Tag Archives: rsp

How I Plan To Profit From The Next Flash Crash

Summary What happens to some ETFs but not others and why. Managing the risk by using a pair trade. The key is increased market volatility. Introduction As I wrote a series of articles explaining how I created my own portfolio over a lifetime (including the lessons of both success and failure), I received question about how a flash crash occurs. This led me to include an article in the series explaining my understanding about how a flash crash gets started and how some stocks, and particularly some ETFs, end up with such exaggerated extremes during a flash crash. The explanation was very well received by readers. You can find the full article here . The discussion in the comments sections led me to consider how one might profit from the midst of panic. When the crowd is panicking someone is always finding a way to profit from the overreactions that occur. One reader commented that s/he intended to place a good until cancelled order to buy one of the ETFs that got hammered during the flash crash session of August 24, 2015. At first glance it seemed like a reasonable way to take advantage of the situation when the price of an ETF falls significantly below what one could reasonably expect to be the net asset value [NAV] of the underlying assets. But as I thought about it some more I decided there might be a negative catch involved called risk. It seemed like a relatively low risk trade at face value. You commit no funds unless the ETF falls precipitously and you get to buy at a price you otherwise would not believe possible. However, there is also a growing possibility that the next time this happens it could very well not be a flash crash but the beginning of a bear market. That is what I define as the potential risk involved in the trade. It is possible that the speculative trade (not to be confused with investing, which I define as long-term), could still yield a profit if the trader sold the position either near the close or early the next day once the price and NAV normalized. But, if the market falls into a bear market that begins with a waterfall formation of multiple gap-down trading sessions, the profit could disappear in just a few sessions, or even just hours, and not come back for months. My first rule of investing is to limit losses. So, I decided to consider alternative ways to reduce the risk of the trade and limit the potential loss. Before I continue, I want to explain that this is not something I look for on a regular basis. Those who have followed my work will know that I am generally a very conservative, long-term investor looking to increase the income from my portfolio over time. But, occasionally there appears a unique opportunity that I want to take advantage of that poses a relatively low-risk (or limited amount of risk) with a very high reward potential. This is one of those trading opportunities that I look at very infrequently. Also, I do not use very much capital on such a trade. There is no such thing as a sure thing. To limit risk I do two things in this instance: limit how much capital I put at risk to limit my potential loss; and make sure it is a trade that does not require me to guess the direction of the overall market trend. I know what you are thinking: a flash crash, by definition, means the direction of the market is down. But it does not necessarily define the overall trend. After the last two flash crashes (2010 and 2015) the market went higher in subsequent months. A flash crash can happen in either a bear market or a bull market. It is temporary, hence the “flash” component, lasting only a few minutes or hours, at most. Then stock prices snap back to near where prices were prior to the flash crash. This is just a strategy I plan to employ to take advantage of the next one. If you believe that the Federal Reserve and SEC have everything under control and that another flash crash will never occur, you should stop reading now. However, if you believe as I do that another flash crash is likely to occur sometime in the next year or two, then the potential profit from this strategy may make sense to you. What happens to some ETFs but not others and why I want to start with an illustration using the Guggenheim S&P 500 Equal Weight ETF (NYSEARCA: RSP ) and the SPDR S&P 500 EFT (NYSEARCA: SPY ). As the saying goes, “A picture is worth a thousand words.” (click to enlarge) This chart represent hourly price activity for the two Indexes from opening on August 24, 2015 to the close on August 25th. Notice the range from the daily high to the daily low for RSP on August 24th, $75.57 to $43.77. Amazing, is it not? The range of the SPY was $197.48 to $182.40. The range for RSP was a staggering 42.1 percent while the range for a similar ETF, SPY, was only 7.6 percent. How could this happen, you may ask? After all, both ETFs hold the same stocks, components of the S&P 500 (^GSPC), although in two different weighting methods, so how could the prices vary so dramatically? The short answer is volume and liquidity. For the long version I will use an excerpt from my earlier article: Normally a market maker will keep the spread (difference between the bid and ask prices) narrowly around the NAV of the underlying assets of the fund. Under normal circumstances they will gladly buy the ETF for a little under the NAV and then sell it for a little more than the NAV when needed to keep shares trading efficiently. When trading in one of the stocks that make up the ETF is halted by an exchange, having hit its “limit” down as determined by the exchange, the market maker for that ETF must decide what the spread should be and place orders accordingly. Market makers are not in the business to lose money, so when they err it is always on the side of caution. In this case, not knowing what the NAV is (because trading in some stocks has been halted and when those stocks begin trading again the price may be different from when it was halted), the market maker most likely looked for price support levels in the stocks for which a value could not be determined and placed a bid to buy at an assumed NAV based upon those prices. When multiple stocks are halted at the same time, the market maker lowers the bid to make certain that a loss is not incurred. With the market falling so abruptly, the bids by the market makers were set significantly below actual (or the last known) NAV. Hopefully, that is clear enough to explain why some ETFs diverged significantly from the value of the underlying stocks that make up the funds. My best guess is that the market maker for RSP considered its position to contain more risk since it did not have the protection of the weighting for the stable companies at the top. Thus, when several of the stocks that make up the S&P experienced a halt in trading at the same time, especially when many of those issues were of lesser capitalization, the market maker simply chose a technical support level for those shares that it could expect to hold up and set a bid based upon the much lower assumed NAV. In addition, the HFTs, sensing a rout and recognizing a thinly traded ETF in RSP, probably hit the sell button with bids even lower and then probably cancelled those orders before being filled. The HFTs could then place buy orders even lower and pick up shares at deep discounts when there were no other bids if sellers placed market orders. The HFT trading systems are automated so there are rarely humans involved. The programs are set to identify unusual market activity and to predict potential outcomes. They place thousands of orders and can cancel within a few thousandths of a second with the objective to move the price. They move with incredible speed and usually take pennies or fractions of a penny from many thousands or millions of transaction per day. On August 24, 2015, I suspect some HFTs made chunks instead of pennies. Volatility is the friend of HFTs. Managing risk by using a pair trade It should be obvious that if an investor had the presence of mind to have bought shares of RSP when the price got distorted to the downside, s/he would have turned a nice profit. The problem, as I pointed out earlier, is that the next time the market drops like this it may actually be the beginning of a major bear market and the rebound may not be as strong. One way to tell, would be how long the share price of RSP remains extremely low compared to SPY and if the difference begins to narrow over the course of the trading session with SPY falling to reduce the gap over a matter of hours rather than minutes. If that happens my strategy will work even better. There are three ways to enter the trade and I will explain each one. Each has a different risk profile and a different potential return. There is the convenient entry plan, the actively managed entry plan, and the reactionary plan. I do not know which will work the best but have my expectations. I will try out each one and report back if/when we have another flash crash on how each alternative plan of entry worked out. The convenient plan requires me to buy an out-of-the-money put option contract on the SPY with a relatively near-term expiration, say January or March of 2016 with a strike of $185 (or about eight percent below the current market value). At the same time I want to place a limit order to buy 250 shares of RSP at a price of $50. The reason for using 250 shares instead of a round lot is to match the approximate values of the underlying equities represented by the 1 contract of SPY at a price of $185 to the expected ending value of RSP (about four percent below the current price) at about $72. I use four percent because that is the value at which both SPY and RSP fell by the close compared to the previous close during the August 2015 flash crash. The number of shares is also off a few shares but I am not trying to get a perfect balance or match, just a close approximation of similar values. I want both pieces of the trade to have similar values so that a one percent move in either index will make both positions of the underlying move about the same amount. If a flash crash happens on Monday (not expected but always possible), as long as it does not happen before I can enter my positions, I would be positioned to gain significantly from it. So, let’s do the math. In a flash crash, we expect both positions to end up near where we started, maybe a little lower. If both were to settle about four percent lower than the previous close, as happened on August 24, 2015, then RSP would generate a profit of $5,500, while the put on January SPY put option (costing me $150 + commission) might eke out a small gain of a couple hundred dollars or so. At the end of the day I would sell my RSP shares near the close for a gain of about 44 percent. The initial position in the SPY put option, assuming I use a January expiration contract would be about $150 ($1.50 x 100 = $150). This is all I would need until a flash crash actually happens. If RSP suddenly drops to $50 during a flash crash, my order should get filled and that end of the position would cost me $12,500 ($50 x $250 = $12,500). If a flash crash happens I will tie up $12,650 and expect a return of about $5,500. If it does not, I lose the $150. Then, when the January SPY put option is near expiration I can sell it or let it expire worthless (if SPY stays above the strike price, which is likely) and purchase another put option on SPY further out into the future. And then I wait again. This could require a lot of patience since the last two occurrences were over five years apart. If it takes that long again, I could be out $150 a month for 60 months, or $9,000. Buying puts that are expire further into the future could bring the monthly cost down but it would also require lowering the strike price to ensure the trade could be profitable. That changes the risk profile. It does not make much sense. So, the next step is to determine when to initiate the put option position and when to stay on the sidelines to lower the cost and keep the trade profitable. The Key is market volatility This is the hard part to identify. On the days preceding each flash crash there were at least one trading session that exhibited the trait for which I am watching. I want the ^GSPC to fall for the day more than the average daily movement of the preceding two weeks and close at or very near the low of the day. If you look at the charts below from May of 2010 and August of 2015 for both ^GSPC you will notice that within the two days prior to the flash crash, the index had a larger than average down day and closed at or near the low of the day. We will have some false positives along the way but this can reduce how long we are in the market with a put option and bearing the cost of a potentially worthless asset. The same pattern also occurred in both ETF charts. S&P 500 Index from 2010 S&P 500 chart from 2015 I would insert the charts but YCharts does not support bar graphs which are necessary for the illustration and Yahoo! Finance did not let me copy these images. It is clearer on the August 2015 chart, but remember that there are two components: size of the move and closing near the low. The size components is what weeds out most false positives. The second entry plan requires active management. As an alternative to leaving the put option open and letting it expire worthless, one could only buy the option when the set up occurs, hold it for a week or so and then sell it if nothing happens, incurring a much smaller potential loss (or maybe a gain from time to time) from each entry attempt. That is a lot of work, but it could potentially make the trade far more profitable than the convenient alternative. The third entry plan is the reactionary plan. This alternative requires us to just place the limit order to buy the shares of RSP and wait for the flash to start. Then buy the SPY put options about ten percent or more out of the money in the closest expiration month (be sure you are not within just a few days of expiration because you do not want to have the options executed). You will pay more for the options in this scenario but this is the one that makes the most sense to me. I do not want to leave the RSP order completely naked for very long, so if the market begins to fall precipitously I would buy the SPY puts no later than when then price of RSP falls below my order limit price of $50. In this instance, once we have both positions in place we are merely waiting for the prices of the two index ETFs to normalize as we have already locked in the profit defined by the spread between the values of the two positions. This alternative is likely to provide a one-day gain of 35 percent or more. It may never happen. But if the market just continues higher we never make an investment and have no capital at risk. The one big caveat that I need to make clear is that we need to keep an eye on the RSP share price. If the market begins to fall into a bear market without a flash crash it will be necessary to lower the limit order price on RSP. I plan to keep it at about 33-35 percent. In 2015, RSP fell 42.7 percent from the previous day’s closing price but then rebounded to close up 67.5 percent. In 2010, RSP fell 58.1 percent and rebounded 129.2 percent. I am not trying to be greedy and capture all of the move. I just want a reasonable piece out of the middle. Now let us look at the charts. May 2010 RSP chart May 2010 SPY chart Notice that SPY only fell 10.1 percent and rebounded almost 7.6 percent by the close on May 6, 2010. August 2015 RSP chart August 2015 SPY chart Here we see that SPY only fell 7.8 percent from the previous close at the bottom and rebounded by 3.9 percent on August 24, 2015. Conclusion We only want to capture the difference in movement between the two ETFs. It can be looked at as a spread, however, it is not a true spread since I use an option on one end and shares on the other. I do not, as a rule, sell shares short. I use options to hedge against downside risk and intend to use options to protect against the downside potential should the crash turn out to be more than just a flash in the pan, so to speak. Once I have the two positions filled, in the reactionary entry plan, I will profit. There is no doubt of that since the underlying assets will eventually revert back to NAV on both and the difference is very little between the two ETFs while the difference that I intend to lock in will be significant. We have only had two such occurrences to date. There may never be another. But I want to be prepared to enjoy that day if it does come again.

Changes Coming For Guggenheim Large-Cap ETFs

Summary This is the first in a series of (free-standing) articles analyzing the 121 large-cap ETFs that are currently available. Guggenheim currently has five large-cap ETFs, although one will be closed in January and another will be changing its index provider. I rank the five ETFs and come to some interesting conclusions about which of Guggenheim’s funds seems to be the best. In one of my recent articles, 1 I mentioned that a serious all-ETF portfolio needed to have at least one fund focused on U.S. large-caps. Which one? As of this writing, there are 121 ETFs that direct their attention to large-cap holdings, many focusing on the S&P 500 , the Russell 1000 or any of the variants of those two basic indices. 2 Is there a fund that could be said to be, in some meaningful sense, better than the others? Or, at least, is there some identifiable group of funds that seems to be – again, in some sense – better, from amongst which one could choose with a bit of confidence? I propose to do a long-term project involving the comparison of large-cap ETFs. My goal will be to identify funds that have promise, while at the same time identifying funds that might not be as tempting as others. Each article will be restricted to a handful of funds that have something in common (issuer, index, methodology, weighting, etc.); over the course of the project, no doubt some funds will show up more than once. In the end, it is not my expectation that there be one special fund that I hold up as the ” winner ,” but that readers will have some cogent discussions that may help separate the wheat from the chaff. Hopefully, there will be some surprises along the way just to keep things interesting. Along the way, I hope to develop some tools that will help in examining the group of large caps, and possibly help shed some light on other classes of funds, as well. 3 The articles are intended, and expected, to be independent from one another, so readers need not feel that they have to commit to the whole series. 4 The Guggenheim Large-Cap Funds Guggenheim Funds Distributors, LLC currently offers five ETFs that focus on U.S. large caps: Guggenheim Russell 1000 Equal Weight ETF (NYSEARCA: EWRI ) Guggenheim S&P Equal Weight ETF (NYSEARCA: RSP ) Guggenheim S&P 500 Pure Growth ETF (NYSEARCA: RPG ) Guggenheim S&P 500 Pure Value ETF (NYSEARCA: RPV ) Guggenheim Russell Top 50 ETF (NYSEARCA: XLG ) A couple of changes are in the works for two of the funds and will be discussed in due course. Below is a brief description of each fund. EWRI is one of the two Guggenheim ETFs that will face changes on January 27, 2016: this fund will effectively cease to exist , its portfolio will be merged with RSP . Guggenheim’s reason for the merger is that the Russell 1000 is not a pure large-cap index , but includes a substantial number of mid caps, as well. As a result, EWRI – which is intended to be a large-cap fund – overlaps with Guggenheim’s mid-cap ETF and is considered by Morningstar to be a mid-cap blend. 5 According to Guggenheim, after the change, the company’s large-cap, mid-cap and small-cap funds will be distinct and have no overlaps. 6 Guggenheim asserts that the S&P 500 , S&P 400 and S&P 600 indices unambiguously and without overlap cover the large-cap, mid-cap and small-cap stocks, respectively. Finally, RSP has outperformed EWRI , and its smaller portfolio (500 holdings as opposed to EWRI’s 1,930 – now down to 1,023) is more efficient and more easily managed. 7 The transition will involve the flow of EWRI assets to RSP in exchange for shares of RSP ; the accumulated shares of RSP will then be distributed to EWRI shareholders on a pro rata basis, with fractional shares being distributed as cash. 8 Guggenheim expects that there should be no tax liability for shareholders. 9 The fund would seem to be going through some transition pains. Based on its current NAV and ER, compared to its 2014 expenses, it has an expense efficiency 10 rating of 126.48% – too high for a fund with only $71.19 million in assets , 11 and the merger is certain to impose more costs before the fund closes. The fund’s slight assets do provide it with a higher RoNAV . 12 When RSP’s merger with EWRI is finished, the result should not have that much bearing on this prominent ETF. EWRI ‘s assets amount to less than 1% of RSP ‘s, and ultimately they should end up simply increasing the number of shares RSP has of each of its holdings – and that , by only a small margin. I have to confess that I do like this fund – primarily for the fact that it is equal-weighted and has a tendency to outperform funds that are based on the standard S&P 500 , cap-weighted, index. I have come to think of it as my “go-to” fund when I want something to use as a comparison, or when I want to test an ETF-only investment portfolio. 13 RSP offers a nice, if unremarkable yield; as we will see below, its strong suit tends to be its performance. The fund’s managers seem to be keeping the expenses down, resulting in an EER of just under 75% – taking some of the edge off the 0.40% expense ratio. Until I get a better feel for the significance of RoNAV , I will just point out that it’s 1.11% and is towards the low end for the Guggenheim funds. 14 RPG manages to present some of the better numbers of any of the Guggenheim funds, but does so while also putting up some of the more unfortunate numbers of the group. The fund’s portfolio is made up of those in the S&P 500 that show the greatest growth potential, as determined by Standard & Poor’s . Currently, the index lists 106 companies as having “strong growth characteristics.” The fund had a 46% turnover rate for its most recent fiscal year – which is described as “average.” 15 RPG ‘s expense efficiency is very nice – only 54.50% of anticipated expenses. It does have a very low yield – not the fund to turn to if you want dividend income. The lower income also results in a low return on NAV – the lowest of the five funds presented here. RPV ‘s index consists of 123 constituents of the S&P 500 that are deemed by Standard & Poor’s to have strong characteristics regarding value. RPV is perhaps the polar opposite of its sibling, RPG . Where RPG has an extremely nice EER, RPV sports one of 103.64% – over the 100% line. On the other hand, it has the highest yield of the five funds and one of the highest RoNAV of the group. The value portfolio had a turnover rate of 25%. XLG is based on the index of the 50 largest companies (by market capitalization) in the Russell 3000 index ; ETF.com calls it “the ETF for investors who don’t want to hold any companies they haven’t heard of.” 16 The fund is the second of Guggenheim’s large-cap funds that will undergo a change on January 27, 2016; on that date, XLG will have its index changed to the S&P 500 Top 50 Index . The change, according to the issuer, is intended to maintain continuity among its funds, particularly those following S&P-based indices. There should be nominal change in the holdings of XLG (which will retain its ticker, but be renamed the Guggenheim S&P Top 50 ETF ), as it currently appears to have 48 holdings in common with the 50 S&P components having the largest market caps. 17 XLG seems to excel in most measures: it has an expense margin of 91.24% , its expense efficiency is better than 94% (along with a low 0.20% ER ), its RoNAV is a group-best 1.97% , and it has a handsome 2.06% yield. Comparative Performances So, how do they actually stack up? The following chart illustrates the performance of each of the funds since their inceptions: (click to enlarge) As the key to the chart shows, looks can be deceiving. XLG would seem to be outperforming the other four, but – since its inception in 2003 – RSP has increased by 208.81% , outperforming the other four funds, with XLG actually trailing the pack with only 62.72% increase in value. 18 Of course, measuring the funds since their inceptions is misleading, as well; RSP has a two-year advantage over XLG , and a nearly three-year advantage over RPG and RPV (and a seven -year advantage over the doomed EWRI ). The following chart shows performance from the inception date for RPV and RPG : (click to enlarge) Since March 3, 2006, the growth-oriented RPG surpasses RSP by an impressive 6,000 bps – and, again, XLG trails the others. 19 The Recession After looking at both of the above charts, I was intrigued by how the funds performed during the “Great Recession”: all of the funds hit recession-period bottoms on Monday, March 9, 2009 (although, actually, RPV hit its low on the previous Friday, March 6). By all appearances, XLG took a huge tumble, compared to the other funds. How did the funds take the recession? The following chart illustrates: (click to enlarge) Interestingly, RSP and RPV hit their pre-recession highs on June 4, 2007 ($52.67 and $37.40, respectively), while RPG and XLG hit their highs on October 10 ($39.79 and $117.32, respectively). 20 In terms of percentage, both RPG and XLG suffered the least, both losing less than 54%; RSP was about 700 bps behind, at just under 61%, while RPV lost the most, dropping more than 76%. It took 17-20 months for the funds to give up their losses; recovery, for the most part, took a lot longer. RPG surpassed its pre-recession high on October 25, 2010 – 19 months after hitting bottom. RSP would take nearly two more years before reaching a new high of $52.69 on September 12, 2012. RPV would follow in six months , hitting $37.54 in March, 2013, and XLG would reach $117.63 two months later . What I find interesting here is that these funds are all drawn from the same well: the S&P 500 . RPG , RPV , and XLG are all proper subsets of RSP , which is itself a subset of the S&P 500. The S&P reached its pre-recession high of 1565.15 on October 9, 2007 – the day before RPG and XLG reached theirs. The lowest close for the S&P during the recession was 676.83 on March 9, 2009 – the same day as the Guggenheims – for a drop of 57.76%, which places it right in the middle of the Guggenheim funds. This can give us a little insight into a few things: First , RSP lost more value during the recession than either RPG and XLG presumably because RSP has significantly more smaller-capped companies. How do we come to that conclusion? Because RSP underperformed the S&P 500, even though the two would be (in principle) co-extensive, the only difference being that the S&P is cap weighted, while RSP is equal weighted. Being equal weighted, RSP places greater weight on the smaller-capped holdings than does the S&P; thus, if RSP underperforms the S&P, it would be reasonable to assume that the principle cause was the extra weight given the smaller-capped companies. Second , if smaller large-cap companies bore significant losses during the recession, we can assume that the reason for RPV’s performance during this period would be due to a larger number of smaller-capped holdings. This only goes so far as an explanation, in that there is an overlap between these funds: RPG and XLG have 17 funds in common, while RPV and XLG have eight in common (meaning some of the mega-caps are, according to S&P’s formulary, still values). 21 Third , Standard & Poor’s formula for determining growth stock seems to be spot on, as RPG recovered from the recession quicker than the other three funds, and did so by a substantial margin. I take it by “growth” they mean “quick growth” – sprinkle some Miracle-Gro on them. The 2010 “Correction” Given the performances of these funds during the recession, I thought it might be interesting to see how they fared during the recent “correction” the market experienced recently. The following chart gives an indication: (click to enlarge) The chart shows fund performances for the period from June 1, 2015 through November 20, 2015 (the prices on the far left and far right of the chart). It also shows the highest point and lowest point for each fund (the dated prices) – with all highs coming before August 25, the day “the bottom dropped out.” All four ETFs lost more than 10% of share value from their respective highs, with RPV losing the most at 15.79%. For the period illustrated, only one fund – XLG – has shown a gain in share price overall. Needless to say, none of the funds had surpassed their high points for the period. 22 Compound Annual Growth Rate (CAGR) One last consideration ought to be made before trying to “judge” these funds: what one gets from them. The following chart shows returns based on historical prices adjusted to accommodate splits and dividends: (click to enlarge) When we take into account dividends, and particularly when we look at share performance since March 9, 2009, RPV shows a measure of life it hasn’t shown thus far. The value fund’s group-leading yield pushes its fairly modest performance in all other measured data to a post-recession growth of 552.34% , outperforming nearest contender RPG by 213 percentage points. Another way of quantifying the returns realized by these funds is through their CAGR s. The following graph shows the CAGRs for each fund (including EWRI ) computed both from date of inception ( CAGR-I ) and for the five-year interval from November 20, 2010 to 2015 ( CAGR-10 ): (click to enlarge) Head-to-head over the past five years, RPV has markedly outperformed the other funds – again, largely due to its dividend yield. Of course, CAGR data can be misleading, in that it the annual returns each fund would provide as if growth was a constant , which it is not. Nevertheless, however, it is an effective way to illustrate the total returns one might expect from a holding. As illustrated above, moreover, it can show that all of the funds have realized a greater rate of growth in the past five years than is historically the case. Assessment I have to confess that I still have not worked out a way of rating the funds in some way that would be meaningful once all 121 ETFs are put together. For the time being, I am simply weighing each component of the analysis, 23 with each component bearing an equal weight – essentially, scoring is based on ordering for each component. I am trying to keep it simple, in the absence of something cogently complex. Of the five funds considered here, XLG comes out on top, with RPV just nominally behind – and this pretty much sums up two prominent approaches to investing: for growth/security [ XLG ] or for income [ RPV ]. I must confess to being slightly surprised that RPV ended up scoring as high as it did – this may be something of a sleeper. RSP and RPG tied for third place, each one showing its strengths in line with RPV and XLG , respectively. RSP was stronger on the income -based factors, while RPG was stronger in the growth elements. I am somewhat disappointed in how RSP fared. Disclaimers This article is for informational use only. It is not intended as a recommendation or inducement to purchase or sell any financial instrument issued by or pertaining to any company or fund mentioned or described herein. All data contained herein is accurate to the best of my ability to ascertain, and is drawn from the Company’s Prospectus, Statement of Additional Information, and fact sheets. All tables, charts and graphs are produced by me using data acquired from pertinent documents; historical price data from Yahoo! Finance. Data from any other sources (if used) are cited as such. All opinions contained herein are mine unless otherwise indicated. The opinions of others that may be included are identified as such and do not necessarily reflect my own views. Before investing, readers are reminded that they are responsible for performing their own due diligence; they are also reminded that it is possible to lose part or all of their invested money. Please invest carefully. 1 ” QLC: Large-Cap ETF With High-Quality Stocks .” 2 Not counting ETNs (of which there are about six) or leveraged/inverse funds (of which there are ~ 27). 3 I have discussed one such tool already, when I introduced “expense margins.” As I prepared this article I came across two more: return on NAV ( RoNAV ) and expense efficiency rating ( EER ). RoNAV has appeared in a few of my recent articles, and reflects the relationship between NAV and the net income generated therefrom. EER is meant to capture the difference between the expenses actually paid in a fund and the expense ratio on which many investors place great weight. A discussion of what these data represent – and how they are determined – can be found in my blog . 4 Of course, I will not discourage you from reading all of the articles if your tolerance for boredom is sufficiently high. 5 The Guggenheim Russell MidCap Equal Weight ETF (NYSEARCA: EWRM ). EWRM will change index to the S&P MidCap 400 index on January 27, and will become the Guggenheim S&P MidCap 400 Equal Weight ETF (EWMC). 6 Transition of Guggenheim ETFs to S&P Dow Jones Indices, a list of key considerations and FAQs. The Guggenheim Russell 2000 Equal Weight ETF (NYSEARCA: EWRS ) will become the Guggenheim S&P SmallCap 600 Equal Weight ETF (EWSC). Available here . 7 ETF.com adds some additional considerations to the reasons for the merger: 1) EWRI has not traded well, with only an approximately $216,410.00 in average daily volume (compared to RSP ‘s $64.14 million average); 2) on December 23, 2014, PowerShares issued an ETF identical to EWRI – the PowerShares Russell 1000 Equal Weight ETF (NYSEARCA: EQAL ). Implied – there’s not enough market for the ETFs to support two funds. 8 Per ETF.com . 9 Guggenheim FAQs, note 4, above. 10 See EER in note 2, above. 11 An EER > 1 means that it is spending more on expenses than “anticipated” in its expense ratio. 12 See RoNAV in note 2, above. 13 I gave the fund a thorough going-over in ” Guggenheim s RSP: Equal Weight Or Dead Weight? ” I used it for comparison purposes in the QLC article mentioned above, and as a component for a trial portfolio in ” Brown s Permanent Portfolio Vs. Porter s ETF Retirement Portfolio .” 14 Of course, as with any figure related to returns, higher is usually going to be better, but I do not expect to have a clear indication of what sort of RoNAV to expect from large-cap ETFs until I have gotten further through the project. 15 Guggenheim ETFs Prospectus, p. 6. 16 ETF.com . 17 The index itself does not appear to be available yet, and I based the comparison on a list of the top 50 S&P 500 companies generated in finviz.com . 18 On April 27, 2006, RSP underwent a 4-for-1 split. I have adjusted the prices prior to the split to reflect one-fourth of their actual value. 19 I have dropped EWRI from this and subsequent charts because: a) its performance has not been that impressive, and anyway, b) it will cease to exist in less than two months. 20 All prices are closing prices as of the day cited. 21 There are no overlaps between RPV and RPG , and this is why they are considered “pure” – the formula that determines if a holding is a value stock excludes the possibility of a growth stock being included, and vice versa. Since no specific formula is needed (in principle) to determine which stocks have the largest market capitalization, there is no consideration given to “value” or “growth” conditions. 22 XLG did come close on November 3, when its price closed at $148.31 – missing the high by $0.46. 23 Expense margin, expense ratio, expense efficiency rating, return on NAV, yield, and the two CAGRs. I am also considering counting the recovery period from recession and some meaningful assessment for performance over the recent correction.

The Amazing Beauty Of Equal Weight

Summary Most investors look only at capital-weighted indices. They miss two positive anomalies of equal weight. Here are equal-weight ideas and ETFs for passive investing and tactical allocation. Capital-weighted indices in the broad market and specific sectors are getting all the attention of investors. This article aims at proving that equal-weighted indices are better investment vehicles for passive investing and tactical allocation. We will stay in the S&P 500 universe. A few words of theory The statistical bias in favor of an equal weighted set of stocks over the same set weighted on market capitalization has two reasons: Size effect: Lower-range large-caps usually perform better than mega-caps. Rebalancing: Periodically equalizing position sizes in dollar amount among a big set of stocks is a simplistic “buy-low-sell-high” strategy. Simplistic, but not stupid. The interest bias in favor of capital-weighted indices has also good reasons: It is a good representation of real economic activity. Inheritance of the pre-computer era, capital-weighted indices are easier to calculate manually. They are linear functions of share prices, adjusted of structural and corporate events (component list modifications, splits, public offerings, buybacks). It generates less transaction costs for a mutual fund or ETF following it. Equal-weighted S&P 500 The next chart shows in red the equity curve of all S&P 500 stocks, equal-weighted rebalanced on weekly opening between January 1999 and September 2015. The blue line is SPY . In both cases, dividends are accounted and reinvested. It is impossible to implement as a strategy for an individual investor because of the capital needed to absorb transaction costs. Moreover, there is an ETF for that: the Guggenheim S&P Equal Weight ETF (NYSEARCA: RSP ). Since inception on 4/24/2003, it has an annualized excess return of 2% over SPY, making it a better instrument of passive index investing. On the same period, the theoretical annualized excess return of equal-weight S&P 500 with dividends is 3.5%. The difference can be explained by trading costs, management fees, rebalancing frequencies. Next chart: RSP in red versus SPY in blue since 4/24/2003: (click to enlarge) S&P 500 with sectors in equal weight The next chart shows the equity curve of an equal weight portfolio of the 9 Select Sector SPDR ETFs rebalanced weekly: utilities (NYSEARCA: XLU ), energy (NYSEARCA: XLE ), materials (NYSEARCA: XLB ), financials (NYSEARCA: XLF ), healthcare (NYSEARCA: XLV ), industrials (NYSEARCA: XLI ), IT & telecom (NYSEARCA: XLK ), consumer staples (NYSEARCA: XLP ), and consumer discretionary (NYSEARCA: XLY ). Here, the size effect is questionable, but the rebalancing bias applies. (click to enlarge) Individual sectors in equal weight Guggenheim has also sector equal-weight ETFs. The next table compares their annualized returns with the Select Sector SPDR series since inception date (11/1/2006), and the theoretical return of stocks rebalanced weekly in equal weight: Sector Stocks Eq. Weight weekly Eq. weight ETF Ann. return Cap. weight ETF Ann. return Cons. Disc. 9.76% (NYSEARCA: RCD ) 8.63% XLY 9.96% Industrials 9.08% (NYSEARCA: RGI ) 7.64% XLI 7.01% Cons. Staples 12.61% (NYSEARCA: RHS ) 11.72% XLP 9.92% Materials 7.63% (NYSEARCA: RTM ) 6.73% XLB 5.16% Energy 2.83% (NYSEARCA: RYE ) 1.97% XLE 3.26% Financials 2.46% (NYSEARCA: RYF ) 0.02% XLF -2.63% Healthcare 14.91% (NYSEARCA: RYH ) 14.18% XLV 10.96% Technology 8.41% (NYSEARCA: RYT ) 6.95% XLK 8.32% Utilities 7.24% (NYSEARCA: RYU ) 6.33% XLU 5.59% In theory, equal weight brings a better or similar return in all sectors, except energy. After management fees and tracking errors, the consumer discretionary and technology equal-weight ETFs are also failing. Equal weight of equal-weighted sectors As a last paragraph, here is the return since the inception of the Guggenheim ETFs in equal-weight rebalanced weekly compared with the Sector SPDR ETFs in equal weight, RSP and SPY. 1/01/2006-09/16/2015 Guggenheim series eq. weight SPDR series eq. weight RSP SPY Ann. Return 8.35% 7.16% 7.43% 6.31% The solutions with individual stocks in equal weight for each sector work better (1st and 3rd columns), which makes sense: size effect is more beneficial. For an individual investor seeking an equal-weight strategy on the broad index, RSP may be a better solution than the Guggenheim series in equal weight after transaction costs, depending on transaction fees and portfolio size. Conclusion With the exception of the energy sector, equal weight has been systematically superior to capital weight in the S&P 500 universe on the 2 last market cycles (1999-2015). In ETF implementations, fees and tracking errors result in a lag for 2 other sectors. Investors can find here useful investing instruments and ideas for passive investing and sector tactical allocation. Data and charts: Portfolio123 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: I short the S&P 500 for hedging purposes