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Selling At The Best And Worst Possible Times

In a previous article, I expanded on Peter Lynch’s “high and low analysis.” That view looked at potential returns had you bought at the high and low price each and every year. This commentary takes the opposite view: seeing what happens if you sold at the high and low price each and every year. In a previous article , I expanded upon Peter Lynch’s “high and low” analysis. This involves looking at what would have happened if you invested at the very best and worst times (the high and low price, respectively) each and every year. The process was simple, but the takeaway is enormously instructive: “Investing at the high or low, especially over the long term, is not the difference between positive and negative returns. The difference between perfect timing and miserable timing over lengthy time periods is perhaps a couple of percent. Once you figure this out, it becomes clear that you should be focusing on the amount you can contribute and utilizing a long time frame, rather than concerning yourself with unknowable short-term fluctuations.” In Lynch’s example, the difference between perfect yearly purchases and dreadful annual timing was about 1% per annum. In my example, the difference was slightly larger, but the basic conclusion remained intact: “it’s not about timing the market, it’s about time in the market.” These demonstrations were based on the purchase side: “what happens if I bought each and every year?” For this article, I wanted to focus on the selling side. To make the process simple, we can rely on the same high and low price information as generated by the SPDR S&P 500 Trust ETF (NYSEARCA: SPY ). Here’s a look at the low price from each year dating back to 1996: Year Low Date Price 1996 1/10/96 $59.97 1997 4/11/97 $73.38 1998 1/9/98 $92.31 1999 1/14/99 $121.22 2000 12/20/00 $126.25 2001 9/21/01 $97.28 2002 10/9/02 $78.10 2003 3/11/03 $80.52 2004 8/6/04 $106.85 2005 4/20/05 $113.80 2006 6/13/06 $122.55 2007 3/5/07 $137.35 2008 11/20/08 $75.45 2009 3/9/09 $68.11 2010 7/2/10 $102.20 2011 10/3/11 $109.93 2012 1/3/12 $127.50 2013 1/3/13 $145.73 2014 2/3/14 $174.17 Additionally, we have the high price available as well from the same article: Year High Date Price 1996 11/25/96 $76.13 1997 12/5/97 $98.94 1998 12/29/98 $124.31 1999 12/29/99 $146.81 2000 3/24/00 $153.56 2001 2/1/01 $137.93 2002 1/4/02 $117.62 2003 12/31/03 $111.28 2004 12/29/04 $121.36 2005 12/14/05 $127.81 2006 12/14/06 $143.12 2007 10/9/07 $156.48 2008 1/2/08 $144.93 2009 12/28/09 $112.72 2010 12/29/10 $125.92 2011 4/29/11 $136.43 2012 9/14/12 $147.24 2013 12/31/13 $184.69 2014 12/29/14 $208.72 Let’s imagine that you want to supplement your dividend income , such that you take all of the dividends and also begin selling some shares along the way. Now, assuredly it is the goal of a great deal of people to never have to sell a share. However, that doesn’t mean that everyone must follow this route. Nor does it mean that we can’t think about the process. For illustration, let’s imagine that you have a portfolio balance of $1,000,000 back in 1996 (the number isn’t important, just the underlying math). Your idea is to buy shares in an assortment of holdings (in this case an index fund), collect the dividend payments and supplement this by selling an amount of shares each year. Let’s imagine that you want to sell $25,000 worth of shares beginning in 1997, followed by a 2% larger amount in the subsequent years. Here’s what your sold shares would need to amount to through the years: Year Sold Shares 1997 $25,000 1998 $25,500 1999 $26,010 2000 $26,530 2001 $27,061 2002 $27,602 2003 $28,154 2004 $28,717 2005 $29,291 2006 $29,877 2007 $30,475 2008 $31,084 2009 $31,706 2010 $32,340 2011 $32,987 2012 $33,647 2013 $34,320 2014 $35,006 Note that I’m taking a bit of a shortcut here. In reality, instead of focusing solely on the amount of shares you want to sell each year, you’d like to focus both on dividends received and the amount of shares needed to sell in a given year depending on your income requirement. However, with the high and low prices varying dramatically in dates, it’s a rather manual process to figure out the dividends received. It’s not uniform such that sometimes you have more than a year between the high or low price in two consecutive years and sometimes the time frame is just a few months. However, for our purposes, the illustration of selling a certain dollar amount of shares each year will work nicely. Let’s begin by seeing what happens in a “best case” scenario. The low price in 1996 was just under $60 per share. If you bought at this time, you would have been able to purchase 16,675 total shares. Additionally, your expected annual dividend income would have been about $21,000. We can now move on to the process of selling. In 1996, you were able to purchase shares at the best possible time. Let’s presume that you’re also able to sell shares at the best possible time – the highest price of every single year. In 1997, the highest share price was just under $99. In order to generate $25,000 in additional income, you would need to sell roughly 253 shares. As a result, your share count would go down to 16,422 or thereabouts. And so the process continues; in 1998, the highest share price was just over $124. In order to generate $25,500 in supplemental income, you would need to sell 205 shares, bringing your total share count down to 16,217. Here’s a look at your year-end share count from 1996 through 2014 if you kept selling at the high each year: Year Shares 1996 16,675 1997 16,422 1998 16,217 1999 16,040 2000 15,867 2001 15,671 2002 15,436 2003 15,183 2004 14,947 2005 14,718 2006 14,509 2007 14,314 2008 14,100 2009 13,818 2010 13,561 2011 13,320 2012 13,091 2013 12,905 2014 12,738 At first glance, this looks like pretty bad news. You started with 16,675 shares, and nearly two decades later, you’ve sold almost 4,000 shares, bringing your total share count down to “just” 12,700. Yet, it’s important to remain cognizant of what this indicates. Your share count has been reduced, that much is obvious. What’s not as apparent is the idea that you would actually be getting richer over time. Your $1 million beginning portfolio balance would now be worth nearly $2.7 million. Further, in the last 12 months, this amount of shares still would have generated $50,000 worth of dividend payments. Contrary to what many suppose, selling shares doesn’t have to be an exhaustive process to zero. I’m not necessarily personally advocating for this method, but it’s instructive to know that this option exists nonetheless. In this particular case, you would have collected hundreds of thousands in dividends, sold over half a million in shares through the years and still ended up much richer. Of course, this was also a best-case scenario – buying at the low and selling at the high every single year. Let’s take a look at the “worst case”: buying at the high and selling at the low every single year. In 1996, shares of the index traded as high as $76. Had you purchased shares at this price, you would have begun with 13,135 total shares – noticeably lower than the “best” case of buying at the low. Additionally, your expected annual dividend income would be about $17,000. (We could adjust for this in the example, but the illustration is the important part). In 1997, the low share price reached about $73. In turn, in order to reach your $25,000 supplemental income goal, you would need to sell about 341 shares. This would bring your total share count down to fewer than 12,800 (basically where the other example ended). Wash, rinse, and repeat. Here’s a look at your year-end share count each year after selling shares to reach your additional income goals: Year Shares 1996 13,135 1997 12,795 1998 12,518 1999 12,304 2000 12,094 2001 11,816 2002 11,462 2003 11,113 2004 10,844 2005 10,586 2006 10,343 2007 10,121 2008 9,709 2009 9,243 2010 8,927 2011 8,627 2012 8,363 2013 8,127 2014 7,926 Once more it’s obvious that your share count will be reduced each and every year. Moreover, it’s also apparent that this situation is markedly worse than the “best case” scenario. Yet, the output provided here is perhaps even more instructive. You began with a $1 million balance that was purchased at the worst possible price point. Then you went on to make sale after sale at the worst possible time each and every year. However, those 7,900 shares would now be worth almost $1.7 million. Further, over the last 12 months, these shares would have provided over $31,000 in dividend income. Expressed differently, even if you bought and sold at the worst possible moments, you would still get richer over time (with a larger cash flow to boot). The reason this works is due to “selling in moderation.” Obviously, you can’t go out and sell 15% of your portfolio each and every year and expect to end up with a higher portfolio balance over time. However, when done purposefully, selling shares and getting richer do not have to be opposite notions. The thing of it all is that you’re not going to complete either exercise. You’re not going to have perfect timing and you’re not going to have the worst possible timing year-in and year-out. Mathematically it just won’t occur. Yet, even if you did, at least in this illustration, it has been no great tragedy. Regardless of the situation you still ended up with a higher balance. Much like the previous example of consistently buying, it seems that having an underlying plan – rather than figuring out the “best” timing – is a much more important factor. Disclosure: I/we have no positions in any stocks mentioned, and no plans to initiate any positions within the next 72 hours. (More…) I wrote this article myself, and it expresses my own opinions. I am not receiving compensation for it (other than from Seeking Alpha). I have no business relationship with any company whose stock is mentioned in this article.

The Unreliability Of Human Judgment

Human decision-making is greatly influenced by individualistic preferences, making it very unreliable in most situations. We tend to foolishly project our own biased opinions onto other people, which can adversely affect the quality of our judgment. A statistical approach to decision-making, which requires little, if any, subjectivity, is a lot more robust and reliable. Back in the late 1990s, a struggling author and divorced mother on welfare was trying to publish her first book — a story about an orphan boy wizard. It was rejected by 12 publishers, and her agent warned her that she would “Never make money writing children’s books.” This prediction would prove to be spectacularly wrong. As it ironically turned out, 13 was her lucky number when a small London publishing house reluctantly took a chance and agreed to print it. That book, Harry Potter and the Philosopher’s Stone (or Sorcerer’s Stone for the American version) , went on to sell over 100 million copies, making it one of the best-selling books in history. And that author, J.K. Rowling, would eventually write six more books in the Harry Potter series, which collectively sold over 450 million copies and were adapted into a blockbuster film franchise. Not only did J.K. Rowling make money writing children’s books, it in fact made her rich. Stories like this are not uncommon. A publisher turned down George Orwell’s legendary novel, Animal Farm , explaining it was “Impossible to sell animal stories in the U.S.A.” Decca Records turned down a contract with the Beatles, saying “We don’t like their sound, and guitar music is on the way out.” Walt Disney was fired by a newspaper editor because he “lacked imagination and had no good ideas.” Oprah Winfrey got fired from a job as a news reporter because “she couldn’t separate her emotions from her stories.” Arnold Schwarzenegger was told he’d never be a movie star because “his body, name, and accent were all too weird.” These success stories should really make us question the reliability of human judgment. How could a dozen experienced publishers deem the manuscript for the first Harry Potter book unworthy of publication? Why is it that a large recording company, whose job it was to seek out talented musicians, couldn’t recognize the potential of the Beatles? What took Hollywood so long to recognize the star potential of Arnold Schwarzenegger? The answer is simple — human judgment is influenced by individualistic preferences, making it an unreliable predictor of future outcomes. Let’s say a publishers reviewing the original Harry Potter manuscript happened to dislike stories about magic for some reason, this bias against magic would largely determine whether the book gets published or not. But just because one individual, or even a small group of individuals, dislike a book, that doesn’t mean the book won’t become a best-seller. We should never project our own subjective opinions onto others, because it can adversely affect our judgment and decision making. This is something I learned in high school, when my friend and I once turned in identical essays. Luckily for us, not only did our overworked teacher not notice, she gave my essay a 95 (an A) and my friend’s essay an 82 (a B). Perhaps she just liked me more which subconsciously influenced her grading decision (that’s what I told my friend anyway). Or maybe she was in an unusually good mood at the time she was grading my paper. As crazy as it sounds, the second explanation could in fact be true. It’s been shown that even judges, who are trained to be objective, rule more favorably after lunch breaks (because food puts them in a good mood). The inherent subjectivity involved in grading can be quite problematic since a student’s future depends on such imprecise measurements. In one study , for example, researchers collected 120 term papers and had each paper scored independently by eight faculty members. The resulting grades sometimes varied by two or more letter grades. On average they differed by nearly one letter grade. Given that the average opinion is typically more accurate than most of the individual estimates (i.e., “wisdom of crowds”), the best solution here would be to average the eight independent scores for each paper to derive a more objective overall grade. I once recommend that Seeking Alpha implement something similar. The current editing process is highly subjective. It’s unrealistic to think that an editor, who’s as naturally biased as the publishers that rejected Harry Potter , can distinguish so finely between articles to tag one as, say, an “Editors’ Pick” and another as standard (“Regular” or “Premium”). But by having multiple editors independently reviewing and grading the quality of each article, and then averaging their individual opinions, it would eliminate much of the subjectivity inherent in the editing process. Another subjective measurement that receives more credence than it deserves is the rating of wines. My favorite example is the rating of the 1999 vintage of the Mitchelton Blackwood Park Riesling. One wine rating publication gave it five stars out of five and named it “The Wine of the Year,” while another rated it at the bottom of all wines it reviewed, deeming it “the worst vintage of the decade.” This discrepancy is to be expected, of course, given that wine ratings are based on unreliable, subjective taste perceptions of wine tasters. In one series of experiments , judges at wine competitions were given the same wine at different times throughout the day; the results showed that judges are wildly inconsistent in their evaluation. A wine rated 90 out of 100 on one tasting would often be rated 85 or 95 on the next. This inconsistency explains why the probability that a wine which won a gold medal in one competition would win nothing in others was high; in fact, the medals seemed to be spread around at random. This should make you think twice before purchasing an expensive bottle of wine next time. So far we’ve seen that all subjective measurements are flawed and unreliable. The best way to fix this problem is to take a more objective, statistical approach to measurement. A well-known example of this is Moneyball , a true story about a low-budget baseball team that leveraged statistics, rather than the subjective beliefs of baseball insiders, to identify players whose skills were being undervalued by other teams. This statistical approach to player selection revolutionized the game, and has since been implemented in other sports as well. Credit card companies have also learned to appreciate the power of simple statistical measurements. In the past, human judgment was the primary factor used to evaluate a borrower’s credit worthiness. Not only was this a slow process, it was also very subjective and created a lot of variability in the results. But then a statistical formula known as a “credit score” came along and put a solid number on how risky you were to lend to. The investment business is another area where statistics has gained a strong foothold over the past couple of decades. Investors who employ statistical trading methods are usually called “quants.” The world’s most successful quantitative hedge fund is Renaissance Technologies, which uses elaborate algorithms to identify and profit from inefficiencies in various highly liquid instruments around the world. But investors don’t need to be as sophisticated as Renaissance in order to reap benefits from quantitative investing — even very simple statistical models can work quite well. One of the most well-known is the “Magic Formula,” a model that ranks stocks based on just two variables: return on capital (measures quality) and earnings yield (measures cheapness). Researchers have conducted a number of studies on the Magic Formula and found it to be a market beater, both domestically and abroad. But even a simpler one-variable model, which only uses the cheapness metric, has also been shown to beat the market over the long run. The reason quant-style value investing works is because, unlike a more traditional approach to stock selection, it doesn’t attempt to calculate a company’s “intrinsic value” by foolishly attempting to forecast its long-term financial performance. Instead, it systematically buys the cheapest — and often most hated — stocks based purely on historical data (a very contrarian approach). Another problem with the concept of intrinsic value is that there’s absolutely nothing “intrinsic” about it. It’s not an objective measure at all. It depends entirely on the person doing the valuation, just like the quality of wine depends on the person doing the tasting. This is largely because risk preferences vary from person to person, and even in the same person from time to time. This was discovered by neuroscientists studying professional traders. They found that fluctuating hormone levels — like testosterone and cortisol — can wildly alter a trader’s risk taking or risk aversion. And since these shifting risk preferences directly affect discount rates, which determine the present (or intrinsic) value of stocks, it means that intrinsic value isn’t static — it’s actually in constant flux. Traditional stock picking is flawed in other ways as well. Even the mere act of owning a stock, particularly one you’ve spent considerable time researching, can create emotional attachment, leading you to value it more than you would if you didn’t own it. Inheriting a stock can also create a similar emotional attachment. A friend of mine once inherited a large number of shares in General Motors (NYSE: GM ). When I advised him to sell some shares and diversify the proceeds, he said he “Can’t bring himself to part with his grandfather’s gift.” Unfortunately for him, this “gift” became worthless a year later when the company filed for bankruptcy. This irrational tendency to overvalue something just because we own it is called the “endowment effect.” In residential real estate sales, for instance, there is, on average, a 12% gap between what the owner asks and what the average buyer is willing to pay (in a bad market the gap exceeds 30%!). This is because owners truly believe their homes are worth more. Perhaps they’ve lived there for a long time and have many happy memories associated with that house. The buyer, on the other hand, is more likely to care about things like the black mold growing on the ceiling. It’s just difficult for us to see that the person on the other side of the transaction, buyer or seller, isn’t seeing the world as we see it — value is largely subjective. As explained throughout this article, most of our decisions, both big and small, are guided by our subjective emotions and perspectives. This is usually an automatic cognitive process. Psychologists call it “System 1” thinking, which is fast, instinctive, and nearly effortless. The opposite of this is “System 2” thinking, which is slow, deliberate, and effortful. Our brains tend to be lazy, always looking for the easiest way out, so System 1 guides the majority of our day-to-day decisions. And most of the time it’s actually quite effective. For instance, ever drive home without remembering the exact details of the trip? That’s your System 1 at work. But sometimes this type of fast thinking can lead to poor decisions. Consider this famous example: A bat and a ball cost $1.10 in total. The bat costs $1.00 more than the ball. How much does the ball cost? The most common answer — and the one suggested by our System 1 — is 10¢. But the real answer is actually 5¢. It requires the slow, effortful thinking associated with System 2 to get it right. Most people simply don’t want to think that hard, so they give the first answer that comes to mind. These same mistakes occur in every domain. In sports, for instance, decisions worth millions of dollars are made on the basis of a coach’s hunch or a scout’s gut feeling. This explains why there’s a long history of so-called “promising” athletes that never realized their full potential. Moneyball showed us that traditional scouting often focused more on the so-called “eye test” (i.e., if someone “looked” like a major leaguer) than on a more objective, statistical analysis of player potential. I myself was twice offered a full athletic scholarship to play football in college. The funny thing is that I never even played the sport before. The recruiters and coaches — fooled by their quick-thinking System 1 — just assumed that I’d be a good football player because of my size and athleticism. I respectfully decline these generous offers (definitely not worth the injuries). In short, reducing subjectivity is a desirable goal for decision makers of all kinds — from entrepreneurs to investors to individuals dealing with their day-to-day personal problems. However, this isn’t to say that individualistic subjectivity is always a bad thing. There are some situations, mate selection being one of them, where it can be quite useful; beauty is, after all, in the eye of the beholder — it’s subjective and difficult to quantify. However, in most other situations, especially ones involving a financial component to them, subjectivity tends to cause more harm than good. In this particular case, the best way to minimize the probability of being wrong is to leverage the power of a more objective, statistical way of thinking. Disclosure: I/we have no positions in any stocks mentioned, and no plans to initiate any positions within the next 72 hours. (More…) I wrote this article myself, and it expresses my own opinions. I am not receiving compensation for it (other than from Seeking Alpha). I have no business relationship with any company whose stock is mentioned in this article.

Ameren Corporation: Creating Stable Income Streams At Less Risk Than The Market

Summary The public utility sector is going through a challenging period. Experts are mixed on the long-term prospects of the stock, but median estimates give a 12.55% upside at current levels. Ameren has only reduced its dividends once, during the 2008-09 crash. Ameren Corporation (NYSE: AEE ) is a natural gas and electric utility company that operates in Illinois and Missouri. It is operating in a challenging business environment with evolving environmental regulation. The experts are mixed regarding Ameren’s future stock value; however, the median estimate provides an upside of 12.55% at current price levels. Ameren produces a stable and predictable dividend which mitigates a small amount of market risk when holding the stock. The Company is a buy for risk-averse investors who are looking for an income stream that is relatively unlinked to general market risk. Major trends in common to the electric and natural gas utility industry ( F rom the 10-K ) Political, regulatory, and customer resistance to higher rates. Tax law changes that accelerate depreciation deductions, which reduce current tax payments but also result in rate base reductions and limit the ability to claim other deductions and use carry-forward tax benefits. Cybersecurity risks, including loss of operational control of energy centers, and electric and natural gas transmission and distribution systems and/or loss of customer data. Increased competition in supply, generation, and distribution. Pressure to grow customer base in light of economic conditions and energy efficiency initiatives. The availability of fuel and fluctuations in fuel prices. Higher levels of infrastructure investments could result in decreased free cash flows. Company Positioning Ameren’s primary assets are its subsidiaries including Ameren Missouri and Ameren Illinois. Both of these subsidiaries are rate-regulated electric generation, transmission and distribution businesses as well as rate-regulated natural gas transmission and distribution businesses. Ameren’s other subsidiaries are responsible for activities such as the provision of shared services. Another of Ameren’s subsidiaries, ATXI, operates a FERC rate-regulated electric transmission business. (click to enlarge) Ameren’s profits and subsequent dividend payouts are dependent upon these regulated revenue streams. Growth Strategy ( F rom the 10-K) Renewable Mandate: Ameren is expected to increase its renewable energy resources to 10% of its total portfolio by 2015 and 25% by 2025. It is achieving these goals through IPA agreements and long-term contracts with renewable energy suppliers. Transmission and Distribution: AEE is involved in multiple transmission generation products which should alleviate congestion and bring access to new economic zones. Energy Efficiency: Ameren Missouri and Ameren Illinois have implemented energy efficiency programs. In Missouri, the MEEIA established a regulatory framework that allows electric utilities to recover costs related to customer energy efficiency programs. A MEEIA rider allows AEE to collect from or refund to customers any annual difference in the actual amounts incurred and the amounts collected from customers for the MEEIA program costs and lost revenues. Risk Management ( From the 10-K) Regulatory and Environmental Matters: Ameren is subject to a complex legal environment. The EPA is developing and implementing environmental regulations that will have a large impact on the electricity industry. Its coal-fired plants may incur significant costs to comply with these regulations. Natural Gas Price Fluctuation: AEE’s natural gas procurement strategy is designed to ensure immediate delivery of natural gas. The strategy is accomplished by optimizing storage options and various supply and price-hedging agreements that allow for diversification of supply source. Grid Reliability: Significant investment is going into making the grid more reliable. The increased use of distributed generation and the uneven output of renewable generation have complicated grid management, so the Company must invest in more sophisticated grid management systems. Dividends (click to enlarge) From dividend.com (click to enlarge) From dividend.com AEE has a very consistent dividend performance. The Company has only lowered its dividends once, and has maintained stable payouts. Since the dividend payout is stable, the dividend yield moves inversely to the price performance of the underlying stock and mitigates some of the market risk of holding the AEE stock. Expert Opinion (click to enlarge) From Yahoo Finance The expert opinion on AEE is mixed. Most analysts recommend holding the stock and not expanding positions at the current time. The median expert estimate on AEE’s stock price is $42.5, which gives the Company a 12.55% upside at the current price of $37.76 per share. AEE’s beta is 0.21. From Yahoo Finance AEE has been positively surprising the experts with its quarterly EPS releases; this usually means that analysts are undervaluing some portion of the Company. Recent News: Ameren Illinois continuing major upgrades to strengthen the region’s energy delivery network DiversityInc Ranks Ameren First in the Nation Ameren Missouri’s Callaway Energy Center Receives Extended Operating License From the Nuclear Regulatory Commission Retired Chairman and CEO of Unisys (NYSE: UIS ) Elected to Ameren Board of Directors Conclusion Ameren is a straight forward public utility play with exposure in Illinois and Missouri. Its revenues depend upon rate-making policy decisions, environmental policy and natural gas price levels. An investor who is looking for a company that produces stable dividends and has low market risk, would feel right at home with AEE. While the experts are uncertain about the future stock price levels, the median estimate does provide a 12.55% upside at current levels. If you are a risk-averse investor who wants to create a stable income stream with little market risk, Ameren is for you. Disclosure: I/we have no positions in any stocks mentioned, and no plans to initiate any positions within the next 72 hours. (More…) I wrote this article myself, and it expresses my own opinions. I am not receiving compensation for it (other than from Seeking Alpha). I have no business relationship with any company whose stock is mentioned in this article.