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Exploiting Market Inefficiency In Closed-End Funds

Summary Closed-end funds are widely considered to be the most inefficient of tradable securities. A recent paper examining closed-end fund discount and premium status conclusively demonstrates that mean reversion is a feature of the funds and can be the basis of a trading strategy. Mean reversion rates vary among asset classes. Fixed-income fund revert faster than equity funds. Exploiting Market Inefficiency In Closed-End Funds One of the clichés bandied about regarding closed-end funds is that they are the least efficient of investment vehicles. This should be obvious from the fact that the vast majority sell at discounts to their net asset values. By any reasonable interpretation of an efficient market, CEFs should always be selling at or near their NAVs. But such is certainly not the case. A quick look at the universe of 567 funds listed on cefconnect.com shows that 86.4% of them sell at a discount, with the median discount at -8.33%. To illustrate the point, I worked up this chart, showing the P/D distribution for all 567 funds. It illustrates just how contrary to an assumption of market efficiency the closed-end fund universe is. Premiums range from PIMCO Global Stocks Plus (NYSE: PGP ) and PIMCO High Income Fund (NYSE: PHK ) two fixed-income PIMCO funds at the high end of the scale with premiums over 60%, to lows under -30% for two tiny US equity funds, RENN Global Entrepreneurs Fund (NYSEMKT: RCG ) and Foxby Fund (OTCQB: FXBY ) at the bottom. If we take a 1% deviation from NAV as a generous expectation of reasonably efficient pricing, we find that only 5.1% of funds would even meet that loose standard. So, it seems clear that the closed-end fund market is inefficient. But it appears that it’s even more inefficient than this standard might indicate. To demonstrate I want to discuss a paper by Dilip Patro, Louis R. Piccotti and Yangru Wu titled Exploiting Closed-End Fund Discounts: The Market May Be Much More Inefficient Than You Thought . The paper, which is a bit more than a year old, only recently came to my attention. I like it because it validates an approach I’ve been using in my own investing in closed-end funds. An approach I’ve discussed and some commenters have considered to be unjustified. The authors looked at all closed-end funds. They contrasted trading strategies taken from the existing literature that bought funds with the greatest discounts and sold funds with the greatest premiums to a strategy based on an assumption of mean reversion by funds to premium/discount equilibrium levels. They began by formally testing for mean reversion of premiums and discounts for each individual fund, and showed that the majority do exhibit significant mean reversion. Results indicate a mean rate of reversion of 8.6% a month, which implies an average half-life of 7.7 months. Further, they showed significant differences among asset classes. Fixed-income funds have faster rates of mean reversion (10.4% a month) than equity funds (7.5%), and within the equity category, international funds reverted faster than domestic funds. Once they had established the significance of mean reversion in premium/discount they turned to a model arbitrage strategy based on this fact. The strategy consisted of buying the quintile of closed-end funds with the highest estimated returns and selling the quintile of closed-end funds with the lowest estimated returns. Their strategy greatly outperformed one from previous studies involving buying the most deeply discounted funds and selling those with the highest premiums. This table summarizes the results. (click to enlarge) The earlier strategy, buying funds with the lowest discounts and selling those with the highest premiums, generated an annualized mean return of 14.9 percent with a Sharpe ratio of 1.52. The mean-reversion based strategy produced an annualized mean return of 18.2 percent and a Sharpe ratio of 1.92. The chart below shows monthly results. (click to enlarge) They went on to look at commonly used risk factors and concluded that the results could not be explained by the three Fama and French factors, the Carhart momentum factor or the Pástor and Stambaugh tradable liquidity factor. Much of the math used in this study is beyond all but the most sophisticated investor (if you’re inclined to economic statistics, do check out the original paper) and not really useful for routine decision making. Nor is the strategy intended to be applicable as a practical, real-world investing scheme. Typical of academic research, it was designed to isolate and demonstrate the power of using mean reversion as a metric. Most important to a real-world investor is how an awareness of the highlights can inform decisions. Those highlights conclusively demonstrate mean reversion in discount/premium status for closed-end funds. Further they demonstrate that an investing strategy based on the expectation of mean reversion in discount/premium status outperforms strategies based on discount/premium status alone. And finally, they demonstrate that the outperformance of the mean reversion strategy is independent of five factors that might otherwise explain the enhanced return. For an investor the message is clear. First, closed-end funds are in fact the inefficient market vehicle many of us assume them to be. Second, discount/premium status, the manifestation of that inefficiency, does not, in itself, generate the greatest opportunity for exploiting that inefficiency. Third, reversion of discount/premium status to a mean value is a clear reality for closed-end funds. And finally, the market’s mispricing of closed-end funds relative to their NAVs coupled with the tendency to revert to a mean value provides exploitable opportunities. The study validates selection of closed-end funds with an eye to discounts over premiums, and historically exceptional discounts over simply using discount alone. It further validates selection of funds with exceptional deviations below their historical premium/discount status with the expectation of taking profits from the decay of the exceptional deviation. Although this was the only variable investigated by the authors, it is clearly not the sole variable one should use as a basis for choosing among CEF investments. One might, for example devise a strategy that superimposes discount mean-reversion on other factors. However one approaches closed-end fund investing, these results emphasize that it would be wise to incorporate this factor into one’s decisions. Finally, the variation noted among asset classes suggests caution in applying this element too broadly. It would seem to be most applicable to fixed-income funds and less so to domestic equity funds. For the entire study, risk-adjusted return (alpha) from the subsample of foreign funds was greater than that from domestic funds. Alpha from fixed-income funds was greater than that from equities funds. I think it’s fair to suggest that many close observers of closed-end funds have developed an intuitive sense that this is the case. They will be pleased to see their intuitions, gleaned from market observation, are validated by this careful statistical study. Editor’s Note: This article covers one or more stocks trading at less than $1 per share and/or with less than a $100 million market cap. Please be aware of the risks associated with these stocks. Disclosure: The author has no positions in any stocks mentioned, and no plans to initiate any positions within the next 72 hours. (More…) The author wrote this article themselves, and it expresses their own opinions. The author is not receiving compensation for it (other than from Seeking Alpha). The author has no business relationship with any company whose stock is mentioned in this article.

Sell Your Employer, Get VTI Instead

Summary Many employees hold stock in the company that employs them. Taking advantage of plans that offer a discount on stock makes sense, but don’t let it overwhelm your portfolio. By not rebalancing frequently enough, employees may find themselves with diversifiable risk. The excess risk provides no excess (expected) return, and the risk isn’t just having too much of one company in your portfolio. I’m suggesting investors take a better look at replacing their employer’s stock with VTI whenever the option is available. The last week I’ve been doing a great deal of research on behavioral finance. There are several potential pitfalls for investors to avoid, but most investors are not familiar with behavior finance. I’ll be highlighting several of those pitfalls so readers can watch out for them. My focus in this article is why the Vanguard Total Stock Market ETF (NYSEARCA: VTI ) is a better investment than your employer. I can’t say that VTI will provide better returns, but I am confident that the expected return for the level of risk will be superior. Two problems with owning your employer: Problem #1 The first problem should be fairly clear to most investors. Holding individual companies is a fine way to invest, but it creates a substantial amount of diversifiable risk if individual companies are a large part of the portfolio or if multiple companies within the same industry are being selected. When the position in the employer reaches higher levels, say 10 or 15%, it becomes a substantial risk factor for the portfolio. Two problems with owning your employer: Problem #2 The second problem is one that many intelligent people manage to completely overlook. The second risk factor is that you are exposing the value of your portfolio to the same risk factors that are impacting the value of your lifetime earnings. Let’s start with an extreme example: Enron Long-term employees had ample opportunity to build up substantial positions in the company stock. When a company goes out of business, the employees are facing unemployment. If they also held the stock, they risk seeing the value of their portfolio decline substantially. If the firm employs a substantial number of people with their skill set within the geographic area, several former employees may be faced with needing to move in order to find new work. The concentration of that skill set exceeding the number of available positions makes it an unfortunate situation that is even more significant for employees that own their home and will be facing transaction costs on selling the house. Industry risk On top of the company-specific risk, there is also a level of industry risk. If the company is closing locations because the industry is less profitable, finding a job with a competitor will be more difficult. It would be preferable for the employee to have less than normal exposure to his industry within his portfolio. Whether the firm is in biotech or car manufacturing, the price that the employee’s skill set can command in the free market is still dependent upon supply and demand within the industry. Solving the problem There are two ways to solve this problem. An investor can either attempt to build a diversified portfolio that intentionally has less than normal allocation to their industry. However, I think it is much simpler and more cost efficient, due to trading commissions, to simply buy the Vanguard Total Stock Market ETF. I’ve heard people lately talking about how the stock market is being valued too highly. I think some of those analysts raise very legitimate concerns. However, I also believe that market timing has a negative expected value. Attempting to find the right time to jump in may be viable for individual companies, but trying to find the right time for buying the entire market is another challenge entirely. When was the right time to buy? In my opinion, several decades ago would have been great. Since that isn’t an option, I favor investing in the total market at the present time. Is this the perfect moment? I doubt the timing is perfect. Whichever day you buy into the market, there may well be a day in the future that offers a lower price. Buying into the market and having the value never dip under the entry price has more to do with being lucky than good. How I’m doing it Over the next couple months, I’ll be overhauling my positions. The vast majority of my positions are in tax advantaged accounts, so I’m not concerned about the ramifications of capital gains. I’ll do the rebalancing as soon as I finish with filing taxes for 2014. I need to know how I’m going to split up my contributions to Traditional and Roth IRA accounts. I don’t know if the market will move up or down during that time, but I expect VTI to be trading right about NAV due to the enormous trading volume. For investors not familiar with VTI, the average is over 3 million shares per day. I’ll buy at whatever the price happens to be at the time, and I’ll be investing over half of my total investment portfolio. Why VTI? When I started looking at ETFs for my portfolio, I started looking at SPDR S&P 500 Trust ETF (NYSEARCA: SPY ). I started running historical numbers comparing the volatility of portfolios that included ETFs with exposure to several investing factors. I included emerging markets, precious metals, bonds, and bonds in other currencies. What I found was that it was possible (historically) for an investor to find better returns and lower risk through a global portfolio. However, the returns did not take into account any trading costs and the difference was not very substantial. After seeing how well SPY was able to do against the much more complicated portfolios, I decided it would be better to try to replicate it. VTI offers extremely high correlation to SPY, which isn’t surprising given how many of the same equities are being held. However, VTI is offering exposure to smaller cap companies without having such a large position that it would substantially alter the returns. The result is an ETF that offers extremely similar performance to SPY with a slightly lower expense ratio. For VTI it is .05%, for SPY it is .09%. Conclusion If an investor is holding stock in their employer, it would be prudent to consider swapping the position for VTI or SPY. If the position is required as part of a program that allows employees to buy the company stock at a discount to the market price, it may be reasonable to retain the amount of stock required by the program. For any excess cash being invested, VTI or SPY offers dramatically lower risk for the investor’s life. The risk is not simply the standard deviation of the portfolio value. Investors need to be aware that holding their employer exposes their portfolio to precisely the same risks that their career is facing. That is a risk that all investors should seek to diversify. Disclosure: The author has no positions in any stocks mentioned, and no plans to initiate any positions within the next 72 hours. (More…) The author wrote this article themselves, and it expresses their own opinions. The author is not receiving compensation for it (other than from Seeking Alpha). The author has 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. The analyst holds a diversified portfolio including mutual funds or index funds which may include a small long exposure to the stock.

NYSE Margin Debt Dips A Mite In December: Risk Rank At No. 43

Summary New York Stock Exchange margin debt slipped slightly to $456.28 billion in December from $457.11 billion in November. On the same basis, the SPDR S&P 500 Trust ETF’s adjusted closing monthly share price also slipped slightly to $205.54 from $206.06. The risk of speculation appeared lower in December than it did in November, but higher than it did in 69.93 percent of all months ranked by my methodology. New York Stock Exchange margin debt and the SPDR S&P 500 Trust ETF (NYSEARCA: SPY ) moved in the same direction in December for the second straight month, as each was down a wee bit. The level of NYSE margin debt relinquished -$823 million, or -0.18 percent, and the share price of SPY surrendered -$0.52, or -0.25 percent. Many equity market participants consider margin debt a long-term indicator of speculation in the stock market because of their tendency to move either higher or lower together. The NYSE has reported monthly data on securities market credit in three discrete series since 2003 and on margin debt itself since 1959. My primary analyses of these three data series focus on two proprietary metrics, the Margin Debt Directional Indicator, or MDDI, and the Securities Market Credit Risk Rank , or SMC Risk Rank, as described in “NYSE Margin Debt As An Indicator Of Long-Term Movements In S&P 500.” Figure 1: MDDI, January 2014-December 2014 (click to enlarge) Source: This chart is based on a proprietary analysis of monthly margin-debt data at NYSE’s online site. NYSE margin debt in December was -$9.44 billion, or -2.03 percent, lower than it was at its all-time high level in February (Figure 1). The anomalous behavior of margin debt in neither falling a great deal nor rising a great deal during the rest of 2014 appears unsustainable, factoring in the U.S. Federal Reserve’s actual announcement of the end of its latest quantitative easing program Oct. 29 and projected announcement of the beginning of its newest interest rate cycle April 29. This anomalous behavior is reflected by the MDDI, which basically is a comparative assessment of NYSE margin debt in the two most recent months of the data series. If the latest value of the MDDI ( MDDI in the above figure) is higher than its six-month simple moving average ( MDDI 6M SMA in the same figure), then I consider the market to be in bullish mode. If the most recent value of the MDDI is lower than its six-month SMA, then I consider the market to be in bearish mode. The MDDI’s December level is 171, which is lower than its November value of 172 and its six-month SMA of 171.17. As a result, I consider the equity market to have switched modes as of Dec. 31, to bearish from bullish. Based on the January performances of the stock market in general and SPY in particular, I anticipate a continuation of this mode for another month (at least). Figure 2: Highest And Lowest Risk Months, Per SMC Risk Rank (click to enlarge) Source: This table is based on proprietary analyses of monthly securities-market-credit data at NYSE’s online site. December is No. 43 among all 143 months evaluated since the January 2003 baseline by my SMC Risk Rank methodology, which carries out a comparative assessment of the data NYSE has reported in three discrete series: Margin Debt , Free Credit Cash Accounts and Credit Balances in Margin Accounts . The dynamic SMC Risk Rank is designed as a measure of equity market risk associated with speculation, ranking each month in the data set on an ongoing basis. At present, June 2014 is No. 1 , February 2014 is No. 2 and December 2013 is No. 3 among all months ranked (Figure 2). November’s SMC Risk Rank of No. 43 means I consider the stock market risk associated with speculation last month was higher than 69.93 percent and lower than 29.73 percent of all other months evaluated by the methodology. A high SMC Risk Rank for a given month indicates the market may be close to a significant peak, and a low SMC Risk Rank for a given month suggests the market may be close to a significant trough. In my interpretation, the term close in this context typically has meant within three to six months . Figure 3: NYSE Margin Debt And SPY, January 1993-December 2014 (click to enlarge) Source: This chart is based on monthly margin debt data at NYSE’s online site and adjusted closing monthly share prices of SPY at Yahoo Finance . Historically, NYSE margin debt and SPY have tended to move together, with an almost perfect positive correlation coefficient of 0.97 between them since the exchange-traded fund began trading in 1993 (Figure 3). I anticipate this close relationship will become increasingly important in the absence of Federal Reserve asset purchases under a QE program. If I were a party to either side of a margin debt transaction, then this is the time when I would start wondering whether more speculation is the wisest way to go. Disclaimer: The opinions expressed herein by the author do not constitute an investment recommendation, and they are unsuitable for employment in the making of investment decisions. The opinions expressed herein address only certain aspects of potential investment in any securities and cannot substitute for comprehensive investment analysis. The opinions expressed herein are based on an incomplete set of information, illustrative in nature, and limited in scope. In addition, the opinions expressed herein reflect the author’s best judgment as of the date of publication, and they are subject to change without notice. Disclosure: The author has no positions in any stocks mentioned, and no plans to initiate any positions within the next 72 hours. (More…) The author wrote this article themselves, and it expresses their own opinions. The author is not receiving compensation for it (other than from Seeking Alpha). The author has no business relationship with any company whose stock is mentioned in this article.