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Best 20+ Odds-On Oil And Gas E&P Stocks, As Seen By Fund Clients Of Market-Makers

Summary With Crude Oil Prices in mid $40s, up from high $30s, a turn may be coming for independent new extraction technology explorers and producers. Tough times of world price cuts by more than 60% leave only the strongly resourced, well-financed, advantaged survivors. Their rebound time may be near at hand, as seen in large-volume order flows from big-$ investment portfolio managers. Who are the best positioned energy stock survivors? The best candidates are indicated by the “order flow” from big-money “institutional” clients of market-making investment banks, suggesting high-probability additions to their billion-dollar portfolios. (If you have read this story before, please skip directly to Figures 1 and 2) The fund-management clients have extensive, experienced research staffs constantly looking for sound, long-term, rewarding investment candidates. The presence of their interest in these issues typically is a disruptive influence to markets because of their size of transaction orders. The “regular way” every-day “retail” investment transactions largely get handled (or mis-handled) by automated systems developed by advances in transaction technology. Those advances have cut the costs for individual investors to fractions of a cent per share, compared to pre-Y2K costs of sometimes a dollar or more a share. But big-volume “block” orders can’t be handled that way without crashing the system. They must be negotiated among other big players in this very serious game. That is where the market-maker firms play an important role. The MM firms know which players own what, and have a good idea of what their current appetites may be. Usually differences of opinion as to appropriate valuations for specific stocks are not evenly balanced enough among these fund-manager players to instantly “cross” trades of tens or hundreds of thousand shares. So the MM firms even out the balance between buyers and sellers by temporarily committing their own capital. But they don’t go naked. The at-risk commitments of MMs are always hedged in one way or another, and the cost of that protection is borne by the trade-originating client. It is built into the trade “spread” between the single per-share price of the block deal and the current “regular-way” market price. The cost of the hedge deal and the structure it takes is negotiated between the arbitrage artists of the MM firms block trade desks and “Prop” trade desks in open competitive combat. What it costs and the shape it takes reveals what these well-informed, profiting antagonists believe is possible to occur between now and the time it may take to unwind the contracts on derivatives used in the hedge. That often could be as much as a few months. So the range of possible prices implied is not an instantaneous, trivial spread. Often it is 10% to 20% or more, given the uncertainties involved in the underlying security. Where today’s market quote lies in that forecast range may be important in the stock’s future movement. The first thing to remember about this analysis is that it is a “snapshot” of current conditions, dominated by price relationships that are likely to change in coming days, weeks, and months. Those changes are typically the main point on most player scorecards. This article is not an evaluation of how “good” the companies involved are at managing, competing, profiting, or treating their employees or shareholders. It simply tells how well on this date the perceived prospects for each equity investment security candidate may be, compared with those of others, on a variety of matters and measures of concern. This is not a long-term hold evaluation. But it could identify overlooked, near-term value opportunities to be captured by active investing management. The place to start in the analysis is with the market character presented by each of the best dozens of stocks out of the hundred or more once on the scene. Figure 1 tells those stories: Figure 1 (click to enlarge) Source: Yahoo Finance, Peter Way Associates Items of concern here have to do with how easy it may be to get out of a position if in a hurry, and what the cost of doing so might entail. The first four columns do so by calculating how many market days’ average volume of trading at the current price it would take to completely replace existing shareholders. That is not expected to happen, it just gives a realistic comparative measure of how easy or difficult it might be to extricate oneself from an unwanted position. Extreme examples here are Enbridge (NYSE: ENB ), with a million-share-a-day trading volume to take over 3 years to clear its huge $34 billion of outstanding shares. At the other extreme is the market-tracking SPDR S&P 500 Index ETF (NYSEARCA: SPY ) with a five times as large ownership value, but 139 million share daily volume doing the task every 6 days. Yes, Sasol, Ltd.(NYSE: SSL ) shows a capital turn in over a thousand days, but it is a South African company and its principal share trading takes place in markets outside of the US. Another dimension of the distress of departure is what the typical trade cost may be, which can be indicated by the stock’s bid-offer spread. These days that tends to be a tiny fraction of the value per share during normal market hours. But every investor needs to protect themselves against errant or intentional malicious spread quotes by always using price limit orders when changing positions, instead of unrestrained “at market” orders. The other useful matter of perspective in Figure 1 is a sense of each stock’s current price in relation to its past year’s trading range, and a sense of how the size of that range compares to alternative investments. The Range Index [RI] tells what proportion of the whole range lies below the stock’s current price. A low past RI indicates a price depressed in comparison with earlier trading, and a high past RI tells of a stock that has been on the move up near new highs. The range size is a dimension only discussed in the media as an example of either triumph or disaster, but rarely in company of comparable alternatives. The average sizes here in this group are over 100%, meaning that a double in price (or a 50% drop) is commonplace. The latter phase just mentioned of that change scares most investors, as it should. But it is an all-too-common condition, often setting the stage for the former-mentioned next joy. So what does come next? That is what everyone wants to know, and not knowing for sure, everyone guesses at. MMs have a leg up in the game, since they know what their clients, with the money muscle to move markets, are trying to do. The well-informed protection sellers provide deals very likely to assure themselves of nice profits, with little likelihood of having to deliver on the immunization. A done deal tells where the extreme possibilities lie. Those outer limits have been shown in a high proportion of instances to be quite reachable. The agile, fleet-of-foot protection sellers usually manage to profitably transfer the accepted risks to others and get on to the next deal before having to make good on their bet this time (again). So the price range forecasts implied by the capital-risk hedging can be useful information to others interested in the stocks or ETFs involved. To determine how useful the current forecasts may be, we look back to how similar prior forecasts (made without knowledge of what next happened) were actually treated by a merciless marketplace. Figure 2 tells the particulars, and provides a means of ranking the attractiveness for wealth-building active investors. Figure 2 (click to enlarge) source: Peter Way Associates, blockdesk.com At the outset, something about Figure 2 should be understood. Columns (2) and (3) are current-day forecasts, implied by the self-protective actions of market-making professionals in the course of serving transaction orders from big-$ clients at or near column (4). All the remaining columns are matters of record of how prior forecasts for the subjects in column (1), made live in real-time over the past 5 years, have actually performed. Those prior forecasts were only those of the total available in (12) that had upside-to-downside proportions like the current forecast, described in (7). The Range Index [RI] tells what percentage of the whole forecast range lies below (4). The size of this sample set of forecasts has potential statistical implications if it is small. Few of the subjects of Figure 2 have that problem, and none of the top ten. This is the importance of column (12), a dimension pertinent to all references to prior performance. The number of forecasts available in any subject’s current situation is a function of the current Range Index. More will be available when the RI is in the 30-50 area and fewer when the subject is at extremes, nearing zero or 100. Market price behavior varies from subject to subject for a variety of reasons, so attractiveness based solely on RI can be misleading. That makes this kind of analysis in detail important. Additional evaluations may be useful when RIs are at or near extremes. The historical data of Figure 2 differs significantly from “back-test” data because it is based on the live forecasts made at the time, when subsequent price action confirmations were not available. The usual back-test data only is presented when full knowledge of the outcomes is at hand. That makes it impossible to know what kind of decisions might have been made at the time. This historical data applies our standard TERMD portfolio management discipline to buy positions of all column (12) sample forecasts. TERMD has been in existence for over a decade. It is more fully described below . For example, column (6) is an average of the worst-case price drawdowns from the closing price of the subject on the next market day after the forecast, over the holding period up to the position’s closing. This is the relevant measure of risk, since it identifies the greatest loss likely to be taken at the point of maximum emotional stress. Column (8) on the other hand, tells what proportion of the sample forecasts were able to recover from the (6) experience and be closed out profitably by reaching (5) sell targets or by TERMD’s holding period time limit of 3 months. Column (5) relates (2) to (4). Column (9) tells what the closeouts of all subject sample forecast positions averaged, profits, net of losses (by geometric mean). The CAGR of these experiences in (11) uses the average holding period of (10) in conjunction with (9). The promise of (5) is tested by (9) in (13). The proportion of (5) to (6) is shown in (14). Overall, a figure-of-merit is calculated in (15) by odds-weighting (5) by (8) and (6) by (8)’s complement, further conditioned by the frequency of (12). The table’s contents are ranked by (15). That ranking is what ordered Figure 1. What it all suggests Without getting into a detailed discussion of the attributes of interest, comparisons of the best-odds (most attractive by column 15) ten E&P stocks with a market-average tracking alternative ETF, SPY, show upside price changes (5) almost twice as large, and risk exposures (6) about one and a half times as large. Their forecast history translates into CAGR performances (11) four times as good as market results, with odds for profit outcomes (8) about the same, 8 out of every 10. But comparisons with the best 20 propositions from the measurable overall equity population of 2711 alternatives, puts the Oil&Gas E&P stocks at a disadvantage. The difference lies not in the size of the payoff promise, but in its follow-through. The average price gains of the population’s best stocks surpassed their forecasts +11.4% to +10.4% , with 9 out of every 10 experiences profitable, and average holding periods to reach payoffs shorter by 36 market days to 41, or roughly 7 weeks compared to 8. That leads to a CAGR past result (11) of 114%, double the comparable measure of +55% for the E&Ps. Conclusion I appears that there is sufficient early action in volume trade transactions in Oil & Gas independent Explorers and Producers to elevate expectations for their coming stock prices to a level more than competitive with passive market-index ETF investing. Best candidates may be PDC Energy (NASDAQ: PDCE ) and Matador Resources (NYSE: MTDR ). Perhaps in coming weeks this activity will strengthen and raise the prospects higher. But at present there are a number of alternative equity investments that substantially surpass the typical prospects of the best of this group. Commitments among those alternatives should be better rewarded. Patience, my energy friends. 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.

Behavioral Reasons For You Being Merely An Average Investor

Summary Most of us are held back by our behavioral barriers. Knowing them helps you to understand why markets behave as they do. Anchoring and the bandwagon effect are one of the most important. If you are not happy with your investing returns, then you can basically find fault in two areas: Your knowledge of investing, or your behavioral barriers. This article will go through the most common behavioral barriers that you need to understand before you can climb over them towards greater wealth. I have long believed that investment success requires far more than intelligence, good analytical abilities, proprietary sources of information, and so forth. The ability to overcome the natural human tendencies to be extremely irrational when it comes to money is equally important. Warren Buffett agrees, commenting that, “Investing is not a game where the guy with the 160 IQ beats the guy with the 130 IQ… Once you have ordinary intelligence, what you need is the temperament to control the urges that get other people into trouble in investing.” The following text is taken and modified from my master’s thesis that focused on value investing and behavioral finance. If you want to read more on the subject, two excellent books to read are Thinking, Fast and Slow and Beyond Greed and Fear . For even deeper knowledge on the matter, you can look for articles written by people named in the following text. Behavioral financial experts basically do not have much faith in the rationality of investors and therefore are against the idea that markets are efficient. If it was, then value premium would be easily explained by the relationship between risk and return. Lakonishok, Shleifer and Vishny write that, due to irrational behavior, the market prices value stocks lower and growth stocks higher. Naive investors typically overreact to the stock market related news and forecast the same growth far into the future. Because of this type of actions, they enhance the effect that might have already been taking place. In simple cases, purchase happens because stock price has gone up, and selling happens because price had gone down. But, as a simple example, this can be due to one large investor selling or buying a large amount at the same time, resulting in a price change. Some investors might take this as a sign of change and hop on or off the train. This type of investor behavior can also be explained, at least partly, by agency issues. Many professional investors might be under pressure from their bosses, clients, or due to peer competition they are forced to deliver quick results. Therefore, they are being forced to favor short-term profits over better quality investments that require longer holding periods. This type of investment pattern is often seen among institutional investors and even CEOs. Also for any professional investor, it is greatly easier to recommend the purchase of well-doing growth stocks that have a good track-record, than value stocks with a long period of negative returns. Representativeness A financial example to explain representativeness is the winner-loser effect that was proven by De Bondt and Thaler. They find that stocks that have been biggest winners during the past three years do much worse than the stocks that were the biggest losers during that same timeframe. De Bondt proves that as analysts make long-term earnings forecasts, their views tend to be biased to the direction of recent success of the firm. Meaning that analysts are overly optimistic about recent winners and feel pessimistic about recent losers. Also, De Bondt finds that market predictions are overly optimistic (pessimistic) after three-year bull market (bear market). Therefore, it becomes quite clear that analysts’ recommendations are not particularly useful when they can be linked to representativeness. One reason for this behavior is that people underweigh evidence that disconfirms their prior views and overweigh confirming evidence (Shefrin). Overconfidence In simple terms overconfident people overestimate their skills to complete a difficult task and therefore are surprised more often than they anticipated. Clarke and Statman proved that people are overconfident. They showed this by simple questions such as: How long is the Nile? Give your answer with minimum and maximum so that you are 90 percent confident that the actual length is inside your low and high guess. They asked this type of questions in survey form and found that most people are not well aware of such things but are overconfident as their high guesses were often very low compared to the actual numbers. So when people are overly confident they set too narrow confidence bands in such questions and just like financial analysts, are surprised by the results. One way to understand this is to think of a stock you were following and should have sold much earlier than you did, but you didn’t because you kept believing it can’t go lower. Anchoring and Failure to Adjust Mendenhall and Abarbanell and Bernard find evidence that analysts underreact to earnings information. Even when they get to adjust their forecasts based on new information (such as a profit warning), they are still underreacting to actual results. Their work shows that analysts fail to appropriately tweak their forecasts. What happens is that, as analysts anchor their expectations to previous information, then surprises that happen are even larger in the end. This failure to adjust expectations can then lead to value stocks and large price jumps. Psychology and limits to arbitrage Arbitrage refers to a situation where investors are able to gain a riskless profit due to the market mispricing an asset. By buying an undervalued asset and cashing the profit when prices have returned to normal. In reality the risk is that the market can continue to misprice the asset even further. This is called as the “Noise trader risk”, introduced by Long, Shleifer, Summer and Waldman. Noise trader risk happens when irrational investors keep moving the price of an already mispriced asset to the same direction, despite the actions of one or more rational investors. Also transaction costs add more risk to the equation therefore limiting arbitrage behavior. Mental accounting A typical investor does not see every euro that he possesses as being identical. Mental accounting theory helps to explain why it is quite typical for investors to divide their money to “safe” money invested in low-risk assets, while investing their “risk capital” very differently. Once money has been placed in one mental account, it no longer is a direct substitute for money in another mental account. Mental accounting theory tries to understand this psychology of decision making. Mental accounting has three components, according to Thaler. First, outcomes are apprehended and experienced. Based on this, decisions are made and later evaluated. Second, activities and sources are categorized. For example to invest or to save and also the use of these funds for spending such as housing and food. Lastly, these accounting activities are rebalanced daily, weekly, monthly or so depending of that person’s personal preferences. Gross claims that in cases where a client’s investment is at a loss a stockbroker can keep its customers by using words “Transfer your assets”, instead of referring to selling and buying. Selling would lead investors to acknowledge their losses, but now they merely transfer their money from one mental account to another. Myopic loss aversion People have stronger reaction to losses in their wealth, than they do to increases even if gains are bigger than losses. Psychologically losses are taken approximately twice as heavily compared to gains. A myopic investor is defined as a person who tends to make short-term decisions over long-term ones, and often evaluates his/her losses and gains. An example of this would be to follow a myopic and a non-myopic investor. Myopic investors would likely avoid stocks and invest in assets such as safe and stable government bonds. If he had stocks, he would constantly check the market and, in case of a loss, feel it emotionally as very painful. Therefore, myopic loss-aversion leads investors to choose portfolios that are overly conservative. While a non-myopic investor would not check the market as often and would be comfortably unaware if his wealth happens to take an occasional downhill. Therefore, he prefers long-term investments with better returns over safer government bonds. (Thaler, Kahneman, Tversky and Schwarz) Framing As defined by Tversky and Kahneman, the term “decision frame” means the acts, outcomes and contingencies that a decision maker associates with a certain choice. This one frame depends on personal characteristics, norms, habits and also on how the problem is presented. As problems can be presented in many different ways, that can also change the outcome of framing. According to Tversky and Kahneman, “Individuals, who face a decision problem and have a definite preference, might have a different preference in a different framing of the same problem, and are normally unaware of alternative frames of their potential effects on the relative attractiveness of options.” Prospect Theory Developed by Tversky and Kahneman, it is an alternative theory to analyze decision making in situations that contain risk. Prospect Theory (PT) focuses on gains and losses instead of wealth. Also, instead of using probabilities and risk aversion, PT uses decision weights and loss aversion. An outcome is called a prospect, and a prospect includes a decision with some level of risk. Decisions are made in two levels: The editing and evaluation levels. In the editing level, possible outcomes are put in order, according to some heuristic. This can be explained by people looking at the outcomes and they make a mental note of an approximate and possible average outcome. By using that average as their reference point, they’ll then categorize lower outcomes as losses and higher ones as gains. So Tversky and Kahneman state that humans prefer focusing on gains and losses instead of their final wealth. The Bandwagon Effect This is a form of group thinking. With stocks, it refers to a situation when more and more people start to buy a certain stock, the more will follow, therefore increasing the demand more and more. They might do this despite their individual beliefs and opinions, simply because other people are doing it. As more and more people join, those that are still out are under group pressure to “join the fun”. The expression, “hop on the bandwagon” is typically used when this kind of a group effect is happening. Bandwagon effect has two sides to it, according to Shefrin. First, it is believed that a crowd must know something. Second, losers don’t want to be alone. In the case of negative returns, the pain of regret is eased by the knowledge that many others made the same mistake. This theory helps us to understand why growth and value stocks perform as they do. As more and more people abandon the stock, it becomes a value stock when enough people have “left the bandwagon”. Growth stocks are the opposite until they reach their peak when the first people start jumping off. The most rational investors should be the first ones to jump on and off the stock. Conclusion The world is full of information to learn. The hard part is learning to control yourself. When you understand and remember these behavioral barriers, you are above the average investor and closer to greater wealth. The bandwagon effect is one of the most basic ones, but also the most important one, in my opinion. It explains the market behavior during the most critical times, during a bubble and a crash. 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.

1 Unique Method To Successfully Play A Volatile Market

Summary One way to make money no matter what the stock market is doing. Choosing the right sector is the key – in my case is was specific commodities. Knowing consistent price movements over time will determine the trading spread to work within. There is no doubt we’re in a stock market environment ruled by fear, as confirmed by the extreme volatility in the movement of the various indices. Much of this was triggered by the crash of the Chinese stock market, but even before then there was a growing concern about the dizzying heights the market had shot up to without a correction. The U.S. has went through a mini correction, but many believe we need a deeper and more prolonged one to bring share prices back in line with actual values of companies Other factors given as reason for volatility are low interest rates, which have tempted companies to be more reckless in their spending; uncertainty concerning whether or not the Federal Reserve will raise interest rates; slowing Chinese economy; commodity deflation; and signs manufacturing in America is slowing. I could add many more to the list. Together what it says is investors no longer have some clarity on the future, and that has been the impetus behind the extreme volatility in the market. When visibility is down and parts of the global economy collapsing, it generates an environment of fear. And that’s where we are today. One thing we must do as investors is to ignore the endless financial news headlines about the last big plunge in the stock market, and the soon-to-follow “rebound.” That’s stock price movement that historically precedes a major correction. The day-to-day movements are irrelevant. What’s relevant is if after all the movements the direction remains level or continues on down. Trading in times of fear With future uncertainty can come investing paralysis and fear, as investors move their money to the sidelines to wait to see where things go. That’s a good strategy, but there are many others that still want to find ways to grow their capital in these volatile times. I’m going to share one strategy I’ve used to capture profits in situations similar to this. As a matter of fact, it doesn’t matter whether the stock market is going up or down with this type of trade, as it has volatility built into it either way. I’m talking about silver, although I’m simply using it as a proxy for other commodities or markets that are volatile in nature. I’m going to say that again: I’m only using silver as a proxy for a number of opportunities to make money using this method. I’ve used this with silver in the past, but know of some colleagues that are using it with other commodities right now, and in your specific expertise, there could be many other sectors or segments to do the same thing. Silver trade The first thing to do is identify a highly volatile commodity that moves in predictable patterns. The one I know the best is silver, and it’s one I made a lot of money with several years ago. I decided to go with stocks and not silver options or futures. At the time I was trading was when gold and silver were still soaring, and among the top-performing and predictable silver companies at the time was Silver Wheaton (NYSE: SLW ). It was highly volatile, but it still have a primary upward share price movement, which made up for the occasional timing mistake I made, which forced me to hold it a little longer than usual. Remember, it doesn’t matter whether a commodity is going up or down in price, as long as it’s operating within a trending pattern. That’s where a lot of the risk is mitigated. The other thing is there has to be discipline in not trying to get every penny out of the trade. I always sold when the share price moved within the parameters I had put in place. Once it rose within those guidelines, I didn’t get cute, I immediately pulled the trigger and sold. Did I miss some upside? All the time. But I never regretted it. I made money on trade after trade as long as I stayed within my pre-set parameters. How was the trading performance during this time? At the best I had fourteen straight trades I made money on. Under normal conditions I would make five or six trades, and then lose on one. Keep in mind I was trading with a similar amount of money, so it was like taking 5 steps forward and one step back. It could have been even better, but within my parameters I had a holding restriction, meaning if the stock didn’t perform as expected within a specific time frame, I would sell it. That protected me from losing more than what I would make on one trade. What needs to be known In my silver trading I needed to identify the overall trend direction of silver and the daily share price movement of Silver Wheaton within that trend. Everything else I ignored. When I say everything else I ignored, I mean with the exception of something that would point to a reversal in overall trend. For example, when Silver Wheaton surpassed the $40 mark, I knew it was either going to explode in growth or move up a little more, and then start to pull back. That is how it did move, with it topping off between $46 and $47 a share. I don’t believe it ever closed at that level (during the time I was trading it), but it did reach that in intra-day trading. This isn’t rocket science. Volatile markets like silver, still have patterns within them that can be observably known, and it only takes a little research on the level of the price movements of a stock within that pattern. The only tricky part in my experience was when it not only dropped per its normal volatility, but then dropped a little more than usual for some temporary reason. If I hadn’t committed to a trading time frame, I I would have simply held a little longer and waited for it to rebound, which during the trend, it literally always did. That’s how I could hit it so many times in a row. Again, it’s understanding the flow of the pattern, which can be easily identified with any day-to-day chart. What about making money on the downside? After getting some confidence with Silver Wheaton because of my success, I started thinking about a way I could make money when the price dropped. Keeping within my preferred method of stocks or an instrument that would trade like a stock, I decided to go with ProShares UltraShort Silver (NYSEARCA: ZSL ). What ProShares UltraShort Silver does at its basic level is short silver via different financial instruments. My only problem there was I only allowed myself a certain amount of money to use with this type of trading, so I had to break up the amount I spent on Silver Wheaton if I wanted to take advantage of the downward price movement of silver. It wasn’t really a problem, but it limited my upside because of my refusal to break my discipline. That’s the key to success in this type of trading: you have to stay disciplined within your predetermined parameters. Stray outside of them and you’re likely to get hammered, even if you occasionally get lucky. What has to be watched if playing silver for upside and downside, is one of them aren’t on trend, and if it suddenly moves off trend, you could be hit hard. This is another reason I always sold when it reached the level I was looking for; whether the price of silver was going up or down. This protects you from starting to believe you know what you’re doing in regard to price movements. We can know the trends and daily movements, and within a tight trading discipline, do very well. I can’t emphasize that enough. Don’t start to think you have an inside handle on a volatile segment of the market. That’s why there has to be a system in place that is religiously followed, no matter much more that could have made on a trade. Take the gains and run. Then do it over and over again. To give an idea of how one could lose on a trade if you’re not careful and disciplined, check ZSL when it was trading at just under $5,600 a share. That happened because it was going against trend because the price of silver was moving up. On December 1, 2008, it closed at $5,598. On December 15, 2008, it closed at $3,928. You can trade against trend, but that is far riskier. I had no trouble with it, but I kept a constant eye on it throughout the day. Also understand, these were trades I would usually make within an hour or two. Rarely would I hold on longer than that. This isn’t investing, where I was analyzing the company, it’s trading, where I only analyzed price movements and the trend. I was doing this to play both volatile movements. If silver was going down in price, one could play only ZSL and drop Silver Wheaton. Conclusion Unless you have a nice chunk of extra money lying around for high-risk trading, I would stay with one trend direction and first get a grasp of its consistent daily price movements. I say that because you won’t make as much playing two different trends unless you have significant capital to put into play. You’ll have to wait for your trade to clear, which could take several business days before you have access to your capital again. And if you do that on both ends of the trade, the daily price movement could be up, which if that’s the way you’re playing it, you may have to wait a day or two before it rebounds. That means if you sell on a Thursday, you may have to wait until Tuesday before you have access to your money, and then maybe an extra day or two for the price to be positioned correctly for an entry point. If you haven’t done this type of trading before, that may seem like it’s not a big deal. But when you’re used to moving in and out of the market based upon price movements, it can seem like an eternity, and you may be tempted to get in just to be in the game. Once you decide on a commodity, or possibly a volatile stock, be sure you know the macro-economic situation, the general trend of the sector, and then the consistent price movement intervals of the commodity or company. After you have a handle on that, then develop a simple system to work within, with the most important being the price spread you will buy or sell within. You could make more money without the parameters, but you could lose more too. Under this type of discipline I’ve used it to generate significant earnings time and time again. Keep in mind I’m not suggesting to trade in Silver Wheaton here. It’s only a proxy I used because I made a lot of money using this technique with silver and Silver Wheaton in the past, and it represents the type of predictable volatility needed to make money. 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.