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Dumb Alpha: The Ignoramus’s Guide To Asset Allocation

By Joachim Klement, CFA Modern finance constantly busies itself with the development of new, more sophisticated ways to manage risk and generate returns. These efforts, however, generate their own risks – for example, overspecifying a model or falling prey to data mining. On the opposite end of the spectrum are simple ways to invest that have a proven track record of providing superior investment outcomes. This article focuses on investment techniques that are so simple it is surprising how well they work, a phenomenon that Brett Arends of MarketWatch has called “dumb alpha.” The Dumb-Smart Way to Think about the Future Assume you are a middle-aged man with a receding hairline and an expanding waistline. In short, you don’t look like George Clooney – you look like me. Moreover, you need to finance your retirement with your savings. Creating a portfolio to build retirement wealth is no easy feat given the fact that retirement may be 20 to 40 years in the future. A lot can happen in that time: 30 years ago, Japan was on its way to overtaking the United States, China was a closed-up Communist country, Europe and North America had broken the spell of runaway inflation, and Brazil was a basket case. Who can say what the next 30 years will bring? Luckily, you are well aware that it is nigh impossible to predict which investments will do well during the next three decades. And assuming this is true, there are only two logical ways to invest. One possibility is to hold all your savings in cash or the safest short-term bills and bonds. The problem with this approach is that you will have a hard time keeping pace with inflation once taxes and other expenses are taken into account. And in some countries, like Germany and Switzerland, you even face what my colleague Will Ortel calls ” unterest rates .” The other possibility is to invest the same amount of your money in every asset class. This makes sense because you don’t know how stocks will do compared with bonds or real estate investments, or how Apple stock will do compared with Barry Callebaut. The simplest example of this naive equal-weighted approach would be a portfolio split 50/50 between stocks and bonds. Another approach would be to invest one-quarter of your assets in cash, one-quarter in bonds, one-quarter in equities, and one-quarter in precious metals. Similarly, instead of investing in a common stock index such as the cap-weighted S&P 500 Index, you could evenly spread your precious funds across all 500 stocks of the index. The Advantages of a Naive Asset Allocation As it turns out, this way of investing tends to work extremely well in practice. In their 2009 article ” Optimal versus Naive Diversification: How Inefficient Is the 1/N Portfolio Strategy? ,” Victor DeMiguel, Lorenzo Garappi, and Raman Uppal tested this naive asset allocation technique in 14 different cases across seven different asset classes and found that it consistently outperformed the traditional mean-variance optimization technique. None of the more sophisticated asset allocation techniques they used, including minimum-variance portfolios and Bayesian estimators, could systematically outperform naive diversification in terms of returns, risk-adjusted returns, or drawdown risks. Unfortunately, naive asset allocation does not work all the time. Over the last several years, only one asset class generated high returns: stocks. So, a naive asset allocation will not keep up with the more equity-concentrated portfolios during such periods. But it is interesting to note how well a naive approach works over an entire business cycle. Practitioners should compare their portfolios with a naive asset allocation to check whether they really have a portfolio that delivers more than an equal-weighted portfolio. You can create a better (“more sophisticated”) portfolio than the equal-weighted (“dumb”) one, but it is surprisingly hard to do. As a check, you can create an equal-weighted portfolio from the assets or asset classes used in your current portfolio. Then test whether the current portfolio is superior to this equal-weighted benchmark over time in terms of returns, risks, and risk-adjusted returns. If that is the case, congratulations: You have a good portfolio. If not, you should think of ways to improve the performance of your existing portfolio. It is also pretty clear why this dumb alpha works. Within stock markets, putting the same amount of money in every stock systematically prefers value and small-cap stocks over growth and large-cap stocks. These two effects conspire to create outperformance. There is a second effect at play, however. After all, the value and small-cap effect cannot explain why a naive asset allocation also works in a multi-asset-class portfolio. The key reason for its strong showing is its robustness to forecasting errors. Most asset allocation models, like mean-variance optimization, are very sensitive to prediction errors. Unfortunately, even financial experts are terrible at forecasting, and one follows forecasts at one’s peril. By explicitly assuming that you cannot predict future returns at all, an equal-weighted asset allocation is well suited for unexpected surprises in asset class returns – both positive and negative. Since unexpected events happen time and again in financial markets, in the long run an equal-weighted asset allocation tends to catch up with more “sophisticated” asset allocation models whenever an event happens that the latter are unable to reflect. In other words, if the naive asset allocation outperforms a more sophisticated portfolio, it might provide a hint as to why this is the case. Are there too many risky assets in the sophisticated portfolio that directly or indirectly create increased stock market exposure? What are the implicit or explicit assumptions that led to the more sophisticated portfolio that have not materialized and have led to an underperformance relative to a less sophisticated naive asset allocation? In this sense, the naive asset allocation can act as a check to an existing sophisticated portfolio and as a risk management tool. Disclaimer: All posts are the opinion of the author. As such, they should not be construed as investment advice, nor do the opinions expressed necessarily reflect the views of CFA Institute or the author’s employer.

DEX: This Balanced Closed-End Fund Is Trading At A Big Discount

Summary DEX is a leveraged, global balanced CEF about 60% equities, 40% bonds. The 17+% discount to NAV is at three year highs. High distributions produce alpha by capturing some of the discount with every monthly payout. The Delaware Enhanced Global Dividend and Income Fund (NYSE: DEX ) was formed in June, 2007. It invests globally in income-generating securities across multiple asset classes. (Data below is sourced from the Delaware Investments website unless otherwise stated.) The Fund’s primary investment objective is to seek current income, with a secondary objective of capital appreciation. The Fund also uses enhanced income strategies by engaging in dividend capture trading, option overwriting, and realizing gains on the sale of securities, dividend growth and currency forwards. There could be a good medium-term trading opportunity in DEX setting up from now until year-end because of tax loss selling. Over the last year, the average discount to NAV has been -12.75%, while it is currently around -17%. The 1-year discount Z-score is -2.20, which means that the current discount to NAV is more than two standard deviations below the average. Source: cefanalyzer Three Year Historical Premium/Discount for DEX (click to enlarge) From an overall asset allocation perspective, DEX is similar to a global 60-40 balanced fund, but because of the leverage and wide range of asset classes, it is much more diverse than a typical balanced fund you would find at Vanguard or Fidelity. Under normal conditions, the Fund will invest: At most 60% of its net assets in securities of U.S. issuers. At least 40% of its net assets in securities of non-U.S. issuers (but the fund managers have discretion to lower this percentage to 30% if they feel market conditions are unfavorable). This was the asset allocation breakdown as of June 30, 2015: Asset Allocation Breakdown Large-Cap Value 11.54% Real Estate 2.80% International equity 29.76% Emerging markets equity 6.51% Convertible securities 13.13% High yield bonds 32.68% Investment grade bonds 2.36% Other 1.24% DEX has had about average long term NAV performance. But it may be good for a swing trade now because of the very high discount to net asset value. Since inception, it had one big losing year in 2008 when the net asset value fell -38.52%, and it is also struggling so far this year. Here is the total return NAV performance record since inception along with its percentile rank compared to Morningstar’s World Allocation category: DEX NAV Performance World Allocation NAV Percentile Rank in Category 2008 -38.52% -39.30% 50 2009 +48.43% +46.71% 38 2010 +16.60% +23.98% 50 2011 -1.44% -3.21% 38 2012 +17.68% +19.81% 34 2013 +19.01% +11.07% 34 2014 -0.46% +6.14% 90 YTD -7.10% -5.76% 73 The “Top 5” tables below are all as of June 30, 2015: Top 5 Countries United States 51.02% Japan 7.96% France 5.79% United Kingdom 5.24% Canada 2.88% Top 5 foreign equity holdings Teva Pharmaceutical (NYSE: TEVA ) 1.35% Mitsubishi UFJ Financial ( OTCPK:MBFJF ) 1.30% AXA S.A. ( OTCQX:AXAHY ) 1.15% Novartis AG (NYSE: NVS ) 1.14% Toyota Motor (NYSE: TM ) 1.12% Top 5 U.S. equity holdings CA Inc. (NASDAQ: CA ) 0.55% AT&T Inc. (NYSE: T ) 0.52% Pfizer Inc. (NYSE: PFE ) 0.49% ConAgra Foods Inc. (NYSE: CAG ) 0.49% Merck & Co. Inc. (NYSE: MRK ) 0.48% Top 5 U.S. fixed income holdings Inter-American Development Bank 0.46% NuVasive Inc. 0.42% Meritor Inc. 0.41% Blackstone Mortgage Trust Inc. 0.39% Cardtronics Inc. 0.38% Top 5 foreign fixed income holdings Indonesia Govt. Intl. Bond 0.73% Mexican Bonos 0.65% Mexico Govt. Intl. Bond 0.56% Indonesia Govt. Intl. Bond 0.53% Australia & N. Zealand Banking 0.49% Bond Rating Distribution AAA 8.38% AA 0.15% A 5.40% BBB 9.73% BB 24.63% B 36.34% CCC 15.24% CC 0.09% D 0.04% DEX is run by a large team of eleven portfolio managers, which is helpful because of the many asset classes held in the fund. Nine of the managers have earned the CFA designation. The lead manager is Roger A. Early, CPA, CFA. Roger is a Managing Director, Head of Fixed Income Investments with 39 years industry experience. He has been with the fund since 2008. Alpha is Generated by High Discount + High Distributions The high distribution rate of 9.34% along with the 17% discount allows investors to capture some alpha by recovering some of the discount whenever a distribution is paid. Whenever you recover NAV from a fund selling at a 17% discount, the percentage return is 1.00/ 0.83 or about 20.5%. So the alpha generated by the 9.34% distribution is computed as: (0.0934)*(0.205)=0.01915 or about 1.92% a year. Note that this is more than the 1.13% baseline expense ratio, so you are effectively getting the fund managed for free with a negative effective expense ratio! Here are some summary statistics on DEX: Delaware Enhanced Global Dividend and Income Fund Total Assets: 273 Million Total Common assets: 186 Million Annual Distribution (Market) Rate= 9.34% Last Regular Monthly Distribution= $0.075 (Annual= $0.90) Fund Baseline Expense ratio: 1.13% Discount to NAV= -17.44% Portfolio Turnover rate: 56% Credit Rating: Fixed income holdings are mainly high yield Effective Leverage: 30.35% Average Daily Volume (shares)= 65,160 (Source: Yahoo Finance) Average Dollar Volume = $630,000 DEX is only a moderately liquid stock and usually trades with a bid-asked spread about two cents. There is often limited size available on both the bid and asked, so some care must be taken when trading DEX. DEX is an attractive purchase at current levels when the discount to NAV is 15% or higher, although there may be even additional opportunities later this year when tax loss selling kicks in. A reasonable trading approach may be to scale in gradually over the next few months.

Which Way Are Stock Prices Headed? And When? Who Can Tell?

Summary There are folks who know, but they don’t talk. There are lots of other folks who talk, but they don’t know. When spokespeople for the ones that do know do talk, they say it can’t be done. The talkers try to ignore them. Many of the listeners believe the spokesfolk while the non-talkers continue to capture obscene annual payoffs, and retire luxuriously in their 30s. Right! It’s Market-Makers [MMs] who are the subject of attention here How do we know? We have been monitoring how they play the game, daily for the last 15+ years, and a lot earlier. We learned that they have to put their own (the firm’s) money at risk temporarily, and they know how to hedge (transfer) that risk to other MM speculators willing to fade the bet – for a price. And then the MMs get their clients to pay for the risk protection. Sweet deal, huh? If you had it, would you talk? Or be generous with the clients you are “helping”? So what does our “monitoring” tell us? It tells, on a stock-by-stock (or ETF) basis, just how far up in price and how far down in price they think the subject security is likely to travel over the next few weeks or months. And how do they know? By the “order flow” in volume transactions (blocks) from their big-$ clients. Clients they talk to (over dedicated phone lines) dozens of times a day. Like they have for years. In that time, they come to know how the client thinks, and how he tries to hide what he really intends to do, and then does it. The perspective MMs have, of who’s buying and who’s selling, by how much, and how urgently, is augmented by the MMs’ own decades-old, world-wide, 24×7 information-gathering systems and communications networks. Fed into their analytical and evaluative staffs, where every street newbie MBA grad wants to get a job. Like it or not, the MMs are among the best-informed players in the game. They have to be. If they weren’t, their clients would rape them in any transaction they could. (It’s an earned response). Can we prove it? Years ago, we determined how to translate MMs’ hedging actions into explicit forecast price ranges. Then, we created a simplistic measure, the Range Index, whose numeric value is the percentage of the whole forecast range that is between the bottom of the forecast range and the then current market quote. To prove the RI’s usefulness, we looked at over 2,000 stocks and ETFs during the prior 4-5 years daily and measured how much each one’s price had changed from the date of the forecast week by week cumulatively over the next 16 weeks. Figure 1 shows the result, with changes measured in CAGRs: Figure 1 (click to enlarge) The average of these 2,959,450 individual measurements is shown in the blue mid-row. Stepping away from that overall average row progressively to the cheaper side in the row above are the 1.7 million instances of all RIs less than 33, where at least twice as much upside RWD is indicated than is expected in downside RSK. Got the picture? The cheapest opportunities in the top 100: 1 row are paralleled by the most hazardous forecasts of the bottom 1 :100 row. The data speaks for itself. In the aggregate of individual instances, MMs have a compelling understanding of when there is trouble ahead, and instead, when near-term an opportunity calls. Trouble seems to last longer for stocks than opportunity. Well, if they can do so well pervasively for that many stocks, shouldn’t they be able to tell where and when the whole market is headed? They could if stocks were lemmings and they all ran in the same herd at all times. But they only do that at infrequent times. That’s when market moves become apparent. To illustrate the problem, Figure 2 uses the Figure 1 analysis on the SPDR S&P 500 Trust ETF (NYSEARCA: SPY ) by itself as the subject in the same period. (A period “chosen” by happenstance because Figure 1’s large amount of work was already “on the shelf” and was recent). Figure 2 (click to enlarge) Interestingly, SPY’s average (blue row) annual growth in price during these 4-5 years was double that of the larger population, which contains other-than big-cap institutional favorites. The small sample sizes of above-average SPY RIs (the lower #BUYS column) severely penalize their reliability or usefulness. But little divergence from SPY’s average CAGR is seen in its below-average, more attractive Range Indexes. While 2% to 4% gains above market averages seem to titillate academics, most real motivated investors tend to aim considerably higher before putting personal capital at risk. When is price volatility not risk? Answer: When it is opportunity. When what is coming is a big price move to the upside in something you own or could own. When not a big move to the downside. Knowing “when” is what makes the difference. Since the prevailing investment mythology propounded by those spokesfolk is that it can’t be done, and since much of the investing public and most of the media has neither the time, experience, nor the inclination to figure out how to do otherwise, it gets believed. That way the public doesn’t get in the way of the market pros. Obviously, stocks or ETFs with big price volatility from time to time offer big payoffs. That makes them attractive targets to identify their good “whens” from the bad ones. The trick is to find those subject securities that have the combination of big positive payoffs identified in advance frequently. And identified successfully far more often than being deceived; more and bigger winners than losers. We can use the kind of comparisons between MM Range Index forecasts and subsequent market price changes of Figures 1 and 2 to screen candidates for this approach. Three prospects present themselves quickly out of over a hundred eligibles. Here are their price performance comparison credentials: Figure 3 (click to enlarge) Figure 4 (click to enlarge) Figure 5 (click to enlarge) All three of these securities have price trend growth rates of +30% annually. But more importantly, the way the MM community hedges when they are being actively traded in volume tells of likely upcoming price moves at past average rates more than double their admirable trend growth. The magenta numbers in the #BUYS column identify the current level of Range Index for each. The bold white data signify result cells of the table that are significantly different from the value in that column of the blue average row. These are not all exotic operations. Indeed, Tempur Sealy International, Inc. (NYSE: TPX ) is a sleeper: Tempur Sealy International, Inc., together with its subsidiaries, develops, manufactures, markets, and distributes bedding products worldwide. It operates through two segments, North America and International. The company provides mattresses, foundations, and adjustable bases, as well as other products comprising pillows and other accessories. It offers its products under the TEMPUR, Tempur-Pedic, Sealy, Sealy Posturepedic, Optimum, and Stearns & Foster brand names. The company sells its products through furniture and bedding retailers, department stores, specialty retailers, and warehouse clubs; e-commerce platforms, company-owned stores, and call centers; and other third party distributors, and hospitality and healthcare customers. It is also involved in licensing its Sealy, and Stearns & Foster brands, technology, and trademarks to other manufacturers. Tempur Sealy International, Inc. was founded in 1989 and is based in Lexington, Kentucky. – Source: finance.yahoo.com Granted, Alkermes (NASDAQ: ALKS ) has more evident scientific content: Alkermes Public Limited Company, an integrated biopharmaceutical company, engages in the research, development, and commercialization of pharmaceutical products to address unmet medical needs of patients in various therapeutic areas. The company offers RISPERDAL CONSTA for the treatment of schizophrenia and bipolar I disorder; INVEGA SUSTENNA to treat schizophrenia schizoaffective disorder; AMPYRA/FAMPYRA to treat multiple sclerosis; BYDUREON to treat type II diabetes; and VIVITROL for alcohol and opioid dependence. It is also developing Aripiprazole Lauroxil for the treatment of schizophrenia; ALKS 5461 that is under Phase III study for the treatment of depressive disorder; ALKS 3831, a Phase II study medicine to treat schizophrenia; ALKS 8700, a monomethyl fumarate molecule, which is under Phase I study to treat multiple sclerosis; ALKS 7106, a drug candidate to treat pain with intrinsically low potential for abuse and overdose death; and RDB 1419, a proprietary investigational biologic cancer immunotherapy product that is under pre-clinical stage. The company serves pharmaceutical wholesalers, specialty pharmacies, and specialty distributors directly through its sales force. It has collaboration agreements with Janssen Pharmaceutica, NV (NYSE: JNJ ); AstraZeneca plc (NYSE: AZN ); Acorda Therapeutics, Inc. (NASDAQ: ACOR ); and other collaboration partners. Alkermes Public Limited Company was founded in 1987 and is headquartered in Dublin, Ireland. – Source: finance.yahoo.com The SPDR Biotech ETF (NYSEARCA: XBI ) is a non-leveraged exchange-traded fund of stocks active in the research and development of medicines and therapeutics. 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 biotechnology segment of a U.S. total market composite index. In seeking to track the performance of the S&P Biotechnology 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 biotechnology industry group of the S&P Total Market Index (“S&P TMI”). The fund is non-diversified. – Source: finance.yahoo.com There are many other stocks with price volatility that offer gain prospects on average, but few have as competitive odds for profit as the records of these three at this point in time. Here are relevant market capitalization and trading considerations: (click to enlarge) But what next? So far, we have just looked at things that have already happened. Our interest should be in what may come next. That centers around the MMs’ current forecasts of likely coming price ranges, and what has happened in the past when similar forecasts were made. Figure 6 pictures the evolution of such forecasts for TPX, daily over the past 6 months. Figure 6 (used with permission) The vertical lines in Figure 6 are forecasts of price ranges yet to come rather than the traditional plots of actual past prices in those days. The forecast ranges surround the market quote ending the day, which separates the range into prospective upside and downside segments. It is this balance that the forecast Range Indexes measure. The lower thumbnail picture shows the distribution of Range Indexes for the subject over the past 3 years, with the current RI highlighted. The row of data between the two pictures tells what the subsequent price action has been when our standard portfolio management discipline was applied to all 37 of the past 3 years’ RIs like today’s. They averaged +15.1% net gains, in typical holdings of 34 market days, about 7 weeks. Compounded, 7+ times a year the annual rate of gain is +180%. During the typical 34-day holding periods, the average worst-case price drawdowns were -3.6%. Only one of the 37 failed to recover in the 3-month holding limit, a win rate of 97 of 100. Figure 7 provides a two-year picture of once-a-week looks at the past daily forecasts for TPX: Figure 7 (used with permission) There is no guarantee that future price behavior will duplicate these experiences, but when something good happens a dozen times a year over a three-year period, it is more reassuring than an observer’s unsupported assertion that “the stock’s price now looks attractive”. Our second illustration, Alkermes, is in the opportunistically fertile field of healthcare technology. Its prior experiences following MM implied forecasts like today’s have been quite competitive among over 100 such competitors. Figure 8 gives the same look at its current situation as did Figure 6. Figure 8 (used with permission) ALKS currently is benefiting from a recent passing political suggestion that put down the prices of most stocks in the medical care field, particularly those active in the development of new therapeutics. Figure 8 illustrates ALKS’s price volatility potential and its recovery prospects now seen by the MM community. In every prior case of two dozen such forecasts in the last four years, ALKS has gained an average of +16% in 8+ weeks of disciplined holdings management, recovering from average worst-case price drawdowns of -5%. Figure 9 provides a two-year perspective of once-a-week forecasts for ALKS. It illustrates the uptrend underlying the stock’s price volatility that creates the recurring opportunities that are so appealing to active investors. Figure 9 (used with permission) But does greed justify undertaking all this? ALKS is a good illustration of the power of active investment management as opposed to conventional, passive buy&hold, index-oriented risk (and opportunity) – avoiding investment practice. Where the investor has sufficient capital at work to achieve his/her investment objectives from returns in single digits, conventional passive investing may do the job with a minimum of emotional cost. It frees the investors’ time and energy to be applied to other life objectives. Lucky them. But, for many who once saw financial goals within reach of low-double-digit investing returns, the failure of achieving those returns by conventional “growth and income” gains puts them now in a position of considerable discomfort. The passage of inadequate productive years, which cannot be retrieved, makes continuation of leisurely investing practices incapable of reaching prior objectives. A different approach is now required. Active, time-disciplined investing can help at least ease the problem, and in many cases, may retrieve earlier hopes. But active investing takes time, attention, and a different attitude of personal operation. The active investor is taking on a “second job”. It involves repeated decisions that test the personal limits of discomfort that must be set by the investor. That makes the investor an unattractive client for independent wealth managers. The outside investment manager has to live in a competitive world hemmed in by market uncertainty and threat of legal action by clients who have lost money by the advisor’s actions or guidance. He far prefers clients who will be content with conventional passive buy&hold&don’t-worry management. Which is what most are prepared to provide. The individual investor whose situation urges active management typically finds that his/her position is best served by a do-it-yourself (DIY) approach. The quandary is that it is next to impossible to do the necessary job “from scratch”. That requires developing a general market perspective, and then fitting into that, continuing selections from careful research of the prospects of hundreds, even thousands, of alternative choices. An overwhelming prospect. What may be most helpful is a source of information that draws on the required actions of experienced professionals whose everyday activities accomplish and maintain that market perspective. Activities that also provide appraisals of the price prospects of hundreds (or more) of potential portfolio candidates. When the prospects for those candidates can be described in terms of odds and payoffs, ones that the individual investor can tailor to his/her own tradeoff preferences, then we are closer to helpful guidance. The essentials here are issue comparability, and individual investor preferences and self-imposed limits. What of the third illustration? The SPDR Biotech ETF is, in a way, an extension of the ALKS situation. It is helpful in that it shows that some ETFs can develop attractive price velocity without the engineering present in leveraged ETFs. The problem with leveraged ETFs is two-fold. First, the mechanics of those that are structured to provide positive payoffs when the securities involved are declining (the “short” ETFs) have an unavoidable bias over time that causes their price decay. They should not be held “long” except at irregular, intermittent, very brief (days) periods. They typically cannot be borrowed by brokers so these “short” ETFs are usually not available at other times to be sold short. The levered long ETFs do provide ongoing price volatility, which can cut both ways. They often encounter “ordinary” double-digit worst-case price declines during 2-3 month holding periods that can be well beyond most DIY investors’ tolerance limits. Check Figure 10 for the present RI record for XBI and see what it has been: Figure 10 (used with permission) The worst-case price drawdowns following 28 prior RIs for XBI of 21 at -4.4% were about half of the 8.2% gains that were ultimately produced. Since prices of 27 of the 28 forecasts ultimately recovered and reached their top-of-forecast range sell targets, the drawdowns needed to be tolerable. The benefit of the ETF’s diversification among many biotech holdings contributed to the smaller drawdowns. Another aspect of XBI’s appeal to the active investor is the typically short (5+ weeks) holding periods required to reach position closeouts following forecasts at this RI level. Compounding of 8+% gains ten times a year generates returns at a triple-digit rate. Short holding periods not only generate high rates of return, but also provide opportunities to keep capital, liberated by reaching targets, fairly fully employed in other attractive opportune positions. That is an advantage in active investing that provides the compounding of single-digit gains into double- and even triple-digit rates of return for the portfolio as a whole. The repetition of such opportunities is illustrated in the 2-year weekly review of MM forecasts for XBI in Figure 11: Figure 11 (used with permission) Conclusion There are resources available to DIY investors that can help them return the progress of lagging investment programs to (or better than) original visions. But they require both a shift in mindset of how that is to be accomplished, and the time, energy, and conviction that will be required to bring it about. Where the remaining years are few before scheduled financial requirements arrive, such advanced performance may be the only means of accomplishment. But you should know what risks and rewards are likely before venturing into new investing approaches. Seeking Alpha provides a “crowd-source” reservoir of other active investors collectively looking for investing opportunities and drawing on their life experiences in many and varied occupations. Continuing selective reference to SA can help build market and investing perspective, although with the caveat that many contributors who are eager to write and to comment may be little more than beginners at the adventure. So check contributor and commenter profiles. A variety of specialized research product services by SA contributors are available through the site’s PRO program, and others, like the illustrations above, are available at Internet site addresses.