Technical Stock Analysis Tips
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What is a Regression Channel Analysis?
A regression channel is a product of a statistical analysis process called linear regression. In short, a "best fit" line is drawn through the middle of a set of data points encompassing a specific period from the day of a significant low to the day of a significant high (or vice versa). The slope of this line, called the midpoint, reveals the nature of the trend. We prefer to find situations where the midpoint line is significantly sloped either up or down. This alone heightens the odds for directional movement. The next step in our analysis is to use charting software to automatically draw parallel lines above and below the midpoint line. These parallel lines are connected to significant lows and highs and these reference points help form our regression channel. The regression channel also acts as a kind of standard deviation, with the middle line acting as a median. From this, we make note of whether the stock gravitates toward the lower or the upper end of the channel. In short, regression channels simply provide a clear picture of the equity's overall trend. The idea behind regression methodology is to build a channel around the price data of a security and then project that channel forward in time. It is this projected portion of the channel that generates trades. Regression Channel Chart of Calpine (CPN): Breaks outside the channel are often a sign that either a more accelerated trend is in store or a reversal in trend has developed. If the breakout holds, it is often advantageous to trade the direction of the break. As stated above, these channels are based off a regression line, which is calculated using the sum of the least squares method. The actual number crunching is not that important because there are a number of software charting packages that will perform the calculations. rend. Regression Line: While this mathematical calculation identifies the slope of a trend, it is critical to first identify the starting point and ending point of the data to be examined. In order to begin a channel, a significant low must be identified. The term "significant" allows a great deal of flexibility in applying this methodology, which can be adapted to a variety of trading needs. Short-term traders, for example, can create daily or intraday channels. Longer-term traders can draw channels on weekly and monthly charts. Neither style is more "correct" than the other, as each fits different trading styles. Most traders look at regression channels with an eye toward selling near the top of the channel and buying near the bottom of the channel. What we've found is that the most powerful period for traders is when the stock actually breaks out above or below an existing channel, as this tends to imply a more steeply sloped, accelerated uptrend or downtrend for the stock over the next few days or weeks. On the bullish side, a stock that breaks out above the top regression line within an uptrending channel should be purchased on the first pullback that touches that line. The odds suggest that this former resistance line is now support, and an opportunity often appears amid a sharp pullback. If the stock dips below this rail, it is often an indication that the near-term rally has subsided, and is a signal to exit the trade. On the bearish side, when a stock breaks down below the low end of an uptrending regression channel, the short-term consequences are usually a run for the exits by investors. Conversely, if the stock breaks back into the regression channel, it is often an indicator that the stock's selling power has somewhat evaporated, and signals an exit from a bearish position.
What is Stock Technical Analysis?
Stock technical analysis focuses on historical price patterns and volume characteristics to predict the future. Strong fundamentals and technicals are usually a necessary condition for a stock to move higher. However, we believe looking at the fundamentals and technicals alone isn't sufficient to effectively determine in which direction a stock will move. Technical analysis is concerned with the history of trading and price in a stock. Technical analyst's believe that a stock's market price reveals all the known/needed information about the stock including public and insider information and investor sentiment. The founding fathers of technical analysis were Robert D. Edwards and John Magee who first published Technical Analysis of Stock Trends in 1948. Technical analysis usually takes the form of charts and tracks a stock's movements. Usually a pattern or trend emerges from a stock's movement that allows a technical analyst to determine how the stock will likely behave in the future. In 1995, Futures magazine rated the top five popular technical analysis techniques from a sample of 50 seasoned traders and analysts. The number one indicator according to popularity is moving averages, including moving average convergence divergence. Just behind moving averages on the list included breakouts (simple, channel, volatility), trend measurements (DMI/ADX), relative strength index (RSI), and stochastic/momentum oscillators.
What are Investing Volatility Bands?
Volatility bands are used to identify stocks that are prone to enter a period of unusual strength or weakness. These bands are based on a short-term moving average and the stock's own intra-day highs and lows to create upper and lower bands that move with the price action of the stock. As a stock's intraday swings increase, the bands respond by flaring apart. If the stock has enough momentum, it can break outside these bands, a move we refer to as going "out of bands." We consider a high-probability long trade one in which the stock breaks above its upper band amid a pessimistic sentiment backdrop. Conversely, stocks with high levels of optimism that are breaking below their lower band would be considered potential short trades or put buying opportunities. There are two primary patterns associated with the volatility band strategy. The first is the "out-of-bands run," in which the stock breaks outside its bands and begins a rapid move to either the upside or the downside. The second pattern that we key on is the "break, consolidate, and pop" - the stock breaks outside its band, but rather than make an immediate move, it goes through a period of consolidation sideways before popping. As stated above, volatility bands are used to set up the trades. Once a stock breaks above or below bands, it triggers an alert to a possible trade. Since the width of the bands depends on the recent price action of the stock, the methodology will automatically tailor itself to every stock it is applied to. Volatility Bands vs. Bollinger Bands: One issue that frequently comes up concerns the difference between volatility bands and Bollinger bands. Bollinger bands are based on the standard deviation of closing prices over a set period of time, while the volatility bands calculation focuses on the daily range rather than just the closing price. A comparison of Bollinger versus volatility bands shows that Bollinger bands flare out more since they are designed to contain most of the price data. In contrast, the ability of a stock to trend outside its volatility bands is one of the keys to its strength. Many times, both sets of bands are close together and quick pops tend to break outside both bands at the same time. It is where the short powerful trends occur that volatility bands can have the advantage. The ability for a stock to "trend" outside these bands is what we generally look for. Volatility Bands vs. Regression Channels: Another question that often arises is how volatility bands differ from regression channels. The biggest difference is that regression channels are hand-drawn on a chart, while volatility bands are a mathematical calculation that the computer applies. Because volatility bands are always moving with the stock, they quickly adjust to price movements. Both methodologies have their advantages but will trigger different trades at different times.
What is Support & Resistance?
One of the most basic concepts of technical analysis is support and resistance. Key points below the current price are known as support, and those above the current price are resistance. For example, if a stock falls to a level where enough buyers find it worthwhile to enter (and few potential sellers care to exit), the stock price will reverse upward, marking a point of support. Trendlines extending out from important peaks and valleys can also act as support and resistance. Option activity also plays a role in support and resistance levels at round-number strike prices. For example, if there is a great deal of put open interest at the 70 strike of XYZ Company (XYZ), 70 could mark important support. The reason large put open interest often serves as support stems from the fact that market participants who sold put options and have not hedged their positions will buy XYZ shares to keep the stock above the strike price, preventing the option from expiring in the money. The opposite is also true for large amounts of call open interest. In addition, when small speculators gravitate to a particular strike, they are very often incorrect and that option will likely finish out of the money. Various moving averages often serve as support and resistance. A 20-day moving average, for example, is simply the average of the 20 previous day's closes. The trendline formed as this 20-day average moves forward through time is often a juncture at which support or resistance can be found. Moving averages work very well when the security is trending higher or lower for a period of time, but not so well when the security moves sideways (contained in a trading range).
What Are Stock Moving Averages: Simple, Weighted, & Exponential
A moving average smooths out values of adjacent statistical observations and thereby eliminates minor or irregular fluctuations (called "noise"). A moving average is one of the most widely used technical analysis tools in all of trading and is a workhorse for many in the industry. Moving averages are used to identify the market's or an individual equity's trend in order to establish positions in the direction of the trend. While there are numerous methodologies for calculating moving averages, we will deal with the three most commonly used - simple, weighted, and exponential. All are based on the issue's closing price for the time frame used (daily, weekly, or monthly), the idea being that there are many intra-period battles going on in the market and the war isn't won until the close. Some studies will base their calculations on intraday spreads between high and low pricing, but we will not pursue that issue here. We will speak of a "10-day" moving average throughout this discussion, though the calculations for weekly and monthly moving averages will follow the same logic. Simple Moving Average A simple 10-day moving average consists of successive averages of the 10 most recent days' closing values. The calculation is very straightforward - simply add up the daily closing values and divide by 10. With each subsequent day, the newest closing value is incorporated into the average and the value of 10 days previous is dropped. One of the objections some have with the simple moving average calculation is that it assigns equal weight to each of the 10 values. It is not unreasonable to argue that the most current readings should be more important as a reflection of what the stock is doing now. This takes on added importance as the time frame increases (e.g., 20 days). Since the calculation is modified each day by dropping the oldest value in favor of adding the most current one, its fluctuation now becomes a function of just two numbers. That is, if the current value is greater than the one being dropped, the average turns upward. The converse is true - if the current value is lower than that of 10 days ago, the average moves lower. Weighted Moving Average Although the weighted averaging process is basically the same as for a simple moving average, more significance, or "weight," is added to the most current readings (on a closing basis). The weightings may be allocated to suit the individual analyst's taste and don't have to be uniformly progressive (10, 9, 8, 7, etc.). The importance here is that you are consistent in your application. For example, there is no reason why the first five days cannot have equal weightings with the progression occurring in days six through 10 (although you are complicating an already cumbersome calculation). The next step is to multiply the "weighting" by the day's closing price to come up with a "weighted price." For example: Price Weighted Calculation Date Weighting X Closing Price = Weighted Price 6/11/04 1 X 72.12 = 72.12 6/12/04 2 X 72.08 = 144.16 6/13/04 3 X 70.69 = 212.07 6/14/04 4 X 68.90 = 275.60 6/15/04 5 X 68.02 = 340.10 6/18/04 6 X 66.88 = 401.28 6/19/04 7 X 67.32 = 471.24 6/20/04 8 X 69.41 = 555.28 6/21/04 9 X 69.84 = 628.56 6/22/04 10 X 68.83 = 688.30 Sum 55 694.09 = 3788.71 694.09 / 10 = 69.41 simple average 3788.71 / 55 = 68.89 weighted average Exponential Moving Average This form of moving average also assigns greater relevance to the more current values. An exponential system is based upon the assignment of a fixed percentage weight to the current price, say 18 percent (could be any weighting; see below for rationale), and all of the remaining weight (82 percent) to the previous value of the moving average itself. The proportional weight assigned to the most recent reading is often called a "smoothing constant." To determine an exponential "smoothing constant" roughly proportional to a simple moving average of a given time length, divide two by one more than the length of the simple moving average you wish to replicate. It may sound confusing, so let's look at an example. To find a smoothing constant to construct an exponential moving average comparable to a simple 10-day moving average, divide two by 11 (one more than the 10-day simple). The result is 0.18 (why we chose this number above). As a starting point, let us assume day one to be the exponential moving average for that point in time. The exponential moving average is updated by multiplying the newest price by 0.18 (our smoothing constant) and adding that to the product of the previous exponential moving average multiplied by 0.82 (the balance of the 100 percent allocation). Date Closing Exponential Moving Avg. 6/11/04 72.12 Arbitrary start point 71.75 6/12/04 72.08 (0.18 x 72.08 + 0.82 x 71.75 = 71.81) 6/13/04 70.69 (0.18 x 70.69 + 0.82 x 71.81 = 71.61) 6/14/04 68.90 (0.18 x 68.90 + 0.82 x 71.61 = 71.12) 6/15/04 68.02 (0.18 x 68.02 + 0.82 x 71.12 = 70.56) 6/18/04 66.88 (0.18 x 66.88 + 0.82 x 70.56 = 69.90) 6/19/04 67.32 (0.18 x 67.32 + 0.82 x 69.90 = 69.44) 6/20/04 69.41 (0.18 x 69.41 + 0.82 x 69.44 = 69.43) 6/21/04 69.84 (0.18 x 69.84 + 0.82 x 69.43 = 69.51) 6/22/04 68.83 (0.18 x 68.83 + 0.82 x 69.51 = 69.38) Looking at the three types of moving averages, the largest spread between them is 0.52 points, or just 0.75 percent of the simple 10-day moving average. The issue is thus whether the additional work in calculating the weighted and exponential moving averages is justifiable in terms of providing a trading edge. It appears that the exponential moving average seems to react more quickly than the simple moving average, which could possibly signal a quicker entry or exit point for a trade. We recommend that whichever moving average you use, stay consistent with that method. Bouncing from a simple to a weighted average will only confuse you and restrict your ability to recognize equities that have historically reacted well around these trendlines. Time Frames We commonly use 10-unit and 20-unit simple moving averages. "Unit" refers to the time frame you wish to use - daily, weekly, or monthly. This changing of perspectives is like driving up to the Rocky Mountains. From a great distance, the range appears to be one solid piece of rock emanating from the earth's crust (think of this as a long-term or monthly chart). As you get a little closer (weekly chart), you start to notice that the "barren" rock is covered with trees and huge fields of snow. Taking a tram up the mountainside (daily chart), you notice pastures of grass surrounding the tree line, an occasional lake nestled into a flat, not to mention a plethora of wildlife. This short-term, or daily, chart reveals things you could only imagine from the long-term perspective. Each view provides you with a different viewpoint, though each independently does not afford a complete assessment of the mountain. Such is the reasoning behind examining the various chart views and their accompanying moving averages. The longer term charts and the accompanying longer-term moving averages can aid in determining the overall trend of a stock, index, or market. In fact, we consider the 20-month moving average as the line of demarcation between a bull and bear market. Summation There is no perfect moving average style or length. You could probably back-test all sorts of combinations and make a positive case for their predictive reliability for some stock or index. Ultimately, the ideal combination is the one that has worked for you. This brings us back to the concept of consistency. Whatever calculation or duration you use, make it yours and stick with it. Only repetitive trial and error will help you hone your technical skills with respect to moving averages.
What is Relative Strength?
The traditional focus of the relative strength indicator is the comparison of a stock to an underlying index like the S&P 500 Index (SPX), creating a single line showing relative performance. This comparison is usually the performance of a key stock versus the entire market. We think of the relative strength almost like a funnel of money flow. As the stock is outperforming a particular index, money is flowing more heavily toward that equity than that of the broader market. Likewise, if the stock is underperforming in comparison to an index, the equity has money flowing at a slower rate into the equity versus the general market. A stock that displays improving relative strength versus the market or a corresponding sector index may be on the verge of an aggressive move to the upside. Conversely, a stock that begins to show weakness relative to the market or its peers may be poised for a breakdown.
Stock Technical Indicators - Relative Strength Index
Technical indicators that give readings within a pre-defined range are called oscillators, and these work well in trading range periods. For example, Welles Wilder's Relative Strength Index (RSI) is derived from a formula comparing upward and downward moves, and only gives readings between 0 and 100. A high reading is defined as "overbought" and a low reading is "oversold". The reason oscillators such as RSI work well in trading range environments is that overbought situations are more likely to reverse lower and vice versa. If there is an underlying trend, oscillators that fight the trend will often be overpowered, making their signals useful only if they go with the trend. Relative Strength Index: The Relative Strength Index (RSI), an oscillator developed by Welles Wilder, measures the internal strength of a stock by monitoring changes in its closing prices. The formula for RSI is as follows: RSI = 100 - [100/(1 + RS)] Where: RS = average of upward price change over a select number of days/ average of downward price change over the same number of days As with the stochastic indicator, RSI fluctuates between 0 and 100. RSI peaks indicate overbought levels and suggest price tops, while RSI troughs denote oversold levels and share price bottoms. Absolute levels can vary in meaning from stock to stock and in different market environments. Two horizontal reference lines are normally placed at 30 (indicating an oversold area) and 70 (indicating an overbought area). These reference lines can be adjusted depending on the market environment. Some analysts move these lines to 40 and 80 in bull markets (raising the bar, so to speak) and lower them to 20 and 60 in bear markets. It is advised that traders use the "five-percent" rule - RSI spends less than five percent of the time beyond either reference line over a six-month period. You can adjust these reference lines every three months (once per quarter). There is no "holy grail" level dictating guaranteed overbought or oversold readings. RSI can stay overbought in bull markets and oversold in bear markets for prolonged periods. Like most indicators, you will become accustomed to using RSI, getting a "feel" for what works best for you. RSI typically produces three kinds of trading signals, as outlined below in order of significance. Divergence: The most significant signal is generated on "bullish" or "bearish" divergences between the RSI and the price of the underlying stock. A bullish divergence gives a "buy" or long signal and occurs when the stock price makes a new near-term low, but the RSI makes a more shallow trough relative to the previous decline. You would enter a long position as soon as the RSI turns upward from this second bottom. Place a protective stop below the stock's latest minor low. The buy signal is especially strong if the first RSI low drops below the oversold reference line. This indicates that selling pressure is near exhaustion and a directional change (upward) is imminent. A bearish divergence that gives a "sell" or short signal occurs when prices rally to a new near-term peak but the RSI makes a lower peak than during the previous advance by the stock. This calls for selling short or purchasing a put option as soon as the RSI turns down from this second peak. Place a protective stop above the stock's latest minor high. Sell signals are especially strong if the first RSI peak is above the upper or overbought reference line. Charting Patterns: Classical charting methods work well if filtered with the RSI. The RSI indicator can be used to validate trendlines, support/resistance, and even reversal patterns. Since the RSI is a leading or coincident indicator (never a lagging indicator), it can be used to anticipate the completions of these patterns. Reversals: Buy/sell signals can also be obtained simply by following the RSI levels. These signals should be verified by the prevalent trend in the stock. As the RSI rises above the upper reference line, bulls are in control but the stock is considered overbought and is likely vulnerable to selling pressure. When the RSI falls back below the reference line, a sell signal is generated. If the RSI moves below the lower reference line, the bears are in charge, but the stock is considered to be likely oversold and entering a "buy" zone. When the RSI reverses back above the lower reference line, a buy signal is generated. (One word of caution - don't "fade" or bet against the prevailing trend of the stock or market.)
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| Jerry Mayo |
