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How Prices Of ETF BIB Are Seen By Market-Makers

Summary This discussion, not a conventional review of biotech development pipeline conditions, is a study of how prices for the ETF are evaluated by market pros and the market’s subsequent reactions. Market-makers [MMs], regularly called on to negotiate volume (block trade) transactions in BIB have a special insight advantage – knowing trends of buy-side “order flow.” Why buy? or why sell? often is far less important to resulting price trends than “By how much, and how long it is likely to persist.” The MMs reveal their conclusions by the way they protect themselves and their at-risk capital commitments – in hedging. Behavioral analysis lets us know. How has the subject security been behaving? The ProShares Ultra Nasdaq Biotechnology ETF (NASDAQ: BIB ) is an issue with about 2 ½ years of markets transaction history, just under the three-year minimum we like to have for historical research and behavioral analysis. But it turns out to be an active enough subject to provide a good deal of perspective, in a dynamically competitive arena of intense and continuing interest to big-money investment organizations. Figure 1 shows how buy-side transaction orders have been prompting MM’s conclusions about likely coming price ranges day by day over the past 6 months. Figure 2 extends that same analysis to the past 2 years by means of extracting daily forecasts on a once a week basis. Figure 1 (used with permission) Price ranges indicated by vertical lines in these pictures are forward-looking forecasts of the likely extremes for BIB during the life of the derivatives contracts used to hedge MM capital put at risk in the process. The heavy dot in each vertical marks the closing price of the day of the forecast, and separates the range into upside and downside segments. The current day’s Range Index [RI] of 14 measures the percentage of the whole forecast range that is below that market trade. It defines the historic sample of 24 prior forecasts of similar upside-to-downside proportions used to evaluate the present-day forecast. The distribution of RIs available during the past 5 years (only 627 here) is shown in the lower thumb-nail picture. Quality of prior forecasts is indicated by only one of the 24 priors failing to recover from the -4.8% worst-case price drawdowns to earn a gain under the portfolio management discipline standard regularly used to compare alternative investment results. The other 23 (96% of the 24) combined with the loser to produce an average gain of +16.4% in an average holding period of 5 weeks (25 market days). That relatively short holding period contributed to the CAGR of +356%, the magnet of our wealth-building interest. Figure 2 (used with permission) Figure 2’s expanded time dimension provides a sense of its longer experience and how the values seen now relate to the past. Another comparative dimension is how BIB now relates to other investment alternatives. Figure 3 lists other Biotech-focused ETFs and provides perspectives on their size, market liquidity, and year-to-date price behaviors. Figure 3 (click to enlarge) Included in this table are the Market-proxy ETF, the SPDR S&P 500 Trust ETF (NYSEARCA: SPY ) and an inverse ETF, the ProShares UltraShort Nasdaq Biotechnology ETF (NASDAQ: BIS ) . BIS is structured to move in price 2x the opposite direction of its underlying index, while BIB holds mainly derivative instruments that leverage its price moves positively, to 2x the daily action of that same index. The index in question is the NASDAQ Biotech Index which is directly tracked by the iShares Nasdaq Biotechnology ETF (NASDAQ: IBB ). Its holdings are shown in Figure 4, strictly for perspective. Figure 4 An important aspect of any investment comparison is the trade-off between risk and reward. Figures 1 and 2 provide the data for BIB in side-by-side amounts of +13.3% and -2.9% in the rows of data contained in each. A visual comparison of those dimensions can be made from the map of Figure 5. Figure 5 (used with permission) The green % Upside Reward Scale at bottom of the map is quite understandable. But the red vertical scale of % Price downside may raise confusion between the downside portion of the forecasts and the worst-case price drawdowns of prior forecast experiences. Our experience is that the downside segment of the current-day forecasts is often exceeded by price drawdown experiences of prior like forecasts, and in turn, the current forecasts add to the priors. Besides it is not the forecasts that lead to capital losses (risk), but the experience of seeing investment prices descend below their entry cost prices, and staying there or getting worse, to the point where the investor throws in the towel and locks in a loss. When by having the fortitude to ride the stress out, he/she might likely see the position recover to a profit situation. So we use experiences rather than forecasts on the risk side of the equation. In Figure 5, BIB in position [3] clearly dominates most of the alternatives with a better trade-off. That adds to its quality advantage of a proven high-payoff history. BIS up in [6] is at the disadvantage of its “short” structure in a group where the current outlook is for higher stock prices. Conclusion: BIB currently presents a reasonably credible, albeit shorter, history of substantial rates of gain from earlier pro forecasts like that seen today. Investors should add to their own due diligence on the ETF’s competitive and profitability due diligence a hearty encouragement on the price-prospects front from market professionals.

The Deep Value Investing Philosophy During The Fed’s Ongoing War On Deflation

The definition of inflation is a general increase in the price levels for goods and services. Deflation is simply the opposite of inflation, where prices are declinin g, not rising. The Federal Reserve (Fed) is of the belief that targeting inflation at a rate of two percent is the optimal level for keeping the United States (U.S.) economy chugging along. Let’s compartmentalize for a moment whether the Fed is even measuring the true rate of inflation correctly. Taken from the Fed’s website , “Having at least a small level of inflation makes it less likely that the economy will experience harmful deflation if economic conditions weaken.” Former Federal Reserve Chairman Ben Bernanke had a religious devotion to the “inflation good, deflation bad” mentality as indicated by his academic work. Bernanke’s collection of research papers blame the Fed in the 1930s for not increasing the money supply to fight off deflation so as to avoid the Great Depression. Determined not to repeat the same mistake during the crisis in 2008, Bernanke aggressively implemented a quantitative easing program while simultaneously hammering interest rates to the floor. No monetary tool at the Fed remained idle in order to avoid deflation and the perceived risk that falling prices result in a collapsing economy. ​Looking at deflation from more of a bird’s eye view rather than simply looking at Bernanke’s favorite example of the 1930s Great Depression, a different conclusion might be reached regarding falling prices’ perceived linkage to a contracting economy. A previous study showed no connection between deflation and a depressed state in the overall economy. The study looked at more than 100 years of economic data spread out over 17 different countries. No correlation existed between deflation and a contracting economy across all international markets , including the U.S. Even when the microscope was put over the 1929-1934 deflationary period, half of the countries in the study experienced economic growth despite collapsing prices. There does not appear to be compelling evidence that the Fed adds value to the economy by targeting a particular inflation rate in order to avoid the scourge of deflation. As I mentioned in a previous blog , successful entrepreneurs focus on their own individual businesses. Monitoring macroeconomic variables as they do at the Fed is not a productive use of an entrepreneur’s time. Individual investors should have the same mentality when it comes to their portfolios. Rather than guessing the future rate of inflation and what effect it might have on financial assets, investors should focus on the minutiae of which stocks and bonds are of good value to purchase. Sliding the macroeconomic textbooks in a drawer and focusing on what stocks trade at a price point below some measure of intrinsic value is the behavior pattern of successful investors. One de minimis estimate of intrinsic value applied to a stock is its net current asset value calculation. The chart below shows the average annual return following the rigorous value investing criterion of purchasing only stocks trading below net current asset value. The performance results are independent of Fed policy and do not require an investor to have an opinion on the future rate of inflation. *Net Current Asset Value Portfolio has no more than a five percent weighting in any one stock. Dividends and transaction fees are included in all of the calculations. During years where few stocks could be found, funds remained idle in U.S. Treasury Bills.​ That subset of the Fed hierarchy who serve on the Federal Reserve Open Market Committee (FOMC) spend their days analyzing changes in various macroeconomic indicators, looking for clues as to the direction in which the overall economy might be headed. The FOMC is the primary decision-maker as to where short-term interest rates should be targeted. As already mentioned, its attempt at targeting the inflation rate is not consistent with statistical evidence in terms of stimulating the overall economy. Pushing interest rates to the floor in order to target a two percent inflation rate has resulted in retirees’ receiving little to no interest on their savings. This zero interest rate policy (ZIRP) has been in effect by the FOMC over the past 84 months. Unfortunately, an individual investor cannot control the behavior of the masterminds at the FOMC, but he or she can control what stocks to include in a portfolio. As indicated on the chart, embracing a deep value investing philosophy by purchasing only stocks trading below net current asset value outperforms the broad market average over the long term. This holds true both before and after the FOMC scrapes its targeted interest rate off of the floor. It is a peculiar financial world we currently live in. The FOMC pores over the changes in food, clothing, and energy prices purchased by consumers. These prices are manipulated by the Fed, forced to move in a direction that may be in conflict with where Mr. Market feels they should be headed. Over the past seven years, entrepreneurs in this country have been manipulated into misallocating resources via the forced feeding of ZIRP soup by the FOMC. Because of their low interest rate policy, the Fed’s mandate of seeking long-run employment and price stability has morphed into an orgy of enticing reckless speculation with regard to overpriced stocks. Getting paid to manipulate interest rates and blocking a clear view of honest price discovery in stocks seems to be a waste of taxpayer money and a major irritation to investors who embrace a strict value investing philosophy.

Past Vs. Prologue: Cutting Through The Noise Of Investment Returns

Fortunately for investors, there is good information on stock returns which can be used to provide guidance for return expectations. Less fortunately, the translation of that information varies considerably which creates a lot of “noise” that investors must cut through in order to make good investment decisions. Comparing the work of Dimson Marsh and Staunton to that of Jeremy Siegel reveals different approaches and different conclusions. In any endeavor, history can serve as a useful guide to what might happen in the future. The good news for investors is that studies of historic investment returns are far more detailed and accessible than they used to be. Triumph of the Optimists by Dimson, Marsh and Staunton is one of the most useful and should be a core part of any serious investment curriculum, but there are others. The bad news for investors is that even when good information can be attained, its translation into investment advice and portfolio strategy can vary substantially. Much like background noise and poor connection quality can make it hard to understand a person on the other end of a phone call, so too can “noise” interfere with the quality of the signal investors receive in the form of advice. This phenomenon is readily apparent in regards to establishing appropriate guidelines for expected investment returns. For starters, the quality of underlying data regarding returns is fairly good – which is often not the case with investment research. It encompasses long periods of time and multiple geographic markets. The Dimson Marsh and Staunton (DMS) study (see [ here ] for our book review) encompasses returns between 1900 and 2000 for 16 different countries. Jeremy Siegel also conducted a study of stock returns focusing on just the US but dating back to 1802 which he popularized in his book, Stocks for the Long Run . The studies are similar for the depth of their research and for the fact that both found US stocks providing a real return of 6.7% over their study periods. The path of these research efforts diverges when it comes to interpreting the results for the purpose of establishing expectations, however. DMS focuses on analyzing the patterns they see in the historical returns and normalizing them as the basis for making a sensible forecast. One of the key points they highlight is that valuations have changed considerably over their study period and this provided a one-time, unsustainable boost to returns. They report, “Since 1900, there has also been a dramatic change in the valuation basis for equity markets. The price/dividend ratio (the reciprocal of the dividend yield) is much higher now than it was in 1900. After adjusting for the difference, they conclude that the ex ante risk premium for US stocks is 1.7% lower than the historical premium. “Our assertion in this book … is that the equity premium is markedly lower than many people suggest.” Indeed, this outlook is very consistent with Dimson’s recent assessment in the Economist [ here ] that “the likely future long-term real return on a balanced portfolio of equities and bonds will be 2-2.5%.” A second finding from DMS is that the unusually strong returns in the second half of the twentieth century appear to be statistical flukes and unlikely to be repeated. They note, “This was a period [the latter half of the twentieth century] when most things turned out better than expected. There was no third world war, the Cuban Missile Crisis was defused, the Berlin Wall fell, and the Cold War ended. There was unprecedented growth in productivity and efficiency, improvements in management and corporate guidance, and extensive technological change. Corporate cash flows grew faster than expected, and in all likelihood the equity risk premium fell, further boosting stock prices. In short, it was the triumph of the optimists.” In other words, the phrase for their book title, Triumph of the Optimists , is intended to be a mild warning in regards to expectations. They conclude their study by highlighting, “Statistical logic tells us that future expectations must lie below today’s optimists’ dreams. We can hope for, but we cannot expect, the optimists to triumph in the future. Future returns from equities are likely to be lower than those achieved in recent decades … experience should teach us realism, not optimism.” Siegel, by contrast, take a very different approach when establishing expectations for future returns by highlighting the constancy of stock return through history. As he often does, he started and ended his November presentation at the CFA Institute’s Equity Research and Valuation Conference [ here ] with a graph showing the returns to stocks, bonds, bills, gold, and the dollar. The chart shows stocks on a nearly linear upward trajectory with the returns for all of the other assets on considerably less attractive paths. Although he stops short of proclaiming 6.7% as his expected return for stocks, he clearly relishes in the moniker “Siegel’s constant” being applied to his findings. By leaving the graph of historical stock returns on the screen at the end of the presentation, he leaves a strong visual impression, and implied message, that past is prologue. Siegel also takes a very different approach to the subject of valuation. For one, he prefers using price/earnings (PE) as an indicator, despite the fact that just like with returns, one year’s worth of earnings can be hugely unrepresentative. To his credit, he does discuss Shiller’s cyclically adjusted price to earnings ratio (CAPE) which actually does a very good job of indicating future returns. However, after noting that the conventional CAPE methodology forecasts only 2% real returns for stocks, he moves on to describing how he believes the CAPE metric should be adjusted. His conclusion is that with certain adjustments, current valuation metrics point to expected returns to stocks very much in line with the long term average of 6.7% So we have two very different takes on essentially the same data set of stock returns. Siegel is bullish in finding stocks right on track to continue their long run record of 6.7% real returns – which is well above the returns of other asset classes. DMS, while also recognizing the historical superiority of stocks, are considerably more cautious in their expectations for future returns. Both perspectives are well informed views by respected academics. Unfortunately, this conflict creates even more of a challenge for conscientious investors trying to establish an appropriate portfolio strategy. How should investors cut through the noise? In an important sense, we enjoy having multiple sides to debates like this because it forces us to understand the positions very clearly and to disentangle what can be very subtle issues and assumptions. The case of return expectations is an excellent example because both views seem quite plausible. We begin our investigation, as we often do, by searching for inconsistencies and differences in underlying assumptions. One key assumption Siegel makes is that although stocks can deviate materially over the short term, those deviations become progressively smaller over longer periods. This is an important tenet in his thesis “stocks for the long run” but one that is not uncontroversial. Zvi Bodie, another noted academic, argues that Siegel’s view understates the long run risk of stocks. He describes in his paper “The long run risk of stock market investing: Is equity investing hazardous to your client’s wealth?” in the Financial Analysts Journal [ here ] that, “Economic uncertainty, especially, is magnified with time. What is the worst thing that can happen over the next 5 years compared with over the next 10,15,20,30, or 100 years? In 100 years’ time, a myriad of catastrophic things could happen.” This is an issue we highlighted in the blog post “Spring Cleaning” [ here ] where we noted that this observation is common in fields outside of economics and is a key factor in engineering (long term) infrastructure projects. Two other academics, Lubos Pastor and Robert Stambaugh, also addressed this issue in a paper entitled “Are stock really less volatile in the long run?” [ here ]. They acknowledge that “Conventional wisdom views stock returns as less volatile over longer investment horizons.” However, they also report that “stocks are actually more volatile over long horizons from an investor’s perspective.” They go on to explain: “Investors condition on available information but realize their knowledge is limited in two key respects. First, even after observing 206 years of data (1802-2007), investors do not know the values of the parameters of the return-generating process, especially the parameters related to the conditional expected return. Second, investors recognize that observable “predictors” used to forecast returns deliver only an imperfect proxy for the conditional expected return, whether or not the parameter values are known. When viewed from this perspective, the return variance per year at a 50-year horizon is at least 1.3 times higher than the variance at a 1-year horizon.” In other words, the future is uncertain and hard to predict. Indeed, an important element of their findings is that they explicitly call out the difference between assessing variance after the fact, or ex post , and assessing variance in the future, or ex ante . In contrast to Siegel, the notion that the future is inherently less certain permeates the language of DMS. This is evidenced when they say, “downside risk is always present,” and “because of the power of compound interest rates, the very worst that could happen to an equity investor worsens as the investment horizon is lengthened.” When DMS “examine the range of risk premia that can be anticipated over various future time horizons,” they find that “There is clearly a substantial probability of achieving a negative risk premium, even over long investment horizons.” Another subject that Siegel treats very differently than DMS is valuation. It is interesting to note that while Siegel sees fit to examine 200 years of stock returns, he uses only the current year’s price/earnings as his primary valuation metric. Using a single year’s worth of earnings makes his analysis vulnerable to being incredibly unrepresentative of the longer term and in doing so, seemingly antithetical to his effort to capture the big picture revealed by an extensive history. He does also consider a more robust valuation metric, the Shiller CAPE, which has one of the best records among valuation metrics for correlating with future returns (higher CAPE suggests lower future returns). However, when he finds that the current CAPE suggests future returns to stocks on the order of 2%, he deems it appropriate to adjust the earnings input to CAPE. In doing so he arrives at a CAPE ratio that suggests “very slight overvaluation” and an expected return to stocks very much in line with the historical average of 6.7%. There are at least a couple of things interesting about Siegel’s approach to valuation. For one, he does not appear to make an effort to calibrate for the fact that market valuations today are higher than they were at the beginning of the study periods. DMS explicitly address this as an issue that likely overstated historical returns relative to what can be expected in the future. Siegel makes no such valuation adjustment which means that in order to enjoy the same equity returns in the future as the past, valuations will have to continue to rise at the same rate, all else being equal. Another interesting aspect of Siegel’s approach to valuation regards the adjustment he makes to earnings for CAPE. Rather than comparing the price of the S&P 500 to the earnings of S&P 500 companies, he compares it to the profits from the entire economy. Effectively, he compares apples to oranges. John Hussman provided an excellent analysis of the “adjustment” [ here ] and James Montier at GMO has also chimed in with well- reasoned, and critical analysis of Siegel’s position [ here ] and [ here ]. In summary, we find flaws in several key aspects of Siegel’s thesis that serious challenge the credibility of his return expectations. For one, reference to any set of asset returns as a “constant” is absurd and defies underlying economic reality. In addition, the failure to clearly highlight the difference between realized historical variance and the variance of uncertain future events unnecessarily biases and complicates the assessment of return expectations. Further, Siegel’s valuation work suffers from clear inconsistencies in what Montier calls “a strange way of honestly adjusting a valuation measure.” It is also striking that Siegel does not call out the unusually strong returns in recent years and the negative impact those results may have on future returns. Specifically, the S&P 500 has returned 14.40% per year over the five years through November 2015. This is even greater than the 13.6% annual return achieved between 1982 and 1999 in what Siegel himself calls “the greatest bull market in history”, a period which he acknowledges as having generated returns more than double the longer term average. As a result, one key takeaway from this analysis is that we place more weight on the DMS work in regards to return expectations than that of Siegel. While we believe that, in general, stocks are worthy long term investments, we also believe they entail real risk, especially over horizons of less than ten or twenty years. Currently, based on the conventional CAPE ratio, we believe stock returns for the next ten to twelve years will be in the very low single digits, nearing zero. This is relevant for anyone who depends on achieving much higher returns, is retired or may be retiring shortly, or for whatever reason may need access to their investment funds in less than 30 or 40 years. We also believe that “Siegel’s constant” of 6.7% is an interesting historical occurrence, but that it says very little about the future and creates an “anchor” that can inhibit more productive intellectual inquiry. In order to calibrate that realized return of 6.7% to potential future results, we must consider how things may differ in the future. We know that the US experienced remarkable growth since 1802 and that is unlikely to repeat, at least not to the same degree. We know that productivity has recently crashed and that if it remains at current levels, it will be extremely difficult to achieve historical return levels. Demographic trends point to an aging society which is typically more averse to risk and has less demand for stocks. And debt and entitlement burdens are at record highs. Any one of these issues could depress future returns and if all of them exert pressure, future returns could be materially lower. After all, equity is only what is left after all other liabilities. Finally, this exercise also reveals one of the great challenges of investing and is symbolic of one of the industry’s major shortcomings: the almost constant need to cut through the noise. While we respect Dr. Siegel’s work, at the same time we believe that much of it used to fuel a bullish narrative at the expense of a clear discussion of issues relevant for investors. This doesn’t happen because he isn’t aware of the issues. Unfortunately, it makes things harder for investors when smart, authoritative figures produce overly ebullient outlooks that inflame the already troublesome tendency many have to extrapolate past results into the future. History can inform the future, but past is not prologue. We believe the more useful approach is that of DMS which appropriately tempers that enthusiasm with the lesson that “experience should teach us realism, not optimism”.