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Are You Ready For CEFL’s Year-End Rebalancing?

Summary The index for CEFL/YYY was last rebalanced in December 2014, and changes to the index were made public a few days before the event. Last year, heavy buying or selling pressure in particular index components forced CEFL/YYY to buy-high and sell-low, causing significant losses to CEFL/YYY unitholders. How will CEFL’s rebalancing be handled this year? Introduction The ETRACS Monthly Pay 2xLeveraged Closed-End Fund ETN (NYSEARCA: CEFL ) is a 2x leveraged ETN that tracks twice the monthly performance of the ISE High Income Index [symbol YLDA]. The YieldShares High Income ETF (NYSEARCA: YYY ) is an unleveraged version of CEFL. CEFL is popular among retail investors for its high income, which is paid out monthly. (Source: Pro Spring Team ) YLDA holds 30 closed-end funds [CEFs], and is rebalanced at the end of every calendar year. The changes were publicly announced on the ISE website on Dec. 24, 2014, or about five days prior to the rebalancing event. According to YYY’s prospectus (emphasis mine): Index constituents are reviewed for eligibility and the Index is reconstituted and rebalanced on an annual basis. The review is conducted in December of each year and constituent changes are made after the close of the last trading day in December and effective at the opening of the next trading day . As CEFL is an ETN, it is not forced to buy or sell the constituent ETFs, but one would imagine that the note issuer, UBS (NYSE: UBS ), would be inclined to do so to hedge its exposure of the note. Rebalancing shenanigans Unfortunately, CEFL/YYY unitholders were hurt by the rebalancing mechanism last year. I first noticed that something was wrong when CEFL fell -2.96% (and YYY -1.25%) on Jan. 2nd, 2015, a day where both stocks and bonds held relatively steady, and where the comparable PowerShares CEF Income Composite Portfolio ETF (NYSEARCA: PCEF ), an ETF-of-CEFs that tracks a different index, rose +0.21%. A bit of detective work on my part revealed that the CEFs that were to be added to the index received heavy buying pressure in the days between the index change announcement and rebalancing day, while the CEFs that were to be removed came under tremendous selling pressure. This caused the prices of the added CEFs to rise significantly during that period, which was topped off by an upwards price spike on rebalancing day, while the prices of the CEFs to be removed declined markedly in price, culminating in a downwards spike on rebalancing day. As a consequence, the index and hence YYY were forced to “buy high and sell low” on rebalancing day, causing about 1.3% of the net asset value [NAV] of YYY to be vaporized in an instant. This findings were presented in my Jan. 4th article ” Frontrunning Yield Shares High Income ETF YYY And ETRACS Monthly Pay 2xLeveraged Closed-End Fund ETN CEFL: Could You Have Profited ?” However, the pain was not over for CEFL/YYY holders. The upwards price spike of the CEFs to be added on rebalancing day occurred on top of the artificially-inflated prices caused by the buying pressure days before the actual event. After rebalancing, the added CEFs possessed premium/discount values dangerously above their historical averages, as I warned in ” Beware Reversion In YieldShares High Income ETF And ETRACS 2x Closed-End Fund ETN ,” leading to further losses as the premium/discount of those CEFs reverted back to their original levels. How much were CEFL/YYY investors hurt? How much were CEFL/YYY holders hurt by last year’s rebalancing mechanism? It is impossible to provide an exact number, but here is my estimate. The 10 added CEFs with the largest increases in allocation rose by 2.96% in one week, while the 10 with the largest decreases in allocation declined by -3.38% in one week (as presented in my Jan. 4th article). Assuming that CEFL is equally-weighted*, these events would have caused an overall 2.11% decline in asset value. Up to a further 1.25% was lost on rebalancing day due to price spikes. Moreover, the 10 CEFs that were added to the index declined by 1.26% two weeks after rebalancing as mean reversion possibly took place (as discussed in ” 2 Weeks Later: Did Mean Reversion Of CEFs Take Place? “), contributing a further 0.42% decline of the index, again assuming equal-weight. This sums to a 3.8% loss for YYY holders, or about a 7.6% loss for CEFL holders, not an insignificant amount. Note that this number is likely to be an underestimate because only the top 10 CEFs undergoing the highest increases and decreases in allocation were considered. In actuality, 19 funds were added, and 17 were removed. *(CEFL is actually not equal-weighted, but it is not entirely top-heavy either. See my Jan. 4th article linked above for details to the index weighting methodology). An alternative methodology for calculating the underperformance of CEFL/YYY is to simply compare the performance of YYY to PCEF, as both are ETFs-of-CEFs, but track different indexes. As analyzed in ” Has CEFL Done As Badly As It Looks? ” YYY underperformed PCEF by a total of 5.3% in the months of December and January, i.e. the months surrounding the rebalancing date. Although this approach is only approximate (as the exact composition of the two funds differ), it does produce a number that is on a similar order of magntitude as the 3.8% loss calculated with the first approach. Either way you cut it, a 4% or higher loss for the index/YYY (double that for CEFL, due to leverage) because of factors outside of “normal” market behavior hurts. Moreover, the fact that the index was forced to buy high and sell low necessarily results in a lower income for the fund going forward, as the fund would not have been able to purchase as many shares of the new CEFs than it “should” have been entitled to. Indeed, each share of CEFL paid out a total of only $4.03 in 2015, down from $4.40 in 2014, representing a 8.5% decrease in income paid for the year. I lost…so who won? So if CEFL/YYY unitholders were hurt during rebalancing, who profited? Most likely, it was the savvy investors who purchased the CEFs to be added to the index and shorted the CEFs to be removed as soon as the index changes became public. This could, in fact, include UBS themselves, who are free to adjust their hedges for CEFL anytime they like (because CEFL is an ETN rather than an ETF), and not only on rebalancing day. This creates an ironic situation in which the act of UBS adjusting their hedges at more favorable prices before rebalancing could have actually and directly hurt investors in their very fund. Why is this a problem for CEFL and not other funds? The main problem appears to be the lack of liquidity for CEFs, as well as the fact that arbitraging price differences for CEFs can be risky as they often trade at premium or discount values around their intrinsic NAV, meaning that it would be difficult for arbitrageurs to determine the “true” value of a CEF. An insightful comment from a reader in my previous article reveal that this has happened to other funds as well, and also illustrates a possible solution to this problem: [We] also had a FTSE 100 tracking fund run externally by a well known global indexing house. I recall at one index rebalance, said fund had a MOC order to buy one of the new index constituents, and ended up paying about 25% MORE than the prevailing market price was 1 minute before. All index tracking funds got completely shafted as guess what, the next day the stock was back down to the price it was before its index inclusion. … Some index managers get friendly brokers to ‘warehouse’ stocks (take them onto their own book) for a few days, buying them up ahead of inclusion in a particular index, the fund then takes an average price, and doesn’t get the shaft with a MOC order. It can lead to a bit of ‘tracking error’ mind you. This time it’s…different? As a CEFL unitholder and with the end of the year rolling around, I thought I would refresh myself on the rebalancing mechanism of the index YLDA to confirm exactly when the CEF changes would be announced, so that I could…uh…you know…get in on the frontrunning action and profit at the expense of fellow CEFL/YYY holders. Just kidding, I would have definitely shared this information with all my loyal readers! (Please do click the “follow” button next to my name if you haven’t done so already if you enjoy my ETF analysis.) So I fired up the YLDA methodology guide and looked for the rebalancing date… and looked, and looked…only it wasn’t there! I then checked the date of issue of the methodology guide: December 4th, 2015. So this couldn’t have been the guide I was reading when I was writing my earlier CEFL articles this year. Luckily, I had a version of the guide stashed in my downloads folder, and the relevant section (4.3) is dutifully reproduced below (emphasis mine): 4.3. Scheduled component changes and review ( OLD v1.2 ) The ISE High IncomeTM Index has an annual review in December of each year conducted by the index provider. Component changes are made after the close on the last trading day in December , and become effective at the opening on the next trading day. Changes are announced on ISE’s publicly available website at least five trading days prior to the effective date . How does this compare with the current version of the methodology (emphasis mine)? 4.3. Scheduled component changes and review ( NEW v1.3 ) The ISE High IncomeTM Index has an annual review in December of each year conducted by the index provider. The index employs a “rolling” rebalance schedule in that one third of component changes are implemented at the close of trading on each of the first, second and third trading days in January of the following year and each change becomes effective at the opening on the second, third and fourth trading day of the new year, respectively. No prizes for spotting the difference! Not only has the statement about the announcement of changes been removed, the rebalancing is now not performed all at once at the close of the last trading day in December, but is now equally spread through the first, second and third trading days of the following year. I then used the free PDF comparison tool ( DiffPDF ) to scan for any additional changes to the methodology between last and this year’s. Besides being nearly foiled by the addition of two blank pages in this year’s edition, the software showed that, besides the aforementioned change in Section 4.3, a similar statement to the above had been removed from the index description in Chapter 2: Chapter 2. Index Description ( bold sentence in OLD guide only ) Companies are added or removed by the ISE based on the methodology described herein. Whenever possible, ISE will publicly announce changes to the index on its website at least five trading days in advance of the actual change . No changes were made to the constitution or weighting mechanisms of the fund. Appendix B of the current document lists the entirety of the changes as “Rebalance revision (4.3).” What does this mean for investors? Analysis of the old and new methodology guide reveals two major changes: The changes to the index will not be public beforehand. Instead of rebalancing the components all at once, the rebalancing will be conducted in three equal parts spread across three days. What does this mean for investors? I believe that the first change is well-intended, but may ultimately prove fruitless. The methodology for index inclusion and weighting is relatively complex, but is publicly available (it’s found in the methodology document), and I have no doubt that professional investors will be able to determine the changes even before they happen. In fact they may be doing this right now as I am writing this, and also later, when you are reading this. The second change is, I believe, a positive one, but only if it means one of two possible ways that one could construe “one-third.” The guide states that ” one-third of component changes are implemented… on each of the first, second and third trading days in January .” So if 10 CEFs have to be added to the index, does it mean that 33.3% of the total dollar value of the 10 CEFs will be purchased on each of the three days? In this case, the liquidity situation will be improved because each CEF will be purchased over three days. This would decrease the likelihood of a price spike occurring upon rebalancing (presumably by YYY, the ETF), which ameliorates the buy-high sell-low situation faced by the index last year. If instead, it means that 4 CEFs will be 100% purchased on the first day, 3 on the second, and 3 on the third, then unfortunately I don’t think that the liquidity situation will improve, as the trading in each CEF is still going to be concentrated in a single day, despite the fact that different CEFs may be spread out on different days. What do readers think about how this sentence should be interpreted? So, it appears that this time may actually be different. However, personally, I’m not waiting around to find out. I’ve recently sold all but a single share of CEFL to keep my interest in the fund, and replaced it with several better-performing CEFs (such as the PIMCO Dynamic Income Fund (NYSE: PDI )), as recommended in Left Banker’s article here .

Past Vs. Prologue: Cutting Through The Noise Of Investment Returns

Fortunately for investors, there is good information on stock returns which can be used to provide guidance for return expectations. Less fortunately, the translation of that information varies considerably which creates a lot of “noise” that investors must cut through in order to make good investment decisions. Comparing the work of Dimson Marsh and Staunton to that of Jeremy Siegel reveals different approaches and different conclusions. In any endeavor, history can serve as a useful guide to what might happen in the future. The good news for investors is that studies of historic investment returns are far more detailed and accessible than they used to be. Triumph of the Optimists by Dimson, Marsh and Staunton is one of the most useful and should be a core part of any serious investment curriculum, but there are others. The bad news for investors is that even when good information can be attained, its translation into investment advice and portfolio strategy can vary substantially. Much like background noise and poor connection quality can make it hard to understand a person on the other end of a phone call, so too can “noise” interfere with the quality of the signal investors receive in the form of advice. This phenomenon is readily apparent in regards to establishing appropriate guidelines for expected investment returns. For starters, the quality of underlying data regarding returns is fairly good – which is often not the case with investment research. It encompasses long periods of time and multiple geographic markets. The Dimson Marsh and Staunton (DMS) study (see [ here ] for our book review) encompasses returns between 1900 and 2000 for 16 different countries. Jeremy Siegel also conducted a study of stock returns focusing on just the US but dating back to 1802 which he popularized in his book, Stocks for the Long Run . The studies are similar for the depth of their research and for the fact that both found US stocks providing a real return of 6.7% over their study periods. The path of these research efforts diverges when it comes to interpreting the results for the purpose of establishing expectations, however. DMS focuses on analyzing the patterns they see in the historical returns and normalizing them as the basis for making a sensible forecast. One of the key points they highlight is that valuations have changed considerably over their study period and this provided a one-time, unsustainable boost to returns. They report, “Since 1900, there has also been a dramatic change in the valuation basis for equity markets. The price/dividend ratio (the reciprocal of the dividend yield) is much higher now than it was in 1900. After adjusting for the difference, they conclude that the ex ante risk premium for US stocks is 1.7% lower than the historical premium. “Our assertion in this book … is that the equity premium is markedly lower than many people suggest.” Indeed, this outlook is very consistent with Dimson’s recent assessment in the Economist [ here ] that “the likely future long-term real return on a balanced portfolio of equities and bonds will be 2-2.5%.” A second finding from DMS is that the unusually strong returns in the second half of the twentieth century appear to be statistical flukes and unlikely to be repeated. They note, “This was a period [the latter half of the twentieth century] when most things turned out better than expected. There was no third world war, the Cuban Missile Crisis was defused, the Berlin Wall fell, and the Cold War ended. There was unprecedented growth in productivity and efficiency, improvements in management and corporate guidance, and extensive technological change. Corporate cash flows grew faster than expected, and in all likelihood the equity risk premium fell, further boosting stock prices. In short, it was the triumph of the optimists.” In other words, the phrase for their book title, Triumph of the Optimists , is intended to be a mild warning in regards to expectations. They conclude their study by highlighting, “Statistical logic tells us that future expectations must lie below today’s optimists’ dreams. We can hope for, but we cannot expect, the optimists to triumph in the future. Future returns from equities are likely to be lower than those achieved in recent decades … experience should teach us realism, not optimism.” Siegel, by contrast, take a very different approach when establishing expectations for future returns by highlighting the constancy of stock return through history. As he often does, he started and ended his November presentation at the CFA Institute’s Equity Research and Valuation Conference [ here ] with a graph showing the returns to stocks, bonds, bills, gold, and the dollar. The chart shows stocks on a nearly linear upward trajectory with the returns for all of the other assets on considerably less attractive paths. Although he stops short of proclaiming 6.7% as his expected return for stocks, he clearly relishes in the moniker “Siegel’s constant” being applied to his findings. By leaving the graph of historical stock returns on the screen at the end of the presentation, he leaves a strong visual impression, and implied message, that past is prologue. Siegel also takes a very different approach to the subject of valuation. For one, he prefers using price/earnings (PE) as an indicator, despite the fact that just like with returns, one year’s worth of earnings can be hugely unrepresentative. To his credit, he does discuss Shiller’s cyclically adjusted price to earnings ratio (CAPE) which actually does a very good job of indicating future returns. However, after noting that the conventional CAPE methodology forecasts only 2% real returns for stocks, he moves on to describing how he believes the CAPE metric should be adjusted. His conclusion is that with certain adjustments, current valuation metrics point to expected returns to stocks very much in line with the long term average of 6.7% So we have two very different takes on essentially the same data set of stock returns. Siegel is bullish in finding stocks right on track to continue their long run record of 6.7% real returns – which is well above the returns of other asset classes. DMS, while also recognizing the historical superiority of stocks, are considerably more cautious in their expectations for future returns. Both perspectives are well informed views by respected academics. Unfortunately, this conflict creates even more of a challenge for conscientious investors trying to establish an appropriate portfolio strategy. How should investors cut through the noise? In an important sense, we enjoy having multiple sides to debates like this because it forces us to understand the positions very clearly and to disentangle what can be very subtle issues and assumptions. The case of return expectations is an excellent example because both views seem quite plausible. We begin our investigation, as we often do, by searching for inconsistencies and differences in underlying assumptions. One key assumption Siegel makes is that although stocks can deviate materially over the short term, those deviations become progressively smaller over longer periods. This is an important tenet in his thesis “stocks for the long run” but one that is not uncontroversial. Zvi Bodie, another noted academic, argues that Siegel’s view understates the long run risk of stocks. He describes in his paper “The long run risk of stock market investing: Is equity investing hazardous to your client’s wealth?” in the Financial Analysts Journal [ here ] that, “Economic uncertainty, especially, is magnified with time. What is the worst thing that can happen over the next 5 years compared with over the next 10,15,20,30, or 100 years? In 100 years’ time, a myriad of catastrophic things could happen.” This is an issue we highlighted in the blog post “Spring Cleaning” [ here ] where we noted that this observation is common in fields outside of economics and is a key factor in engineering (long term) infrastructure projects. Two other academics, Lubos Pastor and Robert Stambaugh, also addressed this issue in a paper entitled “Are stock really less volatile in the long run?” [ here ]. They acknowledge that “Conventional wisdom views stock returns as less volatile over longer investment horizons.” However, they also report that “stocks are actually more volatile over long horizons from an investor’s perspective.” They go on to explain: “Investors condition on available information but realize their knowledge is limited in two key respects. First, even after observing 206 years of data (1802-2007), investors do not know the values of the parameters of the return-generating process, especially the parameters related to the conditional expected return. Second, investors recognize that observable “predictors” used to forecast returns deliver only an imperfect proxy for the conditional expected return, whether or not the parameter values are known. When viewed from this perspective, the return variance per year at a 50-year horizon is at least 1.3 times higher than the variance at a 1-year horizon.” In other words, the future is uncertain and hard to predict. Indeed, an important element of their findings is that they explicitly call out the difference between assessing variance after the fact, or ex post , and assessing variance in the future, or ex ante . In contrast to Siegel, the notion that the future is inherently less certain permeates the language of DMS. This is evidenced when they say, “downside risk is always present,” and “because of the power of compound interest rates, the very worst that could happen to an equity investor worsens as the investment horizon is lengthened.” When DMS “examine the range of risk premia that can be anticipated over various future time horizons,” they find that “There is clearly a substantial probability of achieving a negative risk premium, even over long investment horizons.” Another subject that Siegel treats very differently than DMS is valuation. It is interesting to note that while Siegel sees fit to examine 200 years of stock returns, he uses only the current year’s price/earnings as his primary valuation metric. Using a single year’s worth of earnings makes his analysis vulnerable to being incredibly unrepresentative of the longer term and in doing so, seemingly antithetical to his effort to capture the big picture revealed by an extensive history. He does also consider a more robust valuation metric, the Shiller CAPE, which has one of the best records among valuation metrics for correlating with future returns (higher CAPE suggests lower future returns). However, when he finds that the current CAPE suggests future returns to stocks on the order of 2%, he deems it appropriate to adjust the earnings input to CAPE. In doing so he arrives at a CAPE ratio that suggests “very slight overvaluation” and an expected return to stocks very much in line with the historical average of 6.7%. There are at least a couple of things interesting about Siegel’s approach to valuation. For one, he does not appear to make an effort to calibrate for the fact that market valuations today are higher than they were at the beginning of the study periods. DMS explicitly address this as an issue that likely overstated historical returns relative to what can be expected in the future. Siegel makes no such valuation adjustment which means that in order to enjoy the same equity returns in the future as the past, valuations will have to continue to rise at the same rate, all else being equal. Another interesting aspect of Siegel’s approach to valuation regards the adjustment he makes to earnings for CAPE. Rather than comparing the price of the S&P 500 to the earnings of S&P 500 companies, he compares it to the profits from the entire economy. Effectively, he compares apples to oranges. John Hussman provided an excellent analysis of the “adjustment” [ here ] and James Montier at GMO has also chimed in with well- reasoned, and critical analysis of Siegel’s position [ here ] and [ here ]. In summary, we find flaws in several key aspects of Siegel’s thesis that serious challenge the credibility of his return expectations. For one, reference to any set of asset returns as a “constant” is absurd and defies underlying economic reality. In addition, the failure to clearly highlight the difference between realized historical variance and the variance of uncertain future events unnecessarily biases and complicates the assessment of return expectations. Further, Siegel’s valuation work suffers from clear inconsistencies in what Montier calls “a strange way of honestly adjusting a valuation measure.” It is also striking that Siegel does not call out the unusually strong returns in recent years and the negative impact those results may have on future returns. Specifically, the S&P 500 has returned 14.40% per year over the five years through November 2015. This is even greater than the 13.6% annual return achieved between 1982 and 1999 in what Siegel himself calls “the greatest bull market in history”, a period which he acknowledges as having generated returns more than double the longer term average. As a result, one key takeaway from this analysis is that we place more weight on the DMS work in regards to return expectations than that of Siegel. While we believe that, in general, stocks are worthy long term investments, we also believe they entail real risk, especially over horizons of less than ten or twenty years. Currently, based on the conventional CAPE ratio, we believe stock returns for the next ten to twelve years will be in the very low single digits, nearing zero. This is relevant for anyone who depends on achieving much higher returns, is retired or may be retiring shortly, or for whatever reason may need access to their investment funds in less than 30 or 40 years. We also believe that “Siegel’s constant” of 6.7% is an interesting historical occurrence, but that it says very little about the future and creates an “anchor” that can inhibit more productive intellectual inquiry. In order to calibrate that realized return of 6.7% to potential future results, we must consider how things may differ in the future. We know that the US experienced remarkable growth since 1802 and that is unlikely to repeat, at least not to the same degree. We know that productivity has recently crashed and that if it remains at current levels, it will be extremely difficult to achieve historical return levels. Demographic trends point to an aging society which is typically more averse to risk and has less demand for stocks. And debt and entitlement burdens are at record highs. Any one of these issues could depress future returns and if all of them exert pressure, future returns could be materially lower. After all, equity is only what is left after all other liabilities. Finally, this exercise also reveals one of the great challenges of investing and is symbolic of one of the industry’s major shortcomings: the almost constant need to cut through the noise. While we respect Dr. Siegel’s work, at the same time we believe that much of it used to fuel a bullish narrative at the expense of a clear discussion of issues relevant for investors. This doesn’t happen because he isn’t aware of the issues. Unfortunately, it makes things harder for investors when smart, authoritative figures produce overly ebullient outlooks that inflame the already troublesome tendency many have to extrapolate past results into the future. History can inform the future, but past is not prologue. We believe the more useful approach is that of DMS which appropriately tempers that enthusiasm with the lesson that “experience should teach us realism, not optimism”.

No Respite For Oil And Energy ETFs In 2016?

The vicious trading of oil and the energy sector is likely to persist for more months especially after the Fed finally pulled its trigger on the first rate hike in almost a decade. Higher interest rates will drive the U.S. dollar upward, making dollar-denominated assets more expensive for foreign investors, and thus, dampening the appeal for the commodity. In addition, it will make the borrowings, in particular for high-yield firms, costlier and result in less money flows into capital-intensive shale oil and gas drilling projects. This in turn will lead to higher bankruptcies, hitting the already battered energy sector. Following the rate hike announcement, U.S. crude dropped nearly 5% to $35.52 per barrel, just a few dollars away from $32.40 that it hit during the financial crisis in 2008. Meanwhile, Brent oil tumbled to the nearly 11-year low of $37.11, which is not very far from the December 2008 low of $36.20. Analysts expect breaking the 2008 levels could take oil prices to levels not seen since 2004 given fears of growing global glut and weak demand that have been weighing on the oil prices. Weak Trends The latest inventory storage report from the EIA for the last week showed that U.S. crude stockpiles unexpectedly rose by 4.8 million barrels against the expected 1.4 million-barrel drawdown, underscoring further weakness in the energy sector. This is because production has been on the rise across the globe with the Organization of the Petroleum Exporting Countries (OPEC) continuing to pump near-record levels of oil to maintain market share against non-OPEC members like Russia and the U.S. Additionally, Iran is looking to boost its production once the Tehran sanctions are lifted. On the other hand, demand for oil across the globe looks tepid given slower growth in most developed and developing economies. In particular, persistent weakness in the world’s biggest consumer of energy – China – will continue to weigh on the demand outlook. Further, a warm winter in the U.S. will depress demand for energy and energy-related products. Adding to the grim outlook is the International Energy Agency’s (IEA) expectation that the global oil supply glut will persist through 2016 as worldwide demand will soften next year to 1.2 million barrels a day after climbing to a five-year high of 1.8 million barrels this year. ETF Impact The Fed move and the bearish inventory data have battered the oil and energy ETFs and are expected to continue doing so in the coming months with bleak oil fundamentals. In particular, the iPath S&P Crude Oil Total Return Index ETN (NYSEARCA: OIL ) , the United States Oil ETF (NYSEARCA: USO ) , the PowerShares DB Oil ETF (NYSEARCA: DBO ) and the United States Brent Oil ETF (NYSEARCA: BNO ) lost over 3% in Wednesday’s trading session. All these products focus on the oil futures market and are directly linked to the U.S. crude or Brent oil prices. In the equity energy ETF space, the First Trust ISE-Revere Natural Gas Index ETF (NYSEARCA: FCG ) and the SPDR S&P Oil & Gas Exploration & Production ETF (NYSEARCA: XOP ) were the worst hit, shedding 2.7% and 2.2%, respectively. These were followed by declines of 2% for the Market Vectors Unconventional Oil & Gas ETF (NYSEARCA: FRAK ) and the PowerShares S&P SmallCap Energy Portfolio ETF (NASDAQ: PSCE ) . FCG This fund offers exposure to the U.S. stocks that derive a substantial portion of their revenues from the exploration and production of natural gas. It follows the ISE-REVERE Natural Gas Index and holds 30 stocks in its basket that are well spread out across each component with none holding more than 6.95% of the assets. The fund has amassed $161.1 million in its asset base while charging 60 bps in annual fees. Volume is solid with more than 1.8 million shares exchanged per day on average. XOP This fund provides equal-weight exposure to 66 firms by tracking the S&P Oil & Gas Exploration & Production Select Industry Index. Each holding makes up for less than 2.3% of the total assets. XOP is one of the largest and popular funds in the energy space with an AUM of $1.5 billion and expense ratio of 0.35%. It trades in heavy volume of around 12 million shares a day on average (see all the energy ETFs here ). FRAK This ETF provides exposure to the unconventional oil and gas segment, which includes coalbed methane, coal seam gas, shale oil & gas, and sands market. This fund follows the Market Vectors Global Unconventional Oil & Gas Index, holding 57 stocks in the basket. Average daily volume at 39,000 shares and an AUM of $41 million are quite low for the fund while expense ratio is at 0.54%. PSCE This fund provides exposure to the energy sector of the U.S. small-cap segment by tracking the S&P Small Cap 600 Capped Energy Index. Holding 32 securities in its basket, it is heavily concentrated on the top two firms that collectively make up for one-fourth of the portfolio. Other firms hold less than 5.8% of total assets. The fund is less popular and less liquid with an AUM of $33 million and average daily volume of about 19,000 shares. Expense ratio came in at 0.29%. In Conclusion Investors should stay away from the above-mentioned funds as more pain is in store for oil and the energy sector. FRAK and FCG have a Zacks ETF Rank of 5 or “Strong Sell” rating while XOP and PSCE have a Zacks ETF Rank of 4 or “Sell” rating, suggesting their continued underperformance going into the New Year. Original post