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RPV Is A Strong ETF For Exposure To The Value Portion Of SPY

Summary The performance of the ETF has been fairly solid. The standard deviation gives it some risk, but not too much. The holdings of the ETF are at least adequately diversified and I like the positions. The decent liquidity doesn’t hurt when investors want to rebalance their portfolios. The Guggenheim S&P 500® Pure Value ETF (NYSEARCA: RPV ) has surprised me. With a higher turnover ratio and expense ratio, the fund has thoroughly outperformed SPY since inception. During the time frame I used for my regression, RPV was up 119% relative to the SPDR S&P 500 Trust ETF (NYSEARCA: SPY ) being up 96%. Impressive work and great for the people that decided to buy into it when the ETF started. What does RPV do? RPV attempts to track the investment results of S&P 500 Pure Value Index. The ETF falls under the category of “Large Value” presently, but was classified under “Mid-Cap Value” previously. The category may be prone to change as the ETF has a 25% portfolio turnover. Does RPV provide diversification benefits to a portfolio? Each investor may hold a different portfolio, but I use SPY as the basis for my analysis. I believe SPY, or another large cap U.S. fund with similar properties, represents the reasonable first step for many investors designing an ETF portfolio. Therefore, I start my diversification analysis by seeing how it works with SPY. The correlation is about 88.86%, which is low enough to allow more diversification benefits than I would expect in a fund referencing the S&P 500. Standard deviation of monthly returns (dividend adjusted, measured since March, 2006) The standard deviation is terrible. If investors want to ensure that they are keeping volatility out of their portfolio, this won’t be the ETF. That’s a little ironic to me because over long sample periods I wouldn’t expect a value ETF to show so much more volatility than SPY. For the period I’ve chosen, the standard deviation of monthly returns was 7.021%. For SPY, it was 4.416% over the same period. Mixing it with SPY I also run comparison on the standard deviation of monthly returns for the portfolio assuming that the portfolio is combined with the S&P 500. For research, I assume monthly rebalancing because it dramatically simplifies the math. With a 50/50 weighting in a portfolio holding only SPY and RPV, the standard deviation of monthly returns across the entire portfolio is 5.566%. If the position in SPY is raised to 80% while RPV is used at 20% the standard deviation of monthly returns drops down to 4.824%. In practice, I think the best way to use RPV is a position smaller than 20% and used in a diversified portfolio. The moderate correlation makes a strong case for using RPV in a small position so the volatility has less impact on the overall portfolio. At 5%, the standard deviation of the portfolio would have been 4.510%. Compared to SPY at 4.416%, this is a fairly low increase in the risk level measured by the standard deviation. Why I use standard deviation of monthly returns I don’t believe historical returns have predictive power for future returns, but I do believe historical values for standard deviations of returns relative to other ETFs have some predictive power on future risks and correlations. Yield & Taxes The distribution yield is 1.98%. It’s a little on the low side for the value focus, but not too low if it is only being considered for a portion of the portfolio. Due to the higher volatility of returns on this “value” ETF, I really appreciate seeing a higher distribution yield. The major risk, in my opinion, is that investors tend to withdraw their money at the worst possible times. Expense Ratio The expense ratios are both running .35%. It isn’t too bad and seems to be the standard for Guggenheim ETFs. I’d prefer lower, but this is still within reason. Market to NAV The ETF is trading at a .06% discount to NAV currently. I think any ETF is significantly less attractive when it trades above NAV and more attractive below NAV. A .06% discount is not enough to matter though. Investors should check prior to placing an order, but the liquidity in RPV should be a great hedge against any meaningful premiums or discounts. Lately there have been more than 120,000 shares trading hands each day. With each share over $50, the resulting liquidity is enough that I would have no concerns. Largest Holdings The diversification is pretty good. I see nothing to complain about here. (click to enlarge) Conclusion RPV delivers a strong showing in my initial assessment. The liquidity is excellent and the correlation is about what I would expect for the ETF having a focus on the S&P 500 index. The performance was fairly solid over the test period in every regard. The biggest weakness would have to be the volatility of returns, but that sure won’t stop the ETF from reaching the next stage. The Guggenheim S&P 500 Pure Growth ETF (NYSEARCA: RPG ) tracks the other side of the index, having a focus on growth stocks. The interesting thing is over the last five years both RPV and RPG significantly outperformed SPY. If we limit the comparison to the last 5 years, SPY was up 111.5%, RPG was up 148.2% and RPV was up 134%. When I looked up the ETF they were holding 119 of the constituents of the S&P 500. Frequently the contenders for the value exposure in my portfolio will have fairly strong dividend yields. The yield on RPV isn’t that strong, but that seems like a fairly minor issue for me since I don’t anticipate any withdrawals from the portfolio for a long time. Within the 119 companies, the diversification isn’t bad. Only one holding was over 2.02% and I can’t complain about the selections. All around, I feel like this is a fairly solid group of companies the ETF is holding. The expense ratio is not too bad, cheaper than most though a certainly higher than my goals. I’m certainly willing to deal with that if the ETF fits nicely into my overall portfolio. Disclosure: I/we have no positions in any stocks mentioned, and no plans to initiate any positions within the next 72 hours. (More…) I wrote this article myself, and it expresses my own opinions. I am not receiving compensation for it (other than from Seeking Alpha). I have no business relationship with any company whose stock is mentioned in this article. Additional disclosure: 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.

But Why? VXX And XIV Are Already Just Perfect

Summary High Contango Is Not a Reflection of Free Market Failure. High Contango Is Your Best Investment Friend. 2011 AAA Downgrade of US Treasuries Lead to The Low Volatility Regime of the S&P 500. VXX/XIV disproving efficient markets. How can a product go up or down EVERY year?! Contango should narrow if efficient market. A couple of days ago I received this tweet from one of my followers on Twitter. While the question is very valid, it belies a common misunderstanding about the two biggest vehicles used to trade volatility – The iPath S&P 500 VIX Short-Term Futures ETN (NYSEARCA: VXX ) and the VelocityShares Daily Inverse VIX Short-Term ETN (NASDAQ: XIV ). In this article, I will try to shed light on the inner workings of VXX and XIV and explain why their behavior has nothing to do with market efficiency and some to do with official government policy and even more to do with the AAA downgrade episode. The Search for the Perfect Trading Vehicle for Volatility VXX has about $800 million in AUM with $950 million trading daily. VXX was launched in January 30th, 2009. It has now been around 6+ years. XIV has about $850 million AUM. The XIV arrived on November 30th, 2010 and has been around for nearly 5 years. XIV and VXX are exact opposites of each other with the VXX going up a certain amount when the VIX goes up that day and XIV going down a similar amount. However, it is important to realize that VXX and XIV do not track the VIX exactly. What they track will be discussed further down. There exists this unfulfilled desire amongst traders of the S&P 500 index and related option and futures instruments to have the perfect hedging vehicle that will eliminate all the risk from their trading endeavors. I mean who doesn’t want that? Buy the VIX at the top of the market, may be put 5% into spot VIX vehicle. Market goes down 5%, VIX goes up 60-70%, no money, no love lost. You get to keep your clients and your money with minimal work. When things go up, make money. When things go down, stay the same. Never lose money, always in the money. Live happily ever after. Unfortunately in the real world, risk exists and risk is forever. There is always a Damoclean sword hanging over your investments. Things can go bad at any moment and no amount of financial trickery and innovation will get you rid of that. The best you can do is replace one risk with another less likely risk. There never will be a trading vehicle that exactly matches the spot VIX index at its sub-second calculation interval. We should never forget that the CBOE VIX is a calculation. It is not an asset like a stock or a bond that has buyers and sellers. It is a calculation that tracks something. It is an absolute technological miracle that it can be calculated in close to real-time as it is. It is an insurmountable logistical challenge to have an intra-day futures market that efficiently settles pricing of daily futures on a second or even minute basis. Once you have that intra-day VIX futures market you can power an ETF that will precisely match the VIX. But even having a daily futures market is close to a physical impossibility. You not only need the technical power to do it (which is astounding). You also need the depth of market, wide ranging liquidity and sufficient participation to enable proper pricing. May be that will become a reality in the future, but at present it isn’t. I see some feeble attempts at it, but I don’t see the true effort that is going to make this a reality. Maybe nobody (except some VIX purists) cares. Why? The VXX and XIV are Already Just Perfect Like all original designs, XIV and VXX are very close to achieving ultimate perfection in the goal they set out to achieve – which is provide a vehicle to trade the VIX. The closest you can get to matching spot VIX in reality is by having a futures market where buyers and sellers get to haggle on what the price of the VIX should be. There is one caveat however. There is no way to haggle about the price of the VIX right now because it is a calculation. You already know mathematically what it is. You also know what it was in the past. What you don’t know is how much it will be in the future. That is where the futures market comes in and buyers and sellers can say – hey I think the VIX is going to be this amount in the future. The buyer puts in a bid, the seller puts in an ask and the haggling goes on happily ever after. So if you want to trade the VIX, your best bet is trading the front month future (which I will call VIX1 henceforth). And a lot of professional traders do just that. But the futures markets are not for the faint of heart. A position is $30,000. You need a special account and approval. Access to futures market is generally only available for professional traders or very sophisticated retail investors. The retail investor population is essentially priced out or qualified out of them. But even if you are pro, the VIX is a very volatile animal and you can lose your shirt rather quickly in the futures market especially as the VIX1 future nears it expiration and then must match the VIX more and more. On settlement day VIX1 is always equal to the VIX. But the VIX can go up or down 20% in one day. In the futures market that means bankruptcy. No ETF maker will undertake this kind of risk. They will be out of business on the first VIX spikage. So they have to devise something that is a little less volatile. Enter VIX2 future. The VIX2 future is a little farther in the future and is not so tied into the present day VIX value. So you would buy the VIX2 future and hedge that by selling the VIX1 future. Ok, now we are getting somewhere. This looks like it could be the makings of an ETF that is a little less volatile and won’t make the issuer bankrupt, but at the same does a serviceable job of giving us an instrument tied to the VIX. May be not a 100% match of the VIX, but a match of 50% is better than nothing (remember, prior to 2009, there was absolutely nothing). Well, this is exactly what VXX does! The VXX buys VIX2 futures and sells VIX1 futures on a daily basis. The closer we are to VIX1 expiration, the smaller the amount of VIX1 futures and the larger the amount of VIX2 futures that are traded. The amount is proportional to the time to expiration. The allocation weight inside the VXX/XIV of VIX1 futures is T1/(T1+T2) and for VIX2 futures it is T2/(T1+T2). The daily weights of the VXX and XIV can be found here (TradingVolatility.net -> Data -> VIX Futures page): The XIV does exactly the same, except for it shorts VIX2 and covers VIX1 daily. And this way, the two ETNs try to approximate the VIX, which I think is still the best way to do accomplish this task baring the emergence of daily VIX Futures market. The Importance of Contango Now that we understand how VXX/XIV work, it isn’t unreasonable to come to the conclusion that the price spread between the VIX1 and VIX2 futures is of particular importance. After all these are your buy /sell prices or short/cover prices. So is there anything to know about the VIX1 and VIX2 pricing spread? Well, there sure is! The price spread between VIX1 and VIX2 is called Contango . Mathematically, Contango = (VIX2/VIX1) – 1 and is measured with a percentage. Before we continue on the topic of Contango, let’s take a broader look of the VIX Futures Curve. (click to enlarge) Source: vixcentral.com The futures curve depicted above is the usual distribution of futures prices in the VIX futures market. The VIX index was designed to be mean reverting so by definition any time the VIX trades at levels below the historical average (which is roughly 20), the market anticipates that the VIX will rise in the future to reach that historical average. In fact, if there was an infinite VIX future, it’s value will be the historical average of 19.46. The condition when second month VIX future (VIX2) is higher than the front-month VIX future (VIX1) is called Contango . So when the VIX Futures Curve is in the above formation, it is considered to be in Contango formation. When the situation is reversed and VIX2 is smaller than VIX1, then the VIX Futures Curve is usually in the below formation which is called Backwardation . (click to enlarge) Source: vixcentral.com Wait a second? Why should the VIX futures try to reach its long term average? The answer can be found on the VIX Primer page on CFE VIX Futures site where they explain how to calculate the Fair Value of a VIX Future. I am going to shamelessly reprint their content here: Fair Value of VIX Futures Futures traders are most familiar with the fair value of stock index futures derived from the cost-of carry relationship between the futures and the underlying stock index. Since there is no carry between VIX and a position in VIX futures, the fair value of VIX futures cannot be derived by a similar relationship. Instead the fair value is derived by pricing the forward 30-day variance which underlies the settlement price of VIX futures. The fair value of VIX futures is the square root of this expected variance less an adjustment factor which reflects the concavity of the square root function used to extract volatility from variance. In percentage points, the fair value of VIX futures is: In this expression, Pt is the forward price of de-annualized variance in the 30 days after the futures expiration, and -vart[FT] is the concavity adjustment. The adjustment subtracts the variance of the futures price at expiration, which can also be expressed as the cumulative daily variance of VIX futures from the current date to expiration. Using methods similar to those on which the calculation of VIX is based, the forward price of the 30-day variance can be determined from a synthetic calendar spread of S&P 500 options bracketing the 30 days after the futures expiration. The variance of the futures price can be estimated from historical data on the daily variance of VIX futures. I don’t want to go into deep mathematical analysis here, the end result of that calculation is that a VIX Future contract over the long term tries to reach the average spot VIX value. The farther out in time the future, the closer the fair value will be to the average historical VIX value. The delta between the future price approximation and the average value goes exponentially closer to zero. The flipside of that calculation is that the nearest term VIX future has the largest difference to the long-term average, the second term VIX Future – the second largest difference, the third term VIX Future – the third largest difference, etc. The exponential decline in the delta can be plainly seen in the usual VIX Future Curve formation depicted above (Contango formation). So as a result, you can kind of guess that Contango is usually some healthy percentage not exactly close to 0%. In fact, the VIX spends most of its time declining from elevated levels. While the average VIX is around 20, the VIX has spent 60% of the time below 20 since its inception in 1990. Since the bull market start in 2009 and the beginning of active Central Bank suppression of volatility that percentage is even higher at 65%. Since 2012 once the AAA downgrade episode passed and QE Infinity was announced, the VIX has spent a remarkable 92% of the time below 20! Since the inception of the VIX Futures in 2004, the average Contango between VIX1 and VIX2 has been 5.6%. Since onset of QE Infinity in 2012, Contango has averaged 7.2% High Contango is NOT a Reflection of Free Market Failure Financial markets are very efficient and well priced. In this age of High Frequency Trading, the bid-ask spread is almost zero for most instruments. There is plenty of liquidity out there. A buyer will always find a seller at a price readily quoted in real time. Yes, there have been technical glitches and blowups but technology can and will be fixed over time. However, the markets are also very, very manipulated. Central Banks have the power of the printing press and can overwhelm financial markets with the liquidity available to them. It is critical to understand that it is a core mandate of the Central Banks to suppress volatility . After all, “stable prices” is mandate #2 of the Federal Reserve. The Central Banks do not want the S&P 500 index to go down 50%. In fact, they don’t want it to go down 10%. They want the index to go up or trade in a small range at worst, regardless of fundamental valuation. Stock market panics and large drawdowns have had large spillover effects on the broader economy and in 2000 and 2008 brought about recessions. The FED and other Central Banks want to avoid a repeat of those episodes and as such deploy rarely announced techniques to suppress volatility and honest price discovery. The Bank of Japan, for example, buys stock futures in the open market. Central Banks of other smaller countries also purchase stock futures. In fact, the Chicago Mercantile Exchange (NASDAQ: CME ) has a Central Bank Incentive Program where non-US Central Banks can buy S&P 500 E-mini Equity Index Futures and Options at a discount. Whether that is right or wrong is above my pay grade, the point is that it is happening. However, as much we want to blame the FED for everything, it ultimately is not the FED’s fault that markets have risen non-stop since 2012 with very little volatility. The AAA downgrade episode in 2012 marked a fundamental change in what is perceived as a risk free asset. Prior to 2012, US government treasuries were the de-facto risk free asset featuring a AAA credit rating. Well, US government debt is no longer AAA rated. Not according to the Standard & Poors. However, the S&P 500 is definitely still AAA rated. The S&P 500 features the best of American and international industry with steady earnings and cash flow. If you were Black Rock and had tens of billions to invest, where would you invest? In AA+ US government long-term debt that barely yields 2.5% or the S&P 500 that has a 1.9% dividend yield, usually a 5% expected annual earnings growth and is AAA rated? I think you have seen the answer. Since 2012, every major institutional investor whether it is foreign central banks, college endowments, large asset managers, etc have been pouring money into the S&P500 non stop with no end in sight. So as much as we want to blame the FED for the compression of volatility, the FED is partly to blame. Majority of the blame falls on the divided and dysfunctional US government and Standard & Poors, who for a change, have refused to close their eyes to reality and have assigned the proper credit rating. So high Contango is here to stay until the US government regains its AAA rating. So How Can I Benefit From High Contango? Now that you know that contango has been high and will continue to be high, how do we turn that into investment profits? You can gain an edge in these Central Bank controlled markets by including outperforming volatility products in your portfolio. After all, you do know volatility is being suppressed. What you don’t know is whether companies will continue to increase earnings. You don’t know with certainty if companies can match with earnings, the price assigned to them by the market. In 2015, they have been failing in that regard and as a result the P/E ratio of the S&P 500 has continued to grind higher and higher. However, as valuations soar, it gets harder and harder for individual stocks to appreciate significantly on a percentage basis. So instead of being blindsided by earnings and company valuations, you can simply trade Central Bank policy directly. You can accomplish that via the volatility ETNs. (click to enlarge) Source: Yahoo Finance Since, you know volatility is going to be suppressed by the Central Banks, your attention should be focused on the short volatility ETN- XIV. The edge of the short volatility ETFs can be somewhat spectacular, especially in light of the risk undertaken. Since 2012, the short volatility ETF XIV has significantly outperformed the SPY. Some years in a dramatic fashion. In the bull market years of 2012 and 2013, XIV returned in excess of 100% on the year. In fact XIV is up almost 500% since its inception and is up nearly 1000% since its closing low in 2011 of $4.91. It is currently trading in the $47-48 range! Source: vixcontango.com High Contango Is Your Best Investment Friend What is the reason for this outperformance? Because the XIV shorts VIX2 futures and covers VIX1 futures daily, what the XIV essentially does is short high and cover low on a daily basis resulting in an uninterrupted series of profitable trades. So long as the Contango is positive and high that results in automatic increase in the XIV even if the SPX and spot VIX are flat for the day. Vice versa, that results in automatic decrease for the VXX. For example, if the Contango is 10%, that usually means the XIV will increase 0.5% automatically provided there are no changes to the spot VIX. Because average Contango is so high, over time XIV (Short Volatility ETN) can be expected to gain value above the average reduction in the spot VIX. This explains the XIV outperformance over the S&P 500 index and it is important to understand that it is not an accident and it is not something that is propped up artificially high because “there a lot of buyers”. The Volatility ETFs stick to their formula and if there is additional demand, they simply issue more shares. If there is less demand, they reduce the share count. But the share price of the ETFs follows the mathematical formula, period. As such the XIV gains value based on VIX Futures fair value math and contango. So long as spot VIX is low and contango high, there is no limit to how high XIV can go. And vice versa, there is no limit to how low VXX can go. VXX Warning While the VXX is advertised to the general public as “portfolio insurance” product, it is anything but. Due to contango, the VXX may not rise when the market falls down. If contango is high and the market is slowly grinding down, the VXX will lose money daily. More often than not, the VXX will contribute significant percentage losses to your portfolio. Unless you are a day trader with volatility expertise, you should avoid investing or trading in VXX or other long volatility products. Contango alone, however, doesn’t tell the whole story with regards to the XIV. If the market drops and the VIX Futures Curve gets reset higher, the Contango is of lower importance now as what was formerly shorted VIX2 at 15 (for example) inside the XIV, now has to be covered as VIX1 at 17 for a loss. This is what causes the XIV to post massive daily losses during one or two day sell-offs in the market and why if the entire futures curve moves higher, the XIV can start to lose you money quick. That is why while the XIV can be a very powerful passive investment instrument, it still needs to be monitored constantly in order to avoid the large percentage drawdowns that inevitably come about (see performance of XIV in the back half of 2014). Disclosure: I/we have no positions in any stocks mentioned, but may initiate a long position in XIV over the next 72 hours. (More…) I wrote this article myself, and it expresses my own opinions. I am not receiving compensation for it. I have no business relationship with any company whose stock is mentioned in this article.

The Low Volatility Anomaly: Leverage Aversion Hypothesis

This series digs deeper into the Low Volatility Anomaly, or why lower risk stocks have historically produced stronger risk-adjusted returns than higher risk stocks or the broader market. The CAPM links expected returns with an asset’s sensitivity to systematic risk, but the model assumptions are impractical. This article covers a deviation between model and market that may contribute to the outperformance of low volatility strategies. Given the long-run structural alpha generated by low volatility strategies, I am dedicating a more detailed discussion of the efficacy of this style of investing. In the first article in this series , I provided an introduction to the strategy with a simple example demonstrating a low volatility factor tilt (replicated through SPLV ) from the S&P 500 (NYSEARCA: SPY ) that has generated long-run alpha. In the second article in this series , I provided a theoretical underpinning for the presence and persistence of a Low Volatility Anomaly, and linked to articles depicting its success dating back to the 1930s. This article demonstrates that violations of the assumption of the Capital Asset Pricing Model (CAPM) lead to deviations between model and market that pervert the presumed relationship between risk and return. Empirical evidence, academic research and long time series studies across asset classes and geographies have shown that the actual relationship between risk and return is flatter than the model or market expectations suggests. The third article in this theory lays out a hypothesis for why low volatility strategies have produced higher risk-adjusted returns over time. Leverage Aversion Hypothesis The fallacy of the Capital Asset Pricing Model assumption that investors are able to borrow and lend at the risk-free rate might be the supposition that most perverts the model application from real world practice. Certainly not all investors are able to use leverage, and the cost and availability of leverage can deviate materially from any notion of a risk-free rate in times of stress. Intuitively, leverage-constrained or leverage-averse investors often choose to overweight riskier assets, increasing the price of risky assets and lowering expected return. If some market participants are overweight riskier assets characterized by lower expected returns, then they must be underweight lower risk assets which would be characterized by higher expected returns. In the CAPM model, rational market participants seeking to maximize their economic utility invest in the portfolio with the highest expected return per unit of risk, and lever or de-lever their portfolio to suit their own risk tolerance. In practice, however, many large institutional investors including most mutual funds and certain pension funds are constrained by the level of leverage that they can take. Furthermore, many individual investors lack the sophistication or access to attractively priced leverage. The growing increase in the assets under management of exchange traded fund products with embedded leverage could well signal small investor’s inability to access leverage directly on favorable terms. If market participants respond by being overweight riskier securities, then the relationship between risk and expected return is altered. Building on the long time series studies from Black and Haugen of the relative outperformance of lower volatility assets in the last article in this series, Frazzini and Pederson (2010) empirically demonstrated the alpha-generative nature of low beta assets across twenty international equity markets, Treasury bonds, corporate bonds, and futures. The duo also introduced a “Betting Against Beta” factor that gave the paper its name. The factor is effectively a zero beta portfolio that is long leveraged low-beta assets and short high-beta assets to produce statistically significant risk-adjusted across many markets, geographies, and time intervals. This study also demonstrated that the return of the BAB factor is sensitive to funding constraints as one would expected in a trade involving leverage. The persistence of an alpha-generative strategy involving leverage applied to low volatility assets, whose excess return is in part a function of the funding environment, supports the Leverage Aversion Hypothesis as an explanation for the Low Volatility Anomaly. In the next section of this series, we will tackle how the delegated agency model typical of investment management may also contribute to the outperformance of Low Volatility strategies. Disclaimer My articles may contain statements and projections that are forward-looking in nature, and therefore, inherently subject to numerous risks, uncertainties and assumptions. While my articles focus on generating long-term risk-adjusted returns, investment decisions necessarily involve the risk of loss of principal. Individual investor circumstances vary significantly, and information gleaned from my articles should be applied to your own unique investment situation, objectives, risk tolerance, and investment horizon. Disclosure: I am/we are long SPLV, SPY. (More…) I wrote this article myself, and it expresses my own opinions. I am not receiving compensation for it (other than from Seeking Alpha). I have no business relationship with any company whose stock is mentioned in this article.