Tag Archives: top-ten

PMR Vs. RTH: Using Your Discretion

Consumer Cyclicals and Consumer Non-Cyclicals may be invested in separate ETFs. An alternative is to choose a ‘blended’ Consumer Cyclicals and Non-Cyclical funds. Blended funds happen to be top performers in their asset class. Consumers drive the economy of the United States. Household spending accounts for, roughly, 70% of the US economy. Some of that spending is done of necessity: food, clothing, transportation, home heating and medical costs to name a few. These fundamental things of life which one must purchase, as time goes by, are classified as ‘ non-discretionary ‘ items. On the other hand, consumer capital which remains after the bills have been paid may be spent as one chooses: entertainment, travel and leisure, home improvements or durable goods. This is classified as ‘discretionary spending’. So important are the differences between discretionary and non-discretionary spending, investment fund managers carefully delineate the two into different sectors. Further, the non-discretionary sector is considered a ‘defensive’ sector since consumers must continue to spend for goods and services produced by those companies which in that sector; whereas discretionary spending is considered cyclically sensitive , that is to say that consumers will spend less on certain items when the economy slows and consumers are uncertain about jobs and incomes. The question the potential investor might ask, especially in the light of economic global uncertainty, is it prudent to invest in the consumer discretionary sector if the economy might contract a bit? The answer is quite general: it is extraordinarily difficult to pick market tops or bottoms. The best any individual investor might do is to accumulate shares through disciplined investing and dollar cost averaging over both good and bad times. If so, does it make sense to have both types in a portfolio? Fortunately, a third alternative is available. There are retail ETF investment products which offer a blend of both consumer cyclical and non-cyclical companies. Two of these are top performers: the Market Vectors Retail ETF (NYSEARCA: RTH ) and the PowerShares Dynamic Retail Portfolio ETF (NYSEARCA: PMR ) . (click to enlarge) According to Van Eck Global , RTH tracks their own Market Vectors US Listed Retail 25 Index (MVRTHTR) , “… a rules based index intended to track the overall performance of 25 of the largest US listed, publicly traded retail companies …” The fund consists of 25 US listed retailers. According to Invesco , PMR is based on the Dynamic Retail Intellidex Index filtering companies based on “… price momentum, earnings momentum, quality, management action, and value …” The fund consists of 30 US listed retailers. Although the funds come under the heading of ‘Consumer Discretionary’ (using the Seeking Alpha ETF Hub filter ) , they are actually a blend of both. The Market Vectors Retail fund blends 55.8% of Consumer Discretionary, with 34.2% of Consumer Staples and some Health Care 9.9%. The PowerShares Dynamic Retail Portfolio is a blend of 50.09% Consumer Discretionary, 41.95% Consumer Staples, 2.75% Industrials, 2.65% IT and 2.54% Materials. Hence both funds are similar in the number of holdings but differ in the underlying tracking indexes; both funds have comparatively few holdings yet perform rather well. The table below lists four of best performing funds in this sector. Fund Name Number of Holdings 1-Month 1-Year 3 Year Type Market Vectors Retail ETF (RTH) 26 -2.75% 21.63% 75.13% Blend of cyclical, non-cyclical and HealthCare Consumer Discretionary Select Sector SPDR ETF (NYSEARCA: XLY ) 88 -2.71% 14.13% 69.11% Consumer Discretionary PowerShares Dynamic Retail Portfolio ETF (PMR) 30 -3.64% 12.79% 55.46% Blend of cyclical, non-cyclical, IT, Industrials and Materials Vanguard Consumer Discretionary ETF (NYSEARCA: VCR ) 385 -2.94% 12.67% 68.92% Consumer Discretionary Data from Seeking Alpha ETF Hub Since RTH leads the similarly constructed PMR, it would be interesting to make a side-by-side comparison and perhaps determine what makes the difference. Surprisingly, the funds have few companies in common. With the exception of Home Depot (NYSE: HD ) at 8.57% of RTH vs 4.93% of PMR, the weighting of the other companies in common, are roughly the same. RTH with Weightings RTH with Weightings PMR with Weightings PMR with Weightings Costco (NASDAQ: COST ) 5.07% Ltd Brands (NYSE: LB ) 3.07% Costco 5.033% Ltd Brands 5.41% CVS Caremark (NYSE: CVS ) 6.90% Target (NYSE: TGT ) 4.35% CVS Caremark 4.78% Target 4.913% Home Depot 8.57% Walgreen (NASDAQ: WBA ) 5.69% Home Depot 4.93% Walgreen 5.041% Kroger (NYSE: KR ) 4.43% Whole Foods (NASDAQ: WFM ) 1.47% Kroger 5.274% Whole Foods 2.71% Data from Van Eck and Invesco Next, since the top ten heaviest weighted companies affect the overall performance of a fund, the funds ten heaviest weightings should be compared. The bar charts below, demonstrates that PMR’s top ten heaviest weighted holdings are pretty much evenly distributed, and slightly biased towards Consumer Staples at about 56.253% of those top ten. It should also be noted that about 46.54% of the fund’s total holdings are concentrated in the top ten. Data from Invesco The next table demonstrates that RTH’s top ten heaviest weighted holdings are not as evenly distributed as PMR and has a Consumer Discretionary bias at 54.85% of the top ten. Further a large portion of that is concentrated in the top two holdings Amazon (NASDAQ: AMZN ) and Home Depot , accounting for 33.06% of the top ten and almost 22% of the funds entire holdings. Lastly, 65.63% of RTH’s total holdings are concentrated in those top ten holdings. Data from Van Eck Hence, it seems that RTH has a slightly more bias towards Consumer Cyclicals than PMR and is skewed towards its heaviest weighted holdings (as of September 18), and then towards two of those top ten. On the other hand, PMR has a more even distribution of its top ten holdings and those top ten holdings account for less than half of the portfolio’s total holdings. Lastly, a few ETF technical items need to be compared. Fund and Inception Date 30 day SEC Yield Shares Outstanding Net Assets Net Expense Ratio Price/ Earnings 3 year Beta Open Option Interest RTH 12/20/2011 1.19% (annual Distributions) 2,671,531 $204.2 million 0.35% capped until 2/1/2016 20.00 0.88 Yes PMR 10/26/2005 0.70% 650,000 $25.103 million 0.63% 20.83 0.89 Yes Data from Invesco and VanEck The entire point of the matter is this: for a disciplined investor with limited funds, building a well-diversified concise portfolio of ETFs with the long term in mind, there’s no need to allocate towards Consumer Cyclicals and Non-Cyclicals separately. Instead, by selecting one of the available funds with a blend of Consumer Cyclicals and Non-Cyclical, will result in a far more efficient way to invest, and by needing to allocate into one blended fund instead of two separate funds will save on management fees and commissions over the long term. 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: CFDs, spreadbetting and FX can result in losses exceeding your initial deposit. They are not suitable for everyone, so please ensure you understand the risks. Seek independent financial advice if necessary. Nothing in this article should be considered a personal recommendation. It does not account for your personal circumstances or appetite for risk.

The Guggenheim S&P 500 Equal Weight Utilities ETF: Utilitarianism

An alternatives to a traditional government bond holding. Utilities offer steady, consistent returns and are largely immune to the business cycle. This equal weight utilities fund is biased towards low dividend risk, yet has a respectable return. The world of investing has changed much over the past five years due to the financial crises of 2008 and its subsequent recession. The realization that investing may never be the same is a growing one, particular when it comes to income. As it stands now, even if central banks are able to normalize policy, it still may be years before government bond yields normalize, and that’s under the assumption that all advanced economies will continue to grow uniformly. Recent economic reversals in newly emerged economies, particularly the “BRICS” along with the collapse in commodity prices and the astonishing overproduction of crude petroleum have all weighed on high quality assets yields. High quality government securities have been pressed to their limits. Furthermore, cross market technology, institutional trading, pension fund demands and ‘carry asset’ strategies have created much higher volatility in the once mundane government bond market. The point of the matter is that the individual investor may be saving for retirement in a completely new world. The strategy of holding long term government bonds as a portfolio cornerstone has become an ‘old world’ concept. Utilities assets may be one replacement solution for government bond holdings. There are several to choose from, and one of the top yielding in the class is the Guggenheim S&P 500 Equal Weight Utilities ETF (NYSEARCA: RYU ) . According to Guggenheim, the fund “… Seeks to replicate as closely as possible, before fees and expenses, the performance of the S&P 500 Equal Weight Index Telecommunication Services & Utilities. ..” A word about the ‘equal weight’ S&P Index: according to S&P, the equal weight S&P 500 index is an alternative version of its renowned S&P 500 market cap weighted index. In the equal weight index each S&P 500 member constitutes 20 basis points of the S&P 500 index with a quarterly rebalancing in order to prevent excessive turnover. The S&P 500 equal weight Telecommunications and Utility Index is merely a subset of the equal weight S&P 500 index. Since the fund is based on ‘equal weightings’, it seems superfluous to analyze the top ten holdings. Instead, since the objective here is dividend risk assessment it would be more useful to analyze the potential risk to regular distributions. This may be achieved by comparing a company’s payout ratio to the dividend. Since a payout ratio is defined to be the proportion of earnings paid out as dividends, the lower the payout ratio the less likely the dividend will be reduced and conversely, the higher the payout ratio, the more likely a dividend may be reduced. The fund has 34 holdings and an average dividend yield of 4.0571%. The average payout ratio is 73.62%. (This is less than the S&P 500 market cap weighted payout ratio of almost 85). Five of the holdings have payout ratios of over 100%; 21 of the 34 holdings are below the average payout ratio; 11 are above; 2 have non applicable payout ratios; 14 of the holdings are above the fund’s average yield, and 20 are below the fund’s average yield. Hence, the fund is biased towards the ability of the holding to continue to pay or increase dividends. The chart below summarizes the payout ratio (in blue) and the yield (in red). (click to enlarge) (Data from Reuters and Guggenheim) The 10 lowest payout ratios average out to 44.39% with an average yield of 3.563%. There are no Telecom Service companies in the fund with a payout ratio low enough to place it in the ten lowest of the fund. (Data from Reuters and Guggenheim) The 10 holdings with the lowest payout ratio are summarized in the table below. Company Type Price/Earnings (TTM) Price/Cash Flow Price/Book Divided Yield Payout Ratio AES Corp (NYSE: AES ) Independent Power and Renewable 9.70 3.24 2.14 3.31% 23.43% Edison International (NYSE: EIX ) Electric Utility 12.60 5.52 1.72 2.80% 33.70% PPL Corp (NYSE: PPL ) Electric Utility 10.84 6.49 2.11 4.81% 38.81% Dominion Resources (NYSE: D ) Multi-Utility 24.29 12.25 3.40 3.65% 41.43% Scana Corp (NYSE: SCG ) Multi-Utility 10.29 6.69 1.44 4.04% 43.98% Nextera Energy (NYSE: NEE ) Electric Utility 15.56 8.11 2.16 3.02% 45.61% Sempra Energy (NYSE: SRE ) Multi-Utility 17.77 9.24 2.07 2.88% 48.80% Public Service Enterprise (NYSE: PEG ) Multi-Utility 11.13 6.56 1.61 3.85% 52.13% Eversource Energy (NYSE: ES ) Electric Utility 16.76 9.80 1.50 3.46% 55.99% Exelon Corp (NYSE: EXC ) Electric Utility 11.59 4.20 1.15 3.95% 56.51% (Data from Reuters and Guggenheim) There are, as one might expect, different types of Utility Companies. Diversified Telecommunications includes entertainment, mobile, internet and voice services; Electric Utilities are, as the name implies, electricity providers although some, Duke Energy for instance, provide natural gas as well; Independent Power and Renewables generate power through renewable resources like wind and solar and also install residential and business solar systems; Multi-Utilities provide natural gas, electricity, storage facilities and pipeline delivery. (Data from Reuters and Guggenheim) For a few detailed examples: AES is global, providing services to Chile, Columbia, Argentina, Brazil, Central America, the Caribbean, Europe and Asia. AES generates renewable power from solar, wind, hydro, bio mass and landfill gas. Scana Corporation, classified by the Guggenheim fund as ‘Multi-Utility’ provides natural gas as well as fiber-optic and telecomm services. Dominion Resources distributes natural gas, electricity, natural gas storage, LNG transportation and risk management services. It also has an equity stake in a joint venture with Caiman Energy called Blue Racer , a Marcellus Shale natural gas processing company; neither are publically owned companies. NiSource Inc (NYSE: NI ) is a holding company providing services through 13 subsidiaries for gas, electric and pipeline as well as a financing service. Many of these companies also hedge or trade derivative contracts. The point being that for utility funds with only a few holdings, it’s worth examining the descriptions or company profiles of the holdings to fully understand the depth of the individual holdings. (click to enlarge) Lastly, the fund has a reasonably long history, incepted in November of 2006. Its expense ratio is reasonable at 0.40%. Its total net assets are over $112,487,000 distributed over 34 holdings with a cash reserve. The average daily volume is 186,066 shares per day and there are 1.6 million outstanding shares. It currently trades at a slight discount, $-0.08 per share to NAV. The fund has paid a total of $17.80 in quarterly dividends since inception. Hence, the fund provides a reasonable yield in today’s low yield environment, low volatility with a beta of 0.87 and reasonable liquidity. Should the global economy contract because of a readjustment in the Chinese economy, and the U.S. economy remains reasonably strong with depressed commodity prices, a utility fund such as the Guggenheim S&P 500 Equal Weight Utilities ETF would do well generating good returns with relative safety for some time to come. 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: Additional disclosure: CFDs, spreadbetting and FX can result in losses exceeding your initial deposit. They are not suitable for everyone, so please ensure you understand the risks. Seek independent financial advice if necessary. Nothing in this article should be considered a personal recommendation. It does not account for your personal circumstances or appetite for risk.

Today’s Strongly Competitive Wealth-Builder Sector ETF Investment

Summary From a population of some 350 actively-traded, substantial, and growing ETFs, this is a currently attractive addition to a portfolio whose principal objective is wealth accumulation by active investing. We daily evaluate future near-term price gain prospects for quality, market-seasoned ETFs, based on the expectations of market-makers [MMs], drawing on their insights from client order-flows. The analysis of our subject ETFs’ price prospects is reinforced by parallel MM forecasts for each of the ETF’s ten largest holdings. Qualitative appraisals of the forecasts are derived from how well the MMs have foreseen subsequent price behaviors following prior forecasts similar to today’s. Size of prospective gains, odds of winning transactions, worst-case price drawdowns, and marketability measures are all taken into account. Today’s most attractive ETF Today’s most attractive ETF is the SPDR S&P Retail ETF (NYSEARCA: XRT ). The investment seeks to provide investment results that, before fees and expenses, correspond generally to the total return performance of an index derived from the retail segment of a U.S. total market composite index. In seeking to track the performance of the S&P Retail Select Industry Index (the “index”), the fund employs a sampling strategy. It generally invests substantially all, but at least 80%, of its total assets in the securities comprising the index. The index represents the retail industry group of the S&P Total Market Index (“S&P TMI”). The fund is non-diversified (Description from Yahoo Finance) Figure 1 (used with permission) The vertical lines of Figure 1 are a visual history of forward-looking expectations of coming prices for the subject ETF. They are not a backward-in-time look at actual daily price ranges, but the heavy dot in each range is the ending market quote of the day the forecast was made. What is important in the picture is the balance of upside prospects in comparison to downside concerns. That ratio is expressed in the Range Index [RI], whose number tells what percentage of the whole range lies below the then current price. Today’s Range Index is used to evaluate how well prior forecasts of similar RIs for this ETF have previously worked out. The size of that historic sample is given near the right-hand end of the data line below the picture. The current RI’s size in relation to all available RIs of the past 5 years is indicated in the small blue thumbnail distribution at the bottom of Figure 1. The first items in the data line are current information: The current high and low of the forecast range, and the percent change from the market quote to the top of the range, as a sell target. The Range Index is of the current forecast. Other items of data are all derived from the history of prior forecasts. They stem from applying a T ime- E fficient R isk M anagement D iscipline to hypothetical holdings initiated by the MM forecasts. That discipline requires a next-day closing price cost position be held no longer than 63 market days (3 months) unless first encountered by a market close equal to or above the sell target. The net payoffs are the cumulative average simple percent gains of all such forecast positions, including losses. Days held are average market rather than calendar days held in the sample positions. Drawdown exposure indicates the typical worst-case price experience during those holding periods. Win odds tells what percentage proportion of the sample recovered from the drawdowns to produce a gain. The cred(ibility) ratio compares the sell target prospect with the historic net payoff experiences. Figure 2 provides a longer-time perspective by drawing a once-a week look from the Figure 1 source forecasts, back over two years. Figure 2 (used with permission) What does this ETF hold, causing such price expectations? Figure 3 is a table of securities held by the subject ETF, indicating its concentration in the top ten largest holdings, and their percentage of the ETF’s total value. Figure 3 source: Yahoo Finance XRT apparently takes a low-concentration approach to holdings, with an average of 1¼% of its assets in each of its top ten commitments. This provides a wide dispersion of holdings among competitive investment contestants in an industry where success rewards can be huge, while failures may be complete. If the remaining 88% of assets are distributed on a comparable basis 99 separate bets may be being made, offering great diversification, as well as dilution of encountered bonanzas. Where ultimate payoffs are less dependent on initial capital commitment size, this may be an advantaged strategy. Figure 4 is a table of data lines similar to that contained in Figure 1, for each of the top ten holdings of XRT. Figure 4 (click to enlarge) In an industry as unpredictably dynamic as this, wide variations in market experience seem to be the rule. Column (5) contains the upside price change forecasts between current market prices and the upper limit of prices regarded by MMs as being worth paying for price change protection. The average of +10.2% of the top ten XRT holdings is near the population average of all 2600+ equities MM forecasts of +13.4%. It is about double the upside forecast for SPY price change prospects. The other side of the coin is column (6), which shows what actual worst-case price drawdowns have been typical in the 3 months following each time there has been a forecast like those of the present day. Those risk exposures have been about -7% in the holdings top ten, less than -9 by equities at large, and only -3.2% on the SPY ETF. But these holdings are attractive reward tradeoffs between returns and risks, with the top ten (column 14) at a ratio of 1.4, compared to equities overall at 1.6 times. The market average of SPY provides a ratio of 1.6 times risk avoidance. Another qualitative consideration is the credibility of the ten XRT big holdings after previous forecasts like today’s. The net average price change (column 13) of the ten has been only 0.5 times the size of the upside forecast average, +4.8% compared to +10.2%. The equity population’s actual price gain achievement, net of losses has been a pitiful +3.3% compared to promises of 13.4%. The ability of XRT holdings to recover from those worst-case drawdowns and achieve profits occurred in 75% of experiences. The equity population only recovered less than two thirds of the time, and while the SPY experiences were more consistent like the ten XRT holdings, the achieved gains were much smaller. SPY has had only +3.2% gains previously from like forecasts of +5.2%. The 20 top prospective equities from our overall equity population have superior credentials historically, given the past performance of present MM price range outlooks. Their reward-risk score of 1.8 is the highest of the four blue row averages. Their price recovery ability at 89% contributes mightily to their upside price forecast credibility and their % payoff achievement. Moving to targets more quickly than others has generated annual rates of gain (11) three times the XRT holdings and five times the rate of the population and market average. Conclusion XRT provides competitive forecast price gains in comparison to many other sector ETFs, supported by the outlooks for their largest holdings. Both the ETF and many of its major holdings offer strong prospects in near-term price behaviors, demonstrated by previous experiences following prior similar forecasts by market makers. In a market environment many consider to be at risk they present a reasonable defensive alternative. 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.