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The Great Debate

Much ink has been spilled over whether investors should use active or passive management in their portfolios. Often, the loudest critics on either side of this debate are firms defending their own interests, “torturing the numbers” to sway the crowd towards an “obvious” decision. As with many aspects of the investment management world, this is an emotionally charged issue, and those emotions can lead to poor decision making. What’s needed is a fair and objective framework to help you decide what is best for your own portfolio. Weighing Pros and Cons In the simplest terms, passive management, also called indexing, is a long-term style of management where mutual and exchange traded funds mirror a market index, such as the S&P 500. Conversely, active management refers to a manager making investment decisions using research, forecasts and experience, in an attempt to outperform a benchmark index. Let’s start with the simpler side of the debate. Indexing has several uncontested advantages, including low cost, transparency, tax efficiency, and no chance of significant underperformance. This is an attractive set of attributes, but what are the downsides of indexing? There are two big ones: •There is no chance of outperformance (i.e., assured mediocrity.) Indexing takes away the hope of outperformance. This may be acceptable if we believe we don’t have a better option. •Market-cap weighted indexes (which include most of the major indexes) are popularity weighted indexes. The higher a company stock goes, the more weight it carries. As Rob Arnott says, “The Achilles’ heel of indexing is that when you have a bubble and a stock is trading way higher than it should, you have your peak exposure at its peak price.” For example, the S&P 500’s highest industry weighting just before the tech bubble burst was technology, and its highest weighting just before the financial crises in 2007 was financials. Ouch! Side Note: One flavor of study that drives me absolutely nuts is when supporters of indexing use the fact that this year’s best managers are often not the best managers of the following year–and a lot of times in the bottom half of their peer group-as “proof” that active managers have no skill. This makes about as much sense to me as asking if the people who ran the fastest first mile in a marathon are the same people who ran the best second mile. Who cares! As great investor Seth Klarman1 said, “…If someone asked me to invest their money with the goal of turning a quick profit over the next six or twelve months, I’d have no idea how…You might as well go to a casino…” Or, in Charlie Munger’s words, “In investment management today, everybody wants not only to win, but to have a yearly outcome path that never diverges very much from a standard path except on the upside. Well, that is a very artificial, crazy construct.” I have never, ever, read from one of the greats of investing that their goal was to maximize returns over a twelve month period. In fact, if you understand how much randomness dominates the short-term, shooting to maximize returns over periods as short as twelve months is, to me, a tell tail sign of being a novice investor. Active management’s advantages and drawbacks are largely the opposite of indexing. Its advantages are a potential for outperformance and the ability to shun absurdly popular and overvalued companies. Meanwhile, the disadvantages include higher cost, higher taxes, less transparency and the potential for underperformance. While investing in bonds and equities is a “positive-sum game” (you are participating in the economic growth of the world), active management is a “negative-sum game.” All active investors are investing in the same pool (the global securities market), and therefore, if you are overweight a stock, somebody, somewhere, has to underweight it. Globally, the performance of all active managers has to be the market return minus their extra fees. Of course, the key question with active management is: can I pick managers that are above average enough to make up for their extra fees? I believe that with the right framework, you can. The Biggest Problem While how to pick an active manager is beyond the scope of this paper ( see our Insights Paper, “The Art of Manager Selection ” )there is enough industry and academic research to support the idea that by using some commonsensical filters, you can fish for an active manager in a pond where the odds of outperformance are tilted in your favor. Consider a study from Capital Group1, which looked at manager performance between 1994 and 2014, filtering active managers using two simple criteria: low cost and that the portfolio manager was personally invested in the fund they were managing. The results were dramatic: 100% of domestic managers and 90% of international managers outperformed their benchmark over a 10-year period. Unfortunately, picking an active manager that performed over the long-term is not the critical problem. The biggest problem in this debate, and for investing in general, is that investors use recent returns as validation of whether something “worked.” Take two visceral examples: •The Fidelity® Magellan® Fund was run by investment legend Peter Lynch, who delivered an astonishing 29% average annual return between 1977 and 1990. But Fidelity found that the average Magellan investor actually lost money!2 •The last decade’s best performing U.S. diversified stock mutual fund (ending December 29, 2009) was the CGM Focus Fund, which had an average annual total return of 18.2%. The average investor’s return in that same fund over the same time period was -11%, a 29% under-performance!3 How is it possible that investors in both cases underperformed the very fund they were using by 29%? Performance chasing. Investors bought these managers after a hot streak and sold them off once they had a period of poor performance. A perceptive reader will notice that what you’re doing, in effect, is selling the manager low and buying them high-not exactly a winning strategy. As these statistics reveal, the biggest problem investors face is jumping strategies mid-stream due to emotion. When an investor sees their recently brilliant fund manager start to lag the market and even lose money, fear of loss can quickly lead to unthoughtful decision making. Smart managers can look dumb for a long time. Index investors suffer from similar emotional biases. Indexes, by definition, experience 100% of the downside of what they are indexing. How many people abandoned their S&P 500 index fund late in the financial crisis? Too many. Lessons in Discipline Every active portfolio manager underperforms; the key question is, “why are they underperforming?” There are good and bad reasons to underperform. Probably the best reason to underperform is that a portfolio manager is sticking to disciplined, fundamentally based investing in the middle of a bubble. Let’s take a look at some of America’s best managers in the biggest U.S. stock market bubble of all: the late 90s technology bubble. Here are some charts from Frederik Vanhaverbeke (the author of Excess Returns). What’s interesting to note is that among this collection of great investors, not one kept up with the tech-heavy Nasdaq and only one, Warren Buffett, kept up with the less tech-heavy S&P 500. Did all these legendary managers get stupid at the same time? Or is it that they knew that chasing a technology bubble, which has happened many times in history and where the only hope of success is timing when to get out, was highly imprudent. When you chart out the Nasdaq’s ~80% drawdown, it’s clear this stable of portfolio managers were simply being disciplined tortoises in an era of technology hares. This brings me to a seldom discussed attribute of disciplined investing. When the market is losing its head in a bubbilicious wave of optimism, it is a badge of honor to underperform. It is this very discipline that causes short-term underperformance (as long as the bubble is raging) to capture long-term performance (once the bubble bursts.) This is why it’s so important to judge managers over a full investment cycle – a bull and a bear market. Often, the hot portfolio managers of the day are hot because they are being reckless and their gains are temporary illusions. This is further complicated by people’s emotional timeframes. Many investors judge their portfolio managers’ performance across a 2-to-3-year period. For an underperforming manager, a typical scenario goes like this: Year 1: Investors are disappointed/irritated Year 2: Investors are mad Year 3: Investors fire the portfolio manager Therefore, there is a big mismatch between people’s emotional timeframes and an investment era’s timeframe, which can last as long as 6 to 9 years. The problem with this myopic view is that active managers will underperform consistently in certain eras. For example, consider a chart of some of the world’s best managers’ underperformance streaks (chart again from Mr. Vanhaverbeke): What is striking (and remember that this is a cluster of the very best in the business) is how long some of their droughts last. For example, from 1980 to 2004, Lou Simpson, who managed GEICO’s portfolio for Warren Buffett, “produced an average annual gain of 20.3%, compared to 13.5% for the S&P 500. In that time, he had only three negative years, and only four years of less than double-digit returns.”4 Yet, he had an entire 10-year period where he underperformed his benchmark (probably the decade ending in 1999.) In fact, most of these legends had 5-to-6-year droughts in performance. Thus, if you use shorter term performance as a primary factor in hiring a manager, you are almost sure to sell them at the wrong time. Taking the Long View A more appropriate framework to judge active managers is to think of the market in phases or eras. If the current environment is an era of low caution and bubbly valuations and you have a disciplined value investor in your stable of portfolio managers, a year-by-year assessment of performance is useless. You know there is a high likelihood the manager is going to underperform as long as the speculative trend continues. One comforting fact is that you can be 100% sure an era will end. In the financial markets, change is arguably the only certainty. Understanding the current era relative to a portfolio manager’s strategy is essential to giving you the patience and confidence to hold onto them. Ever wonder what financial professionals mean when they say they are “long-term investors?” We mean wait until the next era, judge an active manager not only on what is going on today but also on how they perform once the markets transition to the next era. As noted, by certain metrics, May 2015 was the second highest valuation of all time for the U.S. stock market. Indexing is much more attractive when the index you are investing in is reasonably valued or cheap. When indexes are reasonably valued, it allows you to “sail” with the index as opposed to using active management to “row” by identifying better than average stocks within the index. Unfortunately, flows into index funds have been enormous late in this bull market. As you can see from the chart below, investors have been selling their active managers in droves to go buy index funds. Click to enlarge While I have no biases against indexing for the long-term (given that you know what you’re getting and that you’ll be disciplined about it), the timing of this tidal wave of assets to indexing looks like pure performance chasing to me. People are likely to have a rude awakening when their index fund experiences 100% of the downside of the next bear market. Then you’re likely to see news headlines like “active managers are back!” and “index funds are dangerous!” Click to enlarge As the chart above shows, passive versus active management itself goes through eras. The popularity weighted indexes enjoy good times as the popular stocks of the day get even more popular during a bull market, and then they suffer tremendous losses when a bear market comes along and hits the most popular (expensive) stocks the hardest. The firm G.M.O. put out a great paper this year predicting active managers over and underperformance relative to their index.5 The punchline was simple yet eye opening. Most funds are not pure to their index. A fund benchmarked to the S&P 500 for example will usually own some cash, some non-S&P 500 stocks and even a few international stocks. While this extra diversification hurts if the fund’s main benchmark is the highest performing index of an era, it also softens the blow on the way down. Unless, of course, an investor sold their fund in the interim for an S&P 500 index fund. An Antidote to the Dilemma If you are going to jump into using active management, there is only one way to ensure you do not sell your active managers at the wrong times, and that is by doing enough research to acquire a deep understanding of the manager’s portfolio strategy and investment thesis and continually updating your assessment of that manager through qualitative reasoning. This is why Warren Buffett, even though wildly successful with active management, recommends most people index. He knows that for most people, investing is simply not a big enough part of their lives to do the necessary research. This is also the key to knowing when to fire a manager. You fire them when the reasoning no longer appeals to you, when the strategy shifts in a direction of which you don’t approve, when their “why” no longer inspires confidence. Although admittedly tough to do, this process should be independent of recent returns. Given this insight and analysis, here are some definitive answers for investors when it comes to active versus passive management: •Due to the cyclicality of performance, if you’re using recent returns (3-5 years) as the primary determinant of when to hire and fire an active manager, you have very little hope of success. •If you’re not willing to put the work in to understand and follow your active managers, use index funds. •By extension, if you use a financial advisor, and they can’t explain the “why” of the performance in their funds, they should be indexing. •If you decide to index, don’t use recent returns to validate or discredit your approach. Indexes will have long periods of both great and awful performance; you just have to know that going in. •If you’re going to use active management, you must first develop a belief system and then seek portfolio managers that use a similar belief system. When they underperform, you’re much more likely to stick with them. •Ideally, you want a manager who has a strategy that you 100% buy into, who has a wonderful long-term track record but who has underperformed recently for identifiable reasons. •Nobody can outperform all the time, but with a disciplined process, we believe it’s possible to find active managers that outperform over time. •While investing using active management holds the potential for outperformance, it takes a lot of work, patience and discipline to have any hope of using active management effectively. Calibrate your expectations accordingly.

The Confounding Bias For Investment Complexity

“Simplicity is a great virtue but it requires hard work to achieve it and education to appreciate it. And to make matters worse: complexity sells better.” – Edsger W. Dijkstra 1 Our tenure in the investment business has made us keenly aware of a profound investor bias toward complexity. In this article, we examine the reasons for the bias, which we believe are behavioral in nature. One reason is the rationalization by asset managers that to charge higher fees requires offering more complex strategies. A similar line of reasoning may also influence those who recommend managers: consultants and advisors. A second reason for the bias is the rationalization by investors that a complicated strategy is necessary to beat the market. Each explanation has implications-biased toward the negative-for an investor’s long-term performance. Complexity Can Confound Performance In contrast to the overwhelming pressure from all sides in advancing complexity, our experience, as well as our research and that of others, supports the virtues of a simple approach. For example, in 2009, DeMiguel, Garlappi, and Uppal demonstrated that numerically optimized portfolios using various expected return models generally perform no better than a simple equal-weighted approach. An example of our research in this area, the article “A Survey of Alternative Equity Index Strategies” by Chow et al. (2011), is an analysis of the most popular smart beta strategies. We found that simple, low-turnover and complex, high-turnover strategies all work roughly the same on a gross-of-fee basis, suggesting on a net-of-fee basis the simple, low-turnover strategies might have an advantage. Looking beyond the story telling that characterizes various investment philosophies, the long-term return drivers of many complex smart beta strategies are tilts toward well-known factor/style exposures, such as value, size, and low volatility. Each exposure is a natural outcome of breaking the link between portfolio weighting and price, and of the requisite rebalancing. Indeed, little data or research supports one “best” way to construct an exposure (e.g., value or low volatility) that maximizes the factor premium capture. Complex constructions in the historical backtest appear to mostly guarantee higher turnover, higher management fees, and potentially worse out-of-sample returns. So, if complexity doesn’t naturally lead to outperformance, why do asset managers persist in offering increasingly complicated strategies to investors, and why do investors persist on investing in them? Allow John to tell an illustrative parable. John’s Fish Tale The oceans in which fish hide from fisherman are amazingly complex ecosystems. The circumstances leading to a successful day (or not) on the water are almost innumerable. The fish obviously have to be at the fishing spot. But that’s probably less than half the battle. A veritable mosaic of tides, currents, sunlight, moonlight the night before, available prey, time of day, tackle, and so on, influence the catch. With such a myriad of factors, it’s no small wonder that tens of thousands of fishing products jam their way into even the smallest of tackle shops. But, as an avid deep sea angler, I can attest to catching twice as many tuna with the simplest of lures than all of the rest combined. The lure? The innocuous-looking cedar plug pictured in Exhibit A . Simple? Yes! For crying out loud, it’s a piece of lead attached to an unpainted piece of wood with one lousy hook! It looks like an industrial part. Sexy and complex? Most certainly not. Imagine you get the itch to catch some tuna. Perhaps it’s your first foray into tuna fishing so you decide to delegate the task to an expert charter boat captain. But which one? You stroll along the dock and ask each captain how they catch tuna. The first presents a cedar plug, just like the one in Exhibit A, and tells you, “I go out to where I see signs of fish and then I drag four of these lures behind the boat at a steady speed until I catch some. Then I keep doing it until it’s time to head in.” The second captain displays a dozen tackle drawers filled with lures resembling those shown in Exhibit B and proclaims, “Tuna are very elusive. I have perfected a system over many years that optimizes my lure selection among 60 lures, five sunlight conditions, seven moon phases, and six different tidal stages. I troll, adjusting my speed in five-minute intervals, based again on very extensive testing.” You hate long boat rides, but are starving for fresh sashimi. Which captain would you choose? Most sashimi lovers would pick the second captain. The ocean is big, and multiple factors influence the tuna catch. It seems like the higher-calibrated approach would be the way to go. But I can tell you (admittedly anecdotally, as I’m still waiting for Research Affiliates to approve my request for a more exhaustive scientific survey!) that it would probably yield a lower catch. Investors’ Preference for Complexity Complexity likewise appeals to investors because the markets that drive securities prices, like the teeming and mysterious ocean, are deep and complex. It only stands to reason (right?) that a sophisticated strategy is a requirement for mastering and benefiting from the intricate web of financial markets and asset classes. The globally integrated investment markets and economies are anything but simple, so it would not at first appear that a simple strategy could carry the day. The belief that simple relationships exist is absolutely counterintuitive to most casual-and sometimes, not so casual-market observers. Persuading an investor that a complicated strategy-often derived through data mining (i.e., back testing historical data until it produces what can be viewed as a signal)-is unlikely to perform as expected, can be a real challenge. The air of scientific authority exuded by PhDs who scribble differential calculus equations as fast as Charles Schultz drew Peanuts comic strips gives just that much more “credibility” to black box approaches. And agents compound the issue. Advisors or consultants hired to help investors make sense of the noise in the market and to find the skilled managers are also incented by the complex. Charging a respectable fee for a manager selection process that puts the client into a simple, straightforward strategy is not so easily justified to the client. The very natural, economic, and rational response to this conundrum is to recommend (in the case of advisors) or to offer (in the case of managers) the more complex strategies. Asset managers certainly find it easier to charge a higher fee for a complex strategy (i.e., flashier lures with molded plastic and psychedelic paints) than for a simple strategy (i.e., unpainted cedar plugs). Simplicity vs. Complexity: Why Does It Matter? The point we wish to make is not that simple strategies always perform on par or better than the complex ones. Our point is that complexity creates a problem for investors, which is unfortunately largely self-induced: complexity encourages performance chasing. We can better understand why this is true if we apply Daniel Kahneman’s construct of System 1 and System 2 thinking, as described in his book Thinking, Fast and Slow (2011). System 1 thinking is described as automatic, emotional, and passive, whereas System 2 thinking is effortful, deliberate, and active. When presented with a complicated investment strategy, an investor engages first in System 1 thinking, which triggers an immediate response such as “I don’t understand the strategy. Clearly I’m not as smart as this asset manager.” System 2 thinking then takes over, and the investor’s response transitions to “Because this asset manager is so smart, her strategy must outperform. I think I’d like to invest with this asset manager.” The investor then feels safe and comfortable in making a rational delegation decision. At the end of the day, the acceptance of complexity is related to calming the investor’s ego-at least, temporarily. This thinking works in reverse, however, if the asset manager fails to perform as expected. Neuroscientists, such as Knutson and Peterson (2004), have demonstrated that the anticipation of receiving money triggers a dopamine reward in the brain. Conversely, the anticipation of losing money removes that pleasurable experience. When this happens, the System 1 response is “Yikes! I need to fire this manager so I can stop feeling so bad.” Then the System 2 response kicks in with the rationalization, “I didn’t make the decisions that created the underperformance, so I’m not to blame.” Because the investor doesn’t “own” making the “bad” decisions, it is easier to end the relationship. Following this line of thinking, investors are liable to sell a complicated, poorly understood strategy with little provocation as soon as performance takes a nose dive. The long-term result is apt to be especially disappointing performance if the investor becomes ensnared in a whipsaw pattern of buying and selling at all the wrong times. Our research (Hsu, Myers, and Whitby [2015]) shows that the frequent hiring and firing of managers based on short-term performance is the primary cause of investor underperformance. Our findings are valid even when investors hire skilled managers. Although never a good idea for investors to make buy and sell decisions based on short-term performance, a poorly understood strategy can compound the harm. An example of how Kahneman’s System 1 and 2 thinking supports an investor’s choice of a simple behavioral factor strategy, let’s consider the following scenario. Upon first encountering the strategy, the investor’s System 1 thinking blurts, “This strategy is intuitive to me. I am a smart investment professional. This will work.” But soon his System 2 thinking chimes in, “I don’t need to pay a high fee for this. I just need a low-cost implementer of systematic strategies to execute on my chosen factor.” When the strategy fails to perform as expected, the investor’s System 1 reaction is, “I am not wrong. The market is wrong.” Then his System 2 thinking kicks in, reasoning, “I vetted the research behind this factor carefully. Short-term performance is noisy. This exposure will work well in the long run.” The investor chooses to hold his strategy. Investors in simple strategies generally trade in and out of their managers infrequently. Our research finds that these investors tend to achieve meaningfully better results versus their counterparts who actively turn over managers due to recent performance. Simplicity leads to better investor outcomes not because simplicity in and of itself produces better investment returns, but because a simple strategy forces investors to own their decisions and to be less likely to overreact to short-term noise. A Simple Choice We believe that making investors aware of the benefits of selecting a simple approach, strategy, or model is important. Unnecessary complexity is costly, not only directly (i.e., fees), but indirectly. Complexity can dampen investor understanding, which can lead to poor investment decision making so that an investor’s long-term financial goals are not achieved. As Steve Jobs said, “Some people think design means how it looks. But of course, if you dig deeper, it’s really how it works” (Wolf, 1996). If a simple design works, ample evidence suggests that the investor benefits by choosing simplicity. Endnote 1. Edsger W. Dijkstra was a Dutch computer scientist and winner of the Turing Prize in 1972 for fundamental contributions to developing programming languages. References Chow, Tzee Mann, Jason Hsu, Vitali Kalesnik, and Bryce Little. 2011. ” A Survey of Alternative Equity Index Strategies .” Financial Analysts Journal , vol. 67, no. 5 (September/October):37-57. DeMiguel, Victor, Lorenzo Garlappi, and Raman Uppal. 2009. “Optimal Versus Naïve Diversification: How Inefficient Is the 1/N Portfolio Strategy?” Review of Financial Studies , vol. 22, no. 5 (May):1915-1953. Hsu, Jason, Brett Myers, and Brian Whitby. Forthcoming 2016. ” Timing Poorly: A Guide to Generating Poor Returns While Investing in Successful Strategies .” Journal of Portfolio Management , vol. 42, no. 2 (Winter). Kahneman, Daniel. 2011. Thinking, Fast and Slow . New York: Farrar, Straus and Giroux. Knutson, Brian, and Richard Peterson. 2005. “Neurally Reconstructing Expected Utility.” Games and Economic Behavior , vol. 52, no. 2 (August):305-315. Wolf, Gary. 1996. ” Steve Jobs: The Next Insanely Great Thing .” Wired Magazine (February)

Middle East Stocks Crash On Iran Sanctions: ETFs To Watch

After China and oil issues, developments in the Middle East are posing further hindrance to the stock market that may worsen the global rout this week. This is especially true following the historic deal between Iran and the world major powers that lifted oil sanctions imposed on the former in late 2000. The relaxation would add a fresh stock of oil to the already oversupplied global market as Iran is expected to increase its crude oil exports by half a million barrels a day immediately and a million barrels a day within a year of lifting the ban. Notably, Iran is the world’s fourth-largest reserve holder of oil with 158 billion barrels of crude oil, according to the Oil & Gas Journal . The country also accounts for almost 10% of the world’s crude oil reserves and 13% of reserves held by the Organization of the Petroleum Exporting Countries (OPEC). The liftoff spread panic in the Middle East and crashed all the seven Gulf stock markets. In fact, the stocks saw a bloodbath wiping out more than £27 billion from the Middle East markets in Sunday’s trading session (read: Guide to Middle East ETF Investing ). The Bloomberg GCC 200 Index, which tracks 200 of the six-nation Gulf Cooperation Council’s biggest companies, plunged to the lowest level in almost seven years. Saudi Arabian stocks fell 5.4%, Kuwait and Qatar stock exchanges experienced 3.1% and 4.6% drop, respectively, while stocks in Qatar saw an enormous 7% decline on the day. ETFs to Watch The terrible trading in the Gulf stocks will have a big impact in the ETF world as well. In particular, the Market Vectors Gulf States Index ETF (NYSEARCA: MES ) , the WisdomTree Middle East Dividend Fund (NASDAQ: GULF ) , the iShares MSCI Qatar Capped ETF (NASDAQ: QAT ) and the iShares MSCI UAE Capped ETF (NASDAQ: UAE ) should be on investor’s watch list of the funds that are likely to be badly hurt by the Iran sanctions liftoff. From a year-to-date look, these funds shed 13.7%, 10.2%, 13.4% and 9.2%, respectively. MES: The fund provides exposure to 60 stocks that generate at least 50% of their revenues in the Gulf Cooperation Council (GCC) region by tracking the Market Vectors GDP GCC Index. About one-third portfolio is allotted to firms in United Arab Emirates, followed by Qatar (25.9%) and Kuwait (19.3%). The product is often overlooked by investors as depicted by its AUM of $8 million and average daily volume of about 3,000 shares. The fund charges a higher annual fee of 99 bps from investors. GULF: This ETF follows the WisdomTree Middle East Dividend Index, which measures the performance of dividend-paying companies in the Middle East. It holds a basket of 70 stocks with the largest exposure of at least 23% to firms in Qatar, Kuwait and United Arab Emirates. The fund has amassed $22.8 million in its asset base while trades in paltry volume of 9,000 shares a day. Expense ratio comes in at 0.88% (see: all the Africa-Middle East Equity ETFs ). QAT: This fund provides exposure to 29 Qatari stocks by tracking the MSCI All Qatar Capped Index. It has accumulated $40.5 million in its asset base while see volume of 7,000 shares a day on average. QAT charges 64 bps in fees per year. UAE: This ETF targets the United Arab Emirates stock market and follows the MSCI All UAE Capped Index. Holding 33 stocks in its basket, it has been able to manage $23.6 million in AUM so far and charges 64 bps in annual fees. Volume is light at around 10,000 shares a day on average. What Lies Ahead? Oil price, which contributes more than 80% of the Middle East revenues, has fallen 20% this year and over 70% since late 2014. This trend will likely persist in the months ahead given unfavorable demand/supply dynamics. In fact, a number of investment banks are projecting oil price to drop as low as $10 per barrel, the lowest since 1998. This is because oil production has risen worldwide with OPEC continuing to pump near-record levels, and higher output from the likes of U.S., Iran and Libya. Additionally, a strengthening U.S. dollar backed by a rate hike is making dollar-denominated assets more expensive for foreign investors and thus dampening the appeal for oil. 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, the four products detailed above have a bottom Zacks Rank of ‘4’ (Sell) or ‘5’ (Strong Sell), suggesting that these will continue to underperform in the months ahead. All these suggest that investors should avoid investing in the Middle East until and unless oil prices stabilize or rebound. Link to the original post on Zacks.com