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have delved deeply into the fundamentals urging shifts in capital allocations; now they take actions on their private, unpublished conclusions.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 We look to some 30 ETFs with holdings concentrated in stocks of economic sectors. They provide a wide array of interests and an opportunity to see comparisons being made of expectations for price change on common footings. Please see Figure 1. Figure 1 (click to enlarge) 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, in several of the Vanguard ETFs. At their typical average daily volume of trading, less than half a million shares, in many cases it would take over 100 days for all investors to escape a change in outlook. 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. 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 SPDR Metals & Mining ETF (NYSEARCA: XME ), fluctuated the most, by 133% low to high, while the SPDR Consumer Staples ETF (NYSEARCA: XLP ) traveled by only 17%. The difference is mainly a substantial loss in gold stocks, compared to capital perceived to be risk-exposed fled to a defensive grouping. 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, when and if it happens. 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 pf 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. For XME at a 52wRI of 3, the damages during the past year continue to be evident at this point in time. For XLP a 52wRI of 75 reflects the supportive influence of buying up to the present. The ratio of 3x as much downside as upside prospective price change is not that concerning to many if next year’s sector price behavior is like the recent year. After all, 3/4ths of 17% is only about -12%. That’s far better than 3/4ths of a range in the Vanguard Health Care ETF (NYSEARCA: VHT ) where the 52wRI of 77 comes up against a range of 60%, or minus 45% 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. The historical 52wRI can’t do much more than frame the past, a reference that may produce poor guidance. Knowledgeable forecasting 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 of likely coming prices that lies behind such forecasts. Hedging-implied price range forecasts 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 price range between each row of columns 2 and 3, what percentage lies between column 3 and 4. What part of the forecast price range 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 strongly suggests that the overall market environment is neither dangerously overpriced or strongly depressed in price, confirmed by the SPDR S&P 500 ETF (NYSEARCA: SPY ) at [9]. The high-return, high-risk group is the previously noted, price-depressed XME metals sector at [8]. Precious metals may rebound or they may get worse; no clear indication seems present from this analysis. Numerous low-risk, low-return alternatives are offered at [11] and [16], with symbols offered in the blue field at right. VHT, the previously compared historical risk(?) alternative to XLP, now demonstrates the fallacy of driving the portfolio car by sole use of the rear-view mirror. Earlier a possibility of -45% downside exposure was intimated. Current appraisals of VHT in [11] and Figure 2’s columns (5) and (6) show an upside price change prospect of +4.4% and experienced worst-case price drawdowns of only -2.7%. Clearly, big-money is not scared of losing much of the past gains. They may be influenced by the knowledge that 88% of forecasts like today’s have wound up as profitable holdings over the next 3 months. Typically those net gains were achieved in about 5 weeks for a +37% CAGR. Compared to the market proxy ETF, SPY, the clearest advantage seen in Figure 3 is [17], the SPDR Retail ETF, with an upside of +8.7% and price drawdowns of less than -3%. The bottom blue row of Figure 2, included for such comparison purposes shows SPY with an upside of almost +7% and downside experiences of -4.5%. The other blue comparison rows of Figure 2 provide perspectives in terms of an average of all the 28 sector ETFs above, then an average of the day’s 20 best-ranked stocks and ETFs, using an odds-weighted Risk~Reward scale, and then the overall population averages of over 2,000 securities. 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 At present there is no outstanding sector ETF choice for asset allocation emphasis or the commitment of new capital. Neither is there grave concern for dangerous outcome from present sector positions. The SPDR Energy Sector ETF (NYSEARCA: XLE ) shows the most downside exposure as experienced by prior like forecasts, and recent history suggests that its problems may not yet be over. Active investors may find attraction in the higher-ranked (by figure 2’s column 15) sector ETFS sufficient to consider shifts of some capital from XLE to other health care or information technology ETFs.