to assess if higher returns are due to superior investment performance or from taking additional risk. In Figure 1, I plotted a red line that represents the Sharpe Ratio associated with HYG. If an asset is above the line, it has a higher Sharpe Ratio than HYG. Conversely, if an asset is below the line, the reward-to-risk is worse than HYG. Some interesting observations are evident from the figure. High Z-score CEFs are substantially more volatile than HYG. This is not surprising since CEFs can sell at discounts and many use leverage. With the exception of VTA, the CEFs had larger absolute returns than HYG. However, when volatility is factored into the calculation, only 4 CEFs (GDL, GLO, MGU, and MSD) beat HYG on a risk-adjusted basis. Two other CEFs (TLI and MCU) had risk-adjusted performances similar to HYG. Among the CEFs, MSD was the best performer followed by GLO, MGU, and GDL. The worst performer on a risk-adjusted and absolute basis was VTA. These funds utilized different investment strategies, so I wanted to assess how much diversification you might receive by buying multiple funds. To be “diversified,” you want to choose assets such that when some assets are down, others are up. In mathematical terms, you want to select assets that are uncorrelated (or at least not highly correlated) with each other. I calculated the pair-wise correlations associated with the funds. For reference, I also included the SPDR S&P 500 Trust ETF (NYSEARCA: SPY ) as a proxy for the overall stock market. The results are presented in Figure 2. (click to enlarge) Figure 2. Correlation over the bear-bull cycle The figure presents what is called a correlation matrix. The symbols for the funds are listed in the first column on the left side of the figure. The symbols are also listed along the first row at the top. The number in the intersection of the row and column is the correlation between the two assets. For example, if you follow VTA to the right for three columns, you will see that the intersection with GLO is 0.650. This indicates that, over the past bear-bull cycle, the price of VTA and GLO were 65% correlated. Note that all assets are 100% correlated with themselves so the values along the diagonal of the matrix are all ones. As shown in the figure, the CEFs were not very correlated with HYG or among themselves. The highest correlation was between SPY and GLO, which was expected since GLO contained a large position in equities. The overall conclusion is that you can obtain diversification by purchasing more than one of these funds. Next, I wanted to see how these funds fared during more recent times so I used a 5-year look-back period. The results are shown in Figure 3 and what a difference a few years made. The CEFs are still more volatile than HYG, but HYG now beats all the CEFs in terms of risk-adjusted performance. MSD fell from being the best performer to the worst, and VTA moved up from being at the bottom to the third best. MGU had by far the best risk-adjusted performance among the CEFs, with GLO coming in second. GDL was again the least volatile but also did not have a high return. (click to enlarge) Figure 3. Risk versus reward over past 5 years My final analysis used a 3-year look-back period, and the results are shown in Figure 4. During this period, GLO, MGU, and MCN were the top performers on a risk-adjusted basis. These CEFs outperformed HYG on both an absolute and risk-adjusted basis. MSD continued its poor performance, booking a negative return. (click to enlarge) Figure 4. Risk versus reward over the past 3 years Bottom Line These large Z-score CEFs had a wide range of performance relative to each other and to HYG. All of these CEFs are much more volatile than high yield bonds so they would only be suitable for risk tolerant investors. These CEFs are at historically wide discounts and may be bargains in terms of discounts but their overall performance left something to be desired. If you want to take a gamble on these funds, I would recommend MGU. GLO could also be considered, but I am a little cautious of this fund’s ROC. No one can predict the future, but based on the past, these two CEFs have consistently outperformed their peers on a risk-adjusted basis. Disclosure: I/we have no positions in any stocks mentioned, but may initiate a long position in MGU over 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.

Debunking The Misleading Big Data ETF

PureFunds introduces new big data-focused ETF, tracking the ISE big data index. A deeper look at the index reveals social media networks, credit data providers, and Internet companies in the ETFs’ top holdings. Investors should look under the hood of non-trivial sector-focused ETFs. ETF provider PureFunds is a relatively new player in the ETF market, competing fiercely with financial giants that dominate the ETF market, like Vanguard, Blackrock’s (NYSE: BLK ) iShares, State Street’s (NYSE: STT ) SPDR, etc. PureFunds is familiar to most investors as the provider of the Cyber Security ETF (NYSEARCA: HACK ) that was launched in November 2014, which attempts to provide a passive investment vehicle into the emerging cybersecurity market. Since its inception, HACK yielded a 10% return, providing a modest return for the $1.1B in net assets that were invested in the ETF. As shown in Chart 1 below, HACK’s return is much lower than the leading cyber security stocks, but it also offers a passive investment vehicle into the industry that allows investors to invest in this emerging industry without cherry-picking particular stocks. Since PureFunds introduced the HACK ETF, the firm released three more ETFs: the PureFunds ISE Junior Silver ETF (NYSEARCA: SILJ ), the PureFunds ISE Mobile Payments ETF ( IPAY ), and the PureFunds ISE Big Data ETF ( BDAT ). As a strong believer in the growth potential of the big data industry and its leading players, I cover many big data topics, both in Seeking Alpha and in my firm, from industry trends through earnings reviews to extensive long/short investment thesis and ad-hoc analyses. There are so many public companies involved in the big data industry including analytics, visualization, Hadoop integration, and IaaS/PaaS services that I was pretty excited when I first heard of Purefunds Big Data ETF. However, as the title implies, I was very disappointed by the outcome. The general idea of Purefunds to launch investment vehicles that invest in emerging sectors, such as big data, mobile payments, and cyber security, is great, and I think there is a demand for such vehicles. However, an ETF is a passive investment tool that tracks a third party index – in BDAT’s case, it is the ISE Big Data™ Index. Looking at the component eligibility requirements in the index methodology guide unveils a wider definition of a big data company as shown in the excerpt below. According to the document, there are two types of companies that are entitled to join the index: either a big data product developer/service provider or a company that aggregates massive data sets. While the first part makes sense-this is a big-data index and should include big-data companies-the second part (bullet ii above) basically paves the way for any large Internet company to join the index, whether it has some connection to the big-data market or not. Let’s look at ETF’s top 10 holdings, as presented below in an excerpt from the fact sheet, and see how many big-data companies are there. Out of the top 10 holdings, five companies have very weak links to the big-data industry and are included in the ETF just because of bullet point ii above-Facebook (NASDAQ: FB ), Twitter (NYSE: TWTR ), Thomson Reuters (NYSE: TRI ), Nielsen (NYSE: NLSN ), and Yahoo (NASDAQ: YHOO )-while the other five have stronger links to big data, but it is absolutely not their core business nor the main impact on their financials. Going down the list of holdings (31 in total) will also reveal LinkedIn (NYSE: LNKD ) and Dun & Bradstreet (NYSE: DNB ), which also have a weak link to the big-data industry. I agree that it might be difficult to find 30 companies that are big data focused, but if the criteria are widened, I believe Amazon (NASDAQ: AMZN ), Rackspace (NYSE: RAX ), and EMC (NYSE: EMC ) will be found to have more to do with big data than the social media companies introduced in the index and ETF. In my opinion, this is a big deal. A big data ETF should include big data pure-play companies or companies that directly relate to that industry; having Facebook and Twitter in the top 10 holdings is missing the point. If ISE and PureFunds couldn’t find enough suitable companies to be included in the big data ETF, I would have suggested for them to include prominent SaaS, IaaS, and PaaS providers, rather than social media networks and credit/business data providers, as they have stronger links to the industry and are strongly impacted by it. For now, as BDAT does not provide pure big data exposure, I suggest investors to avoid using this ETF as an investment vehicle into the big data industry. Once PureFunds/ ISE have adjusted their ETF holdings/Index criteria, I will revise the avoid recommendation above, and if another big data ETF is introduced, I will perform the same due diligence again. 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. Additional disclosure: The information provided in this article is for informational purposes only and should not be regarded as investment advice or a recommendation regarding any particular security or course of action. This information is the writer’s opinion about the companies mentioned in the article. Investors should conduct their due diligence and consult with a registered financial adviser before making any investment decision. Lior Ronen and Finro are not registered financial advisers and shall not have any liability for any damages of any kind whatsoever relating to this material. By accepting this material, you acknowledge, understand and accept the foregoing.

Stocks Will Go Higher

China-led market volatility has roiled global asset markets, and potentially shaken investors faith in the current bull market. Loss averse investors heading to the sidelines should understand the performance of domestic equities over rolling 10 and 20-yr time periods to avoid missing future gains. This article borrows from recent quotes from famed investor Warren Buffett and stock price information from Nobel laureate Robert Shiller. Market optimism is falling with global share prices, but I want to offer some respite to Seeking Alpha readers. Stocks will go higher. I can not tell you about today, this week, this month, or even the rest of this year. However, as you extend your investment horizon, stocks almost invariably perform. In an August 10th interview on CNBC, Warren Buffett, the famed investor and chairman and CEO of Berkshire Hathaway ( BRK.A , BRK.B ) stated: ” Stocks are going to be higher, and perhaps a lot higher 10 years from now, 20 years for now .” To test his time horizon, I pulled from the long time series of online data that Robert Shiller uses to calculate his famed Cyclically Adjusted Price Earnings (NYSEARCA: CAPE ) Ratio. Below I show cumulative ten-year total returns for the S&P 500 (NYSEARCA: SPY ) and predecessor indices from the Shiller data dating back to 1900. The blue lines are cumulative price returns and the pink lines include dividends. Periods of negative ten year cumulative returns are very limited. The presence of negative ten-year cumulative periods overlapping the tech bubble collapse and the global financial crisis may make myopic investors unduly concerned about the long-run prospects of domestic equities. (click to enlarge) Buffett’s quote first focused on ten-year periods, but expanding a holding period to twenty-years would have only yielded negative total returns (including dividends) in a period that overlapped the 1929 stock market crash and World War II. (click to enlarge) In this interview, Buffett went further stating that “my game is to own decent businesses and decent prices and you are going to make a lot of money over time if you do it, but I think the ability of people to dance in and out of markets is quite limited and in my case is zero.” This statement is consistent with the s tudies linking Buffett’s performance to low volatility equities – he buys businesses that perform through multiple business cycles. Long-time readers know that I am not an unabashed bull, cautioning against the prospect of subnormal returns and increased volatility in my semi-annual market outlook . I also demonstrated earlier this year that equity multiples appeared stretched , including a look at the aforementioned Shiller data. However, if you are uncertain what to do with your domestic stock holdings in these times of heightened volatility, plan to buy high quality businesses on weakness and be prepared to hold these investments for long time periods. If history is a guide, you are very likely to come out a winner. Disclaimer : My articles may contain statements and projections that are forward-looking in nature, and therefore inherently subject to numerous risks, uncertainties and assumptions. While my articles focus on generating long-term risk-adjusted returns, investment decisions necessarily involve the risk of loss of principal. Individual investor circumstances vary significantly, and information gleaned from my articles should be applied to your own unique investment situation, objectives, risk tolerance, and investment horizon. Disclosure: I am/we are long SPY. (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.