The following are descriptions of some of the most popular technical indicators and includes descriptions of the technical indicator as well as methods of calculation.

· Relative Strength Index (RSI)
· Moving Averages
· Bollinger Bands
· Moving Average Convergence Divergence (MACD)
· Stochastics
· On Balance Volume (OBV)
· Momentum & Rate Of Change (ROC)
· Advance Decline Line
· Advance Decline Noncumulative
· Breadth Advance Decline Indicator
· Commodity Channel Index
· Directional Movement Indicator
· Dividend Yields
· Arm's Ease Of Movement
· Haurlan Index
· Linear Regression
· Arm's Short Term Trading Index (TRIN)
· McClellan Oscillator
· Odd Lot Balance
· Williams %R
· Upside/Downside Ratio
· Correlation Analysis
· Detrended Price Oscillator

 

 

Relative Strength Index - RSI

RSI is a momentum indicator which measures an equity's price relative to itself. It is relative to its past performance. It is also front weighted. Therefore, it gives a better velocity reading than other indicators. RSI is less affected by sharp rises or drops in an equity's price performance. Thus, it filters out some of the 'noise' in a security's trading activity.

RSI's absolute levels are 0 and 100. Traditionally, buy signals are triggered at 30, and sell signals are triggered at 70. However, many analysts are now using 20 for buy signals and 80 for sell signals. I have found some interesting variations of these buy and sell levels.

My analysis indicates that the buy and sell level will vary somewhat depending on the amount of days used in the calculation. A shorter span of days will result in a more volatile indicator which reaches further extremes. A longer amount of days used in the calculation results in a less volatile reading which reaches extremes far less often.

I have also found that despite the fact that RSI is designed to be able to measure multiple equities against each other, it doesn't quite work out that way. Some securities may pull back some when their RSI indicator reaches about 68, others at 70, etc. Different securities seem to have slightly different levels at which the price changes direction. These levels are close to each other. But they seem to be particular to each equity. Basically, the vast majority do seem to change direction at 30 and 70. My point is that this is not a hard and fast rule. There are subtle differences.

RSI treats price as a rubberband. The rubberband can be stretched just so far. After a certain point, unless it breaks, the rubberband is forced to contract. Keep in mind that trades are not placed on RSI alone. RSI is a momentum indicator which usually turns ahead of price. The important thing to remember is that price is the ultimate determinant.

RSI is also an indicator which lends itself to trendlines, support and resistance lines, and divergence. Trendlines, and support and resistance lines can be drawn in the same manner as on a price chart. Further, I have observed that they carry as much reliability on an RSI chart as they do on a price chart.

One of the more important aspects of RSI is to look for divergence between price action and RSI. Upwardly sloping price and downward sloping RSI, should be taken as a warning. Usually, one of them is wrong. More often than not, this indicates that price is about to break down. The reverse is true for downward sloping price and upward sloping RSI. It usually indicates that price is about to break out of a decline.

Formula For RSI

RSI equals the average of the closes of the up days divided by the average of the closes of the down days. The time frame specified determines the volatility of the indicator. For instance, a nine day time period under study will be more volatile than a 21 day time span.

For a 22 day RSI calculation, the following are the steps involved.

Add the closing values for the up days and divide this total by 22.

Add the closing values for the down days and divide this total by 22.

Divide the up day average by the down day average. This results in the RS factor in the formula.

Add 1 to the RS.

Divide 100 by the number arrived at in step 4 above.

Subtract the number arrived at in step 5 above from 100.

Repeat steps 1-6 for day number 23. Drop day number 1 from the calculation. As enough days are accumulated, the results can be plotted in graphical format.

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Moving Averages

Moving averages are one of the oldest technical indicators in existence. I also find moving averages to be one of the most useful indicators. A basic definition of a moving average is that it is the average price of a security at a specific point in time. A moving average shows a trend. The purpose of the moving average is to show the trend in a smoothed fashion.

The user specifies the time span. For stocks, the most common time periods are 10 days, 30 days, 50 days, 100 days, and 200 day moving averages. Most technicians, however, use variations of these numbers to suit their individual needs. There really isn't just one "right" time frame. Moving averages with different time spans each tell a different story. The shorter the time span, the more sensitive the moving average will be to price changes. The longer the time span, the less sensitive or the more smoothed the moving average will be.

The other component a person needs to specify is what value to use for the price of the stock. The most common value to use is the close for that particular day. However, technicians use several variations of this. They are: (high+low)/2; (close+high+low)/3; (open+close+high+low)/4; and the weighted variation is (high+low+close+close)/4; For my explanations here, I'm going to use the day's closing price. Also, closing prices are much more significant because they represent positions that investors are willing to carry overnight.

Perhaps the best way to understand a moving average is with an example. Let's assume that we have been tracking the closing price of IBM for the past 100 days and we want to create a 30 day moving average. First, we add the closing prices together for the first 30 days. Then we divide this amount by thirty. This is the first point we would plot on the chart. Then we add the closing prices together for day 2 through day 31. We then divide this amount by thirty. This is the second point on the chart. Then we add the closing prices for days 3 through 32 together. We divide this number by 30. And this can go on forever. We connect all the points we plotted together in a line and run it through the price bars. This moving average shows us the smoothed price trend. A valid buy signal is given when price crosses above the moving average and the moving average is directed upward. A valid sell signal is given when price crosses below the moving average and the moving average is directed downward. Valid buy and sell signals are not given when the moving average changes direction but price does not cross above or below the moving average.

Moving averages can become more powerful when multiple moving averages are plotted on the same chart. One combination that I use is to plot a 10 day moving average and a 30 day moving average on the same chart. A valid buy signal is given when the 10 day moving average crosses above the 30 day moving average and both moving averages are in an upward direction. A valid sell signal is given when the 10 day moving average crosses below the 30 day moving average and both moving averages are directed downward.

Because false signals can be given when using moving averages, technicians always use other indicators to confirm the direction of price. This generally occurs when price fluctuates in a broad sideways pattern.

Up until now our discussion on moving averages has focused on what we call a simple moving average. However, there are two other types of moving averages. These are the weighted moving average and the exponential moving average. When a simple moving average is centered, the signal is delayed. To overcome this, many technicians use a weighted moving average. With this type of moving average, the data is weighted in favor of the most recent observations. A weighted moving average has the ability to reverse direction more quickly than a simple moving average. The most frequently used method to weight a moving average is as follows. Let's assume, for simplicity, a 5 day moving average. Multiply the first observation by 1; the second observation by 2; the third observation by 3; the fourth observation by 4; the fifth observation by 5. Then divide this sum by the sum of the weights. In this case, the divisor is 1+2+3+4+5= 15. The sum in the first part of the equation is divided by 15. With a weighted moving average, a buy or sell signal is given when the weighted moving average changes direction.

An exponential moving average is a form of a weighted moving average. Let me give you an example. To construct a 20 day exponential moving average you must first construct a 20 day simple moving average. This simple moving average is the starting point for the exponential moving average. Assume that the simple moving average value for day 20 is 42; the simple moving average value for day 21 is 43; and the simple moving average value for day 21 is 44. We then subtract the day 20 moving average value from day 21 simple moving average value and get a difference of 1.00. This value (1.00) is multiplied by an exponent. In this case, the exponent is .1. We then add .1 to the simple moving average value of day 20. The exponential moving average value of day 20 now becomes 42.100. And this goes on indefinitely. To calculate the exponent, divide 2 by the time period. In our case, we divided 2 by 20 to arrive at .1.

Martin Pring in his book, "Technical Analysis Explained", and Robert Edwards and John Magee in their book "Technical Analysis of Stock Trends", brings up the following excellent points about moving averages. The average itself can act as an area of support and resistance. The more times a moving average is touched, the greater the significance of a violation. A violation of the moving average is a warning that a change in trend may have or may be taking place. Confirmations of trend changes should be sought from alternative technical sources. Generally, the longer the time frame of the moving average, the greater the significance of a violation. Reversals in the direction of a moving average are usually more reliable than a moving average crossover.

In an uptrend, the following conditions apply. Long positions are maintained as long as price remains above the moving average. If price crosses above the moving average, a buy signal is generated. If price falls to the 200 day moving average but doesn't cross it and then moves back up, a buy signal is generated. If price drops sharply below the moving average line a rebound toward the moving average line may occur resulting in a whipsaw action. In a downtrend, short positions are held as long as price remains below the moving average. A sell signal is generated when price moves above a declining moving average line. If price moves up to the moving average line but doesn't cross it and drops down again, a sell signal is generated.

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Bollinger Bands

Bollinger Bands are envelopes which surround the price bars on a chart. Bollinger Bands are plotted two standard deviations away from a simple moving average. This is the primary difference between Bollinger Bands and envelopes. Envelopes are plotted a fixed percentage above and below a moving average. Because standard deviation is a measure of volatility, the Bollinger Bands adjust themselves to the market conditions. They widen during volatile market periods and contract during less volatile periods. Bollinger Bands become moving standard deviation bands.

Bollinger Bands are sometimes displayed with a third line. This is the simple moving average line. The time period for this moving average can vary. However, Mr. Bollinger recommends 10 days for short term trading, 20 days for intermediate term trading, and 50 days for longer term trading.

Additionally, the standard deviation value can be varied. Many technicians increase the value of the standard deviation from 2 standard deviations to 2-1/2 standard deviations away from the moving average when using a 50 day moving average. Conversely, many technicians lower the value of the standard deviation from 2 to 1-1/2 standard deviations away from the moving average when using a 10 day moving average.

An important thing to keep in mind is that Bollinger Bands do not generate buy and sell signals alone. They should be used with another indicator. I prefer to use Bollinger Bands with RSI. This is because when price touches one of the bands, it could indicate one of two things. It could indicate a continuation of the trend; or it could indicate a reaction the other way. So Bollinger Bands used by themselves do not provide all of what technicians need to know. Which is when to buy and sell. MACD can be substituted for RSI.

However, when combined with an indicator such as RSI, they become quite powerful. RSI is an excellent indicator with respect to overbought and oversold conditions. Generally, when price touches the upper Bollinger Band, and RSI is below 70, we have an indication that the trend will continue. Conversely, when price touches the lower Bollinger Band, and RSI is above 30, we have an indication that the trend should continue.

If we run into a situation where price touches the upper Bollinger Band and RSI is above 70 (possibly approaching 80) we have an indication that the trend may reverse itself and move downward. On the other hand, if price touches the lower Bollinger Band and RSI is below 30 (possibly approaching 20) we have an indication that the trend may reverse itself and move upward.

Above, I have talked about the use of a second indicator to work with Bollinger Bands. Avoid the trap of using several different indicators all working off the same input data. If you're using RSI with the Bollinger Bands, don't use MACD too. They both rely on the same inputs. You might consider using On Balance Volume, or Money Flow. RSI, On Balance Volume, and Money Flow, rely on different inputs. They measure different things. They can be used together as further confirmation of a trend. The technical term for this is 'Avoiding Multicolinearity'

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Moving Average Convergence Divergence (MACD)

MACD is an oscillator which is derived by dividing one moving average by another. In today's computer programs, the moving averages are usually exponentially weighted, thus giving more weight to the more recent data. It is plotted in a chart with a horizontal equilibrium line. The equilibrium line is important. When the two moving averages cross below the equilibrium line, it means that the shorter EMA is at a value less than the longer EMA. This is a bearish signal. When the EMA's are above the equilibrium line, it means that the shorter EMA has a value greater than the longer EMA. This is a bullish signal.

The name of the indicator is derived from the fact that the shorter EMA is continually converging toward and diverging away from the longer EMA. Many MACD systems also use histograms. the histogram which acts as the oscillator. MACD's can be used for an infinite number of time periods. Many technicians, for buy signals, use a combination of 8, 17, and 9 days for their daily EMA's. However, they use 12, 25, and 9, days for their sell signals.

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Stochastics

The stochastic oscillator compares where a security's price has closed relative to its price range over a specifically identified period of time. George Lane, who developed this indicator, theorized that in an upwardly trending market, prices tend to close near their high; and during a downward trending market, prices tend to close near their low. Further, as an upward trend matures, price tends to close further away from its high; and as a downward trend matures, price tends to close away from its low.

The stochastic indicator attempts to determine when prices start to cluster around their low of the day for an uptrending market, and when the tend to cluster around their high in a downtrending market. Lane's theory is these are the conditions which indicate a trend reversal is beginning to occur.

The stochastic indicator is plotted as two lines. They are the %D line and the %K line. The %D line is more important than the %K line. The stochastic is plotted on a chart with values ranging from 0 to 100. The value can never fall below 0 or above 100. Readings above 80 are strong and indicate that price is closing near its high. Readings below 20 are strong and indicate that price is closing near its low.

Ordinarily, the %K line will change direction before the %D line. However, when the %D line changes direction prior to the %K line, a slow and steady reversal is usually indicated.

When both %K and %D lines change direction, and the faster %K line subsequently changes direction to retest a crossing of the %D line, but doesn't cross it, this is a good confirmation of the stability of the prior reversal.

A very powerful move is underway when the indicator reaches its extremes around 0 and 100. Following a pullback in price, if the indicator retests these extremes, a good entry point is indicated.
Many times, when the %K or %D lines begin to flatten out, this is an indication that the trend will reverse during the next trading range.

Quite often, divergence's set up on the chart. That is, price may be making higher highs, but the stochastic oscillator is making lower lows. Or conversely, price may be making lower highs, and the stochastic oscillator is making higher highs. In either case, the indicator usually is demonstrating a change in price before price itself is changing.

The formula for %k is as follows:

%K = 100[(C - L5close)/(H5 - L5)]

Where:

· C = the most recent close
· L5 = the lowest low for the last 5 trading periods
· H5 = highest high for the same five trading periods

%D is a smoothed version of the %K line. Usually, 3 periods is used. The %K formulas is as follows:

%D = 100 X (H3/L3)

Where:

· H3 = the 3 period sum of (C - L5)
· L3 = the 3 period sum of (H5 - L5)

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On Balance Volume (OBV)

Personally, I don't care too much to look at volume bars on the bottom of a chart. I've never felt it was precise enough to gain much insight from other than to get a general idea as to how volume is running. Also, it's hard to relate volume to price with just volume bars.

This is why I consider On Balance Volume to be such a useful indicator. It was developed by Joseph Granville. On Balance Volume creates a volume line along the bottom of a price chart. OBV is relatively easy to construct. We first start with a beginning number. It should be relatively high. I use 50,000. Then, on day one, if the close is positive, that days volume is added to the 50,000. If the days close was lower, the volume is subtracted. So on up days, volume is added. And on down days, the volume is subtracted. The result is a fluctuating line.

The value of the On Balance Volume is that it generally is a precursor to a change in trend. The holding is that smart money leaves a security first when it is near a top; and also that the smart money is buying when a security is near a low. When the general public catches on to a security's rise in price, volume will increase substantially and the OBV line will increase rapidly faster. Conversely, On Balance Volume will start to decrease while price is still rising. This indicates that the smart money is leaving the security.

Another valuable aspect of On Balance Volume is when divergence's occur. When OBV is decreasing while the price is increasing, a signal is generated that the rally may not be as solid as it appears. When price is declining and OBV is increasing, it is a sign that the investor shouldn't become too bearish. The decline may not last too long.

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Momentum And Rate Of Change

Momentum measures the rate of change in price as opposed to price itself. Momentum is calculated by constantly recording prices changes for a fixed period of time. When constructing a 10 day momentum line, subtract the first days close from the latest days close. The resulting number is plotted against a zero line. The shorter the time span the more sensitive the line is. The longer the time span is the less sensitive the line is.

When first using momentum, one should first plot a short momentum indicator of about 6 periods. This will show where the highest points are and where the lowest bottoms are.

After the short momentum line is created, mark where the highs and lows are. Then construct a longer time period momentum line of about 10 periods (although any number of periods can be used). Then the indicator can be used to buy at the predetermined lows after the indicator and price have turned up; and to sell when the indicator has hit its predetermined highs after the indicator and price have turned down. Always wait for price to confirm the trend.

The price calculation for simple momentum is as follows:

M = V - Vx

Where

V = the latest closing price
Vx = the closing price x days ago

Rate Of Change

Rate of Change is very similar to the momentum indicator with one exception. That is, the price of the last day is divided by the price of the first day. This result is a series of points, connected in the form of a line, which oscillate above and below a central reference line. When the ROC line is above the central line, the price is higher today than it was 10 periods ago. When the ROC line is below the central line, the price is lower today than it was 10 days ago. If the ROC line is above the central line, the price is higher than it was 10 days ago, but the range is narrowing. If the ROC line is below the central line but rising, the price is still lower today than it was 10 days ago, but the range is narrowing.

The following is a description as to how to create the central reference line. Today's ROC value is used as the central number and all subsequent observations fall above or below this observation.

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Advance Decline Line

The advance decline line is simply a cumulative total of the number of advancing issues minus the number of declining issues. First, a large number is chosen, e.g. 20,000. Each day thereafter, the difference between the number of advancing issues and declining issues is added or subtracted. Usually, New York Stock Exchange data is used for the calculation.

The problem with the advance decline line is that it can be quite subjective in interpretation. In retrospect, large divergence's can be seen. However, it is hard to see them developing when the analyst needs the information the most. This is not a forward looking indicator. At best it can be used as a trend indicator.

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Advance Decline Noncumulative

I think that it's easier to show what this indicator is in formula form rather than describe it. So here it is.

(Advancing Issues - Declining Issues) divided by (Total Number of Issues Traded)

The theory is that strengthening market internals preceded increases in stock price movements. And weakening in market internals preceded decreases in stock price movements. Daily and weekly data can be used for this.

Colby and Meyers found that using a 10 period moving average for either daily or weekly data for a reading of .25 or higher an average gain of 4.07% occurred in the S&P 500 one month later, 8.05% three months later, 13.43% 6 months later, and 17.69% twelve months later. Additionally, Colby and Meyers found that readings of -.219 and lower resulted in very bearish periods in the 1 month, 3 month, 6 month, and 12 month periods that followed.

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Breadth Advance Decline Indicator

The formula for breadth advance decline is as follows:

It is a 10 day simple moving average of the following:

(number of advancing issues) divided by [(number of advancing issues) + (number of declining issues)]

New York Stock Exchange data is used in the calculation

Colby and Meyers found that for readings above .66 significant bullish gains were recorded with very few losses. They found that a gain of 3.55% one month later, a gain of 9.10% three months later, a gain of 15.06% six months later, and a gain of 22.13% twelve months later. Similar results were obtained with very bearish signals of .367 or lower.

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Commodity Channel Index

The first thing to know about this indicator is that it works for stocks too.

I would provide you with the formula for CCI, however, we create all our documents using Microsoft Office and it won't convert complicated formulas using their equation editor into a form which can be put up on the internet. And we haven't had much luck with other software programs in our efforts to do this. You generally, would not do this by hand. Almost every software package I've seen has CCI in it. Understand the concept.

A description of the formula is as follows:

First, Calculate each periods mean. This is the high, plus the low, plus the close, divided by 3.

Second, calculate the n period simple moving average of these means. I recommend using 52 weeks as the period for n. However, don't hesitate to play around with this length and optimize the formula for you.

Third, from each periods mean price, subtract the n period simple moving average of mean prices.

Fourth, Compute the mean deviation. This is the differences between each period's mean price and the n period simple moving average of those mean prices.

Fifth, Multiply the mean deviation by .015.

Sixth, the mean price, which we calculated in step three, is divided by .015 times the mean deviations from step 5.

Ordinarily, CCI ranges in value from +100 to -100. The rules are to buy and go long when CCI crosses above +100 and close the long when CCI falls back below +100. Conversely, sell short when CCI crosses below -100 and close the short when CCI crosses back above -100. Using a one line CCI, I use 50 days as n with daily charts. I also place a zero line going across the screen. However, I have found that using a two line CCI (which is standard on my technical analysis software) I use a 40 day input for n and a 60 day input for n. I have found that valid long and short signals are given when the 40 day line crosses the 60 day line.

As always, I tend to mess around and experiment with different variations of indicators. As I keep mentioning, there is always a new and different way of using these indicators. 999 out of 1,000 don't work, however, there is always that 1 which does work.

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Wilder's Directional Movement Indicator

Directional Movement was developed by Welles Wilder and is explained in his book "New Concepts in Technical Trading Systems". The indicator is used to determine if a security is 'trending' or if it is not trending. After all, except for some option strategies, one would normally want to buy a stock that is trending upward or short a stock which is trending downward. There's no way I'm going to provide the formula for this indicator here. It's just too complicated and long. The only real way to use this indicator is with a computer and technical analysis software.

What is important to know is how to use DMI and what you see when you put it on your screen. DMI has three significant lines. They are the +DI, the -DI, and the ADX, lines. Wilder suggests that the user buys when the +DI crosses above the -DI. He suggests selling when the +DI crosses below the -DI. ADX is a smoothed version of the directional movement.

Wilder also uses what he calls the 'extreme point rule'. Don't buy or sell on the day the +DI crosses above or below the -DI. Rather, note the high or low of the day. Then, wait to execute the trade until on a subsequent day the price reaches either the high or low depending on whether the stock is moving up or down.

Colby and Meyers found that 11 weeks was the optimal length for evaluating weekly data. They also found that this indicator is very good for risk adverse traders. I like to use 30 days as the time frame for daily data. I find on daily data that shorter time frames tend to give too many whipsaw signals.

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Dividend Yields

Dividend yields is a longer term trading vehicle. Dividend yields is the average dividend payout per share for the last four quarters for the stocks comprising the S&P 500. Simply add all the dividend payouts per share for each of the S&P 500 stocks for the last four quarters and divide by the S&P 500 index value. Use a simple moving average to smooth the data. A 12 month simple moving average is what is generally used. The rules for trading this indicator are as follows:

Buy and go long when the S&P 500 month end close is greater than the 12 month simple moving average and the S&P dividend yield is 3.4% or greater.

Sell the long positions when the S&P 500 month end close is less than the 12 month simple moving average or the S&P 500 dividend yield is less than 3.4%

Sell short when the S&P 500 month end close is less than the 12 month simple moving average and the S&P 500 dividend yield is less than 3.0%

Cover the short positions when the S&P 500 month end close is greater than the 12 month simple moving average or the S&P 500 dividend yield is greater than 5.2%.

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Arms' Ease Of Movement Value

The formula for Arms' ease of movement is as follows:

[((H + L)/2) - ((Hp + Lp)/2)] divided by ((v)/ H - L))

Where:

H = Current periods high price
L = Current periods low price
Hp = the previous periods high price
Lp = the previous periods low price
V = current periods volume

Example:

25 = this weeks high price
21 = this weeks low price
10,000 = this weeks volume
26 = last weeks high price
22 = last weeks low price
8,000 = last weeks volume

EMV = [((25+21)/2) - ((26+22)/2)] divided by 10,000/(25-21)

EMV = [(46/2) - (48/2)] divided by 10,000/4

EMV = (23 - 24) / 10,000/4

EMV = -1/ 2,500

EMV = -.0004

Arms Ease of Movement requires the analyst to buy when the simple moving average crosses above zero and to sell when the simple moving average falls below zero.

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Haurlan Index

This is a market breadth indicator. It was developed by P.N. Haurlan.

There are three components to this indicator. There is a short term component, intermediate term component, and a long term component. The short term component is a 3 day exponential moving average of the net difference between the number of advancing issues and the number of declining issues. The intermediate term component is a 20 day exponential moving average of the net difference between the number of advancing issues and the number of declining issues. The long term component is a 200 day exponential moving average of the net difference between the number of advancing issues and the number of declining issues.

When the short term component moves above +100, a short term buy signal is generated. It remains in effect until the short term component moves down to -150. At -150, a short term sell signal (shorting level) is reached. Stay short until the indicator reaches +100.

The intermediate component is used to confirm breaks of support and resistance. With confirmation, buy and sell signals are generated.

The long term component is used to determine the primary trend in price.

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Linear Regression

Linear regression is a statistical tool used to measure trends. Linear regression uses the least squares method to plot the line. The linear regression line is a straight line extending through the prices. The formula for linear regression is as follows:

y = a + bx

where:

· y = the closing price
· x = the total number of time periods
· a = y - bx divided by n
· b = n(xy) - (x)(y) divided by nx2 - (x)2

There are two primary ways to use linear regression. The first is to trade in the direction of the linear regression line. Colby and Meyers found that trading in this manner provided good results using a 66 week figure for n. The only drawback was a large drawdown in relation to the profitable trades.

The second way to trade using linear regression is to plot the linear regression line. Then plot two parallel lines to the linear regression line - one above and one below - the linear regression line. These should be equidistant from the linear regression line. To determine the distance, use a point which is the furthest away from the linear regression line on a price bar.

These two lines form a linear regression channel. The two lines act as support and resistance. Once the lines are broken for a sustained period of time, this is an indication that the trend has reversed or gained tremendous momentum. A stock which is moving slightly upward or downward for a period of time which suddenly moves outside the channel in the same direction of the previous move, is showing signs that it will continue the move. A stock which was trending upward or downward and has changed direction and broken the opposite channel for a sustained period is showing signs that the trend will probably continue.

The space inside the channel is where equilibrium exists. This is the area in which prices can be expected to deviate from the original linear regression line. What I have found is that generally, when prices move outside or to the extreme channel line, price tends to move back to the opposite channel line.

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Arms Short Term Trading Index - TRIN

The calculation of TRIN is the ratio of the number of advancing issues to the number of declining issues divided by the ratio of the volume of the advancing issues to the volume of declining issues. New York Stock Exchange daily data is used in the calculation.

(advancing issues/declining issues) divided by (volume of advancing issues/volume of declining issues)

Arms Ease of Movement measures the relative strength of the volume associated with advancing stocks and conversely, with declining stocks. At a level of 1.00 the market is in balance. Readings above 1 indicate that more volume is moving into declining stocks. A reading below 1 indicates that more volume is moving into advancing stocks. On the technical analysis software program I use, TRIN is in balance at 100 and fluctuates above and below that mark. Some programs use 1 and others 100. No big deal. Just be aware of it.

I have found that this indicator is somewhat reliable when it reaches the extremes. That is, above 1.300 and below .400 I find it to relate a strong tendency in the market. However, at these extremes, it becomes obvious what's happening by looking at what's going on in the market. Therefore, it is fair to say that I don't use this indicator much on daily data.

However, I have used this indicator to forecast intra day S&P futures direction. I use it in the following manner. I decide on the number of intra day bars to use. Then I use moving average envelopes with about a 10% deviation from a simple moving average. When the bars hit the moving average band, it seems to be a reliable indication that the move has gone too far too fast. I have then found that the futures move in the other direction and close in on the simple moving average line. I have used this technique to trade S&P futures at the extremes for a bounce up or down. I also don't look to pick up more than 12 ticks or 60 points.

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McClellan Oscillator

McClellan Oscillator is a market breadth indicator. It is used primarily for short term and intermediate term trading. A small number of stocks making large gains characterizes a weakening bull market. It looks like the overall market is healthy; however, in reality the rising prices may come to an end soon. Conversely, when a bear market is still declining, but a smaller amount of stocks are declining, an end to the bear market may be near.

The calculation for the McClellan Oscillator is as follows:

Subtract a 39 day exponential moving average of advancing issues - declining issues from a 19 day exponential moving average of advancing issues - declining issues. New York Stock Exchange data is used for the calculation.

In a bear market, when the oscillator reaches about -150, it may indicate that the bear market is ending. In a bull market, when the oscillator reaches a reading of about +100, it may indicate that the bull market is ending. Also, when the oscillator goes from below zero to above zero, a bullish signal is indicated. Conversely, when the oscillator goes from above zero to below zero, a bearish signal is indicated.

The McClellan Summation Index is a cumulative total of the McClellan Oscillator. It is used for intermediate term and long term trading. Major tops occur when the index reaches +1600. Major bottoms occur when the index reaches -1300. After moving 3600 points in either direction, and the indicator reaches a level above or below +1900 or -1900, a significant bull or bear market is underway.

A full and extensive discussion of the McClellan Oscillator is available in "Patterns for Profit: The McClellan Oscillator and Summation Index" by Sherman and Marian McClellan.

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Odd Lot Balance Index

The odd lot balance index is a market sentiment indicator. It operates under the assumption that the smallest traders (those people that can't afford to purchase round lots of 100 shares of stock), are wrong about the direction of the market. It is a contrary opinion market sentiment indicator.

The calculation is arrived at by dividing odd lot sales by odd lot purchases. I use a 10 day moving average to smooth the data. Although different technicians use various time frames.

Colby and Meyers found that when they used a 10 period moving average and the index was reading 2.75 or greater, there was a strong bullish tendency. They found a gain (measured against the S&P 500) of 3.03% one month later, 6.01% three months later, 10.55% six months later, and 19.97% twelve months later.

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Williams %R

Williams %R is a momentum indicator. This is also an indicator which is plotted upside down on a scale using negative numbers. For interpretation purposes it is the absolute value which counts so disregard the negative sign. The indicator itself measures overbought and oversold levels. The calculation is as follows:

[(Highest High in n periods minus today's close) divided by (Highest High in n periods minus Lowest Low in n periods)] * (times) -100.

Always wait for a change in the security's price before taking action based on an oversold/overbought indicator like Williams %R. This is because overbought/oversold indicators tend to be leading indicators in that they turn before the security.

Oversold readings tend to occur in the 80 to 100 range and overbought readings tend to occur in the 0 to 20 range.

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Upside Downside Ratio

The upside downside ratio is the volume of advancing New York Stock Exchange issues divided by the volume of declining New York Stock Exchange Issues. This ratio measures buying and selling pressure. A 10 period moving average can be used to smooth the data. However, most technicians will try different lengths of moving averages for smoothing. This indicator works best for short term moves in the market.

Very high readings above 4 are considered bullish signals, and very low readings below .75 are considered bearish signals. Additionally, Martin Zweig of "The Zweig Forecast" has found in additional research that readings greater than 9 to 1 have preceded every bull market and many strong intermediate uptrends.

This indicator doesn't give many signals. However, the one's it does generate seem to be reliable

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Correlation Analysis

Correlation analysis measures the inter-relationship between two variables. The output of this measurement is called the 'correlation coefficient'. A correlation coefficient will ranges between -1.0 and +1.0. A correlation coefficient of +1.0 is a perfect positive correlation. A correlation coefficient of -1.0 is a perfect negative correlation.

The inputs are variables. There may be two or more variables. If there is no relationship between the variables they will have a correlation coefficient of zero.

With correlation analysis there is always one "dependent" variable. There may be one or more 'independent' variables. The dependent variable is always the security's price. The independent variable can be an indicator or one or more securities.

When a technician is using correlation analysis, he is measuring the degree to which a change in the independent variable will result in a change in the dependent variable. A low correlation coefficient (e.g., 0.15) suggests that the relationship between the two variables is weak or non-existent. A high correlation coefficient (e.g., 0.85) indicates that the dependent variable will change when the Independent variable (e.g. an indicator) predicts a change in the dependent variable.

Many technicians will forward shift periods. The independent variable, which might be an indicator, will be shifted forward x period of time. One might shift the independent variable forward 7 days to see if there is in fact any predictive power in the indicator. Any time period can be used.

When one uses this method of technical analysis, it is very important to not only back-test the method, but to also forward-test this method without putting any money on the trades.

Keep in mind that the trader may encounter a very low correlation such as -.85. If this occurs the security's price will move in the opposite direction. It is also a very strong indication and can be used to successfully trade. One will also notice that certain securities tend to lead other securities or will move in opposite directions.

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Detrended Price Oscillator

The Detrended Price Oscillator is a technical indicator that smoothes the trend in prices. When price is detrended using the detrended price oscillator, many technicians believe that cycles and overbought and oversold levels can be more easily identified. The principal is similar to using longer length technical indicators rather than shorter length technical indicators. It removes some of the 'noise'.

To calculate the detrended price oscillator an x-period moving average is centered. This is done by shifting the moving average back [(x/2) + 1] period. This centered moving average is then subtracted from the close. Because it is set up as an oscillator, it will cross above and below zero. The last [(x/2) + 1] period will have no value. This is because the detrended price oscillator is shifted back [(x/2) + 1] period. The detrended price oscillator may recognize underlying cyclical movements in price.

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Source: Equity Analytics, Ltd.