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A Look At Direxion’s Revised S&P 500 Volatility Response Shares ETF

Summary Direxion’s newly revised VSPY offers investors a transparent, formula-based volatility hedge for U.S. equities. The fund employs dynamic, daily-rebalanced exposure, rather than attempting to time entry/exit points. I recreate a similar index to back-test Direxion’s strategy on two recent “black-swan” events. Back in January of 2012, Direxion made a few ripples when it announced the launch of three new ETFs giving investors access to the S&P Dow Jones Indices’ Dynamic Risk Control Index series. Unlike the few existing hedge products of the day, these ETFs didn’t try switching between the market and the VIX itself, rather they employed a more conservative approach and, in times of heightened volatility, switch into Treasury Bills instead. Certain aspects of these funds must have fallen out of favor however, as in August of 2014 Direxion announced an index and name change to its largest of the three funds, the Direxion S&P 500 RC Volatility Response Shares ETF (NYSEARCA: VSPY ) . VSPY follows the S&P DJI index of the same name (Bloomberg ID: SPXVRT). If you’re trying to find the index’s specific page on S&P’s website, I’m afraid it doesn’t exist. An e-mail to S&P in February returned the simple response “…the page is still under development at this time.” Regardless, VSPY’s literature explains the fund’s process in enough detail. Methodology From VSPY’s fact sheet : The strategy follows a quantitative rules-based equity index that seeks to mitigate risk by dynamically changing total equity exposure based on volatility signals. The strategy reallocates exposure between equities and U.S. Treasury Bills (T-Bills) based on recent volatility levels of the S&P 500 ® Index. The strategy employs a downside risk mitigation strategy during periods of higher volatility and increases equity exposure when appropriate. Basically, VSPY holds the S&P 500 U.S. Large-Cap Index and tracks some formula of market volatility to determine how much to stow away into Treasuries. That formula is comprised of two parts: a Volatility Level, and a Volatility Signal. The Volatility Level is simply determined by tracking the 20-day moving average of the CBOE Volatility Index (VIX), and pulling the value from the following table: Calculation of the Volatility Signal is less clear. In “Step 2” on VSPY’s fact sheet, it’s referred to as simply the “…(standard deviation) of the S&P 500 Index,” yet from the fund’s prospectus, “The [fund] then reviews several volatility factors of the S&P 500 Index. The volatility factors of the S&P 500 Index are exponentially weighted with more emphasis placed on the most recent historical periods.” This duality begs a couple questions: What are these several factors? Over what period are these factors analyzed? How are they exponentially weighted? My guess is Direxion needs to keep at least some part of this fund a trade secret, but we digress. Once calculated, the fund then uses these two volatility values to determine its equity holding, according to the following formula: This method is fully capable of holding 100% equity, and per the rules, never holds less than 10%. Running the spectrum of possible inputs generates the following Equity Exposure chart: (click to enlarge) The result is the fund is able to withdraw from the market when the water gets choppy, and ease back in when volatility settles. The three distinct Volatility Levels (probably derived from historical analysis) allow the fund to maintain appropriate equity exposure during varying degrees of whatever happens to be “normal” volatility. VSPY, unlike most lumbering ETFs that rebalanced on a quarterly basis, has the ability to modify its exposure daily, and does so at least monthly. There’s mention of “thresholds” the fund employs to likely keep from rebalancing too often and running up transaction costs. Investors in VSPY of course want to know how it performs relative to just the plain old S&P 500. The SPDR S&P 500 Trust ETF (NYSEARCA: SPY ) is a good benchmark. Data for VSPY however only goes back to January 2012 when the fund began trading. It should be no surprise that throughout the ongoing bull market VSPY has underperformed the S&P 500. As the chart below shows, VSPY on average does return ~1.5% less volatility on a monthly basis; however, its low trading volume and lower yield have resulted in periods where its volatility actually exceeded that of the S&P 500: (click to enlarge) Obviously, comparing a volatility hedge fund to its equity index isn’t fair in a bull market. Since we’re essentially comparing risk-returns, I’m sure someone in the comments will ask “Well, why don’t you just compare their Sharpe Ratios?” I’ll caution that the Sharpe Ratio is best for apples-to-oranges comparisons where the strategies and holdings are different. VSPY and SPY hold the exact same equities; a chart of these funds’ returns vs. their risks will just be a translation of VSPY’s equity exposure chart. Notwithstanding, strategies like these still beg to be stress tested. As I discuss later, I believe VSPY’s target audience is probably the crowd that fears drawdowns above all. Two popular “black-swan” events of the recent past are the Dot-Com bust of the early 2000s and the Mortgage Bubble collapse of 2008. Since neither VSPY’s data (nor index) go that far back, we’ll need to use the equity allocation formula above to reconstruct this fund’s index. The Volatility Level is easily gathered from historical VIX values, however, that Volatility Signal remains a mystery. For this analysis, I’m using a 20-day moving average of the S&P 500’s annualized volatility. I also blindly (i.e. no threshold) rebalance the index once a week, based on the previous week’s determined equity exposure. The chart below compares my best attempt at recreating the S&P 500 Volatility Response Shares Index with VSPY: (click to enlarge) As you can see, it’s not perfect. Clearly, VSPY’s threshold for rebalancing and/or the mysterious means it uses to determine S&P 500 volatility are large performance factors. Despite the green-line correlation dipping negative for some moments, our recreated index’s overall correlation for this period is actually above 0.90. I believe that’s enough to press on with our stress tests, but please take the following charts with a bowl of salt: (click to enlarge) (click to enlarge) At first glance, it works! VSPY’s equity allocation algorithm successfully allows the fund to avoid catastrophic plunges. The long game however is a different story. Since as far back as SPY’s data goes, our reconstructed index has struggled to keep up. I’ve also included the Vanguard Balanced Index Fund (MUTF: VBINX ) for comparison: (click to enlarge) Again, my attempt at reconstructing the S&P 500 Volatility Response Index was less than stellar and underperformed the actual VSPY for its first year. However, the inclusion of VBINX in the above chart is to emphasize that while a carefully constructed volatility hedging strategy might lessen the blow of an economic downturn, so does diversification. Replicating the Strategy Yourself One thing to watch out for is purveyors of these boutique funds like to charge significant expense ratios, some more justified than others. In VSPY’s case, the fund is simply switching between two components, the S&P 500 and short-term U.S. Treasuries. Go figure there’s a world of low-cost ETFs for both of those asset classes; we have SPY to access large-cap U.S. equities and the Schwab Short-Term U.S. Treasury ETF (NYSEARCA: SCHO ) for short-term Treasuries. Expense ratios are 0.0945% and 0.08% respectively. In comparison, VSPY’s expense ratio of 0.45% is more than quadruple that of SPY, but there’s two catches: If your platform charges any more than $0.99 for commissions, rebalancing on a daily or weekly basis, even with just one ETF, will kill your returns. The 500 components of the S&P 500 all operate on different dividend schedules, when you lump them into an ETF like SPY, you as an investor have a once-a-month shot to capture those dividends. Since VSPY owns 500+ individual stocks within its equity portfolio, it can far more efficiently expose its assets to that income calendar. For these reasons, I think VSPY’s expense ratio of 0.45% is quite reasonable, it’s also half that of the average hedged ETF . Similar ETFs RBS runs a similar series of volatility-averse funds called the Trendpilot family. When a simple 200-day moving average trigger is reached, these funds dump all of their holdings into Treasuries until the trend breaks and they re-enter their equity position. Though the prospectus for their RBS U.S. Large Cap Trendpilot ETN (NYSEARCA: TRND ) claims long-term outperformance of its benchmark, the 100% on/off strategy can result in a very choppy investing experience. As I postulate in this article , these switching-style funds are most likely marketed towards the Nervous Nellie’s. Folks that reasonably don’t want to be caught off-guard by a dot-com bust or hidden mortgage crisis. On the same note however, I can also imagine how watching assets skyrocket while one’s supposed sleep-well fund is still holding flat-line Treasuries probably induces the same performance anxiety. Dynamic exposure, as we see in VSPY, is a fair compromise. Alternative Strategies As a dozen asset allocation articles on Seeking Alpha will tell you, diversification is not to be overlooked. The same risk-return profile offered by VSPY can easily be achieved with proper diversification. Replacing one’s equity portfolio allocation with VSPY might produce an interesting conservative combo. Selling calls against one’s equity holdings can also generate income and help reduce volatility. A variety of passive ETFs exist to make this alternative easy. Though it’s enjoyable to sell one’s own calls, watch your brokerage for added costs. I quit using OptionsHouse because they started charging a processing fee on letting options expire. Closing Remarks Direxion’s VSPY offers investors convenient, low-cost access to U.S. equities while hedging against short- to mid-term rises in volatility. Rather than attempt to time the market like similar ETFs, VSPY reacts organically, withdrawing when the water gets choppy and easing back in when skies begin to clear. Our reconstructed index shows the strategy can help avoid catastrophic downturns, but will lag in bull markets. Low volume and little dividends also hurt performance. Alternative strategies such as covered-call selling or asset diversification can probably produce the same hedging effects. 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.

Long/Short Hedge Fund Factors: Low-Cost Downside Protection?

By Wesley R. Gray, Ph.D. The holy grail of financial markets is finding strategies that have misaligned risk and reward characteristics. In the traditional view, investors try to do the following: Identify strategies that have high returns , then… find ways to get the exposure with the lowest risk possible . However, there is another angle on this concept… Identify strategies that have great risk-management benefits , then… find ways to get the exposure at the lowest cost possible . For example, you might buy out of the money puts, which in a crisis will finish in the money and generate insurance-like returns. But puts might be expensive… What if you could identify an asset where the cost of this insurance is de minimus or – better yet – you get paid to own the insurance? That is, if you commit capital, you will, in expectation, generate positive returns over time-and get an insurance benefit. This would be the holy grail! This line of thought is a bit unorthodox, but may lead to creative portfolio solutions. An applied example: The US Treasury Bond. First, let’s frame the question through the typical lens: focus on expected returns first, volatility second. Many consider the US Treasury Bond to have low expected return, but high potential risk. The low expected return is due to low yields, and the high potential risk is associated with the fact that if we were to move down the “banana republic” path, long bonds would arguably get crushed. Everyone seems to know this. Conclusion: Bad investment. Next, let’s frame the question through a different lens: focus on risk-management benefits first, expected returns second. When we look at the US Treasury Bond as a risk-management instrument, we identify some amazing historical benefits that are distinct from its expected return characteristics. The results below highlight the top 30 drawdowns in the S&P 500 Total Return Index from 1927 to 2013. Next to the S&P 500 return is the corresponding total return on the 10-Year (LTR) over the same drawdown period: (click to enlarge) The results are hypothetical results and are NOT an indicator of future results and do NOT represent returns that any investor actually attained. Indexes are unmanaged, do not reflect management or trading fees, and one cannot invest directly in an index. Additional information regarding the construction of these results is available upon request. Leaving aside (for a moment) questions about long-run returns, the US Treasury Bond suddenly looks more like an insurance contract, and less like a traditional investment. Again, with a traditional investment, we would tend to focus first on expected return and standard deviation. Conclusion: We’ve potentially identified an insurance contract that pays us to hold it. Moving from US Treasury Bonds to Hedge Fund Factors The example above is not meant to be a pitch for or against US Treasury Bonds. The analysis is merely meant to highlight how framing the investment decision can potentially lead to different conclusions. In our quest to find additional low-cost-or free-portfolio insurance assets, we started playing with common “factor” returns. As insurance contracts, do these exhibit characteristics similar to what we saw before with respect to Treasury bonds? The results were surprising… We examine 3 common hedge fund “factor” portfolios alongside the S&P 500 Index: SP 500 = SP 500 Total Return Index HML = The average of 2 value portfolios (small and large) minus the average return of two growth portfolios (again, small and large) MOM = The average of 2 high return portfolios (small and large) minus the average return of two low return portfolios (small and large) QMJ = The average of 2 high-quality portfolios (small and large) minus the average return of two low-quality portfolios (small and large) Results are gross of management fees and transaction costs. All returns are total returns and include the reinvestment of distributions (e.g., dividends). Data are from AQR and Ken French . Summary Statistics: Here are the returns (1/1/1963-12/31/2014): (click to enlarge) The results are hypothetical results and are NOT an indicator of future results and do NOT represent returns that any investor actually attained. Indexes are unmanaged, do not reflect management or trading fees, and one cannot invest directly in an index. Additional information regarding the construction of these results is available upon request. Conclusion: You got paid to hold the hedge fund factors over the long-term. Insurance Benefit Analysis: In the context of a traditional asset pricing model, such as the Capital Asset Pricing Model (CAPM), an asset that actually delivers returns when the rest of the world is blowing up (i.e., negative beta during treacherous times), should have a negative expected return because of the diversification benefits. For example, the CAPM says the expected return of an asset equals the risk-free rate plus beta times the expected excess return of the market portfolio: r a = r rf + B a (r m -r rf ) In this equation, if beta is negative, then the asset could earn negative returns and the investor should be happy owning it. For example, let’s say rf=3%, Rm-rf= 4%, and B=-1. The expected return = -1%. Hence, under CAPM, you have to pay for an insurance contract. Yet as the analysis above highlights, all of these L/S factors have positive carry. In a traditional asset pricing framework, these assets should not act like portfolio insurance. But how do these strategies perform as insurance contracts? When we look at the worst 30 drawdowns on the SP 500 since 1963 we see a very interesting pattern – Factors tend to rip higher during crisis. In other words, hedge fund factors look and feel like insurance contracts that pay off during chaos. (click to enlarge) The results are hypothetical results and are NOT an indicator of future results and do NOT represent returns that any investor actually attained. Indexes are unmanaged, do not reflect management or trading fees, and one cannot invest directly in an index. Additional information regarding the construction of these results is available upon request. Conclusion: Hedge fund factors are VERY interesting in a portfolio context. Original Post

3 Agricultural ETFs Rising On Wet Weather

After a rough patch over the last six months, thanks to a stronger dollar and accelerated crop plantation on a favorable weather outlook, agricultural ETFs seem to have turned the corner. Last week was great for the beaten down agro-based commodities, as worries over wet weather in America’s key growing belts led traders to bet on the contracts of several agricultural commodities. Almost all agro-based commodities added gains last week (as of June 26, 2015) and are likely to see more surges in the short term. Fears that led to this spike revolved around weather in the key grains growing states in the Midwest. Existing wet and cold weather and predictions for more rains are causing delay in the planting of this year’s crops by farmers. Some analysts have been pointing to El Nino for this wet weather condition in North America. In fact, Citigroup expects agro-based commodities to deliver as much as 25% gains this summer ( per Bloomberg ). Investors should note that El Niño, a warm-water phenomenon that blows up off the Pacific coast of South America, causes drought in some regions of the world and floods in others. Below we highlight a few agricultural exchange-traded products which have the potential to trounce the overall agro-based commodity space and offer investors some sweet returns from the wet weather despite the broad-based commodity market gloom on the dollar strength. Wheat Speculation of cold weather in the U.S. pushed the wheat prices to a 6-month high as such weather would curb production in the U.S. southern Great Plains . The area has already experienced massive rains that can even cause a flood. High levels of humidity go against crop quality, causing farmers to hold back the cropping. Due to this, wheat prices have also been soaring. Investors can easily play this trend via Teucrium Wheat ETF (NYSEARCA: WEAT ), a commodity product from the issuer Teucrium. This fund invests in wheat futures that are traded on the CBOT, but does it in a way that looks to lower contango issues. This $27.3 million wheat ETF was the top-performer last week, having returned over 12%. Corn Much like the wheat market, the price of corn is also rallying. Thunderstorms have already hurt budding corn crops in a few areas and now lower plantings will likely have an adverse effect on stock piles. Teucrium Corn ETF (NYSEARCA: CORN ) – a fund that provides investors direct exposure to the corn commodity – was up about 6% last week. The $82 million fund was otherwise down 21% in the last one-year period. Soybean Farmers are sowing soybeans at the most sluggish pace seen in 19 years, this time of the year . A delayed planting will result in a below-average yield, per the source. As a result, soybeans futures are seeing an uptrend. The $6.4 million Teucrium Soybean Fund (NYSEARCA: SOYB ), which looks to track the daily changes of a weighted average of the closing prices for three futures contracts for soybeans, was up 3.5% last week. Notably, the grain was at a five-year low level to start the month. Miscellaneous ETF Choices There are options for investors interested to play the above three commodities via a single product. To do this, investors should not tap the pure play choice; rather they should target a host of miscellaneous ETFs having exposure in the trio. MLCX Grains Index TR ETN (NYSEARCA: GRU ), DJ-UBS Grains Total Return Sub-Index ETN (NYSEARCA: JJG ) and DJ-UBS Agriculture Subindex Total Return ETN (NYSEARCA: JJA ) are some of the ETFs which are highly invested in the trio and accordingly shot up last week. GRU, JJG and JJA were up 12%, 9.6% and 7.3% respectively. Original Post