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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.

Upgrade Your Investment Approach And Put Some Fears To Rest

Despite the pleas of many consultants and wealth managers for investors to ignore tumult in the markets, the fact is that oftentimes such fears are warranted. Although long term investors should not impulsively react to small market moves, they should be alert to signs that things are “not right”. The mean-variance approach to investing is a very common one, but time has revealed a great number of weaknesses that unnecessarily expose its adherents to risk. The Kelly criterion is a very useful approach to investing that also corresponds more closely to the way markets actually work. The investment services industry as a whole has been slow to disseminate improvements in investment theory and practice. We are born with some pretty good warning mechanisms and most people are pretty good at sensing when things are not right. Martin J. Dougherty makes exactly this point in his book Special Forces Unarmed Combat Guide : “Victims of assault often say afterwards that they could see it coming.” He continues, “The problem, then, is not being able to spot danger but being willing to act on this information and avoid it.” While this is just one manifestation of our defense network, it does highlight our natural ability to “spot danger”. It also highlights the imperative of being able to act on useful warnings. Given that volatility and risk are endemic to the exercise of investing, there is no particular reason why most market behavior should cause undue duress for a well-informed investor. And yet times of unsettled markets and high volatility can keep a lot of investors awake at night, including seasoned investment professionals. Oftentimes, concerns revolve around a sense of uncertainty – a sense that something isn’t quite right or that something is being missed. Sometimes it comes from an uneasy feeling that a prescribed course just doesn’t seem right. Indeed, it may just be that one’s approach to investing is the source of discomfort as much or more than market moves. Two common approaches to investing vary substantially in their assumptions and in the logic of how they aim to get you from point A to point B. If you are feeling uneasy, it may be a good time to make sure that your investment approach will allow you act so as to avoid danger. One approach focuses on the importance of diversification and uses statistical analysis to design portfolios that maximize returns for a given level of risk. It is well entrenched in investment theory and practice. This approach is characterized by graphs that show the upper and lower bounds of growth in assets and gives assurance that if you just stick to the plan, you will have an extremely high chance of meeting your investment goals. It makes a lot of sense and is hard to refute. Another approach is described by William Poundstone in Fortune’s Formula as being one that “offers the highest compound return consistent with no risk of going broke.” It is well recognized in investment theory, though probably less so in practice. It can certainly be characterized by wide swings, but gives the assurance that if you just stick to the plan, you will maximize your wealth over your investment horizon. It makes a lot of sense and is hard to refute. This juxtaposition of strategies highlights a common investment challenge: how can you tell which one is better and/or which one is more appropriate for you? Do you know which one your financial planner or wealth manager or consultant uses? These are exactly the types of fundamental questions that are so critical to long term investment success but are so rarely discussed thoroughly. The fact is that both approaches have merit to them, but both also rely on important assumptions. The first approach is referred to as the mean-variance framework and is a part of a body of thinking called “modern portfolio theory”. While the mean-variance approach correctly highlights the importance of diversification, it does so at the expense of some serious structural shortcomings (For an excellent, though technical discussion, see Michael Mauboussin’s interview with the physicist Ole Peters here ) . One of the flaws of the approach is that it models returns using only mean and variance. Unfortunately, the reality is that return distributions have other dimensions that are extremely important to investors. Considering only mean and variance is akin to describing a three dimensional object with only two dimensions. The description will be at best incomplete and at worst, wholly unrepresentative. The implication is that all of those great graphs of wealth accumulation are at best possibilities and at worst complete fantasy. Another important flaw of the mean-variance framework is that it relies on expectation values. In theory, according to Ole Peters, expectation values represent an “ensemble of imagined parallel universes” and can potentially serve as the “basis for sensible behavior”. In practice, however, most firms simply apply averages from the past, but these past actualities fall well short of representing all imaginable future possibilities. In other words, since (arguably) most firms do not populate the model with the right information, one cannot expect it to produce useful results. Garbage in, garbage out. This common deficiency almost completely undermines the case for using mean-variance as an investment strategy. The second approach is referred to as the Kelly criterion and gained notoriety as a betting system. Michael Mauboussin gives a nice overview in “Size Matters” here : “Based on information theory, the Kelly Criterion says an investor should choose the investment(s) with the highest geometric mean return. This strategy is distinct from those based on mean/variance efficiency.” In general, Mauboussin continues, “The Kelly Criterion works well when you parlay your bets, face repeated opportunities, and know what the underlying distribution looks like.” Poundstone adds, “The Kelly criterion is meaningful only when gambling profits are reinvested. A practical theory of investment must largely be a theory of reinvestment.” This is a key point: most people do think of and act on investments as discrete opportunities that change over time and not as a singular procedure that operates like a reliable machine. In this way, the Kelly approach seems to correspond with the way many people actually invest. According to Poundstone, “They [most people] buy stocks and bonds and hang on to them until they have a strong reason to sell. Market bets ride by default.” It is also natural to recognize the importance of reinvestment: One good investment does not a retirement make. You need to keep it up. Poundstone clarifies the strategy: “The Kelly formula says that you should wager this fraction of your bankroll on a favorable bet: edge/odds. The edge is how much you expect to win, on the average, assuming you could make this wager over and over with the same probabilities. It is a fraction because the profit is always in proportion to how much you wager.” As Mauboussin puts it, “As an investor, maximizing wealth over time requires you to do two things: find situations where you have an analytical edge; and allocate the appropriate amount of capital when you do have an edge.” An important condition for the Kelly approach is that the system only works as long as the investor “stays in the game long enough for the law of large numbers to work.” Further, it is also natural to think of calibrating the magnitude of investments according to their attractiveness. While the Kelly approach does require one to have an edge in order to make an investment, it doesn’t require one to invest when no edge exists. This all makes common sense – which ought to make it easier to adhere to even in tough times. Conversely, investors may have trouble adhering to a mean-variance approach because it isn’t that hard to perceive problems with its assumptions and logical consistency. For one, it’s not an inherently bad idea to look to past returns for an indication of what future returns might be, but why should that be the only input? Other things matter a lot such as valuations and your starting point. Likewise with assessing diversification benefits. It’s not bad to look at past cross correlations for starters, but why not also consider the potential for increased global interconnectedness to increase correlations and reduce diversification benefits in the future? Arguably the biggest issue with the mean-variance approach, however, is that it understates risk. It would make sense that unprecedented levels of central bank intervention the last seven years is a factor that ought to be incorporated into one’s investment approach, and yet mean-variance ignores it. It is also true that sometimes bad things do happen and it makes sense to try to avoid them. The mean-variance approach is very weak at adapting to change: it essentially says that since the vast majority of the time you don’t get attacked in dark alleys, you shouldn’t worry about dark alleys. Thus, although this approach is an industry standard and used by countless wealth managers, financial planners, consultants, and other industry participants, it actually serves as a very weak foundation upon which to base one’s investments. It treats the market as a utility, reliably cranking out returns, but that isn’t how the market actually works – as anyone who follows it knows all too well. As a result, it may well be that much of the anxiety investors feel in regards to unsettled markets has a lot to do with the discord that they feel in regards to the mean-variance approach. To be fair, it is not like the mean-variance framework is an obviously bad idea that never should have taken hold. The theory is over fifty years old though and a great deal has been learned during that time to improve and refine investment approaches. As one example among many, advances in behavioral economics have been a major development. Indeed it is one of the weaknesses of the investment services industry that it has been slow to disseminate many of the useful advances in investment theory and practice nearly as quickly as markets have evolved. The Kelly approach isn’t the end of the line either, but it does represent progress. Just like walking alone down a dark alley at night can intuitively seem like a bad idea, so can navigating through markets with an investment strategy that you don’t really trust. Neither may seem incredibly risky at the time and you might even be able to get by unscathed a few times. Don’t let anyone convince you that such actions are a good idea though. People are usually pretty good at spotting danger; make sure you are just as good at responding to it. If you don’t have a good idea of where to go, ask for help. (click to enlarge)

A Volatile, Illiquid Paradise

Summary Two characteristics of today’s market – volatility and illiquidity – are in focus for many investors. What many small investors fail to realize is that straightforward Graham-style investing isn’t the only way to profit from volatility. This market is paradise for the small, self-directed value investor with a willingness to take on insurance liabilities. There is a lot of confusion about volatility . Some people think that volatility is the square root of the variance in a price series. They would be correct, except when they’re not. Others think that volatility is whatever the CBOE’s VIX metric says. This is also true, but limiting. Similarly, still others would argue that volatility is whatever the derivatives market implies that volatility is. Most will agree, however, that volatility is bad . We say “most,” but Seeking Alpha really isn’t “most” people. Any investor with even a cursory understanding of Graham-style investing knows the metaphor of Mr. Market, the moody, irrational purveyor of market prices. If we are patient with him, we can take advantage of his irrationality, which is what we ought to do as investors. In this understanding, volatility is simply noise , and it certainly isn’t a bad thing. As value-driven investors, we encourage this latter mentality, but we wonder if “volatility-as-noise” cuts the conversation too short. We see more opportunity here than the traditional Graham paradigm suggests. Taking advantage of more When we take advantage of what we estimate to be mispriced securities, we are directly using the volatility of the market to our advantage. The idea is that our counterparties (sellers or buyers) are simply lacking in time, cash, or information (or perhaps they are limited by fiduciary obligations), and when we trade shares, their loss is our gain. What if we take this one step further? If we are comfortable taking advantage of others’ value miscalculations by buying or selling a stock at a certain price, why would we not also be comfortable taking advantage of our counterparties’ miscalculations (or irrational obsession) with volatility itself? Return to the popular impressions of volatility. Each has profound limitations. When we take the square root of a variance , we are more often than not simply using a security’s end-of-day closing prices. This ignores daily ranges, which can be quite significant. When we refer only to the VIX , we correlate volatility almost exclusively with indices’ downside and thereby mistake “volatility” for “fear” (thank the financial media for this). When we rely on the implied volatility of derivatives, we assume a standard deviation of returns in a stock, largely ignoring the possibility of gapping and skewed returns. Assessing risk with any one of these volatility measures is a fool’s errand — and there are plenty of fools in the market. The illiquidity trap When we view volatility as baseless noise rather than risk , a whole world of opportunity presents itself. I.e., if we think that Mr. Market’s irrationality presents us with opportunity, then others’ “risk” can be our reward. If you were afraid of volatility (here meaning simply variation in a price series), as many portfolio managers are (think pensions), you would be eager to hedge against it. This has always been the case, though as we gaze into the maw of a potential bear market, survival instinct makes portfolio insurance more appealing than ever. As a corollary, selling insurance (puts) in periods of (VIX-style) volatility can be quite profitable. August 24th demonstrated, however, that this is not “normal” volatility. In the last few years, the Wild West of HFT penny-spread market-making turned the average transaction size into a tiny fraction of what it used to be, and largely pushed other market-makers out of the game. When the exchanges then gradually disincentivized even HFT market-making (thank you Michael Lewis ), no one was left to provide liquidity — especially in times of uncertainty (see 2010 Flash Crash ). What this means for the aforementioned portfolio managers is that the exchanges are not friendly places to do business in volume. For large orders, crossing networks and dark pools are preferred. The problem with these venues is that your counterparty is typically as well-informed as you are (i.e., they won’t be buyers when things are hairy). With nobody to sell to, paying a premium for a put option (and guaranteeing yourself a customer at a pre-determined price) becomes even more appealing. Selling insurance Value investors have beliefs about the intrinsic value of companies . Whether by virtue of cash-flow growth, “real options,” management savvy, or relative undervaluation, we can determine a range of prices at which we would be happy to own any publicly traded stock. Sometimes those ranges are small and confident; sometimes they are wide and uncertain; sometimes they converge at $0.00. Regardless, we have a basis for investment and a preferred entry point. The upshot to this assumption is that by selling insurance to portfolio managers in the form of put options, we can have our cake and eat it too. By selling a put at a strike price within our target range, we can not only provide ourselves the opportunity to buy into a stock at a favorable price, but also collect premium for our trouble (regardless). Furthermore, since brokers tend to be generous in their risk calculations for put-sellers (thank the Black-Scholes-Merton equation for conventional risk-assessment), we can get our fingers into all sorts of opportunities at relatively low cost, spread risk across multiple sectors, and collect premium while we wait. To most speculators, “risk of assignment” in the case of a decline in price would be detrimental. To a value investor, “risk of assignment” at a favorable price doesn’t sound much like risk at all. This is the strength of being a value-oriented investor. Ignoring a high-volatility, high-premium market environment is a missed opportunity. To some readers, this will already seem mind-numbingly obvious. Indeed, some contributors on Seeking Alpha are already practitioners of this philosophy (though they are not usually the most visible). Others, however, may not have seen an opportunity for this approach in the frothier, low-implied-volatility markets of the past few years, and may have discarded the idea out of hand. Now – in a high-volatility, high-uncertainty, and low-liquidity market – is the time to reconsider.