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MLP ETFs Trading At A Huge Discount To NAV

The collapse in oil price has battered the energy sector as a whole, not sparing the master limited partnerships (MLPs) either. In fact, some MLP ETFs have fallen faster than the value of their underlying securities, creating a huge discount to their net asset value or NAV. This suggests an attractive entry point for long-term investors. This is especially true as the authorized participants (NYSE: AP ) of a discounted ETF steps in and redeems the underlying shares to remove the discount and restore the fund’s value back to its NAV. This process results in profits for the ETF holder when the market price rises relative to NAV (read: Is This the Worst Time For MLP ETF Investing? ). MLP: Is A Good Bet Right Now? Trading at deep discounts, the outlook for MLPs is bright amid the oil price rout. This is because most MLPs, which are engaged in the processing and transportation of energy commodities such as natural gas, crude oil, and refined products, are best positioned to withstand the decline in oil prices and be the major beneficiaries of an oil boom in the long term. Acting as toll-takers, these MLPs earn revenues on the volumes flowing through pipes and not on the commodity price. This nature of business will definitely give a boost to these stocks given that worldwide oil production is on the rise. Unlike exploration and production companies whose profits are directly correlated with commodity prices, MLPs have relatively consistent and predictable cash flows, making them safer and less risky than other plays in the broader energy space (read: Oil Hits 12-Year Low: Short Energy Stocks with ETFs ). Beyond the stability, yields are also pretty high thanks to some favorable tax rules – like we see in the REIT space – that push firms in the MLP space to pay out substantially all of their income to investors on a regular basis. Further, MLPs represent a great way of tapping the growing revolutionary developments in the field of unconventional energy. As a result, the steep decline in MLP stocks and ETFs provides an attractive investment opportunity to long-term investors, looking for growth and income. Below, we highlight some products that were trading at a steep discount to NAV as of January 15 (as per Fidelity ): UBS ETRACS Alerian MLP Infrastructure Index ETN (NYSEARCA: MLPI ) : Discount – 5.32% This product tracks the Alerian MLP Infrastructure Index, which comprises 25 mid-stream energy infrastructure MLPs. It has attracted $1.5 billion in AUM and trades in solid volume of 967,000 shares per day. The note charges 85 bps a year in fees and pays out a hefty yield of 8.04%. Credit Suisse Equal Weight MLP Index ETN (NYSEARCA: MLPN ) : Discount – 5.13% This ETN follows the 30 MLP Index, an equally weighted index that uses a formulaic, proprietary valuation methodology and comprises of 30 midstream MLPs. It has attracted $365.5 million in its assets base so far and sees good average daily volume of more than 325,000 shares. Expense ratio came in at 0.85%. The note pays out 7.53% in annual yield. UBS ETRACS Wells Fargo MLP Index ETN (NYSEARCA: MLPW ) : Discount – 4.69% This note tracks the Wells Fargo Master Limited Partnership Index, which provides exposure to all energy MLPs listed on the New York Stock Exchange or NASDAQ with market cap of at least $200 million. It failed to garner enough investor interest with AUM of just $7 million and sees paltry volume of about 13,000 shares. MLPW charges 85 bps in annual fees and expenses, and pays a solid yield of 9.82%. UBS ETRACS Alerian MLP Index ETN (NYSEARCA: AMU ) : Discount – 4.68% This product tracks the performance of the Alerian MLP Index, which provides exposure to 50 publicly traded energy MLPs. It has amassed $351.4 million in its asset base and trades in solid volume of nearly 468,000 shares. It charges 80 bps in annual fees and sports a dividend yield of 7.16%. RBC Yorkville MLP ETN (NYSEARCA: YGRO ) : Discount – 4.57% This note seeks to offer return of the Yorkville MLP Distribution Growth Leaders Liquid Index, which offers access to 25 MLPs exhibiting the highest distribution growth and superior liquidity profiles. It is also unpopular with AUM of $14.5 million and average daily volume of around 15,000 shares. Expense ratio came in at 0.90% and dividend yield stands at 8.54%. MLP ETNs vs MLP ETFs Unfortunately, there are some tax headaches when using the MLP structure, namely the possible need of a K-1 form at tax time. But this issue can be avoided by looking at MLPs that use an exchange-traded structure. This is because ETNs do not actually hold the securities of an underlying index. Instead, an ETN is an unsubordinated debt security that promises to pay out a return that is equal to an index. This is completely unlike an ETF that buys and sells the securities making up a particular benchmark. Due to this advantage, investors can buy MLP ETNs without the hassle of K-1 at tax time, making the above-products excellent choices for those seeking high yield without the taxation headache. Link to the original post on Zacks.com

SilverPepper Posts Pair Of First-Place Finishes

Alternative mutual fund company SilverPepper prides itself on making “hedge fund strategies” available to “the rest of us.” The Lake Forest, Illinois-based firm has a number of investor-friendly videos at its website , and its marketing materials generally aim to entertain as well as inform. SilverPepper’s approach is working. The firm recently celebrated its second anniversary, and for the second straight year, two of its mutual funds had the honor of finishing first within their categories: the SilverPepper Merger Arbitrage Fund (MUTF: SPAIX ) was the top-performing merger-arbitrage mutual fund for the 12 months ending October 31, and the SilverPepper Commodity Strategies Global Macro Fund (MUTF: SPCIX ) finished first out of 157 funds in the “Commodities Broad Basket” Morningstar category. SPAIX also had a strong showing in comparison to funds in the broader Market Neutral category, finishing 11th out of 158 funds for the time period being considered. For the year ending December 31, 2015, the fund returned an impressive 8.49%, ranking in the top 3% of the broad category. SilverPepper president Patrick Reinkemeyer attributed the fund’s outperformance to “hedge fund expert” Steve Gerbel, who “controlled risk by avoiding failed mergers” and boosted returns by investing in smaller-cap companies “where regulatory hurdles tend to be less, yet merger spreads are typically wider.” SPCIX finished 1st out of 157 funds for the year ending Halloween 2015, but that doesn’t mean it actually generated positive returns for what was a tough 12 months for commodities. Nevertheless, it outperformed the category average by a whopping 14 percentage points, and over the next three months, its -0.80% return remained in the top 4% of the category. Mr. Reinkemeyer said fund manager Renee Haugerud “deserves credit” for “using her fingernails-in-the-dirt research to largely avoid some of the worst commodity sectors,” including oil, and “hedging its bets” as part of “an overt tactic to protect investors’ assets.” For more information, visit silverpepperfunds.com. Past performance does not necessarily predict future results. Jason Seagraves contributed to this article.

Dumb Alpha: The Drawbacks Of Compound Interest

By Joachim Klement, CFA The second installment of this series presented evidence that a simple random walk forecast typically performs better than the amassed expertise of professional forecasters for short-term forecasts of about 12 months. In this post, I argue that estimation uncertainty is not reduced for long-term forecasts either, because mean reversion cannot overcome the effects of compound interest. Luckily, there is a range of techniques, from simple to sophisticated, that can help long-term investors with this challenge. The “Muffin Top” Problem As most middle-aged people can confirm, age inexorably leads to a slowing metabolism. If you don’t change your diet, your waistline expands quite generously. In my case, I refused to notice these changes until I grew an undeniable “muffin top” of belly fat above my belt line. Chagrined, I changed my diet and stepped up my exercise, but so far — muffin doin’. This little anecdote is a rather fitting (if unappealing) metaphor for long-term investing. What I tried to force my body to do was to revert back to its original state (the mean), but the forces of mean reversion were not strong enough to do so. This scenario can happen in the world of investing as well. Imagine someone who wants to invest for the next 10 years and who is thus not interested in short-term forecasts so much as the long-term average expected returns of assets. Common wisdom states that, while return forecasts can be widely off the mark in any given year, in the long run, returns should converge towards a rather stable long-term mean. Because of mean reversion, it should be easier to forecast long-term returns than short-term returns. Compound Interest Ruins the Day In an important article in the Journal of Finance , however, University of Chicago economists Lubos Pastor and Robert Stambaugh showed that, in the presence of estimation uncertainty, mean reversion is not strong enough to reduce the volatility and uncertainty of long-term stock market returns. The main reason is that an estimation error in the first year will propagate and compound over the subsequent nine years, an estimation error in the second year will compound over the subsequent eight years, etc. Take, for example, an investment you know will average an annual return of 10% per year over the next 10 years. If in the first year the return is -10%, the average return over the subsequent nine years needs to be about 12.48% per year to make up for this shortfall. In other words, a 20% estimation error in the first year requires a relative increase in annual returns over the next nine years of 24.8%. If, on the other hand, the asset in the first year has a return of 0%, the average return over the subsequent nine years needs to be about 11.17% to make up for the shortfall. So a 10% estimation error in the first year requires a relative increase in annual returns of 11.7%. Half the estimation error requires less than half the relative return increase to make up for the shortfall. The investment results of the first few years have an oversized influence on the long-term investment returns — something that retirement professionals know as “sequence risk.” If you start saving for retirement and experience a major bear market in the first few years, you are much less likely to achieve your long-term financial goals than if you experience a rather benign environment at first and a bear market later. While the research by Pastor and Stambaugh is theoretical in nature, there is empirical evidence that long-term return forecasts are, in fact, just as uncertain and “inaccurate” as short-term forecasts. Ivo Welch and Amit Goyal have looked at the predictive power of many different variables that are commonly used to forecast equity market returns. They find that the forecast error does not materially change for forecast horizons between one month and 10 years. In other words, despite the existence of mean reversion, the uncertainty about future equity returns does not decrease in the long run. Facing the Challenge If long-term return forecasts are just as difficult to make as short-term forecasts, what can long-term investors do to create robust long-term portfolios? After all, we know that traditional Markowitz mean-variance optimization is about 10 times more sensitive to return forecast errors than to forecast errors in variances . There are in my view several possibilities, increasing from least to most in degree of sophistication: The equal weight asset allocation discussed in the first part of this series does not rely on forecasts, and thus is a simple and effective way to create robust long-term portfolios. Minimum variance portfolios and risk parity portfolios do not require any return forecasts and, if done properly, can outperform traditional portfolios by a wide margin. More sophisticated methods like resampled efficient frontier methodologies or Bayesian estimators can include estimation errors into the portfolio construction process and thus create portfolios that are more immune to unexpected events. Whatever technique one favors, there are ways to deal with forecast errors. Most critically, it is time investors take estimation uncertainty more seriously for the benefit of their clients and the long-term success of their portfolios. 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