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- Spreads
Spreads illustrate the difference between the price of two securities. They are usually used for comparing futures.
A spread involves buying one security and selling a second with the goal of making a profit from the narrowing or expanding of the difference between the two securities.
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- Standard Deviation
Standard Deviation is a statistical measurement of volatility. It measures how widely values range from the average value. The larger the difference between the closing prices and the average closing price, the higher the standard deviation will be and the higher the volatility. The closer the closing prices are to the average price, the lower the standard deviation and the lower the volatility.
High volatility levels can be used to time trend reversals such as market tops and bottoms. Low volatility levels can sometimes be used to time the beginning of new upward price trends following periods of consolidation.
Standard Deviation is calculated by taking the square root of the variance, the average of the squared deviations from the mean.
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- Standard Deviation Channel
The Standard Deviation Channel is two lines plotted parallel to the Linear Regression Trendline. These lines are distanced by n number of standard deviations above and below the LRT.
Over time, prices generally move from one extreme to another. As market participants become overly optimistic, prices are driven up at an unsustainable rate. Likewise, when market participants are overly pessimistic, prices move down at an unsustainable rate.
Given this, markets tend to have an equilibrium pricing point. While the Linear Regression Trendline can help determine where such a point lies, it is the Standard Deviation Channel that is helpful in determining where the extremes fall.
Statistical analysis dictates that 67% of the points on a graph will fall in between one standard deviation above and below the LRT. Increase to two the number of standard deviations and 95% of all the data will fall between these two lines.
If the price happens to go above or below either one of these lines, it should move back into the channel, unless a major trend reversal is taking place.
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- Standard Error
Standard Error measurement is based upon how closely the price of a security falls from the Linear Regression Trendline. The closer prices are to the LRT, the stronger the trend. The more variance from the regression line, the larger the standard error and the less reliable the trend.
High Standard Error values indicate that the price is quite volatile. Any changes in the prevailing trend is usually preceded by a rapidly increasing standard error.
This indicator can be used in combination with R-Squared. Most trend changes are usually preceded by decreasing R-Squared values and increasing Standard Error. When the two are at extreme values and begin to converge, expect a change.
However, be aware that changes in trend does not necessarily mean that an upward trend will reverse to a downward trend. Sideways movement is also considered a change.
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- Standard Error Bands
Created by Jon Anderson, Standard Error Bands are two moving averages based on standard error levels above and below the Linear Regression Indicator. As a type of envelope, they are similar in appearance to Bollinger Bands but are calculated and interpreted quite differently. While Bollinger Bands are plotted at standard deviation levels above and below a moving average, Standard Error Bands are plotted at standard error levels above and below the linear regression plot.
Because the spacing between Standard Error Bands is based on the Standard Error of the security, when the two bands are close together, it signifies a strong trend. When the two bands are far apart, prices are more volatile and will tend to fluctuate between the two bands. If the bands are close and then begin to widen, it may signify that the trend is weakening and may possibly be due for a reversal.
The R-Squared indicator works well in combination with Standard Error Bands. Use a high R2 combined with tight bands to confirm a strong trend. A low R2 combined with wide bands confirms that prices are consolidating.
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- Standard Error Channel
Standard Error Channels are calculated by plotting parallel lines above and below the Linear Regression Trendline. The lines are plotted a specified number of standard errors away from the linear regression trendline.
Price movements are characterized by swings from one extreme to the other as the market reflects the collective mood of trader. As the market becomes overly optimistic, prices are driven up. When the mood of the market becomes overly pessimistic, prices are driven down.
Every issue tends to have an equilibrium point towards which prices seem to be drawn to. While Linear Regression analysis can be helpful in determining where this point will fall, Standard Error Channel analysis can show if prices are cycling higher or lower than equilibrium and if a change in trend may be about to occur.
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- STARC Bands
STARC Bands were developed by Manning Stoller and consist of a channel surrounding a Simple Moving Average. The width of the channel created will vary with the period of the average range and thus gives rise to the indicator's name (Stoller Average Range Channel).
Like Bollinger bands, STARC Bands will tighten in steady or low volatility markets and widen as volatility increases. The difference lies in that rather than being based on closes, STARC Bands are based on the Average True Range. This gives a more in depth picture of the market volatility. While the penetration of a Bollinger Band may indicate a continuation of a price move, STARC Bands define the upper and lower limits for normal price action.
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- STIX
From The Polymetric Report, STIX is a short-term trading oscillator used to determine the momentum of the market by comparing the volume flowing into advancing and declining stocks.
The STIX indicator is calculated using a variation of the Advance/Decline Ratio and provides a relative percentage of advancing stocks. To calculate first derive the A/D Ratio:
| A/D Ratio |
= |
( |
Advancing Issues
Advancing Issues-Declining Issues |
) |
*100 |
STIX is then a 21-period (9%) exponential moving average of the above A/D Ratio:
STIX = (A/D Ratio * 0.09) + (yesterday's STIX * 0.91)
The STIX will typically oscillate around 50. Values over 50 are generated when there have been more stocks advancing than declining. Values less than 50 are generated when more stocks have been decreasing in price. A general rule for using the STIX as an overbought/oversold indicator:
- >58: Extremely Overbought
- >56: Fairly Overbought
- <45: Fairly Oversold
- <42: Extremely Oversold
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- Stochastic Momentum Index
The Stochastic Momentum Index was developed by William Blau as introduced in the in the January 1993 issue of Technical Analysis of Stocks & Commodities. While similar to the Stochastic Oscillator, the SMI displays where the close is relative to the midpoint of the recent high/low range, as compared to the close relative to the recent high/low with the Stochastic Oscillator. This results is an oscillator that ranges between -100 and +100 and can be a bit less erratic than an equal period Stochastic Oscillator.
The oscillator is comprised of two lines, the SMI (blue) and the moving average of the SMI (red). When the close is greater than the midpoint of the range, the SMI will be positive. When the close is less than the midpoint of the range, it will be negative. The interpretation of the SMI is virtually identical to that of the Stochastic Oscillator. The most basic pattern to trade from is to buy when the SMI falls below -40 and then returns above it. Sell when the SMI rises above +40 and then falls back below that level. Another trading signal is buy when the SMI rises above the moving average, and sell when the SMI falls below the moving average.
As always, before basing any trades on strict overbought / oversold levels it is recommended that one first qualify the trendiness of the market using an indicator such as R-Squared. If indicators suggest a non-trending market, then trades based on strict overbought/oversold levels should produce the best results.
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- Stochastic Oscillator
The Stochastic Oscillator compares the closing price of a security to its price range over a given time period. Its displayed by two lines, a main line called %K (drawn in solid blue) and a secondary line (in dotted green) called %D. The %D line is the moving average of the %K.
The Stochastic Oscillator contains four variables:
- %K Periods: This is the number of time periods used in the stochastic calculation.
- %K Slowing Periods: This value controls the internal smoothing of %K. A value of 1 is considered a fast stochastic while a value of 3 is considered a slow stochastic.
- %D Periods: This is the number of time periods used when calculating the moving average of %K.
- %D Method: The method (Exponential, Simple, Time Series, Triangular, Variable, or Weighted) used to calculate %D
When trading using the Stochastic Oscillator, one method is to buy when either %K or %D falls below 20 and then rises back above that level. Similarlily, sell when the either line rises above 80 and then falls back below. Another pattern to look for when timing trades is buy when the %K line rises above the %D line or sell when the %K line falls below the %D line. Lastly, one should always be on the lookout for diveregnces. For example, if prices are making a series of new highs and the Stochastic Oscillator fails to surpass its previous highs, the indicator typically will provide the clue as to where prices will soon head.
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- Stochastic RSI
The Stochastic RSI, as the name implies, is an Indicator of an Indicator. While the Stochastic Oscillator monitors relationships between closing prices and the range, the Stochastic RSI monitors the RSI values and their relationship over time.
The Stochastic RSI oscillator is calculated:
| [ |
(Today's RSI - Lowest RSI in %K periods)
(Highest RSI in %K periods - Lowest RSI in %K periods) | ] |
*100 |
As with the Stochastic Oscillator, the Stochastic RSI is usually accompanied by a second line %D which is an EMA of the Stochastic values. From this point the crossover events can be used to provide entry triggers as well as confirmation to other indicators.
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- Stochastic, Fast
The Stochastic Oscillator was popularized by George Lane (president of Investment Educators, Inc., Watseka, IL). It is based on the observation that as prices increase, closing prices tend to be closer to the upper end of the price range. In downtrends the closing price tends to be near the lower end of the range.
The Stochastic Oscillator is made up of two lines that oscillate between a vertical scale of 0 to 100. The %K is the main line and it is drawn as a solid line. The second is the %D line and is a moving average of %K. The %D line is drawn as a dotted line.
The Fast Stochastic is the average of the last three %K and a Slow Stochastic is a three day average of the Fast Stochastic. Use as a buy/sell signal generator, buying when fast moves above slow and selling when fast moves below slow. Most traders use the Slow Stochastics because of its more reliable signals.
Three ways to interpret the Stochastic Oscillator:
Buy when the Oscillator (either %K or %D) falls below 20 and then rises back above that level. Sell when the Oscillator rises above 80 and then falls below that level.
Buy when the %K line rises above the %D line and sell when the %K line falls below the %D line.
Look for divergences - prices making a series of new highs as the Stochastic Oscillator is failing to surpass its previous highs.
Information provided by John Murphy, author of Technical Analysis of the Financial Markets and The Visual Investor.
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- Stochastic, Full
The Full Stochastic is a generalization of the Fast Stochastic and the Slow Stochastic and uses three parameters:
As in the Fast and Slow Stochastics, the first parameter is the number of periods used to create the initial %K line and %D is again the number of periods used to create the signal line.
What makes the Full Stochastic unique is its use of a "smoothing factor" for the initial %K line. The %K (full) line plotted is a n-period SMA of the initial %K line (where n is equal to the middle parameter).
The Full Stochastic Oscillator is more advanced and more flexible than the Fast and Slow Stochastic and can even be used to generate them. For example, a (14, 1, 3) Full Stochastic is equivalent to a (14, 3) Fast Stochastic while a (12, 3, 2) Full Stochastic is identical to a (12, 2) Slow Stochastic.
Look for readings below 20 as an oversold signal while readings above 80 act as an overbought signal. However, securities can continue to rise after the Stochastic Oscillator has reached 80 and can continue to fall after it has reached 20. It may be better to wait for the oscillator to move from overbought territory back below 80 or from oversold territory to back above 20 before trading.
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- Stochastic, Slow
The Slow Stochastic charts the daily stochastic as well as a five-day moving average of a 12-day interval. This smoothing of the Stochastic Oscillator is an attempt to reduce volatility and improve signal accuracy.
As with the other stochastic indicators, the signals to look for are oversold securities with values are less than 20 and overbought when greater than 80.
Stochastics work best in broad trading ranges, or in a mild trend with a slight upward or downward bias. The worst market for normal use of stochastics is a persistent trending market that has only minor corrections. It is possible to trade stochastics in a trend by ignoring the usual overbought and oversold levels and entering the market when the end of a reaction against the trend is signaled by a stochastic crossover from any level.
Information provided by Charles LeBeau's Technical Traders Guide to Computer Analysis of the Futures Market.
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- Stochastics, Double Smoothed
Developed by William Blau, Double Smoothed Stochastics is a variation on Slow Stochastics that Prophet has implemented upon a user request.
Use this as an indicator to discover if a security is overbought or oversold.
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- Swing Index
The Swing Index compares the relationships between the current prices (open, high, low, and close) and the previous period's prices to isolate the "real" price of a security. The Swing Index is primarily used as a component of the Accumulation Swing Index as by itself it generates an erratic plot.
The basic formula for the Swing Index is:
| = 50 * |
[ |
Cy - C + 0.5(Cy - Oy) + 0.25(C - O)
R |
* |
] |
K
T |
Where:
| C = |
Today's closing price |
| L = |
Today's lowest price |
| O = |
Today's opening price |
| Cy = |
Yesterday's closing price |
| Ly = |
Yesterday's lowest price |
| Oy = |
Yesterday's opening price |
| Hy = |
Yesterday's highest price |
| K = |
The larger of either (Hy - C) or (Ly - C) |
| R = |
A variable based on the relationship between today's closing price and yesterday's high and low |
| T = |
The limit move value |
Step-by-step instructions on calculating the Swing Index can be found in Wilder's book, New Concepts In Technical Trading Systems.
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real-time data |
delayed data |
end-of-day data
