Commodity Channel Index (CCI)

Introduction

Developed by Donald Lambert, the Commodity Channel Index (CCI) was designed to identify cyclical turns in commodities. The assumption behind the indicator is that commodities (or stocks or bonds) move in cycles, with highs and lows coming at periodic intervals. Lambert recommended using 1/3 of a complete cycle (low to low or high to high) as a time frame for the CCI. (Note: Determination of the cycle's length is independent of the CCI.) If the cycle runs 60 days (a low about every 60 days), then a 20-day CCI would be recommended. For the purpose of this example, a 20-day CCI is used

Calculation

There are 4 steps involved in the calculation of the CCI:

1. Calculate the last period's Typical Price (TP) = (H+L+C)/3 where H = high, L = low, and C = close.
2. Calculate the 20-period Simple Moving Average of the Typical Price (SMATP).
3. Calculate the Mean Deviation. First, calculate the absolute value of the difference between the last period's SMATP and the typical price for each of the past 20 periods. Add all of these absolute values together and divide by 20 to find the Mean Deviation.
4. The final step is to apply the Typical Price (TP), the Simple Moving Average of the Typical Price (SMATP), the Mean Deviation and a Constant (.015) to the following formula:

CCI = ( Typical Price - SMATP ) / ( .015 X Mean Deviation )

(Click here to download an Excel spreadsheet that contains a example of the CCI being calculated.)

For scaling purposes, Lambert set the constant at .015 to ensure that approximately 70 to 80 percent of CCI values would fall between -100 and +100. The CCI fluctuates above and below zero. The percentage of CCI values that fall between +100 and -100 will depend on the number of periods used. A shorter CCI will be more volatile with a smaller percentage of values between +100 and -100. Conversely, the more periods used to calculate the CCI, the higher the percentage of values between +100 and -100.

Lambert's trading guidelines for the CCI focused on movements above +100 and below -100 to generate buy and sell signals. Because about 70 to 80 percent of the CCI values are between +100 and -100, a buy or sell signal will be in force only 20 to 30 percent of the time. When the CCI moves above +100, a security is considered to be entering into a strong uptrend and a buy signal is given. The position should be closed when the CCI moves back below +100. When the CCI moves below -100, the security is considered to be in a strong downtrend and a sell signal is given. The position should be closed when the CCI moves back above -100.

Since Lambert's original guidelines, traders have also found the CCI valuable for identifying reversals. The CCI is a versatile indicator capable of producing a wide array of buy and sell signals.

• CCI can be used to identify overbought and oversold levels. A security would be deemed oversold when the CCI dips below -100 and overbought when it exceeds +100. From oversold levels, a buy signal might be given when the CCI moves back above -100. From overbought levels, a sell signal might be given when the CCI moved back below +100.

• As with most oscillators, divergences can also be applied to increase the robustness of signals. A positive divergence below -100 would increase the robustness of a signal based on a move back above -100. A negative divergence above +100 would increase the robustness of a signal based on a move back below +100.

• Trend line breaks can be used to generate signals. Trend lines can be drawn connecting the peaks and troughs. From oversold levels, an advance above -100 and trend line breakout could be considered bullish. From overbought levels, a decline below +100 and a trend line break could be considered bearish.

Traders and investors use the CCI to help identify price reversals, price extremes and trend strength. As with most indicators, the CCI should be used in conjunction with other aspects of technical analysis. CCI fits into the momentum category of oscillators. In addition to momentum, volume indicators and the price chart may also influence a technical assessment.

Example

The 20-day CCI for Brooktrout (BRKT) provides an example using Lambert's guidelines. Even though a few signals are good, using crosses above and below +100/-100 resulted in plenty of whipsaws. In January, the stock broke resistance at 20, and proceeded to double in the next few weeks. The CCI moved above and below +100 several times, but the stock remained in a strong uptrend. The CCI did manage to remain above +50 for about 7 weeks (blue oval), but the whipsaws below +100 could have caused an early exit. Whipsaws do not make an indicator bad. However, traders and investors should learn to use the CCI in conjunction with other indicators and chart analysis. In addition, various time frames for the CCI should be tested, and you should test buy and sell points, as well. What works for one stock may not necessarily work for another stock. For Brooktrout, a buy point on a cross above and below +50 may have worked better.

Source:http://stockcharts.com/

Bollinger Band Width

Introduction

Bollinger Band Width is an indicator derived from Bollinger Bands. In his book, Bollinger on Bollinger Bands, John Bollinger refers to Bollinger BandWidth as one of two indicators that can be derived from Bollinger Bands. The other indicator is %B.

Non-normalized BandWidth measures the distance, or difference, between the upper band and the lower band. BandWidth decreases as Bollinger Bands narrow and increases as Bollinger Bands widen. Because Bollinger Bands are based on the standard deviation, falling Bandwidth reflects decreasing volatility and rising Bandwidth reflects increasing volatility.

SharpCharts Calculation

(Upper Band - Lower Band)

Bollinger Bands consist of a middle band with two outer bands. The middle band is a simple moving average usually set at 20 periods. 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. BandWidth is simply the difference between the upper band and the lower band.

The chart above shows the S&P 500 ETF (SPY) with Bollinger Bands, Bandwidth and the Standard Deviation. Notice how Bandwidth tracks the Standard Deviation (volatility). The image below shows a spreadsheet with the calculations for June 2009.

Defining Narrowness

It is important to remember that non-normalized BandWidth varies according to security's volatility and price. For reference, normalized Bandwidth divides the difference in Bollinger Bands by the middle band. A Bandwidth value of 5 would be considered narrow for $100 a stock, but wide for a $30 stock. Five is 5% of 100, but 16.6% of 30. Usually, Bandwith is considered low (narrow) when it is 5-10% of a security's price. Low BandWidth for a $50 stock would range from 2.5 to 5, while low Bandwidth for a $20 stock would range from .50 to 1. Depending on underlying volatility, the definition of narrowness may vary from stocks to stock. Bandwidth for Google (GOOG) will be generally high than Bandwidth for Consolidated Edison (ED), which is a utility.

Narrow Bandwidth can also be gauged relative to prior Bandwidth values over a period of time. It is important to get a good look-back period to define Bandwidth range. For example, a one year chart will show Bandwidth highs and lows over a significant timeframe. Bandwidth is considered narrow as it approaches it the lows of its one year range and high as it approaches the highs of its range.

Signal: The Squeeze

Bollinger BandWidth is best for identifying The Squeeze. This occurs when volatility falls to a very low level, as evidenced by the narrowing bands. The upper and lower bands are based on the standard deviation, which is a measure of volatility. Therefore, volatility contracts as the bands narrow. The bands narrow as price flattens or moves within a relatively narrow range. The theory is that periods of low volatility are followed by periods of high volatility. Relatively narrow BandWidth (a.k.a. the Squeeze) can foreshadow the start of a new advance or decline. After a Squeeze, a price surge and subsequent band break signal that a new move has started. A new advance starts with a Squeeze and subsequent break above the upper band. A new decline starts with a Squeeze and subsequent break below the lower band.

Chart 2 shows Alaska Airlines (ALK) with a squeeze in mid June. After declining in April-May, ALK stabilized in early June as Bollinger Bands narrowed. BandWidth dipped to around 1.5 to put the Squeeze play on in mid June. With the stock around 15-16, BandWidth was less than 10% of the stock price. With the subsequent surge above the upper band, the stock broke out to trigger an extended advance.

Chart 3 shows Aeropostale (ARO) with a couple of Squeezes. The second Squeeze occurred in October as ARO consolidated around 43 and BandWidth dipped below 3. Aeropostale is priced higher than Alaska Airlines and this means its non-normalized BandWidth will be relatively higher. Low Bandwith for ARO is below 4. Relatively low BandWidth in ARO alerted traders to be ready for a move in mid August. ARO subsequently broke the lower band with a move below 40 and this triggered an extended decline. The advance stalled in late September and BandWidth narrowed in October. Notice how BandWidth declined back to its August lows in early October and then flattened out. The subsequent break below the lower Bollinger Band triggered a bearish signal in late October.

The Squeeze can also be applied to weekly charts or longer timeframes. As expected, band breaks can take longer to materialize. Chart 4 shows Barrick Gold (ABX) consolidating throughout 2006 and into 2007. As the consolidation narrowed and a triangle formed, Bollinger Bands contracted and BandWidth dipped below 5. Notice how Bandwidth remained at low levels as the consolidation extended. A bullish signal triggered with the breakout in July 2007. BandWidth also rose as prices moved sharply in one direction and Bollinger Bands widened.

Chart 5 shows Honeywell (HON) with an extended trading range around 55. There was a move to the upper band in May, but no breakout for a signal. Instead, HON clearly broke below the lower band to trigger a bearish signal.

Conclusions

The Bandwidth indicator can be used to identify the Bollinger Band Squeeze. This alerts chartists to prepare for a move, but direction depends on the subsequent band break. A Squeeze and break above the upper band is bullish, while a Squeeze and break below the lower band is bearish. Be careful for head-fakes though. Sometimes the first break fails to hold as prices reverse the move the other way. Strong breaks hold, but weak breaks are challenged. An upside breakout followed by an immediately pullback should serve as a warning.

Source:http://stockcharts.com/

Bollinger Band %B

Introduction

%B is an indicator derived from Bollinger Bands. In his book, Bollinger on Bollinger Bands, John Bollinger refers to %B as one of two indicators that can be derived from Bollinger Bands. The other indicator is Bollinger Band width.

%B quantifies a security's price relative to the upper and lower Bollinger Band. There are six basic relationship levels:

• %B equals 1 when price is at the upper band
• %B equals 0 when price is at the lower band
• %B is above 1 when price is above the upper band
• %B is below 0 when price is below the lower band
• %B is above .50 when price is above the 20-day moving average
• %B is below .50 when price is below the 20-day moving average

Calculation

%B = (Price - Lower Band)/(Upper Band - Lower Band)

The default setting for %B is based on the default setting for Bollinger Bands (20,2). The bands are set 2 standard deviations above and below the 20-day simple moving average. Security price is the close or the last trade.

Signals: Overbought/Oversold

%B can be used to identify overbought and oversold situations. However, it is important to know when to look for overbought readings and when to look for oversold readings. As with most momentum oscillators, it is best to look for short-term oversold situations when the medium-term trend is up and short-term overbought situations when the medium-term trend is down. In other words, look for opportunities in the direction of the bigger trend, such as a pullback within a bigger uptrend. Define the bigger trend before looking for overbought or oversold readings.

Chart 1 shows Apple (AAPL) within a strong uptrend. Notice how %B moved above 1 several times, but did not even come close to 0. Even though %B moved above 1 numerous times, these "overbought" readings did not produce good sell signals. Pullbacks were shallow as Apple reversed well above the lower band and resumed its uptrend. John Bollinger refers to "walking the band" during strong trends. In a strong uptrend, prices can walk up the upper band and rarely touch the lower band. Conversely, prices can walk down the lower band and rarely touch the upper band in a strong downtrend.

After identifying a bigger up trend, %B can be considered oversold when it moves to zero or below. Remember, %B moves to zero when price hits the lower band and below zero when price moves below the lower band. This represents a move that is 2 standard deviations below the 20-day moving average. Chart 2 shows the Nasdaq 100 ETF (QQQQ) within an uptrend that began in March 2009. %B moved below zero three times during this uptrend. The oversold readings in early July and late October provided good entry points to partake in the bigger uptrend.

Signals: Trend Identification

John Bollinger's book also featured a trend-following system using %B with the Money Force Index, also known as the Money Flow Index (MFI). An uptrend begins when %B is above .80 and MFI is above 80. MFI is bound between zero and a hundred. A move above 80 places MFI in the upper 20% of its range, which is a strong reading. Bollinger suggested setting MFI periods at 1/2 the number of Bollinger Band periods, which would be 10. Downtrends are identified when %B is below .20 and MFI is below 20.

Chart 3 shows FedEx (FDX) with Bollinger Bands (20,2), %B and MFI (10). An uptrend started in late July when %B was above .80 and MFI was above 80. This uptrend was subsequently affirmed with two more signals in early September and mid November. While these signals were good for trend identification, traders would likely have had issues with the risk-reward ratio after such big moves. It takes a substantial price surge to push %B above .80 and MFI above 80 at the same time. Traders might consider using this method to identify the trend and then look for appropriate overbought or oversold levels for better entry points.

Conclusions

%B quantifies the relationship between price and Bollinger Bands. Readings above .80 indicate that price is near the upper band. Readings below .20 indicate that price is near the lower band. Surges towards upper band show strength, but can sometimes be interpreted as overbought. Plunges to the lower band show weakness, but can sometimes be interpreted as oversold. A lot depends on the underlying trend and other indicators. While %B can have some value on its own, it is best when used in conjunction with other indicators or price analysis. Click here for a live chart with Bollinger Bands.

%B and SharpCharts

%B can be found in the indicator list on SharpCharts. The default parameters (20,2) are based on the default parameters for Bollinger Bands. These can be changed accordingly. 20 represents the simple moving average. 2 represents the number of standard deviations for the upper and lower band. %B can be positioned above the price plot, behind the price plot or below the price plot. Click here to see a live example of %B.

Source:http://stockcharts.com/

Average True Range (ATR)

Introduction

Developed by J. Welles Wilder and introduced in his book, New Concepts in Technical Trading Systems (1978), the Average True Range (ATR) indicator measures a security's volatility. As such, the indicator does not provide an indication of price direction or duration, it simply shows the degree of price movement or volatility.

As with most of his indicators, Wilder designed ATR with commodities and daily prices in mind. In 1978, commodities were frequently more volatile than stocks. They were (and still are) often subject to gaps and limit moves. (A limit move occurs when a commodity opens up or down its maximum allowed move for the session.) The resulting bar or candlestick would simply be a small dash.) In order to accurately reflect the volatility associated with commodities, Wilder sought to account for gaps, limit moves, and small high-low ranges in his calculations. A volatility formula based on only the high-low range would fail to capture the actual volatility created by the gap or limit move.

True Range

Wilder started with a concept called True Range (TR), which is defined as the greatest of the following:

• Current High less the current Low
• Current High less the previous Close (absolute value)
• Current Low less the previous Close (absolute value)

Absolute values are used to insure positive numbers. After all, we are interested in measuring the distance between these two points. If the current high-low range is large, chances are it will be used as the True Range. If the current high-low range is small, one of the other two methods would likely be used to calculate the True Range. The last two possibilities usually arise when the previous close is greater than the current high (signaling a potential gap down or limit move) or the previous close is lower than the current low (signaling a potential gap up or limit move). The high-low range is used as the TR for day one because it is impossible to use the previous close for the first day.

Example A: A small high/low range formed after a gap up. The TR equals the absolute value of the difference between the current high and the previous close.

Example B: A small high/low range formed after a gap down. The TR equals the absolute value of the difference between the current low and the previous close.

Example C: Even though the current close is within the previous high/low range, the current high/low range is quite small. In fact, it is smaller than the absolute value of the difference between the current high and the previous close, which is used to value the TR.

Calculation

Typically, the Average True Range (ATR) is based on 14 periods and can be calculated on an intraday, daily, weekly or monthly basis. For this example, the ATR will be based on daily data. Because there must be a beginning, the first TR value in a series is simply the High minus the Low, and the first 14-day ATR is the average of the daily TR values for the last 14 days. After that, Wilder sought to smooth the data set, by incorporating the previous period's ATR value.

             
Current ATR = [(Prior ATR x 13) + Current TR] / 14

- Multiply the previous 14-day ATR by 13.
- Add the most recent day's TR value.
- Divide the total by 14

Click here for an Excel Spreadsheet showing the start of an ATR calculation for QQQQ.

In the Spreadsheet example, the first True Range value (.91) equals the High minus the Low (yellow cells). The first 14-day ATR value (.56)) was calculated by finding the average of the first 14 True Range values (blue cell). Subsequent ATR values were smoothed using the formula above. The spreadsheet values correspond with the yellow area on the chart below. Notice how ATR surged as QQQQ plunged in May with many long candlesticks.

For those trying this at home, a few caveats apply. First, ATR values depend on where you begin. The first True Range value is simply the current High minus the current Low and the first ATR is an average of the first 14 True Range values. The real ATR formula does not kick in until day 15. Even so, the remnants of these first two calculations linger and slightly affect ATR values. Spreadsheet values for a small subset of data may not match exactly with what is seen on the price chart. Decimal rounding can also slightly affect ATR values.

Absolute ATR

ATR is based on the True Range, which uses absolute price changes. As such, ATR reflects volatility as absolute level. In other words, ATR is not shown as a percentage of the current close. This means low priced stocks will have lower ATR values than high price stocks. For example, a $20-30 security will have much lower ATR values than a $200-300 security. Because of this, ATR values are not comparable. Even large price movements for a single security, such as a decline from 70 to 20, can make long-term ATR comparisons impractical. Chart 4 shows Google with double digit ATR values and chart 5 shows Microsoft with ATR values below 1. Despite different values, their ATR lines have similar shapes.

Conclusions

ATR is not a directional indicator, such as MACD or RSI. Instead, ATR is a unique volatility indicator that reflects the degree of interest or disinterest in a move. Strong moves, in either direction, are often accompanied by large ranges, or large True Ranges. This is especially true at the beginning of a move. Uninspiring moves can be accompanied by relatively narrow ranges. As such, ATR can be used to validate the enthusiasm behind a move or breakout. A bullish reversal with an increase in ATR would show bullish enthusiasm and reinforce the reversal. A bearish support break with an increase in ATR would show strong selling pressure and reinforce the support break.

Source:http://stockcharts.com/

Average Directional Index (ADX)

Introduction

J. Welles Wilder developed the Average Directional Index (ADX) to evaluate the strength of a current trend, be it up or down. It's important to determine whether the market is trending or trading (moving sideways), because certain indicators give more useful results depending on the market doing one or the other.

The ADX is an oscillator that fluctuates between 0 and 100. Even though the scale is from 0 to 100, readings above 60 are relatively rare. Low readings, below 20, indicate a weak trend and high readings, above 40, indicate a strong trend. The indicator does not grade the trend as bullish or bearish, but merely assesses the strength of the current trend. A reading above 40 can indicate a strong downtrend as well as a strong uptrend.

ADX can also be used to identify potential changes in a market from trending to non-trending. When ADX begins to strengthen from below 20 and moves above 20, it is a sign that the trading range is ending and a trend is developing.

When ADX begins to weaken from above 40 and moves below 40, it is a sign that the current trend is losing strength and a trading range could develop.

Positive/Negative Directional Indicators

The ADX is derived from two other indicators, also developed by Wilder, called the Positive Directional Indicator (sometimes written +DI) and the Negative Directional Indicator (-DI).

When the ADX Indicator is selected, SharpCharts plots the Positive Directional Indicator (+DI), Negative Directional Indicator (-DI) and Average Directional Index (ADX). With the Default color scheme on SharpCharts, ADX is the thick black line with less fluctuation, +DI is green and -DI is red. +DI measures the force of the up moves and -DI measures the force of the down moves over a set period. The default setting is 14 periods, but users are encouraged to modify these settings according to their personal preferences.

In its most basic form, buy and sell signals can be generated by +DI/-DI crosses. A buy signal occurs when +DI moves above -DI and a sell signal when -DI moves above the +DI. Be careful, though; when a security is in a trading range, this system may produce many whipsaws. As with most technical indicators, +DI/-DI crosses should be used in conjunction with other aspects of technical analysis.

The ADX combines +DI with -DI, and then smooths the data with a moving average to provide a measurement of trend strength. Because it uses both +DI and -DI, ADX does not offer any indication of trend direction, just strength. Generally, readings above 40 indicate a strong trend and readings below 20 a weak trend. To catch a trend in its early stages, you might look for stocks with ADX that advances above 20. Conversely, an ADX decline from above 40 might signal that the current trend is weakening and a trading range is developing.

Source:http://stockcharts.com/

Aroon

Introduction

Developed by Tushar Chande in 1995, Aroon is an indicator system that can be used to determine whether a stock is trending or not and how strong the trend is. "Aroon" means "Dawn's Early Light" in Sanskrit and Chande chose that name for this indicator since it is designed to reveal the beginning of a new trend.

The Aroon indicator system consists of two lines, 'Aroon(up)' and 'Aroon(down)'. It takes a single parameter which is the number of time periods to use in the calculation. Aroon(up) is the amount of time (on a percentage basis) that has elapsed between the start of the time period and the point at which the highest price during that time period occurred. If the stock closes at a new high for the given period, Aroon(up) will be +100. For each subsequent period that passes without another new high, Aroon(up) moves down by an amount equal to (1 / # of periods) x 100.

Technically, the formula for Aroon(up) is:

[ [ (# of periods) - (# of periods since highest high during that time) ] / (# of periods) ] x 100

For example, consider plotting a 10-period Aroon(up) line on a daily chart. If the highest price for the past ten days occurred 6 days ago (4 days since the start of the time period), Aroon(up) for today would be equal to ((10-6)/10) x 100 = 40.

Aroon(down) is calculated in just the opposite manner, looking for new lows instead of new highs. When a new low is set, Aroon(down) is equal to +100. For each subsequent period that passes without another new low, Aroon(down) moves down by an amount equal to (1 / # of periods) x 100.

The formula for Aroon(down) is :

[ [ (# of periods) - (# of periods since lowest low during that time) ] / (# of periods) ] x 100

Continuing the example above, if the lowest price in that same ten-day period happened yesterday (i.e. on day 9), Aroon(down) for today would be 90.

Aroon Oscillator

A separate indicator called the Aroon Oscillator can be constructed by subtracting Aroon(down) from Aroon(up). Since Aroon(up) and Aroon(down) oscillate between 0 and +100, the Aroon Oscillator will oscillate between -100 and +100 with zero as the center crossover line.

Interpretation Guidelines

Chande states that when Aroon(up) and Aroon(down) are moving lower in close proximity, it signals that a consolidation phase is under way and no strong trend is evident. When Aroon(up) dips below 50, it indicates that the current trend has lost its upward momentum. Similarly, when Aroon(down) dips below 50, the current downtrend has lost its momentum. Values above 70 indicate a strong trend in the same direction as the Aroon (up or down) is under way.

The Aroon Oscillator signals an upward trend is underway when it is above zero and a downward trend is underway when it falls below zero. The farther away the oscillator is from the zero line, the stronger the trend.

In some ways, Aroon is similar to Wilder's DMI system (and the Aroon Oscillator is similar to Wilder's ADX line) however the Aroon is constructed in a completely different manner. Divergences between the two systems may be very instructive.

Source:http://stockcharts.com/

Accumulation/Distribution Line

Introduction - Volume and the Flow of Money

There are many indicators available to measure volume and the flow of money for a particular stock, index or security. One of the most popular volume indicators over the years has been the Accumulation/Distribution Line. The basic premise behind volume indicators, including the Accumulation/Distribution Line, is that volume precedes price. Volume reflects the amount of shares traded in a particular stock, and is a direct reflection of the money flowing into and out of a stock. Many times before a stock advances, there will be period of increased volume just prior to the move. Most volume or money flow indicators are designed to identify early increases in positive or negative volume flow to gain an edge before the price moves. (Note: the terms "money flow" and "volume flow" are essentially interchangeable.)

Methodology

The Accumulation/Distribution Line was developed by Marc Chaikin to assess the cumulative flow of money into and out of a security. In order to fully appreciate the methodology behind the Accumulation/Distribution Line, it may be helpful to examine one of the earliest volume indicators and see how it compares.

In 1963, Joe Granville developed On Balance Volume (OBV), which was one of the earliest and most popular indicators to measure positive and negative volume flow. OBV is a relatively simple indicator that adds the corresponding period's volume when the close is up and subtracts it when the close is down. A cumulative total of the positive and negative volume flow (additions and subtractions) forms the OBV line. This line can then be compared with the price chart of the underlying security to look for divergences or confirmation.

In developing the Accumulation/Distribution Line, Chaikin took a different approach. OBV uses the change in closing price from one period to the next to value the volume as positive or negative. Even if a stock opened on the low and closed on the high, the period's OBV value would be negative as long as the close was lower than the previous period's close. Chaikin chose to ignore the change from one period to the next and instead focused on the price action for a given period (day, week, month). He derived a formula to calculate a value based on the location of the close, relative to the range for the period. We will call this value the "Close Location Value" or CLV. The CLV ranges from plus one to minus one with the center point at zero. There are basically five combinations:

( ( (C - L) - (H - C) ) / (H - L) ) = CLV

1. If the stock closes on the high, the top of the range, then the value would be plus one.
2. If the stock closes above the midpoint of the high-low range, but below the high, then the value would be between zero and one.
3. If the stock closes exactly halfway between the high and the low, then the value would be zero.
4. If the stock closes below the midpoint of the high-low range, but above the low, then the value would be negative.
5. If the stock closes on the low, the absolute bottom of the range, then the value would be minus one.

The CLV is then multiplied by the corresponding period's volume, and the cumulative total forms the Accumulation/Distribution Line.

The daily chart of Ciena (CIEN) gives a breakdown of the Accumulation/Distribution Line, and shows how different closing levels affect the value. The top section shows the price chart for CIEN. The closing level relative to the high-low range is clearly visible. The second section with a black histogram is the Closing Location Value (CLV). The CLV is multiplied by volume, and the result appears in the green histogram. Finally, at the bottom, is the Accumulation/Distribution Line.

1. The close is on the low and the CLV = -1. Volume, however, was relatively light, so the Accumulation/Distribution Value for that period is only moderately negative.
2. The close is very near the high and the CLV = +.9273. Volume is relatively high, so the resulting Accumulation/Distribution Value is high.
3. The close is near the low and the CLV = -.75. Volume is moderately high, so the resulting Accumulation/Distribution Value is moderately high as well.
4. The close is about half way between the mid-point of the high-low range and the high, and the CLV = +.51. Volume is very heavy, so the Accumulation/Distribution Value is also very high.

Accumulation/Distribution Line Signals

The signals for the Accumulation/Distribution Line are fairly straightforward and center around the concepts of divergence and confirmation.

Bullish Signals

A bullish signal is given when the Accumulation/Distribution Line forms a positive divergence. Be wary of weak positive divergences that fail to make higher reaction highs or those that are relatively young. The main issue is to identify the general trend of the Accumulation/Distribution Line. A two-week positive divergence may be a bit suspect. However, a multi-month positive divergence deserves serious attention.

On the chart for Alcoa, Inc. (AA), the Accumulation/Distribution Line formed a huge positive divergence that was over 4 months in the making. Even though the stock fell from above 35 to below 30, the Accumulation/Distribution Line continued on a relentless march north. If one did not know better, it would seem that the two plots did not belong together. However, the stock finally caught up with the Accumulation/Distribution Line when it broke resistance in November.

Another means of using the Accumulation/Distribution Line is to confirm the strength or sustainability behind an advance. In a healthy advance, the Accumulation/Distribution Line should keep up or, at the very least, move in an uptrend. If the stock is moving up at a rapid clip, but the Accumulation/Distribution Line has trouble making higher highs or trades sideways, it should serve as an indication that buying pressure is relatively weak.

Wal-Mart Stores (WMT) began a sharp advance in August that was accompanied by an equally strong move in the Accumulation/Distribution Line. In fact, the Accumulation/Distribution Line was stronger than the stock in early September. After a bit of a consolidation, both again started higher and recorded new reaction highs in early October. Volume flows were behind this advance from the very beginning and continued throughout. The stock ended up advancing from 40 to 60 in about 3 months. Interestingly, as of this writing (December 1999) the Accumulation/Distribution Line has started to move sideways and is indicating that buying pressure is beginning to wane.

Bearish Signals

The same principles that apply to positive divergences apply to negative divergences. The key issue is to identify the main trend in the Accumulation/Distribution Line and compare it to the underlying security. Young negative divergences, or those that are relatively flat, should be looked upon with a healthy dose of skepticism.

The Wal-Mart chart shows a relatively flat negative divergence that is just over a month old. This negative divergence has yet to make a lower low, and should probably be given a little more time to mature. The relative weakness in the Accumulation/Distribution Line should serve as a sign that buying pressure is diminishing while the stock remains at lofty levels.

The Delta Air Lines (DAL) chart shows a negative divergence that developed within the confines of a clear downtrend. The stock had clearly broken down, and the Accumulation/Distribution Line was declining in line with the stock. A deteriorating Accumulation/Distribution Line confirmed weakness in the stock. During the June-July rally, the stock recorded a new reaction high, but the Accumulation/Distribution Line failed, thus setting up the negative divergence.

Source:http://stockcharts.com/

ZigZag

Introduction

The ZigZag feature on SharpCharts is not an indicator per se, but rather a means to filter out random noise and compare relative price movements. The ZigZag can be set to acknowledge minimum price changes and ignore those that do not fit the criteria. The minimum price movements are set in percentage terms and can be based on either the close or high/low range.

A ZigZag set at 10% with OHCL bars would yield a line that only reverses after a change from high to low of 10% or greater. All movements less than 10% would be ignored. If a stock traded from a low of 100 to a high of 109, the ZigZag would not draw a line because the move was less than 10%. If the stock advanced from a low of 100 to a high of 110, then the ZigZag would draw a line from 100 to 110. If the stock continued on to a high of 112, this line would be extended to 112 (100 to 112). The ZigZag would not reverse until the stock declined 10% or more from its high. From a high of 112, a stock would have to decline 11.2 points (or to a low of 100.8) for the ZigZag to reverse and display another line.

The ZigZag has zero predictive power and draws lines base on hindsight. Any predictive power will come from applications such as Elliott Wave or Fibonacci retracements and projections.

Uses

Filter:

Volatility and daily price fluctuations can produce erratic movements or noise. The ZigZag can be used to filter this noise. If price movements smaller than 5% are deemed insignificant, then the ZigZag can be set at 5% and all movements less than 5% will be ignored.

Elliott Wave

The ZigZag can be used to identify waves for Elliott Wave counts. (Note: The object of this article is not Elliott Wave Theory, but simply to illustrate methods of using the ZigZag.)

(ZigZag Chart for HPQ)

The HPQ example set the ZigZag at 15%. All moves 15% or greater were drawn and those less that 15% ignored. A large advance began in Oct-99 and formed a 5-wave structure that lasted until mid 2000. Within this larger structure, other smaller waver counts can also be deciphered.

Retracements

The ZigZag can be used to measure retracements. After an advance, it is common for a security to retrace a portion of its advance with a correction. After a decline, it is common for a security to retrace part of its decline with a reaction rally. According to Dow Theory, 1/3, 1/2 and 2/3 retracements are most likely. Based on Fibonacci numbers, 38.2% or 61.8% retracement levels are deemed significant.

(ZigZag Chart for HAL)

During the advance from 34 to 55, HAL corrected twice (waves 2 and 4) and fulfilled two Fibonacci retracement targets: .618 and .786. Perhaps the most important Fibonacci number is .618, which is the golden mean. The square root of .618 is .786 (78.6%), another Fibonacci number used frequently by Scott Carney. In Mar-00, HAL retraced 79.8% of its wave 1 advance (red oval). From the Mar-00 low, the stock advanced 1.70 times its previous decline to form wave 3, which is close to a Fibonacci 1.618. The correction on wave 4 retraced 67.6% of the wave 3 advance. While 67.6% and 79.8% are not exact Fibonacci retracements, they are close enough to 61.8% and 78.6% to warrant attention.

Projections

The ZigZag can be used to measure primary price movements. As opposed to a correction or reaction rally, a primary price movement is in the direction of the underlying trend. Instead of retracing a portion of the previous move, primary moves extend past the previous reaction high or low. Many analysts that use Elliott Wave and Fibonacci sequences project the length of an advance or decline by multiplying a ratio to the previous retracement. If the previous decline (correction) was 50 points and a Fibonacci specialist was looking for new highs on the subsequent advance, the projection might be 1.618 times the previous move, or 81 points (50 x 1.618 = 81). The 81 points would be added to the beginning of the advance for a price target.

Examples

ZigZag (Basic)

(ZigZag Chart for IBM)

The percentage price change for the ZigZag can be changed with the first box to the right. The default setting is 5%. In the example, the indicator was set at 12, or 12 percent. All price movements greater than or equal to 12% will produce a ZigZag line. All price movements less than 12% will be ignored. The ZigZag is plotted as a thick line on top of the price plot.

ZigZag w/Retracements

(ZigZag Chart for IBM)

The ZigZag w/Retracements includes ratios of adjacent price movements. For the IBM example, the ZigZag w/Retracements was set at 12% to filter out all price movements less than 12%. Three pairs of price movements were compared from the Jun-00 to Nov-00. Dotted lines connect the relevant highs or relevant lows and the ratio is labeled in the middle of the dotted line. The first ratio is 1.566, representing an advance that was 156.6% of the previous decline. The formula is calculated in three steps:

• First Price Move - Decline: 122.31 - 100 = 22.31
• Second Price Move - Advance: 134.94 - 100 = 34.94
• Advance/Decline Ratio: 34.94/22.31 = 1.566

Calculations for the other two ratios (1.374 and .309) are shown on the corresponding chart.

The final line for the ZigZag is subject to change. On the IBM example above, the current ZigZag high is 104.38. Because of the recent decline, the ZigZag continued down from 104.38. However, the current decline is well short of the 12% minimum. Should the current decline fail to exceed 12% and should IBM advance above 104.38, then the line from 86.94 would be extended to the new high and the ratio (.363) would change. The red line in the example above provides an idea of what would happen should IBM turn up from current levels and move to 110. The green lines extending from the October low would be replaced by a line extending straight up to 110.

Source:http://stockcharts.com/

Volume by Price

introduction

"Volume by Price" is a horizontal histogram that overlays a price chart. The histogram bars stretch from left to right starting at the left side of the chart. The length of each bar is determined by the cumulative total of all volume bars for the periods during which the closing price fell within the vertical range of the histogram bar. Example

In the chart below, each volume-by-price bar covers a vertical range of 5 points. The longest bar covers the range from 27.5 to 32.5. The length of that bar was determined by adding up all of the volume bars on the days during which the price closed anywhere between 27.5 and 32.5.

Source:http://stockcharts.com/

Price Channels

Introduction

Similar to Bollinger Bands, price channels form boundaries above and below the price line and can be used as indicators of volatility. Price channels are created by specifying a number of periods that will chart an n-period high or low around the price line. For example, a 20-day price channel will chart the level of the highest high in the last 20 days above the price line, and will chart the level of the lowest low in the last 20 days below the price line. If the most recent price is a new n-period high or low, it will be charted outside of the price channel. Price channels differ from Bollinger Bands in that they use maximum and minimum price values instead of moving averages as boundaries.

Price channels can be used on daily, weekly, or monthly charts and can generate buy/sell signals at points of breakouts. When the price line breaks above or below the upper or lower price channel respectively, a new high or low becomes present. When the price breaks above a 20-day price channel, the price has reached a 20-day high and could potentially begin an uptrend. In this situation, the upper price channel breakout may signify that it is a good time to buy the stock.

Example

This chart for IBM illustrates a lower channel breakout (red arrow) followed by a downtrend. This new 20-day low represented a good time to sell the security, and the signal was not reversed until the price line crossed the upper price channel on June 9.

Source:http://stockcharts.com/

Parabolic SAR

Introduction

Developed by Welles Wilder, the Parabolic SAR refers to a price and time based trading system. Wilder called this the "Parabolic Time/Price System". SAR stands for "stop and reverse", which is the actual indicator used in the system. SAR trails price as the trend extends over time. The indicator is below the price when prices are rising and above the price when prices are falling. In this regard, the indicator stops and reverses when the price trend reverses and breaks above or below the indicator. Wilder introduced the indicator in his 1978 book, New Concepts in Technical Trading Systems. This book also includes RSI, Average True Range and the Directional Movement Concept (ADX). Despite being developed before the computer age, Wilder's indicators have stood the test of time and remain extremely popular.

Calculation

Calculation of SAR is complex with a few if/then variables that make it difficult to put in a spreadsheet. Feel free to skip to the interpretation section! These examples will provide a general idea of how SAR is calculated. Because of formula differentials, it is easier to divide the calculation into two parts. The first calculation covers rising SAR and the second covers falling SAR.

Rising SAR

Prior SAR: The SAR value for the previous period.

Extreme Point (EP): The highest high of the current uptrend.

Acceleration Factor (AF): Starting at .02, AF increases by .02 each
time the extreme point makes a new high. AF can reach a maximum
of .20, no matter how long the uptrend extends.

Current SAR = Prior SAR + Prior AF(Prior EP - Prior SAR)
9-Feb-10 SAR = 43.56 = 43.84 + .16(42.07 - 43.84)

The Acceleration Factor is multiplied by the difference between the
Extreme Point and the prior period's SAR. This is then added to the
prior period's SAR. SAR can never be above the prior period's low or
the current low. Should SAR be below one of these, use the lowest
of the two for SAR.

Falling SAR

Prior SAR: The SAR value for the previous period.

Extreme Point (EP): The lowest low of the current downtrend.

Acceleration Factor (AF): Starting at .02, AF increases by .02 each
time the extreme point makes a new low. AF can reach a maximum of .20,
no matter how long the downtrend extends.

Current SAR = Prior SAR - Prior AF(Prior SAR - Prior EP)
13-Apr-10 SAR = 48.28 = 48.13 - .14(48.13 - 49.20)

The Acceleration Factor is multiplied by the difference between the
Prior period's SAR and the Extreme Point. This is then subtracted
from the prior period's SAR. SAR can never be below the prior
period's high or the current high. Should SAR be below one of these,
use the highest of the two for SAR.

Interpretation

SAR follows price and can be considered a trend following indicator. Once a downtrend reverses and starts up, SAR follows prices like a trailing stop. The stop continuously rises as long as the uptrend remains in place. In other words, SAR never decreases in an uptrend and continuously protects profits as prices advance. The indicator acts as a guard against the propensity to lower a stop-loss. Once price stops rising and reverses below SAR, a downtrend starts and SAR is above the price. SAR follows prices lower like a trailing stop. The stop continuously falls as long as the downtrend extends. Because SAR never rises in a downtrend, it continuously protects profits on short positions.

Step Increments

The Acceleration Factor (AF), which is also referred to as the Step, dictates SAR sensitivity. SharpCharts users can set the Step and the Maximum Step. As shown in the spreadsheet example, the Step is a multiplier that influences the rate-of-change in SAR. That is why it is referred to as the Acceleration Factor. Step gradually increases as the trend extends until it hits a maximum. SAR sensitivity can be decreased by decreasing the Step. A lower step moves SAR further from price, which makes a reversal less likely. This will filter out smaller moves in favor of larger moves. Conversely, SAR sensitivity can be increased by increasing the step. A higher step moves SAR closer to the price action, which makes a reversal more likely. However, the indicator will fluctuate above and below the price too often if the step is set too high. This will produce whipsaws and fail to capture the trend. Chart 6 shows IBM with SAR (.01, .20). The step is .01 and the Maximum Step is .20. Chart 7 shows IBM with a higher Step (.03). SAR is more sensitive in chart 6 because there are more reversals. This is because the Step is higher in chart 6 than chart 7 (.01 versus .03).

Maximum Step

The sensitivity of the indicator can also be adjusted using the Maximum Step. While the Maximum Step can influence sensitivity, the Step carries more weight because it sets the incremental rate-of-increase as the trend develops. Also note that increasing the Step insures that the Maximum Step will be hit quicker when a trend develops. Chart 8 shows Best Buy (BBY) with a Maximum Step (.10), which is lower than the default setting (.20). This lower Maximum Step decreases the sensitivity of the indicator and produces fewer reversals. Notice how this setting caught a two month downtrend and a subsequent two month uptrend. Chart 9 shows BBY with a higher Maximum Step (.20). This higher reading produced extra reversals in early February and early April.

Conclusions

The Parabolic SAR works best with trending securities, which Wilder estimates occur roughly 30% of the time. This means the indicator will be prone to whipsaws over 50% of the time or when a security is not trending. After all, SAR is designed to catch the trend and follow it like a trailing stop. As with most indicators, the quality of the signals depends on the settings and the characteristics of the underlying security. The right settings combined with decent trends can produce a great trading system. The wrong settings will result in whipsaws, losses and frustration. There is no golden rule or one-size-fits-all setting. Each security should be evaluated based on its own characteristics. This means the Parabolic SAR should be used in conjunction with other indicators and technical analysis techniques. For example, Wilder's ADX can be used to estimate the strength of the trend. Click here for a live example of Parabolic SAR.

SharpCharts

The Parabolic SAR can be found as an Overlay in SharpCharts. The default parameters are .02 for the Step and .20 for the Maximum Step. As shown above, these can be changed to suit the characteristics of an individual security. The example below shows the indicator in pink with prices in black/white and the chart grid removed. This contrast makes it easier to see the indicator in action and compare with price action.

Scans

Break above falling SAR: This scan starts with stocks that have an average price of $10 or greater over the last three months and average volume greater than 40,000. The scan then filters for stocks that have a bullish SAR reversal (Parabolic SAR (.01,.20)). This scan is just meant as a starter for further refinement.

Break below rising SAR: This scans starts with stocks that have an average price of $10 or greater over the last three months and average volume greater than 40,000. The scan then filters for stocks that have a bearish SAR reversal (Parabolic SAR (.01,.20)). This scan is just meant as a starter for further refinement.

Source:http://stockcharts.com/