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/