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Market-Makers Compare Coming Prices For: Major Market Index ETFs

Summary Behavioral Analysis of the players moving big blocks of securities in and out of $-Billion portfolios provides insights into their expectations for price changes in coming months. Portfolio Managers have delved deeply into the fundamentals urging shifts in capital allocations; now they take actions on their private, unpublished conclusions. These block transactions reveal why. Multi-$Million trades strain market capacity, require temporary capital liquidity facilitation and negotiating help, but are necessary to accomplish significant asset reallocations in big-$ funds. Market-making firms provide that assistance, but only when they can sidestep risks involved by hedge deals intricately designed to transfer exposures to willing (at a price) speculators. Analysis of the prices paid and deal structures involved tell how far coming securities prices are likely to range. Those prospects, good and bad, can be directly compared. This is a Behavioral Analysis of Informed Expectations It follows a rational examination of what experienced, well-informed, highly-motivated professionals normally do, acting in their own best interests. It pits knowledgeable judgments of probable risks during bounded time periods against likely rewards of price changes, both up and down. It involves the skillful arbitrage of contracts demanding specific performances under defined circumstances. Ones traded in regulated markets for derivative securities, usually involving operational and/or financial leverage. The skill sets required for successful practice of these arts are not quickly or easily learned. The conduct of required practices are not widely allowed or casually granted. It makes good economic sense to contract-out the capabilities involved to those high up on the learning curve and reliability scale. It requires, from all parties involved, trust, but verification. What results is a communal judgment about the likely boundaries of price change during defined periods of future time. Those judgments get hammered out in markets between buyers and sellers of risk and of reward. The questions being answered are no longer “Why” buy or sell the subject, but “What Price” makes sense to pay or receive. All involved have their views; the associated hedge agreements translate possibilities into enforceable realities. We simply translate the realities into specific price ranges. Then the risk and benefit possibilities can be compared on common footings. A history of what has followed prior similar implied forecasts may provide further qualitative flavor to belief and influence of the forecasts. Certainty is a rare outcome. Subjects of this analysis Major market indexes are tracked by Exchange Traded Funds of different varieties; all of the major variants are covered here. There are the simple, direct price trackers of indexes that cannot be invested in directly, ETFs often used by market professionals. The ETFs more frequently traded in by public investors may carry prices at levels more conveniently accommodated by portfolios of individual investors. There are leveraged long ETFs with prices structurally engineered (and maintained) to move 2x or 3x the movement of the index being tracked. And there are leveraged short ETFs engineered and maintained to move the inverse of the price of the index being tracked. Here is a quick review of the market characteristics of this article’s subjects, their securities names and symbols and position now in current-year price ranges. Figure 1 (click to enlarge) These symbols are arranged first by the Indexes which can’t be directly invested in, then for each of those indexes the most widely utilized unleveraged ETF, the most heavily long-leveraged ETF, and the inverse, or short-structured ETF. There is no well-recognized symbol for an Index of mid-cap stocks, but three rows of ETFs in the same character sequence as the pattern for the recognized four (boldfaced) indexes close the table. Market liquidity is addressed in the first four columns of Figure 1. What leaps out is the huge capital commitment made, apparently by individual investors, of $66 billion in the Vanguard Mid-Cap ETF (NYSEARCA: VO ). At its average daily volume of trading, less than half a million shares, it would take 5 years for all investors to escape. Other ProShares mid-cap ETFs, like the ProShares Ultra MidCap 400 ETF ( MVV) and the ProShares UltraShort MidCap400 ETF ( MZZ ), also have less liquid involvements of double-digit days to turn over the capital investments, while most other index ETFs need less than 10 days. The largest, the SPDR S&P 500 Trust ETF (NYSEARCA: SPY ) needs only 6 market days to replace its whole commitment. The trade-spread cost to trade these ETFs is typically in single basis points of hundredths of a percent. That is in the same region of a $7 commission on a $10,000 trade ticket. Price-earnings ratios for these subjects range from 15 times earnings to 22 times. But appear to be of little influence in differentiating between their selection for portfolio participation. Notions of capital size or leverage seem to be of much more import. Where behavioral analysis contributes Investor preferences among these ETFs during the past year are indicated in the last two columns of Figure 1, reflecting on their price range experiences in that period, shown in the prior two columns. The Nasdaq 100 index [NDX] fluctuated the most, by 25% low to high, while the S&P500 traveled by only 14%. From a portfolio management viewpoint, what matters most is where holdings are priced now, compared with where their prices may go in coming months. Prices are, after all, what determine the progress of wealth-building, and are what can be a source of expenditure provision as an alternative to interest or dividend income. Ultimately price changes are the principal portfolio performance score-keeping agent. Where prices are now, in comparison to where they have been provides perspective as to what may be coming next. If prices are high in their past year’s range, for them to go higher means that their surroundings must also increase. If price is low relative to prior year scope, a price increase represents recovery. As you think about the security’s environment, does it seem likely in coming months to be one of stability, of increase, or of possible decline? How would such change be likely to impact the security under consideration? First there is a need to be aware of what has recently been going on. The measure for that is the 52-week Range Index. The 52 week RI tells what proportion of the price range of the last 52 weeks is below the present price. A strong, rising investment likely will have a large part of its past-year price range under where it is now. Something above 50, the mid-point of the range is likely, all the way up into the 90’s. At the top of its year’s experience the 52wRI will be 100. At the bottom the 52wRI will be zero. All the 52wRI can do is provide perspective. A look to the future requires a forecast. With that, expressed in terms of prospective price changes, both up and down, a forecast Range Index, 4cRI or just RI, gives a sense of the balance between upcoming reward and risk. This is what behavioral analysis of the actions of large investment organizations, dealing with the professional market-making community, can do. The process of making possible changes of focus for sizable chunks of capital produces the careful thinking that lies behind such forecasts of likely coming prices. Hedging-implied price range forecasts While the four boldfaced widely-recognized market indexes in Figure 1 can’t be directly invested in, professionals in the market-making community use security derivatives of them to perform large-scale hedging of portfolios on an asset class-wide basis. Hence we have forecast implications for those four indexes, as well as for the ETFs listed. Figure 2 tells what the professional hedging activities of the market-makers imply for price range extremes of the symbols of Figure 1, in the same sequence. Columns 2 through 5 are forecast or current data, the remaining columns are historical records of market behavior subsequent to prior instances of forecasts like those of the present. Figure 2 (click to enlarge) A lot of information is contained here, much of potential importance. Some study is deserved. Exactly the same evaluation process is used to derive the price range forecasts in columns 2 and 3 for all the Indexes and ETFs, regardless of leverage or inversion. Column 7’s values are what determine the specifics of columns 6 and 8-15. Each security’s row may present quite different prior conditions from other rows, but that is what is needed in order to make meaningful comparisons between the ETFs today for their appropriate potential future actions. Column 7 tells what balance exists between the prospects for upside price change and downside price change in the forecasts of columns 2 and 3 relative to column 4. The Range Index numbers in column 7 tells of the whole forecast price range between each row of columns 2 and 3, what percentage lies between column 3 and 4. It is what part of the forecast price range that is below the current market quote. That proportion is used to identify similar prior forecasts made in the past 5 years’ market days, counted in column 12. Those prior forecasts produce the histories displayed in the remaining columns. Of most basic interest to all investment considerations is the tradeoff between RISK and REWARD. Column 5 calculates the reward prospect as the upside percentage price change limit of column 2 above column 4. Proper appraisal of RISK requires recognition that it is not a static condition, but is of variable threat, depending on its surroundings. When the risk tree falls in an empty forest of a portfolio not containing that holding, you have no hearing of it, no concern. It is only the period when the subject security is in the portfolio that there is a risk exposure. So we look at each subject security’s price drawdown experiences during prior periods of similar Range Index holdings. And we look for the worst (most extreme) drawdowns, because that is when investors are most likely to accept a loss by selling out, rather than holding on for a recovery and for the higher price objective that induced the investment originally. Columns 5 and 6 are side by side not of an accident. While not the only consideration in investing, this is an important place to start when making comparisons between alternative investment choices. To that end, a picture comparison of these Index and ETF current Risk~Reward tradeoffs is instructive. Please see Figure 3. Figure 3 (used with permission) In this map the dotted diagonal line marks the points where upside price change Prospect (green horizontal scale) equals typical maximum price drawdown Experiences (red vertical scale). Of considerable interest is that the subjects all tend to cluster loosely about that watershed. This despite the fact that several short structured ETF subjects are present, along with several strongly (3x) leveraged ETFs of twin subject matter. If we were in a cheap market situation, or a threatening overpriced one, there would be strong clustering of each type of ETF structure, long and short, with emphasis by the leveraged ones. Instead, this is a mildly confused market with no clear indication of which way it may head next. Well, what about differing focus of investment subjects – giant capitalizations of the DJIA, or technology biases of the NDX, or small capitalizations of the RUT? The most restrained and best advantaged tradeoff is in [2] for the NDX index. Its ETFs are the PowerShares QQQ Trust ETF ( QQQ) at [17] and the leveraged ProShares UltraPro QQQ ETF ( TQQQ) at [8]. The short ProShares UltraPro Short QQQ ETF ( SQQQ) has strong upside prospects, along with ample risk involvement. Only the ProShares UltraPro Short Russell 2000 ETF ( SRTY) at [12] appears more hazardous, and without adequate redeeming reward proportions. Its levered relative, the ProShares UltraPro Russell 2000 ETF ( URTY) at [1], of the RUT and the iShares Russell 2000 ETF ( IWM) clan, may be over-reaching a bit. This kind of comparing between alternative investments is what often distinguishes the experienced investor from the neophyte. There are so many intriguing possible stories of investment bonanzas that it may be difficult to keep focus. And for the newbie investor deciding on what combinations of attributes may be most important is a daunting challenge. An advantage of the behavioral analysis approach is that price prospects suggested by fundamental and competitive analysis are being vetted by experienced, well-informed market professionals on both sides of the trade. Looking back at figure 2, there is a condition that may disrupt the organized notions drawn from Figure 3. Column 8 tells what proportion of the prior similar forecasts persevered in recovering from those worst-case drawdowns, and for the resolute holder turned into profitable outcomes, often reaching their targeted price objectives. Batting averages of 7 out of 8 and 9 out of 10 are quite possible to accomplish by active investors. Column 10 tells how large the payoffs were, not only of the recoveries, but including the losses. And those gains, in comparison with the forecast promises of column 5 offer a measure of the credibility of the forecast. There will be circumstances where credibility will be low and recovery odds worse than 50-50. When such conditions appear pervasive, cash is a low-risk temporary investment, sometimes the treasured resource. Conclusion Major market indexes currently present an array of reward-to-risk alternatives, but not in any clearcut organization shouting “do this, don’t do that.” Safety-seekers might favor Nasdaq stocks or ETFs over other securities, but the advantages are hardly compelling. At present elaborate preference systems do not offer much advantage, but that may be a passing condition. There are major benefits from using behavioral analysis to extend and enrich conventional fundamental analysis. A principal plus is the ability to make opportunity comparisons between very dissimilar situations. Additional comparative studies of ETFs are in preparation, they should provide further profit opportunities, as they already have this year.

Cancer Immunotherapy ETF Takes Curious Approach To Asset Allocation

Summary The Loncar Cancer Immunotherapy ETF was launched recently with the goal of targeting companies actively engaged in the treatment of cancer through immunotherapy. The fund’s investment in both healthcare mega-caps and biotech small-caps provide very different exposure to immunotherapy treatments. This fund looks more like a broader healthcare ETF than a pure play on cancer immunotherapy. The ETF world is becoming increasingly niche oriented lately and another niche ETF – the Loncar Cancer Immunotherapy ETF (NASDAQ: CNCR ) – recently joined the fray. Biotech has been a popular place to create a new product lately as ETFs targeting companies involved in genomics, drugs in late stage clinical trials and medical breakthroughs have all hit the market in the past 12 months. According to the fund’s fact sheet, the Cancer Immunotherapy ETF “is an equal-weighted index containing both large pharmaceutical and growth-oriented biotechnology companies that are leading in this approach.” It charges an expense ratio of 0.79% and equal weights the portfolio among 30 holdings. How it chooses those 30 holdings is what makes it curious. The fund commits around one third of its assets to some of the world’s biggest pharmaceutical companies that are developing immunotherapy treatment technologies. The remaining two thirds of assets are invested in biotechs that develop their own immunotherapy drugs and treatments. A look at the top holdings of the ETF shows a literal who’s who of the biggest healthcare companies in the world – Celgene (NASDAQ: CELG ), Pfizer (NYSE: PFE ), Amgen (NASDAQ: AMGN ) and Merck (NYSE: MRK ). As a result of the fund’s investment objective and stock selections, the ETF is one third invested in large- and mega-cap stocks and two thirds invested in small- and micro-cap stocks. The portfolio allocation and investing style suggests to me that this fund is more healthcare ETF and less cancer immunotherapy ETF. The mega-cap pharma companies in the portfolio may have cancer immunotherapy as part of their broad corporate strategy but by no means are these companies a pure play on this technology. Even the biotechs that are selected for inclusion in the portfolio have a somewhat low bar for what qualifies them for having exposure to cancer immunotherapy. As would be expected, these companies can have drugs in the pipeline whether they’re in later stage clinical trial or just starting out in the trial phase. But they also qualify if they have something as simple as a partnership with another company to work on developing immunotherapy treatment in the future. The fund’s portfolio makes it difficult to properly categorize this ETF. Its biotech allocation makes it a risky venture since many of these small companies may live or die on the success of a single drug. The significant exposure to the biggest pharmaceutical companies helps limit overall portfolio risk but provides little direct exposure to cancer immunotherapy since they have such broad, developed and diversified drug portfolios. Conclusion Investors looking for a pure play on cancer immunotherapy treatment technologies will likely be disappointed. The mega-cap presence in the portfolio provides a degree of safety for the fund but it also dilutes the exposure to immunotherapy. While many of the biotech holdings employ cancer treatment as a primary goal, there are a handful that have a more diversified drug pipeline further affecting the direct immunotherapy exposure. Individuals looking for more of a broad healthcare and biotech investment may find this choice in the ETF space intriguing but the level of direct exposure to cancer immunotherapy treatments makes this fund less than a pure play.

Fundamental Items Rarely Affect Valuation

By Rupert Hargreaves Almost all fundamental investors based their research, analysis and investment decisions on the assumption that some positive relationships exist over time between equity valuation and key financial metrics. However, while a large amount of investment activity is based on the assumed relationships between the aforementioned factors, research conducted by S&P Capital IQ, shows that for the past decade it has been impossible to prove a strong statistical relationship between commonly referenced fundamental financial statistics and the direction of the equity market, momentum, and valuation: “Whether we are looking at various measures of profit margin, reported revenue and earnings growth, or even estimated future sales and earnings growth, the past decade’s correlations between price-to-earnings (P/E) valuations and a variety of commonly referenced fundamental financial statistics randomly range between strongly positive and negative readings.” – S&P Capital IQ Global Markets Intelligence Valuation versus fundamental data items Any investor that’s been watching the market for more than a year or two will know that the relationship between the valuation assigned to equities by stock market investors and underlying fundamental characteristics, over time, is extremely complex. There are many internal (stock specific) and external factors that can affect valuations. According to S&P Capital IQ ‘s research on the matter, the only net positive correlation relationship with P/E multiples since 2005 is related to selling, general, and administrative expense margins or the ratio of non-price of goods sold expenses to revenues. The best way to explain this relationship is with a table. (click to enlarge) P/E Valuation vs. Fundamental Data Items Based on a decade’s worth of data, S&P Capital’s research shows that a change in a company’s selling, general, and administrative expense margin is the only factor that will consistently impact earnings multiples across sectors. There is a clear reason for this correlation. Higher expenses will compress profit margins, weigh on profit and ultimately investors will abandon the company, driving the P/E lower. However, it’s unclear why a similar relationship doesn’t exist across other fundamental metrics. Prime example The tech sector is a prime example of an industry where the average P/E does not reflect the underlying and improving fundamentals. After the tech stock market bubble burst in 2000, the S&P 500 technology sector entered the economic recovery cycle in the first quarter of 2002 with a forward 12-month P/E valuation ratio of 54x. Between 2002 and 2010, tech sector valuations continued to be consistently marked down, although, the sector’s earnings growth averaged 23% per quarter throughout the period. The sector’s forward P/E reached a low watermark of 10.7 during Q3 2011 and has only recently started to readjust higher – as shown below. (click to enlarge) Interesting trends Aside from the obvious disconnect between P/E multiples and underlying fundamentals, S&P Capital IQ’s data highlights some other interesting trends. For example, the energy sector is currently trading at a forward P/E multiple of 33, exceeding the levels recorded while exiting the 2001 recession. The energy sector exited the 2001 recession with an elevated forward P/E of 24 that steadily declined to 8.6 by Q4 2005, well into the economic recovery and actually half way through the Fed’s tightening cycle, which took place between June 2004 and June 2006. The sector’s P/E bottomed in 2005, steadily increasing as the price of crude oil continued to rise from $50-$60 per barrel in the final quarter of 2005 to as high as $145 in July 2008. The sector P/E reached a peak of 15.3 in Q4 2008. These historic trends show that the current extreme forward energy sector P/E ratio reflects severely depressed anticipated future earnings per share relative to existing share prices, not unlike the excessive valuations seen at the tail-end of the tech stock market bubble in 2000. The excessive valuation now needs to be worked off as revenue and profit growth slowly becomes aligned with market pricing. The consumer discretionary sector illustrates more contemporary equity market valuation-related issues. Specifically, between mid-year 2004 and mid-year 2006, as the Fed continued to raise short-term interest rates at every Federal Open Market Committee meeting, investors became more cautious toward the consumer discretionary sector, pushing the sector’s P/E multiple down to 18.4 in the second quarter of 2006, from 19.4. Over the same period, sector earnings grew at an average of 8.8%: “Moving ahead to current valuations, the consumer discretionary sector’s forward P/E ratio has averaged 19.1x in the past two years while sector earnings per share growth has averaged 10.5%. Interestingly enough, this figure is close to the average P/E of 19.4x recorded by the sector during the prior period of Fed tightening when earnings grew by 8.8%. From this perspective, investors appear to be comfortable with a prospective Fed tightening cycle, as they were during most of the prior tightening cycle, as long as consumer discretionary sector earnings continue to grow at a healthy pace.” – S&P Capital IQ Global Markets Intelligence