Bollinger Bands

Introduction

Developed by John Bollinger, Bollinger Bands are volatility bands that are placed above and below a moving average. The moving average represents the average price over a specific period, which smooths the price series. Volatility is based on the standard deviation. Because Bollinger Bands are based on volatility, they automatically adapt to price changes. The bands automatically widen when volatility increases and narrow when volatility decreases. The dynamic nature of Bollinger Bands also means they can be used on different securities with the standard settings. For signals, Bollinger Bands can be used to confirm M-Tops and W-Bottoms. They can also be used to determine the strength of the trend.

SharpCharts Calculation

  * Middle Band = 20-day simple moving average
* Upper Band = 20-day SMA + (20-day standard deviation of price x 2)
* Lower Band = 20-day SMA - (20-day standard deviation of price x 2)

Click here for download this spreadsheet example.

Bollinger Bands consist of a middle band with two outer bands. The middle band is a simple moving average that is usually set at 20 periods. A simple moving average is used because a simple moving average is also used in the standard deviation formula. The look-back period for the standard deviation is the same as for the simple moving average. The outer bands are usually set 2 standard deviations above and below the middle band.

Settings can be adjusted to suit the characteristics of particular securities or trading styles. Bollinger recommends making small incremental adjustments to the standard deviation multiplier. Changing the number of periods for the moving average also affects the number of periods used to calculate the standard deviation. Therefore, only small adjustments are required for the standard deviation multiplier. An increase in the moving average period would warrant an increase in the standard deviation multiplier. Bollinger suggests setting the standard deviation multiplier at 2.1 for a 50-period moving average. The standard deviation multiplier would be 1.9 for a 10-period moving average.

Signal: W-Bottoms

W-Bottoms were part of Arthur Merrill's work that identified 16 patterns with a basic W shape. Bollinger uses these various W patterns with Bollinger Bands to identify W-Bottoms. A "W-Bottom" forms in a downtrend and involves two reaction lows. In particular, Bollinger looks for W-Bottoms where the second low is lower than the first, but this second low holds above the lower band. There are four steps to confirm a W-Bottom with Bollinger Bands. First, there is a reaction low that forms. This low is usually below the lower band, but it does not have to break the lower band. Second, there is a bounce towards the middle band. Third, there is a new price low in the security, but this low holds above the lower band. The ability to hold above the lower band on the test shows underlying strength. Fourth, the pattern is confirmed with a strong move off the second low and a resistance break.

Chart 2 shows Nordstrom (JWN) with a W-Bottom in January-February 2010. First, the stock formed a reaction low in January (black arrow) and broke below the lower band. Second, there was a bounce back above the middle band. Third, the stock moved below its January low and held above the lower band. Even though the 5-Feb low broke the lower band, Bollinger Bands are calculated using closing prices so it makes sense to based signals on closing prices. Fourth, the stock surged with expanding volume in late February and broke above the early February high. Chart 3 shows Sandisk with a smaller W-Bottom in July-August 2009.

Signal: M-Tops

M-Tops were also part of Arthur Merrills work that identified 16 patterns with a basic M shape. Bollinger uses these various M patterns with Bollinger Bands to identify M Bottoms. According to Bollinger, tops are usually more complicated and drawn out than bottoms. Double tops, head-and-shoulders patterns and diamonds represent evolving tops.

In its most basic form, an M-Top is similar to a double top. However, the reaction highs are not always equal. The first high can be higher or lower than the second high. Bollinger suggests looking for signs of non-confirmation when a security is making new highs. This is basically the opposite of the W-Bottom. A non-confirmation occurs with three steps. First, a security forges a reaction high above the upper band. Second, there is a pullback towards the middle band. Third, prices move above the prior high, but fail to reach the upper band. This is a warning sign. The inability of the second reaction high to reach the upper bands shows waning momentum, which can foreshadow a trend reversal. Final confirmation comes with a support break or bearish indicator signal.

Chart 4 shows Exxon Mobil (XOM) with an M-Top in April-May 2008. The stock moved above the upper band in April. There was a pullback in May and then another push above 90. Even though the stock moved above the upper band on an intraday basis, it did not CLOSE above the upper band. The M-Top was confirmed with a support break two weeks later. Also notice that MACD formed a bearish divergence and moved below its signal line for confirmation.

Chart 5 shows Pulte Homes (PHM) within an uptrend in July-August 2008. Price exceeded the upper band in early September to affirm the uptrend. After a pullback below the 20-day SMA (middle Bollinger Band), the stock moved to a higher high above 17. Despite this new high for the move, price did not exceed the upper band. This flashed a warning sign. The stock broke support a week later and MACD moved below its signal line. Notice that this M-top is more complex because there are lower reaction highs on either side of the peak (blue arrow). A small head-and-shoulders pattern formed.

Signal: Walking the Bands

Moves above or below the bands are not signals per se. As Bollinger puts it, moves that touch or exceed the bands are not signals, but rather "tags". On the face of it, a move to the upper band shows strength, while a sharp move to the lower band shows weakness. Momentum oscillators work much the same way. Overbought is not necessarily bullish. Oversold is not necessarily bearish. Overbought conditions can extend in a strong uptrend. Similarly, prices can "walk the band" with numerous touches during a strong uptrend. Think about it for a moment. The upper band is 2 standard deviations above the 20-period simple moving average. It takes a pretty strong price move to exceed this upper band. An upper band touch that occurs after a Bollinger Band confirmed W-Bottom would signal the start of an uptrend. Just as a strong uptrend produces numerous upper band tags, it is also common for prices to remain above the lower band during an uptrend. The 20-day SMA sometimes acts as support. In fact, dips below the 20-day SMA sometimes provide buying opportunities before the next tag of the upper band.

Chart 6 shows Air Products (APD) with a surge and close above the upper band in mid July. First, notice that this is a strong surge that broke above two resistance levels. A strong upward thrust is a sign of strength, not weakness. Trading turned flat in August and the 20-day SMA moved sideways. The Bollinger Bands narrowed, but APD did not close below the lower band. Prices, and the 20-day SMA, turned up in September. Overall, APD closed above the upper band at least five times over a four month period. The indicator window shows the 10-period Commodity Channel Index (CCI). Dips below -100 are deemed oversold and moves back above -100 signal the start of an oversold bounce (green dotted line). The upper band tag and breakout started the uptrend. CCI then identified tradable pullbacks. This is an example of combining Bollinger Bands with a momentum oscillator for trading signals.

Chart 7 shows Monsanto (MON) with a walk down the lower band. The stock broke down in January with a support break and closed below the lower band. From mid January until early May, Monsanto closed below the lower band at least five times. Notice that the stock did not close above the upper band once during this period. The support break and initial close below the lower band signaled a downtrend. As such, the 10-period Commodity Channel Index (CCI) was used to identify short-term overbought situations. A move above +100 is overbought. A move back below +100 signals a resumption of the downtrend (red arrows). This system caught two good signals in early 2010.

Conclusions

Bollinger Bands reflect direction with the 20-period SMA and volatility with the upper/lower bands. As such, they can be used to determine if prices are relatively high or low. According to Bollinger, the bands should contain 88-89% of the price action. Therefore, a move outside the bands is deemed significant. Technically, prices are relatively high when above the upper band and relatively low when below the lower band. However, relatively high should not be regarded as bearish or as a sell signal. Likewise, relatively low should not be considered bullish or as a buy signal. Prices are high or low for a reason. As with other indicators, Bollinger Bands are not meant to be used as a stand alone tool. Chartists should combine Bollinger Bands with basic trend/price analysis and/or other indicators for confirmation.

Bands and SharpCharts

Bollinger Bands can be found in SharpCharts as a price overlay. As with a simple moving average, Bollinger Bands should be shown on top of a price plot. Upon selecting Bollinger Bands, the default setting will appear in the parameters window (20,2). The first number (20) sets the periods for the simple moving average and the standard deviation. The second number (2) sets the standard deviation multiplier for the upper and lower bands. These default parameters set the bands 2 standard deviations above/below the simple moving average. Users can change the parameters to suit their charting needs. Bollinger Bands (50,2.1) can be used for a longer timeframe or Bollinger Bands (10,1.9) can be used for a shorter timeframe. Click here for a live example.

Source:http://stockcharts.com/

Moving Averages

Introduction

Moving averages smooth the price data to form a trend following indicator. They do not predict price direction, but rather define the current direction with a lag. Moving averages are based on past prices, which means they will lag behind current prices. Price leads and the moving average follows. Moving averages form the building blocks for many other technical indicators and overlays, such as Bollinger Bands, MACD and the McClellan Oscillator. The two most popular types of moving averages are the Simple Moving Average (SMA) and the Exponential Moving Average (EMA). These moving averages can be used to identify the direction of the trend as well as support and resistance levels.

SMA Calculation

A simple moving average is formed by computing the average price of a security over a specific number of periods. Most moving averages are based on the closing prices. A 5-day simple moving average is the five day sum of closing prices divided by five. As its name implies, a moving average is an average that moves. Old data is dropped as new data comes available. This causes the average to move along the time scale. On day 6 of a 5-day SMA, the first day would be dropped from the calculation and the sixth day would be added. If the next closing price is 16, this new data point would be added and the oldest data point (11) would be dropped. In the example below, notice how prices gradually increase from 11 to 17. As expected the 5 day simple moving average also increases from 13 to 17.

Daily Closing Prices: 11,12,13,14,15,16,17 

First 5-day SMA: (11 + 12 + 13 + 14 + 15) / 5 = 13

Second 5-day SMA: (12 + 13 + 14 + 15 + 16) / 5 = 14

Third 5-day SMA: (13 + 14 + 15 + 16 + 17) / 5 = 15

EMA Calculation

Exponential moving averages reduce the lag by applying more weight to recent prices. The weighting applied to the most recent price depends on the number of periods in the moving average. There are three steps to calculating an exponential moving average. First, calculate the simple moving average. An EMA has to start somewhere so a simple moving average is used as the previous period's EMA in the first calculation. Second, calculate the weighting multiplier. Third, calculate the exponential moving average. The formula below is for a 10-day EMA.

SMA: 10 period sum / 10

Multiplier: (2 / (Time periods + 1) ) = (2 / (10 + 1) ) = 0.1818 (18.18%)

EMA: {Close - EMA(previous day)} x multiplier + EMA(previous day).

A 10-period exponential moving average applies an 18.18% weighting to the most recent price. A 10-period EMA can also be called an 18.18% EMA. A 20-period EMA applies a 9.52% weighing to the most recent price (2/(20+1) = .0952). Notice that the weighting for the shorter time period is more than the weighting for the longer time period. In fact, the weighting drops by half every time the moving average period doubles.

Below is a spreadsheet example of a 10-day simple moving average and a 10-day exponential moving average for Intel. Simple moving averages are straight forward and require little explanation. The 10-day average simply moves as new prices become available and old prices drop off. The exponential moving average starts with the simple moving average value (22.37) in the first calculation. After the first calculation, the normal formula takes over. Because an EMA begins with a simple moving average, its true value will not be realized until 20 or so periods later. In other words, the value on the excel spreadsheet may differ from the chart value because of the look-back period. This spreadsheet only goes back 30 periods, which means the affect of the simple moving average has had 20 periods to dissipate. Stockcharts.com goes back 250-periods for its calculations so the effects of the simple moving average in the first calculation have fully dissipated.

Click here for download this spreadsheet example.

The Lag Factor

Moving averages lag the price of the underlying security. This makes sense because they are based on past prices. Moving averages will not pick bottoms or tops. Instead, they will turn or be broken after the actual top or bottom has occurred. This is not necessarily a bad thing. Lag is just a fact of life when it comes to moving averages.

The longer the moving average, the more the lag. A 10-day exponential moving average will hug prices quite well and turn shortly after prices turn. Short moving averages are like speed boats - nimble and quick to change. In contrast, a 100-day moving average contains lots of past data that slows it down. Longer moving averages are like ocean tankers - lethargic and slow to change. It takes a sustained price movement for a 100-day moving average to change course. Chart 2 shows the S&P 500 ETF with a 10-day EMA closely following prices and a 100-day SMA grinding higher. Even with the January-February decline, the 100-day SMA held the course and did not turn down. The 50-day SMA fits somewhere between the 10 and 100 day moving averages when it comes to the lag factor.

Simple Versus Exponential

Even though there are clear differences between simple moving averages and exponential moving averages, one is not necessarily better than the other. Exponential moving averages have less lag and are therefore more sensitive to recent prices - and recent price changes. Exponential moving averages will turn before simple moving averages. Simple moving averages, on the other hand, represent a true average of prices for the entire time period. As such, simple moving averages may be better suited to identify support and resistance levels.

Moving average preference depends on objectives, analytical style and time horizon. Chartists should experiment with both types of moving averages as well as different timeframes to find what suits them the best. Chart 2 shows IBM with the 50-day SMA in red and the 50-day EMA in green. Both peaked in late January, but the decline in the EMA was sharper than the decline in the SMA. The EMA turned up in mid February, but the SMA continued lower until the end of March. Notice that the SMA turned up over a month after the EMA.

Lengths and Timeframes

The length of the moving average depends on the analytical objectives. Short moving averages (5-20 periods) are best suited for short-term trends and trading. Chartists interested in medium-term trends would opt for 20-60 period moving averages. Long-term investors will prefer moving averages with 100 or more periods. Some moving average lengths are more popular than others. The 200-day moving average is perhaps the most popular. Because of its length, this is clearly a long-term moving average. Next, the 50-day moving average is quite popular for the medium-term trend. Many chartists use the 50-day and 200-day moving averages together. Short-term, a 10-day moving average was quite popular in the past because it was easy to calculate. One simply added the numbers and moved the decimal point.

Trend Identification

The same signals can be generated using simple or exponential moving averages. As noted above, the preference depends on each individual. These examples below will use both simple and exponential moving averages. The term "moving average" applies to both simple and exponential moving averages.

The direction of the moving average conveys important information about prices. A rising moving average shows that prices are generally increasing. A falling moving average indicates that prices, on average, are falling. A rising long-term moving average reflects a long-term uptrend. A falling long-term moving average reflects a long-term downtrend.

Chart 4 shows 3M (MMM) with a 150-day exponential moving average. This example shows just how well moving averages work when the trend is strong. The 150-day EMA turned down in November 2007 and again in January 2008. Notice that it took a 15% decline to reverse the direction of this moving average. These lagging indicators identify trend reversals as they occur (at best) or after they occur (at worst). MMM continued lower into March 2009 and then surged 40-50%. Notice that the 150-day EMA did not turn up until after this surge. Once it did, however, MMM continued higher the next 12 months. Moving averages work brilliantly in strong trends.

Double Crossovers

Two moving averages can be used together to generate crossover signals. In Technical Analysis of the Financial Markets, John Murphy calls this the "double crossover method". Double crossovers involve one relatively short moving average and one relatively long moving average. As with all moving averages, the general length of the moving average defines the timeframe for the system. A system using a 5-day EMA and 35-day EMA would be deemed short-term. A system using a 50-day SMA and 200-day SMA would be deemed medium-term, perhaps even long-term.

A bullish crossover occurs when the shorter moving average crosses above the longer moving average. This is also known as a golden cross. A bearish crossover occurs when the shorter moving average crosses below the longer moving average. This is known as a dead cross.

Moving average crossovers produce relatively late signals. After all, the system employs two lagging indicators. The longer the moving average periods, the greater the lag in the signals. These signals work great when a good trend takes hold. However, a moving average crossover system will produce lots of whipsaws in the absence of a strong trend.

There is also a triple crossover method that involves three moving averages. Again, a signal is generated when the shortest moving average crosses the two longer moving averages. A simple triple crossover system might involve 5-day, 10-day and 20-day moving averages.

Chart 5 shows Home Depot (HD) with a 10-day EMA (green dotted line) and 50-day EMA (red line). The black line is the daily close. Using a moving average crossover would have resulting in three whipsaws before catching a good trade. The 10-day EMA broke below the 50-day EMA in late October, but this did not last long as the 10-day moved back above in mid November. This cross lasted longer, but the next bearish crossover occurred near the mid November levels, resulting in another whipsaw. This bearish cross did not last long as the 10-day EMA moved back above the 50-day a few days later. After three bad signals, the fourth signal foreshadowed a strong move as the stock advanced over 20%. There are two takeaways here. First, crossovers are prone to whipsaw. A price or time filter can be applied to help prevent whipsaws. Traders might require the crossover to last 3 days before acting or require 10-day EMA to move above/below the 50-day EMA by a certain amount before acting. Second, MACD can be used to identify and quantify these crossovers. MACD (5,50,1) will show a line representing the difference between the two exponential moving averages. MACD turns positive during a golden cross and negative during a dead cross. The Percentage Price Oscillator (PPO) can be used the same way to show percentage differences. Note that MACD and the PPO are based on exponential moving averages and will not match up with simple moving averages.

Chart 6 shows Oracle (ORCL) with the 50-day EMA, 200-day EMA and MACD(50,200,1). There were four moving average crossovers over a 2 1/2 year period. The first three resulted in whipsaws or bad trades. A sustained trend began with the fourth crossover as ORCL advanced to the mid 20s. Once again, moving average crossovers work great when the trend is strong, but produce losses in the absence of a trend.

Price Crossovers

Moving averages can also be used to generate signals with simple price crossovers. A bullish signal is generated when prices move above the moving average. A bearish signal is generated when prices move below the moving average. Short-term signals would utilize a short moving average, such as 10 days. Long moving averages, such as 200 days, would be better suited for long-term signals.

Price crossovers can be combined to trade within the bigger trend. The longer moving average sets the tone for the bigger trend and the shorter moving average is used to generate the signals. One would look for bullish price crosses only when prices are already above the longer moving average. This would be trading in harmony with the bigger trend. For example, if price is above the 200-day moving average, chartists would only focus on signals where price moves above the 50-day moving average. Obviously, a move below the 50-day moving average would precede such a signal, but such bearish crosses would be ignored because they are not in harmony with the bigger trend. A bearish cross would simply suggest a pullback within a bigger uptrend. A cross back above the 50-day moving average would signal an upturn in prices and continuation of the bigger uptrend.

Chart 7 shows Emerson Electric (EMR) with the 50-day EMA and 200-day EMA. The stock moved above and held above the 200-day moving average in August. There were dips below the 50-day EMA in early November and again in early February. Prices quickly moved back above the 50-day EMA to provide bullish signals (green arrows) in harmony with the bigger uptrend. MACD(1,50,1) is shown in the indicator window to confirm price crosses above or below the 50-day EMA. The 1-day EMA equals the closing prices. MACD(1,50,1) is positive when the close is above the 50-day EMA and negative when the close is below the 50-day EMA.

Support and Resistance

Moving averages can also act as support in an uptrend and resistance in a downtrend. A short-term uptrend might find support near the 20-day simple moving average, which is also used in Bollinger Bands. A long-term uptrend might find support near the 200-day simple moving average, which is the most popular long-term moving average. If fact, the 200-day moving average may offer support or resistance simply because it is so widely used. It is almost like a self-fulfilling prophecy.

Chart 8 shows the NY Composite with the 200-day simple moving average from mid 2004 until the end of 2008. The 200-day provided support numerous times during the advance. Once the trend reversed with a double top support break, the 200-day moving average acted as resistance around 9500.

Do not expect exact support and resistance levels from moving averages, especially longer moving averages. Markets are driven by emotion, which makes them prone to overshoots. Instead of exact levels, chartists can consider using support and resistance zones around a moving average.

Conclusions

The advantages of using moving averages need to be weighed against the disadvantages. Moving averages are trend following, or lagging, indicators that will always be a step behind. This is not necessarily a bad thing though. After all, the trend is your friend and it is best to trade in the direction of the trend. Moving averages will help ensure that a trader is in line with the current trend. However, markets, stocks and securities spend a great deal of time in trading ranges, which render moving averages ineffective. Once in a trend, moving averages will keep you in, but also give late signals. Don't expect to sell at the top and buy at the bottom using moving averages. As with most technical analysis tools, moving averages should not be used on their own, but in conjunction with other complementary tools. Chartists could use moving averages to define the overall trend and then use RSI to define overbought/oversold levels.

MAs and SharpCharts

Moving averages are available as a price overlay feature on SharpCharts. From the price overlay option, users can choose either a simple moving average or an exponential moving average. The first parameter is used to set the number of time periods. An optional second parameter can be added to shift the moving averages to the left (past) or right (future). A negative number (-10) would shift the moving average to the left 10 periods. A positive number (10) would shift the moving average to the right 10 periods. Use a comma to separate the moving average parameter with the shift parameter. Multiple moving averages can be overlaid the price plot by simply adding another. Users can change the colors and style to differentiate between multiple moving averages and suit their preferences. Moving averages can also be added to many indicators. After selecting an indicator, open "advanced options" by clicking the little green triangle. An overlay can be added to RSI, CCI, Volume and many other indicators.

Moving Average Scans

Bullish Moving Average Cross: This scans looks for stocks with a rising 150-day simple moving average and a bullish cross of the 5-day EMA and 35-day EMA. The 150-day moving average is rising as long as it is trading higher than its level five days ago. A bullish cross occurs when the 5-day EMA moves above the 35-day EMA on above average volume.

Bearish Moving Average Cross: This scans looks for stocks with a falling 150-day simple moving average and a bearish cross of the 5-day EMA and 35-day EMA. The 150-day moving average is falling as long as it is trading lower than its level five days ago. A bearish cross occurs when the 5-day EMA moves below the 35-day EMA on above average volume.

Source:http://stockcharts.com/

Raff Regression Channel

Introduction

Developed by Gilbert Raff, the Raff Regression Channel is a linear regression with evenly spaced trendlines above and below. The width of the channel is based on the high or low that is the furthest from the linear regression. The trend is up as long as prices rise within this channel. An uptrend reverses when price breaks below the channel extension. The trend is down as long as prices decline within the channel. Similarly, a downtrend reverses when price breaks above the channel extension.

Formula

The Raff Regression Channel is based on a linear regression, which is the least-squares line-of-best-fit for a price series. Even though the formula is beyond the scope of this article, linear regressions are easy to understand with a visual example. Chart 1 shows the Nasdaq 100 ETF (QQQQ) with the Raff Regression Channel in red. The middle line is the linear regression extending from the July closing low to the January closing high. Note that the linear regression is based on closing prices. This makes the linear regression the line-of-best-fit for the closing prices from the July low to the January high. Next, the width is set by determining the high or low that is the furthest from the linear regression (from early July to mid January). The low immediately after the start is the furthest and it is used to set the distance for the trendlines. The upper trendline is then set the same distance from the linear regression as the lower trendline.

Chart 2 shows an example of QQQQ in a downtrend. The Raff Regression Channel extends from the April (closing) high to the July (closing) low. The early July high defines the width of the channel because it is the furthest high or low from the linear regression. This means the lower trendline is set the same distance from the linear regression as the upper trendline.

Drawing and Signals

The Raff Regression Channel can be drawn to cover the existing trend and subsequently define the trend. Once established, extension lines can be drawn to identify the reversal point. An uptrend extends from the lowest reaction low to the highest reaction high for a move. A downtrend extends from the highest reaction high to the lowest reaction low. Keep in mind that closing prices are used when drawing the Raff Regression Channel, but intraday highs and lows are used to set the equidistant trendlines.

Chart 3 shows Urban Outfitters (URBN) with the Raff Regression Channel drawn from the July 2007 low to the September 2008 high (weekly closes). This covers the uptrend so far. Had URBN moved to a new reaction high in October, the Raff Regression Channel would have extended to that high. Instead of moving to a new high, URBN broke below the regression channel extension to reverse the uptrend. Notice that the lower trendline was extended to extrapolate the channel.

Chart 4 shows Nvidia (NVDA) with a downtrend extending from the October 2007 high to the November 2008 low. The Raff Regression Channel did not extend further because the stock traded flat and held above its November low into 2009. The red dotted line shows the channel extension or the regression channel top. NVDA broke this extension in February-March to start an uptrend.

Conclusions

As a channel based on a linear regression, the Raff Regression Channel is well suited for trend identification. The width of the channel depends on the furthest high or low from the linear regression. As such, spike highs and lows will result in very wide channels that may not capture the true range. When an uptrend starts with a sharp surge, the low a few days after this initial surge is often the furthest high-low from the linear regression. By extension, when a downtrend starts with a sharp decline, the high of this initial decline often the furthest high-low from the linear regression. Sharp initial moves create wide channels with few, if any, reaction highs or lows touching the upper and lower trendlines. Such was the case with the surge off the March 2009 lows (see the QQQQ chart further below). Even though this article only focused on trend identification, the Raff Regression Channel can be drawn early in the trend and extended to forecast future support or resistance levels as well as overbought or oversold levels. Channel extensions can act as support or resistance. Moves outside the channel extensions can also denote overbought or oversold conditions.

Using with SharpCharts

The Raff Regression Channel tool can be found when annotating a SharpChart. The icon is a gray zigzag with a green line through it. Left click on the icon to select it. Left click on the starting point and drag the indicator to the ending point. To rearrange an existing Raff Regression Channel, click on the start or end of the linear regression (middle line) and move accordingly. Extensions can be added manually using the trendline tool in SharpCharts.

Further Study

Book: Reading Price Charts Bar by Bar: The Technical Analysis of Price Action for the Serious Trader by Al Brooks. This book includes a section on trendline and trend channel lines.

Source:http://stockcharts.com/

Kagi Charts

Kagi charts are price charts with thick and thin vertical lines connected by short horizontal lines. Just like P&F charts, Kagi charts only add a new vertical line when prices have reversed enough to cancel the current uptrend or downtrend. Until such a reversal occurs, a Kagi chart will only move up (or down) in its current column. Kagi charts do not have constantly spaced time axes. Here is an example of a Kagi chart:

The word "Kagi" comes from the Japanese art of woodblock printing. A kagi or "key" is the L-shaped guide in a woodblock that a printer used to line up the paper for printing. Because of this, Kagi charts are sometimes referred to as "Key charts." Kagi charts were popularized by Steve Nison in his book Beyond Candlesticks.

The thickness of the Kagi line changes depending on price action. The thick line is called the yang line and the thin line is called the yin line. The locations where the line changed from moving higher to moving lower are called "shoulders" and the locations where the line changed from moving lower to moving higher are called "waists". Whenever a yin (thin) line moves above the previous shoulder, it turns into a yang (thick) line. Similarly, whenever a yang line moves below the previous waist, it turns into a yin line.

The Kagi line will continue to move up (or down) until prices reverse by a specified amount. When that happens, a short horizontal line is added as well as a new vertical line which extends to the new closing price. There are several ways to specify the reversal amount - in absolute points, as a percentage, or by using the Average True Range of recent prices (see below for details).

Interpretation

The simplest way to interpret Kagi charts can be summed up by Steve Nison's expression Buy on yang, sell on yin. When the Kagi line goes from thin to thick, prices have just exceeded their previous important high - that's a bullish signal. The opposite is also true. When the Kagi line goes from thick to thin, prices have just fallen below their previous low, not a good sign for things to come.

Standard support/resistance, trend and chart pattern analysis techniques can also be used with Kagi charts. In fact it is often easier to locate strong support or resistance levels on Kagi charts because of their "clean" appearance.

Another interpretation technique mentioned by Steve Nison is to look for a sequence of nine (mostly consecutive) shoulders or waists. Traders look for strong counter-moves soon after the ninth shoulder or waist appears.

Parameters

There are three ways to specify the reversal amount that is used in the construction of a Kagi chart: Absolute points, Percentage, and Average True Range (ATR).

Absolute Points

With the "Absolute Points" method, you specify the number of points that a stock must reverse before a change in the Kagi line occurs. The advantage of this method is that it is very easy to understand and predict where reversals will occur. The disadvantage is that the point value needs to be different for high priced stocks than for low priced stocks. Typically you will need to choose a value that is roughly 1/20th the average price of the stock during the time frame you want to chart. Common values include 1, 2, 4, and 10.

Important Note: The Default for Kagi "Pts" method is currently 14 which is too large for most stocks. You'll need to change it to a smaller number to get a useful chart.

Percentage

The "Percentage" method causes a reversal each time prices move more that the percentage that you specified. This has the advantage of not needing to change the setting if the value of the stock changes significantly during the time period being charted. The disadvantage is that it isn't easy to predict exactly where the next reversal will occur.

Average True Range (ATR)

The "Average True Range (ATR)" method uses the value of the ATR indicator to determine where the next reversal should occur. The ATR indicator is designed to ignore the normal volatility of a stock and thus it can "automatically" find good reversal levels regardless of the value or volatility of the stock selected. ATR with a value of 14 is the default value for Kagi charts and should generate a very usable chart in most cases.

Source:http://stockcharts.com/

Candlestick Bearish Reversal Patterns

There are dozens of bearish reversal patterns. I have elected to narrow the field by selecting a few of the most popular patterns for detailed explanations. For a complete list of bearish and bullish reversal patterns, see Greg Morris' book, Candlestick Charting Explained. Below are some of the key bearish reversal patterns, with the number of candlesticks required in parentheses.

• Bearish Abandoned Baby (3)
• Engulfing, Bearish (2)
• Harami, Bearish (2)
• Dark Cloud Cover (2)
• Evening Star (3)
• Shooting Star (1)

It is important to remember the following guidelines relating to bearish reversal patterns:

• Most patterns require further bearish confirmation.
• Bearish reversal patterns should form within an uptrend.
• Other aspects of technical analysis should be used as well.

Bearish Confirmation

Bearish reversal patterns can form with one or more candlesticks; most require bearish confirmation. The actual reversal indicates that selling pressure overwhelmed buying pressure for one or more days, but it remains unclear whether or not sustained selling or lack of buyers will continue to push prices lower. Without confirmation, many of these patterns would be considered neutral and merely indicate a potential resistance level at best. Bearish confirmation means further downside follow through, such as a gap down, long black candlestick or high volume decline. Because candlestick patterns are short-term and usually effective for 1-2 weeks, bearish confirmation should come within 1-3 days.

Time Warner (TWX) advanced from the upper fifties to the low seventies in less than two months. The long white candlestick that took the stock above 70 in late March was followed by a long-legged doji in the harami position. A second long-legged doji immediately followed and indicated that the uptrend was beginning to tire. The dark cloud cover (red oval) increased these suspicions and bearish confirmation was provided by the long black candlestick (red arrow).

Existing Uptrend

To be considered a bearish reversal, there should be an existing uptrend to reverse. It does not have to be a major uptrend, but should be up for the short term or at least over the last few days. A dark cloud cover after a sharp decline or near new lows is unlikely to be a valid bearish reversal pattern. Bearish reversal patterns within a downtrend would simply confirm existing selling pressure and could be considered continuation patterns.

There are many methods available to determine the trend. An uptrend can be established using moving averages, peak/trough analysis or trend lines. A security could be deemed in an uptrend based on one or more of the following:

• The security is trading above its 20-day exponential moving average (EMA).
• Each reaction peak and trough is higher than the previous.
• The security is trading above a trend line.

These are just three possible methods. Some traders may prefer shorter uptrends and qualify securities that are trading above their 10-day EMA. Defining criteria will depend on your trading style, time horizon and personal preferences.

Other Technical Analysis

Candlesticks provide an excellent means to identify short-term reversals, but should not be used alone. Other aspects of technical analysis can and should be incorporated to increase the robustness of bearish reversal patterns.

Resistance

In Jan-00, Nike (NKE) gapped up over 5 points and closed above 50. A candlestick with a long upper shadow formed and the stock subsequently traded down to 45. This established a resistance level around 53. After an advance back to resistance at 53, the stock formed a bearish engulfing pattern (red oval). Bearish confirmation came when the stock declined the next day, gapped down below 50 and broke its short-term trend line two days later.

Momentum

Use oscillators to confirm weakening momentum with bearish reversals. Negative divergences in MACD, PPO, Stochastics, RSI, StochRSI or Williams %R indicate weakening momentum and can increase the robustness of a bearish reversal pattern. In addition, bearish moving average crossovers in the PPO and MACD can provide confirmation, as well as trigger line crossovers for the Slow Stochastic Oscillator.

Money Flows

Use volume-based indicators to assess selling pressure and confirm reversals. On Balance Volume (OBV), Chaikin Money Flow and the Accumulation/Distribution Line can be used to spot negative divergences or simply excessive selling pressure. Signs of increased selling pressure can improve the robustness of a bearish reversal pattern.

For those that want to take it one step further, all three aspects could be combined for the ultimate signal. Look for a bearish candlestick reversal in securities trading near resistance with weakening momentum and signs of increased selling pressure. Such signals would be relatively rare, but could offer above-average profit potential.

A number of signals came together for RadioShack (RSH) in early Oct-00. The stock traded up to resistance at 70 for the third time in two months and formed a dark cloud cover pattern (red oval). In addition, the long black candlestick had a long upper shadow to indicate an intraday reversal. Bearish confirmation came the next day with a sharp decline. The negative divergence in the PPO and extremely weak money flows also provided further bearish confirmation.

Bearish Engulfing

The bearish engulfing pattern consists of two candlesticks; the first is white and the second black. The size of the white candlestick is not that important, but should not be a doji, which would be relatively easy to engulf. The second should be a long black candlestick. The bigger it is, the more bearish the reversal. The black body must totally engulf the body of the first, white, candlestick. Ideally, the black body should engulf the shadows as well, but this is not a requirement. Shadows are permitted, but they are usually small or nonexistent on both candlesticks.

After an advance, the second black candlestick begins to form when residual buying pressure causes the security to open above the previous close. However, sellers step in after this opening gap up and begin to drive prices down. By the end of the session, selling becomes so intense that prices move below the previous open. The resulting candlestick engulfs the previous day's body and creates a potential short-term reversal. Further weakness is required for bearish confirmation of this reversal pattern.

After meeting resistance around 30 in mid-January, Ford (F) formed a bearish engulfing (red oval). The pattern was immediately confirmed with a decline and subsequent support break.

Dark Cloud Cover

The dark cloud cover pattern is made up of two candlesticks; the first is white and the second black. Both candlesticks should have fairly large bodies and the shadows are usually small or nonexistent, though not necessarily. The black candlestick must open above the previous close and close below the midpoint of the white candlestick's body. A close above the midpoint might qualify as a reversal, but would not be considered as bearish.

Just as with the bearish engulfing pattern, residual buying pressure forces prices higher on the open, creating an opening gap above the white candlestick's body. However, sellers step in after the strong open and push prices lower. The intensity of the selling drives prices below the midpoint of the white candlestick's body. Further weakness is required for bearish confirmation of this reversal pattern.

After a sharp advance from 37 1/2 to 40.5 in about 2 weeks, Citigroup (C) formed a dark cloud cover pattern (red oval). This pattern was confirmed with two long black candlesticks and marked an abrupt reversal around 40.5.

Shooting Star

The shooting star is made up of one candlestick (white or black) with a small body, long upper shadow and small or nonexistent lower shadow. The size of the upper shadow should be a least twice the length of the body and the high/low range should be relatively large. Large is a relative term and the high/low range should be large relative to the range over the last 10-20 days.

For a candlestick to be in star position, it must gap way from the previous candlestick. In Candlestick Charting Explained, Greg Morris indicates that a shooting star should gap up from the preceding candlestick. However, in Beyond Candlesticks, Steve Nison provides a shooting star example that forms below the previous close. There should be room to maneuver, especially when dealing with stocks and indices, which often open near the previous close. A gap up would definitely enhance the robustness of a shooting star, but the essence of the reversal should not be lost without the gap.

After an advance that was punctuated by a long white candlestick, Chevron (CHV) formed a shooting star candlestick above 90 (red oval). The bearish reversal pattern was confirmed with a gap down the following day

Bearish Harami

The bearish harami is made up of two candlesticks. The first has a large body and the second a small body that is totally encompassed by the first. There are four possible combinations: white/white, white/black, black/white and black/black. Whether a bullish reversal or bearish reversal pattern, all harami look the same. Their bullish or bearish nature depends on the preceding trend. Harami are considered potential bearish reversals after an advance and potential bullish reversals after a decline. No matter what the color of the first candlestick, the smaller the body of the second candlestick is, the more likely the reversal. If the small candlestick is a doji, the chances of a reversal increase.

In his book, Beyond Candlesticks, Steve Nison asserts that any combination of colors can form a harami, but the most bearish are those that form with a black/white or black/black combination. Because the first candlestick has a large body, it implies that the bearish reversal pattern would be stronger if this body were black. This would indicate a sudden and sustained increase in selling pressure. The small candlestick afterwards indicates consolidation before continuation. After an advance, black/white or black/black bearish harami are not as common as white/black or white/white variations.

A white/black or white/white combination can still be regarded as a bearish harami and signal a potential reversal. The first long white candlestick forms in the direction of the trend. It signals that significant buying pressure remains, but could also indicate excessive bullishness. Immediately following, the small candlestick forms with a gap down on the open, indicating a sudden shift towards the sellers and a potential reversal.

After a gap up and rapid advance to 30, Ameritrade (AMTD) formed a bearish harami (red oval). This harami consists of a long black candlestick and a small black candlestick. The decline two days later confirmed the bearish harami and the stock fell to the low twenties.

Merck (MRK) formed a bearish harami with a long white candlestick and long black candlestick (red oval). The long white candlestick confirmed the direction of the current trend. However, the stock gapped down the next day and traded in a narrow range. The decline three days later confirmed the pattern as bearish.

Evening Star

The evening star consists of three candlesticks:

1. A long white candlestick.
2. A small white or black candlestick that gaps above the close (body) of the previous candlestick. This candlestick can also be a doji, in which case the pattern would be a evening doji star.
3. A long black candlestick.

The long white candlestick confirms that buying pressure remains strong and the trend is up. When the second candlestick gaps up, it provides further evidence of residual buying pressure. However, the advance ceases or slows significantly after the gap and a small candlestick forms, indicating indecision and a possible reversal of trend. If the small candlestick is a doji, the chances of a reversal increase. The third long black candlestick provides bearish confirmation of the reversal.

After advancing from 68 to 91 in about two weeks, AT&T (T) formed an evening star (red oval). The middle candlestick is a spinning top, which indicates indecision and possible reversal. The gap above 91 was reversed immediately with a long black candlestick. Even though the stock stabilized in the next few days, it never exceeded the top of the long black candlestick and subsequently fell below 75.

Bearish Abandoned Baby

The bearish abandoned baby resembles the evening doji star and also consists of three candlesticks:

1. A long white candlestick.
2. A doji that gaps above the high of the previous candlestick.
3. A long black candlestick that gaps below the low of the doji.

The main difference between the evening doji star and the bearish abandoned baby are the gaps on either side of the doji. The first gap up signals a continuation of the uptrend and confirms strong buying pressure. However, buying pressure subsides after the gap up and the security closes at or near the open, creating a doji. Following the doji, the gap down and long black candlestick indicate strong and sustained selling pressure to complete the reversal. Further bearish confirmation is not required.

Delta (DAL) formed an abandoned baby to mark a sharp reversal that carried the stock from 57 1/2 to 47 1/2. Although the open and close are not exactly equal, the small white candlestick in the middle captures the essence of a doji. Indecision is reflected with the small body and equal upper and lower shadows. In addition, the middle candlestick is separated by gaps on either side, which add emphasis to the reversal.

Source:http://stockcharts.com/

Support and Resistance

Support and resistance represent key junctures where the forces of supply and demand meet. In the financial markets, prices are driven by excessive supply (down) and demand (up). Supply is synonymous with bearish, bears and selling. Demand is synonymous with bullish, bulls and buying. These terms are used interchangeably throughout this and other articles. As demand increases, prices advance and as supply increases, prices decline. When supply and demand are equal, prices move sideways as bulls and bears slug it out for control.

What Is Support?

Support is the price level at which demand is thought to be strong enough to prevent the price from declining further. The logic dictates that as the price declines towards support and gets cheaper, buyers become more inclined to buy and sellers become less inclined to sell. By the time the price reaches the support level, it is believed that demand will overcome supply and prevent the price from falling below support.

Support does not always hold and a break below support signals that the bears have won out over the bulls. A decline below support indicates a new willingness to sell and/or a lack of incentive to buy. Support breaks and new lows signal that sellers have reduced their expectations and are willing sell at even lower prices. In addition, buyers could not be coerced into buying until prices declined below support or below the previous low. Once support is broken, another support level will have to be established at a lower level.

Where Is Support Established?

Support levels are usually below the current price, but it is not uncommon for a security to trade at or near support. Technical analysis is not an exact science and it is sometimes difficult to set exact support levels. In addition, price movements can be volatile and dip below support briefly. Sometimes it does not seem logical to consider a support level broken if the price closes 1/8 below the established support level. For this reason, some traders and investors establish support zones.

What Is Resistance?

Resistance is the price level at which selling is thought to be strong enough to prevent the price from rising further. The logic dictates that as the price advances towards resistance, sellers become more inclined to sell and buyers become less inclined to buy. By the time the price reaches the resistance level, it is believed that supply will overcome demand and prevent the price from rising above resistance.

Resistance does not always hold and a break above resistance signals that the bulls have won out over the bears. A break above resistance shows a new willingness to buy and/or a lack of incentive to sell. Resistance breaks and new highs indicate buyers have increased their expectations and are willing to buy at even higher prices. In addition, sellers could not be coerced into selling until prices rose above resistance or above the previous high. Once resistance is broken, another resistance level will have to be established at a higher level.

Where Is Resistance Established?

Resistance levels are usually above the current price, but it is not uncommon for a security to trade at or near resistance. In addition, price movements can be volatile and rise above resistance briefly. Sometimes it does not seem logical to consider a resistance level broken if the price closes 1/8 above the established resistance level. For this reason, some traders and investors establish resistance zones.

Methods to Establish Support and Resistance?

Support and resistance are like mirror images and have many common characteristics.

Highs and Lows

Support can be established with the previous reaction lows. Resistance can be established by using the previous reaction highs.

The above chart for Halliburton (HAL) shows a large trading range between Dec-99 and Mar-00. Support was established with the October low around 33. In December, the stock returned to support in the mid-thirties and formed a low around 34. Finally, in February the stock again returned to the support scene and formed a low around 33 1/2.

After each bounce off support, the stock traded all the way up to resistance. Resistance was first established by the September support break at 42.5. After a support level is broken, it can turn into a resistance level. From the October lows, the stock advanced to the new support-turned-resistance level around 42.5. When the stock failed to advance past 42.5, the resistance level was confirmed. The stock subsequently traded up to 42.5 two more times after that and failed to surpass resistance both times.

Support Equals Resistance

Another principle of technical analysis stipulates that support can turn into resistance and visa versa. Once the price breaks below a support level, the broken support level can turn into resistance. The break of support signals that the forces of supply have overcome the forces of demand. Therefore, if the price returns to this level, there is likely to be an increase in supply, and hence resistance.

The other turn of the coin is resistance turning into support. As the price advances above resistance, it signals changes in supply and demand. The breakout above resistance proves that the forces of demand have overwhelmed the forces of supply. If the price returns to this level, there is likely to be an increase in demand and support will be found.

In this example of the NASDAQ 100 Index ($NDX), the stock broke resistance at 935 in May-97 and traded just above this resistance level for over a month. The ability to remain above resistance established 935 as a new support level. The stock subsequently rose to 1150, but then fell back to test support at 935. After the second test of support at 935, this level is well established.

From the PeopleSoft (PSFT) example, we can see that support can turn into resistance and then back into support. PeopleSoft found support at 18 from Oct-98 to Jan-99 (green oval), but broke below support in Mar-99 as the bears overpowered the bulls. When the stock rebounded (red oval), there was still overhead supply at 18 and resistance was met from Jun-99 to Oct-99.

Where does this overhead supply come from? Demand was obviously increasing around 18 from Oct-98 to Mar-99 (green oval). Therefore, there were a lot of buyers in the stock around 18. When the price declined past 18 and to around 14, many of these buyers were probably still holding the stock. This left a supply overhang (commonly known as resistance) around 18. When the stock rebounded to 18, many of the green-oval-buyers (who bought around 18) probably took the opportunity to sell. When this supply was exhausted, the demand was able to overpower supply and advance above resistance at 18.

Trading Range

Trading ranges can play an important role in determining support and resistance as turning points or as continuation patterns. A trading range is a period of time when prices move within a relatively tight range. This signals that the forces of supply and demand are evenly balanced. When the price breaks out of the trading range, above or below, it signals that a winner has emerged. A break above is a victory for the bulls (demand) and a break below is a victory for the bears (supply).

After an extended advance from 27 to 64, WorldCom (WCOM) entered into a trading range between 55 and 63 for about 5 months. There was a false breakout in mid-June when the stock briefly poked its head above 62 (red oval). This did not last long and a gap down a few days later nullified the breakout (black arrow). The stock then proceeded to break support at 55 in Aug-99 and trade as low as 50. Here is another example of support turned resistance as the stock bounced off 55 two more times before heading lower. While this does not always happen, a return to the new resistance level offers a second chance for longs to get out and shorts to enter the fray.

In Nov/Dec-99, Lucent Technologies (LU) formed a trading range that resembled a head and shoulders pattern (red oval). When the stock broke support at 60, there was little or no time to exit. Even though the there is a long black candlestick indicating an open at 59, the stock fell so fast that it was impossible to exit above 44. In hindsight, the support line could have been drawn as an upward sloping neckline (blue line), and the support break would have come at 61. This is only 1 point higher and a trader would have had to take action immediately to avoid a sharp fall. However, the lows match up rather nicely on the neckline, and it is something to consider when drawing support lines.

After Lucent declined, a trading range was established between 40.5 and 47.5 for almost two months (green oval). The resistance level of the trading range was well marked by three reaction peaks at 47.5. The support level was not as clearly marked, but appeared to be between 40 and 41. Some buying interest began to become evident around 44 in mid- to late-February. Notice the array of candlesticks with long lower shadows, or hammers, as they are known. The stock then proceeded to form two up gaps on 24-Feb and 25-Feb, and finally closed above resistance at 48. This was a clear indication of demand winning out over supply. There were still two more opportunities (days) to get in on the action. On the third day after the breakout, the stock gapped up and moved above 56.

Support and Resistance Zones

Because technical analysis is not an exact science, it is useful to create support and resistance zones. This is contrary to the strategy mapped out for Lucent Technologies (LU), but it is sometimes the case. Each security has its own characteristics, and analysis should reflect the intricacies of the security. Sometimes, exact support and resistance levels are best, and, sometimes, zones work better. Generally, the tighter the range, the more exact the level. If the trading range spans less than 2 months and the price range is relatively tight, then more exact support and resistance levels are best suited. If a trading range spans many months and the price range is relatively large, then it is best to use support and resistance zones. These are only meant as general guidelines, and each trading range should be judged on its own merits.

Returning to the analysis of Halliburton (HAL), we can see that the November high of the trading range (33 to 44) extended more than 20% past the low, making the range quite large relative to the price. Because the September support break forms our first resistance level, we are ready to set up a resistance zone after the November high is formed, probably around early December. At this point though, we are still unsure if a large trading range will develop. The subsequent low in December, which was just higher than the October low, offers evidence that a trading range is forming, and we are ready to set the support zone. As long as the stock trades within the boundaries set by the support and resistance zone, we will consider the trading range to be valid. Support may be looked upon as an opportunity to buy, and resistance as an opportunity to sell.

Conclusion

Identification of key support and resistance levels is an essential ingredient to successful technical analysis. Even though it is sometimes difficult to establish exact support and resistance levels, being aware of their existence and location can greatly enhance analysis and forecasting abilities. If a security is approaching an important support level, it can serve as an alert to be extra vigilant in looking for signs of increased buying pressure and a potential reversal. If a security is approaching a resistance level, it can act as an alert to look for signs of increased selling pressure and potential reversal. If a support or resistance level is broken, it signals that the relationship between supply and demand has changed. A resistance breakout signals that demand (bulls) has gained the upper hand and a support break signals that supply (bears) has won the battle.