The Average Directional Index (ADX) represent a group of directional movement indicators combining positive trend movement and negative trend movement to form a trading system.
These two indicators are often collectively referred to as the Directional Movement Indicator (DMI).
The positive trend movement, or Plus Directional Indicator (+DI) and negative trend movement, or Minus Directional Indicator (-DI) are derived from smoothed averages of these differences and measure trend direction over time.
The ADX is in turn is derived from the smoothed averages of the difference between +DI and -DI; it measures the strength of the trend (regardless of direction) over time.
Using these three indicators together, chartists can determine both the direction and strength of the trend.
The Average Directional Movement Index Rating quantifies momentum change in the ADX (see above).
It is calculated by adding two values of ADX (the current value and a value n periods back), then dividing by two.
This additional smoothing makes the ADXR slightly less responsive than ADX.
The interpretation is the same as the ADX; the higher the value, the stronger the trend.
The ADXR is a measure of the spread between the Directional Indicators (+DI and -DI). When the ADXR is declining, it's not advised to use a trend following system. However, a rising ADXR signals that the dominant trend is likely to continue. A rising ADXR, with both the ADXR and DI+ above the D- indicates a strengthening bullish market.
Accumulation/distribution is a cumulative indicator that uses volume and price to assess whether a stock is being accumulated or distributed.
The accumulation/distribution measure seeks to identify divergences between the stock price and volume flow. This provides insight into how strong a trend is.
If the price is rising but the indicator is falling this indicates that buying or accumulation volume may not be enough to support the price rise and a price decline could be forthcoming.
The APZ is a volatility-based indicator that appears as a set of bands placed over a price chart.
Especially useful in non-trending, choppy markets, the APZ was created to help traders find potential turning points in the markets.
The APZ is based on a short-term double-smoothed exponential moving average, or EMA, that reacts quickly to price changes with reduced lag. An EMA of another EMA is utilized to create a fast-reacting average.
The APZ calculations form two bands that appear over a price chart.
The upper and lower APZ bands are neither uniform nor symmetrical. In contrast, the bands that are formed by the APZ take into consideration volatility, and change in shape and width (distance from each other) as changes in price activity occur.
In general, the distance between the upper and lower APZ bands will increase with larger price swings and will constrict during periods of decreased price movement.
Therefore, wide bands are indicative of increased volatility, and narrow bands represent periods of decreased volatility.
Average True Range is an indicator developed by Welles Wilder, which measures market volatility.
High Average True Range values may signal market bottoms while low Average True Range values may signal neutral markets.
The Aroon indicator is used to help identify if a stock is trending or not.
Trends are determined by extreme values (above 80) of both lines (Aroon up and Aroon down), whereas unstable prices are determined when both lines are low (less than 20).
The Aroon indicator is used to help identify if a stock is trending or not.
Trends are determined by extreme values (above 80) of both lines (Aroon up and Aroon down), whereas unstable prices are determined when both lines are low (less than 20).
The Balance of Power indicator measures the market strength of buyers against sellers by assessing the ability of each side to drive prices to an extreme level.
The calculation is: Balance of Power = (Close price – Open price) / (High price – Low price) The resulting value can be smoothed by a moving average.
Traders may use this indicator to help:
Bollinger Bands were invented by John Bollinger in the 1980s. Bollinger Bands measure a high and low trading range using a calculation based on standard deviation.
The interpretation of Bollinger Bands varies greatly among traders. The most common method is to buy when the price touches the lower band and to sell when the price touches the higher band.
TheCCIwas developed by Donald Lambert. The purpose of this indicator is to identify cyclical turns in commodities. The indicator is also frequently used with equities and currencies.
This indicator oscillates between an overbought and oversold zone of +100 and -100 respectively.
The Chande Momentum Oscillator (CMO) is an advanced momentum oscillator derived from linear regression.
Increasingly high values ofCMOmay indicate that prices are trending strongly upwards. Conversely, lower values may indicate that prices are trending strongly downwards.CMOis related toMACDand Price Rate of Change (ROC).
The Center Of Gravity oscillator, by John Ehlers, shows a comparison of recent prices versus older prices within a sliding window.
The prices can be thought of as being placed on two ends of a beam that is supported in the center. The oscillator represents the balance point or center of gravity on the beam.
The Center of Gravity oscillator decreases when prices rise and increases when prices fall.
The Chaikin Money Flow oscillator is a momentum indicator that identifies areas of buying and selling in the market by observing price in relation to volume.
This indicator is based upon Chaikin Accumulation/Distribution, which is based upon the premise that if a stock closes above its midpoint [(high+low)/2] for the day then there was accumulation. Conversely, if it closes below its midpoint, then there was distribution.
A value of 80 is generally considered overbought while a value of 20 oversold.
The Chaikin Oscillator is a moving average oscillator based on the Accumulation/Distribution indicator.
The Chaikin Oscillator is an excellent tool for generating buy and sell signals when its action is compared to price movement. I believe it is a significant improvement over the work that preceded it.
The premise behind my oscillator is three-fold. The first premise is that if a stock or market average closes above its midpoint for the day (as defined by [high + low] / 2), then there was accumulation on that day. The closer a stock or average closes to its high, the more accumulation there was. Conversely, if a stock closes below its midpoint for the day, there was distribution on that day. The closer a stock closes to its low, the more distribution there was.
The second premise is that a healthy advance is accompanied by rising volume and a strong volume accumulation. Since volume is the fuel that powers rallies, it follows that lagging volume on rallies is a sign of less fuel available to move stocks higher.
Conversely, declines are usually accompanied by low volume, but end with panic-like liquidation on the part of institutional investors. Thus, we look for a pickup in volume and then lower-lows on reduced volume with some accumulation before a valid bottom can develop.
The third premise is that by using the Chaikin Oscillator, you can monitor the flow of volume into and out of the market. Comparing this flow to price action can help identify tops and bottoms, both short-term and intermediate-term.
The Chaikin Volatility Oscillator is a moving average derivative of the Accumulation/Distribution index.
The Chaikin Volatility Oscillator adjusts with respect to volatility, independent of long-term price action.
The Coppock Curve, developed by Edwin Coppock and published in Barron’s Magazine in 1962, is based on a 14-month and 11-month rate of change, smoothed by a 10-period weighted moving average.
The Coppock Curve generates buy signals when the value falls below zero and turns upwards from a low point.
The Darvas Box strategy was developed by Nicholas Darvas.
Darvas Box is an indicator that simply draws lines along highs and lows, and then adjusts them as new highs and lows form.
The box limit is not set, but is determined by market forces. If the price is moving between $47 and $48, that creates a box. If it moves higher, the next box may be between $50 and $53, which is the next point where the price stalls and moves back and forth.
A price can stay in a box for as long as it wants. As long as it doesn’t drop below the low of the box, it remains a buy candidate particularly if it moves above the upper limit of the box. The basic Darvas Box strategy rules are as follows:
The double exponential moving average (DEMA), shown in Figure 1, was developed by Patrick Mulloy in an attempt to reduce the amount of lag time found in traditional moving averages.
The DEMA is not just a double EMA with twice the lag time of a single EMA, but is a composite implementation of single and double EMAs producing another EMA with less lag than either of the original two.
In other words, the DEMA is not simply two EMAs combined, or a moving average of a moving average, but it is a calculation of both single and double EMAs.
The DEMA can help traders spot reversals sooner because it is faster to respond to changes in market activity.
In addition to using the DEMA as a standalone indicator or in a crossover setup, the DEMA can be used in a variety of indicators in which the logic is based on a moving average. Substituting the DEMA can help traders spot different buying and selling opportunities that are ahead of those provided by the MAs or EMAs traditionally used in these indicators. Of course, getting into a trend sooner rather than later typically leads to higher profits.
Directional Movement helps determine if a security is "trending." It was developed by Welles Wilder and is explained in his book, New Concepts in Technical Trading Systems.
The basic Directional Movement trading system involves comparing the 14-day +DI ("Directional Indicator") and the 14-day -DI. This can be done by plotting the two indicators on top of each other or by subtracting the +DI from the -DI. Wilder suggests buying when the +DI rises above the -DI and selling when the +DI falls below the -DI.
The ADX is in turn is derived from the smoothed averages of the difference between +DI and -DI; it measures the strength of the trend (regardless of direction) over time. The higher theADXline, the more the market is trending and the more suitable it becomes for a trend-following system.
DI+ represents a measure of uptrend strength and DI- represents a measure of downtrend strength. Detailed information about this indicator can be found in Welles Wilder’s book, “New Concepts in Technical Trading Systems”.
A buy signal is given when DI+ crosses over DI-, a sell signal is given when DI- crosses over DI+.
Wilder qualifies these simple trading rules with the "extreme point rule." This rule is designed to prevent whipsaws and reduce the number of trades. The extreme point rule requires that on the day that the +DI and -DI cross, you note the "extreme point." When the +DI rises above the -DI, the extreme price is the high price on the day the lines cross. When the +DI falls below the -DI, the extreme price is the low price on the day the lines cross.
The extreme point is then used as a trigger point at which you should implement the trade. For example, after receiving a buy signal (the +DI rose above the -DI), you should then wait until the security's price rises above the extreme point (the high price on the day that the +DI and -DI lines crossed) before buying. If the price fails to rise above the extreme point, you should continue to hold your short position.
Measures the difference between the closing price of a security and its average closing price over “x” periods.
From an analytical perspective extreme deviation from an average generally sets up a “reversion to the mean” trade.
Traders will often look for price to reverse and move towards the mean from extreme levels.
Donchian Channels are three lines generated by moving average calculations that comprise an indicator formed by upper and lower bands around a mid-range or median band. The upper band marks the highest price of a security over N periods while the lower band marks the lowest price of a security over N periods.
The area between the upper and lower bands represents the Donchian Channel.
Donchian Channels identify comparative relationships between current price and trading ranges over predetermined periods.
Three values build a visual map of price over time, similar to Bollinger Bands, indicating the extent of bullishness and bearishness for the chosen period.
The top line identifies the extent of bullish energy, highlighting the highest price achieved for the period through the bull-bear conflict.
The center line identifies the median or mean reversion price for the period, highlighting the middle ground achieved for the period through the bull-bear conflict.
The bottom line identifies the extent of bearish energy, highlighting the lowest price achieved for the period through the bull-bear conflict.
The Elder Force Index is calculated by the change in price from the previous to the current day, multiplied by volume.
Buy signals are generated when the two-dayEMAof the Elder Force Index is negative and sell signals are generated when it is positive.
Ehler’s Fisher Transform is an oscillator that is based on the principle that security prices do not have a Gaussian probability distribution function.
The Fisher Transform makes the probability distribution function nearly Gaussian, creating turning points that are sharply peaked for easier identification of trend changes.
A trigger line is typically plotted with Ehler’s Fisher Transform. Buy and sell signals occur when the trigger line crosses over or under the indicator.
The Exponential Moving Average is a type of Moving Average that applies more weight to recent values by adding a small percentage of the current value to the previous value.
A Moving Average is most often used to average values for a smoother representation of the underlying price or indicator.
The Ease of Movement oscillator shows a unique relationship between price change and volume.
The Ease of Movement oscillator rises when prices are trending upwards under low volume and falls when prices are trending downwards under low volume.
The Elder Thermometer indicator is described in Dr. Alexander Elder’s book “Come into my trading room” on page 162.
This indicator measures the “temperature” of the market, indicated by greater or lesser intraday ranges.
“Cold” and “Hot” Elder Thermometer zones tend to precede major moves.
The Elder Ray indicator, developed in 1989 by Dr. Elder, measures bullish and bearish “power” by comparing the daily high and low to a moving average
A buy signal occurs when Bear Power is negative but moving upward and Bull Power has recently increased. Conversely, a sell signal occurs when Bull Power is positive but moving downward and Bear Power has recently decreased.
Displays the maximum and minimum price levels over daily, weekly and monthly intervals.
The Chande Forecast Oscillator calculates the deviation between the current bar’s price and an n-bar linear regression forecast value.
The market is said to be trending when the Chande Forecast Oscillator remains either above or below the zero line for an extended time.
The Gopalakrishnan Range Index (GAPO) by Jayanthi Gopalakrishnan quantifies the variability of price data based on the log of the price range over an n-bar period.
GAPOhelps to identify erratic and smooth markets.
The High Minus Low indicator is quite simply a running index of the high price minus the low price.
This indicator can be used to obtain a view of price volatility.
High Low Bands consist of moving averages calculated from the underling price, shifted up and down by a fixed percentage of the median price.
When prices rise above the upper band or fall below the lower band, a change in direction may occur when the price penetrates the band from the opposite direction.
Historical volatility is the log-normal standard deviation. Historical Volatility is based on the book by Don Fishback, “Odds: The Key to 90% Winners”.
Historical volatility outputs an n-period index ranging between 1 and 0. The formula is Stdev(Log(Close / Close Yesterday), 30) * Sqrt(365)
Higher values indicate market volatility while lower values indicate calmness.
The Intraday Momentum Index (IMI) is a technical indicator that combines aspects of candlestick analysis with the relative strength index (RSI).
The intraday momentum index, orIMI, provides investors with potential buying and selling days based off of signals created on individual days.
Is a chart used in technical analysis that shows support and resistance, and momentum and trend directions for a security or investment.
It is designed to provide relevant information at a glance using moving averages (tenkan-sen and kijun-sen) to show bullish and bearish crossover points.
The “clouds” (kumo, in Japanese) are formed between spans of the average of the tenkan-sen and kijun-sen plotted six months ahead (senkou span B), and of the midpoint of the 52-week high and low (senkou span B) plotted six months ahead.
Kaufman's Adaptive Moving Average (KAMA) is an intelligent moving average that was developed by Perry Kaufman.
The powerful trend-following indicator is based on the Exponential Moving Average (EMA) and is responsive to both trend and volatility. It closely follows price when noise is low and smooths out the noise when price fluctuates.
Like all moving averages, the KAMA can be used to visualize the trend.
Price crossing it indicates a directional change. Price can also bounce off the KAMA, which can act as dynamic support and resistance. It is often used in combination with other signals and analysis techniques.
When calculating Kaufman’s Adaptive Moving Average, the following standard settings are used:
To obtain the value of the KAMA, you must first calculate the value of the Efficiency Ratio and the Smoothing Constant.
When traders use Kaufman’s Adaptive Moving Average indicator, they get a clear picture of the market’s behavior, which they can use to make trading decisions. The indicator uses historical data to obtain the final values. Traders make a decision on the basis of the theory that future trends will continue to develop in the same direction as the past trends.
Keltner Channel is a volatility based moving average envelope that shifts a moving average of the True Range indicator by a certain percentage upwards and downwards.
Prices may reverse sharply after exiting and re-entering either the top or bottom band.
Is a technical price pattern where today’s high is greater than yesterday’s high but price closes lower than yesterday’s close.
A key reversal down without a rally before it is unimportant. The ones that really hammer out gains for a number of bars are those that occur off a good divergence and have internals behind them too.
Is a technical price pattern where today’s low is greater than yesterday’s low but price closes higher than yesterday’s close.
A key reversal up without a solid consolidation/selloff before it will likely fail.
The coefficient of determination R2 measures the proportion of variability in the price data. R2 is simply the square of the sample correlation coefficient between the price and the predicted price.
R2 is most often used to guage market volatility. High values indicate that the market is more volatile than normal while lower values indicate that the market is in a steady trend.
In statistics, linear regression is an approach to modeling the relationship between a scalar variable y and one or more explanatory variables denoted X. Linear regression forecast shows how far prices deviate from their predicted targets.
Linear regression forecast can be used as a type of adaptive moving average.
In statistics, linear regression is an approach to modeling the relationship between a scalar variable y and one or more explanatory variables denoted X. The y intercept is the y value of the linear regression line when X equals zero.
Linear regression intercept can be used as a type of adaptive moving average.
In statistics, linear regression is an approach to modeling the relationship between a scalar variable y and one or more explanatory variables denoted X. The slope is b, and a is the intercept (the value of y when x = 0)
Linear regression slope is often used as trend following indicator.
The log transformation is, arguably, the most popular among the different types of transformations used to transform skewed data to approximately conform to normality. If the original data follows a log-normal distribution or approximately so, then the log-transformed data follows a normal or near normal distribution.
Measuring the daily change in log values provides a means by which price action can be measured. Large changes in log values evidence points of high volatility often preceding large movements in price.
TheMACDis a moving average oscillator that shows potential overbought/oversold phases of market fluctuation. The calculation is based on two different moving averages of the price data.
Buy and sell signals are generated wheneverMACDcrosses a signal line, the zero mark line or when theMACDline diverges from price.
Max price is an indicator that plots the maximum value of price over “X” lookback periods. By default this indicator is set to close price, however the user can choose between other inputs.
The Market Facilitation Index, developed by Dr. Bill Williams, shows prices changes as they relate to volume. The formula is (High – Low) / Volume.
When both the Market Facilitation Index and Volume increase at the same time, it can be said that market participants are becoming more interested. Likewise, when both the Market Facilitation Index and Volume decrease, it can be said that market participants are losing interest.
The McGinley Dynamic is a little-known yet highly reliable indicator invented by John R. McGinley, a Certified Market Technician and former editor of the Market Technicians Association's Journal of Technical Analysis.
Working within the context of moving averages throughout the 1990s, McGinley sought to invent a responsive indicator that would automatically adjust itself in relation to the speed of the market. His eponymous Dynamic, first published in the Journal of Technical Analysis in 1997, is a 10-day simple and exponential moving average with a filter that smooths the data to avoid whipsaws.
McGinley believes moving averages should only be used as a smoothing mechanism rather than a trading system or signal generator. It is a monitor of trends. Further, McGinley found moving averages failed to follow prices since large separations frequently exist between prices and moving average lines. He sought to eliminate these problems by inventing an indicator that would hug prices more closely, avoid price separation and whipsaws, and follow prices automatically in fast or slow markets.
Because of the calculation, the Dynamic Line speeds up in down markets as it follows prices yet moves more slowly in up markets. One wants to be quick to sell in a down market, yet ride an up market as long as possible.
The Median Price is simply the running median of the high and low price data.
The Median Price is often used as an alternative for viewing price action.
The Momentum Oscillator calculates the change in price as a ratio over a specified length of time.
Increasingly high values may indicate that prices are trending strongly upwards. Conversely, lower values may indicate that prices are trending strongly downwards.
There is lots of research done on Moon phases. From the respected peer reviewed academic journal The Journal Of Private Equity to many research papers done at colleges and elsewhere.
Example here
Behavior physiologists have also looked into it. The statistics are undeniable. The market gains 2-3x more during new moons and waxing moons than full to waning moons.
More recently there was a study done by the Royal Bank of Scotland that said if you’d bought the S&P index on a new moon and sold on a full moon from 1928 to 2010 £1,000 would have turned into £1,502,689, compared to £63,846 by just using a buy and hold strategy.
There are some in the industry that believe moon cycles call turning points within a day or two quite nicely. Some of these are intermediate turning points, while others are actual tops and bottoms.
Although it’s not perfect it is suggested that it works about 60-70% of the time. Although you couldn’t trade this strategy by itself, in conjunction with other tools such as cycle analysis, technical analysis and seasonal analysis it can be quite powerful.
Breakfree Trading | Pro 4.0 BETA
Breakfree Trading Discovery description.
This indicator counts the number of bars where today’s low is lower than the prior days low over the last “x” periods.
This indicator counts the number of bars where today’s high is higher than the prior days high over the last “x” periods.
The Negative Volume Index (NVI) is a cumulative indicator, developed by Paul Dysart in the 1930s, that uses the change in volume to decide when the smart money is active. The NVI assumes that smart money will produce moves in price that require less volume than the rest of the investment crowd.
NVI rises on days of positive price change on lower volume, NVI falls on days of negative price change on lower volume, and NVI is unchanged on days of higher volume no matter what the price action.
As with all indicators, NVI should not be used on its own. Instead, chartists should use it in conjunction with other analysis techniques.
The On Balance Volume indicator is calculated based on a cumulative total of volume to show a relationship between price and volume.
On Balance Volume is generally higher when prices are moving with the dominant trend and for this reason, the technical indicator is most often used to confirm a trend.
The Polarised Fractal Efficieny indicator determines price efficiency over a user-defined time period. This indicator fluctuates between -100 and +100 with 0 as the center line.
Securities with a PFE greater than zero are deemed to be trending up, while a reading of less than zero indicates the trend is down. Polarized Fractal Efficiency's signature characteristic is its use of fractal geometry in determining how efficiently a security's price is moving.
The strength of the trend is measured by the position of the Polarized Fractal Efficiency (PFE) relative to the zero line. As a general rule, the further the PFE value is away from zero, the stronger and more efficient the given trend is. A PFE value that fluctuates around the zero line could indicate that the supply and demand for the security are in balance and price may trade sideways.
Generally, strategies using PFE as a signal consider a buy sign as a reversal in the direction of the indicator and its movement from its minimum value to zero. A signal to close a position arises as the value of the indicator reaches its peak above zero. An indicator shift from peak to zero presents a sell signal. As a rule of thumb, all short positions should be covered after a new minimum is formed for the indicator.
The Pretty Good Oscillator measures the distance of the current close from its N-day simple moving average, expressed in terms of an average true range over a similar period.
This indicator finds the nearest prime number from either the top or bottom of the series, and plots the difference between that prime number and the price data.
This indicator can be used to spot market turning points. When the oscillator remains at the same high point for two consecutive periods in the positive range, consider selling. Conversely, when the oscillator remains at a low point for two consecutive periods in the negative range, consider buying.
The percentage price oscillator (PPO) is a technical momentum indicator that shows the relationship between two moving averages in percentage terms.
The moving averages are a 26-period and 12-period exponential moving average(EMA).
The Positive Volume Index measures the price trend for periods where volume increases from the previous volume.
Positive Volume Index is based on the theory that uninformed investors buy when volume increases while informed investors buy when volume decreases.
Price Volume Trend (sometimes referred to as Volume Price Trend) is a technical indicator that compares price to volume. Price Volume Trend is closely related to the On Balance Volume index.
The Price Volume Trend generally precedes price movement. The theory is that well-informed investors are buying when the index rises and uninformed investors are buying when the index falls.
The Performance index tracks the cumulative percentage change of a security over time.
The indicator will calculate using closing price by default however the user can select different price inputs with which to measure performance.
The Price Oscillator displays a spread between two moving averages.
Buying usually occurs when the oscillator rises and selling usually occurs when the oscillator falls.
Range Action Verification Index (RAVI) indicator, developed by Tushar Chande in the late 1990s, attempts to identify trend strength.
Tushar Chande in his original implementation uses two simple moving averages for the calculation and takes the absolute value of the result ensuring all values are positive.
Doing this, the larger the value ofRAVI, the stronger the trend is said to be, however, the trend direction is lost.
The Range indicator compares the intraday range (high - low) to the inter-day (close - previous close) range. When the inter-day range is less than the intraday range, the Range Indicator will be a high value.
This signals an end to the current trend.
When the Range Indicator is at a low level, a new trend is about to start.
Price Rate of Change is calculated by dividing the security’s price over the last n-periods by the total price within the last n-periods window.
If the price from the current day is lower than n-periods ago, PriceROCtrends lower. The actual formula is ((Close – Close n-periods ago ) / Close n-periods ago) * 100
The Price Rate of Change shows whether or not the security is trending up or down.
The Relative Strength Index (RSI) is a technical indicator developed by J. Welles Wilder, which measures the velocity and magnitude of price movements within a security. RSIis computed as the ratio of higher closes to lower closes within an n-period sliding window.
The indicator is most often used with a 14-period setting. Values greater than 70 may indicate that the market is overbought, while values less than 30 may indicate that the market is oversold.
Relative Spread Strength (RSS) is an indicator that identifies price cycle highs and lows by computing Welles Wilder's relative strength index (RSI) using, as an input, the difference (spread) between two moving averages of prices.
Divergence between price extremes and RSS extremes is intended to identify trading opportunities.
The Simple Moving Average is simply an average of values over a specified period of time.
A Moving Average is most often used to average values for a smoother representation of the underlying price or indicator.
The SUM function simply sums a value over “x” periods, i.e. closing price over the last two periods.
This function has practical application when applied to other indicators.
Standard deviation is a measure of variability used in statistics and probability theory. Standard
Deviation is used in finance to show how much volatility exists in the underlying data. Low values indicate that the security’s price is very close to the mean, whereas high values indicate that the price is more volatile than normal.
Major highs and lows often accompany extreme volatility. High values of standard deviations indicate that the price or indicator is more volatile than normal.
Developed by Tushar Chande and Stanley Kroll, StochRSI is an oscillator that measures the level of RSIrelative to its high-low range over a set time period. StochRSI applies the Stochastics formula to RSIvalues, instead of price values. This makes it an indicator of an indicator. The result is an oscillator that fluctuates between 0 and 1.
It is important to remember that StochRSI is an indicator of an indicator, which makes it the second derivative of price.
This means it is two steps (formulas) removed from the price of the underlying security. Price has undergone two changes to become StochRSI.
Converting prices toRSIis one change.
ConvertingRSIto the Stochastic Oscillator is the second change. This is why the end product (StochRSI) looks much different than the original (price).
The Stochastic Oscillator is a popular indicator that shows where a security’s price has closed in proportion to its closing price range over a specified period of time. The Stochastic Oscillator has two components: %K and %D. %K is most often displayed as a solid line and %D is often shown as a dotted line. A smoothing filter is applied to both %K and %D indicators to help better understand underlying momentum trends.
The most widely used method for interpreting the Stochastic Oscillator is to buy when either component rises above 80 or sell when either component falls below 20.
Another way to interpret the Stochastic Oscillator is to buy when %K rises above %D, and conversely, sell when %K falls below %D.
The Swing Index calculates the strength of a security by comparing the open, high, low and close prices with previous values.
The Swing Index is a component of the Accumulation Swing Index, which provides an alternative view of price action.
Triple Exponential Moving Average (also known as TEMA) was developed by Patrick Mulloy and was first published in 1994. Main purpose in developing of this indicator was reducing the lag between the indicator and price action by making it fast-acting and more sensitive to market changes. In similar to other moving averages way, the TEMA indicator is used to identify trends and generate trading signals.
The Triple Exponential Moving Average is used in the same way as other moving averages are. It is trend-following indicator, however with smaller lag when compared to the EMA and SMA and some trader may prefer using it because of that.
Main principles of trading this indicator could be summarized in two points:
Main principles of trading this indicator could be summarized in two points:
The Triangular Moving Average is similar to the Simple Moving Average in that it averages the underlying data over a specified number of previous values.
However, the Triangular Moving Average differs in that it is calculated and averaged n-times. The actual formula isTMA= (SMA1 + SMA2 + SMA3 + SMA4 + …SMAn) / n.
The Triangular Moving Average can be used like any other Moving Average, to obtain a smoother representation of the underlying data. It is important to note that the Triangular Moving Average is typically much smoother than other moving averages.
Based on the popular Chaikin Money Flow indicator, which is in turn derived from the Accumulation Distribution line.
Twiggs Money Flow warns of breakouts and provides useful trend confirmation. It is based on the observation that buying support is normally signaled by increased volume and frequent closes in the top half of the daily range.
Likewise, selling pressure is evidenced by increased volume and frequent closes in the lower half of the daily range.
Twiggs Money Flow also warns of breakouts and provides useful trend confirmation. It is based on the observation that buying support is normally signaled by:
Likewise, selling pressure is evidenced by:
TRIXis a momentum oscillator that shows the rate of change of an exponentially averaged closing price.
The most common interpretation of theTRIXoscillator is to buy when the oscillator rises and sell when the oscillator falls.
In statistics, linear regression is an approach to modeling the relationship between a scalar variable y and one or more explanatory variables denoted X. Linear regression forecast shows how far prices deviate from their predicted targets.
Time Series Forecast can be used as a type of adaptive moving average.
The true strength index is a technical momentum oscillator. The indicator may be useful for determining overbought and oversold conditions, indicating potential trend direction changes via centerline or signal line crossovers, and warning of trend weakness through divergence.
Overbought and oversold levels will vary by the asset being traded.
Trade Volume Index shows whether a security is being accumulated or distributed over period of time.
When the indicator is rising, the security is said to be accumulating. Conversely, when the indicator is falling, the security is said to being distributing. Prices may reverse when the indicator converges with price.
Is an important indicator that allows users to see trends in multi-timeframes. Users are encouraged to create multiple instances of this indicator, aligning period selection with what each user defines as short term, medium term and long term periods.
For example a day trader might set up these indicators using 5 minute, 15 minute and 1 hour timeframe, whilst swing traders and investors would set up using longer timeframes.
In our day trading example users would look to define trends using the 15 minute and one hour trend periods and enter trades in the direction of the trend when the 5 minute trend timeframe aligns.
Typical Price (also known as Pivot Points) is a running average of the high, low and close values.
Typical Price is often used as an alternative for viewing price action.
Ultimate Oscillator was developed by Larry Williams. The indicator is based buying and selling “pressure” represented by when a bar’s closing price falls within the bar’s true range.
The most popular interpretation of the Ultimate Oscillator is based on price and indicator divergence.
The Volatility Index Dynamic Average (VIDYA) indicator is a type of Moving Average derived from the coefficient of determination.
VIDYAcan be used like any other Moving Average, to obtain a smoother representation of the underlying data. BecauseVIDYAis a derivative of linear regression, it quickly adapts to volatility.
The Variable Moving Average is similar to an Exponential Moving Average with the added benefit of being able to adjust to market volatility. For this reason, the Variable Moving Average may be useful in sideways moving markets.
The Variable Moving Average can be used like any other Moving Average, to obtain a smoother representation of the underlying data.
Is the average of volume over “x” lookback periods.
Volume is the number of shares or contracts traded in a security or an entire market during a given period of time.
It is simply the amount of shares that trade hands from sellers to buyers as a measure of activity. If a buyer of a stock purchases 100 shares from a seller, then the volume for that period increases by 100 shares based on that transaction.
Volume Rate of Change is calculated by dividing the security’s volume over the last n-periods by the total volume within the last n-periods window.
If the volume from the current day is lower than n-periods ago, volumeROCtrends lower. The actual formula is ((Volume – Volume n-periods ago ) / Volume n-periods ago) * 100
The Volume Rate of Change shows whether or not volume is trending up or down. This indicator is often used to confirm price breakouts.
The volume weighted average price (VWAP) is a trading benchmark used by traders that gives the average price a security has traded at throughout the day, based on both volume and price. It is important because it provides traders with insight into both the trend and value of a security.
Investors may use VWAP to assess the price they paid for a security throughout the day. At the end of the day, if the price they bought at is higher than the VWAP, then they may have overpaid. If it is less than VWAP, then they purchased shares at a good price for that day.
The Volume Oscillator shows a spread of two different moving averages of volume over a specified period of time.
The Volume Oscillator offers a clear view of whether or not volume is increasing or decreasing.
Volume is the number of shares or contracts traded in a security or an entire market during a given period of time.
If the closing price for the day is greater than the open, volume is considered up for the day. If the closing price for the day is lower than the open volume is considered down for the day.
The Weighted Moving Average is a type of Moving Average that assigns more weight to the most recent data points. The weighted moving average calculation is “(Price * weighting factor) + (Price previous period * weighting factor-1)”...
The Weighted Moving Average can be used like any other Moving Average, to obtain a smoother representation of the underlying data.
It is thought that the Weighted Moving Average provides a better representation of market volatility than the Simple and Exponential Moving Averages.
Weighted Close (also known as Weighted Pivot Points) is a running average of the high, low and close values.
This indicator is similar to standard Pivot Points, except more weight is given to the most recent values in the underlying data.
Weighted Close is often used as an alternative for viewing price action.
Williams %R shows overbought and oversold levels by calculating the current closing price in relation to the high and low prices over the past n-periods.
The most widely used method for interpreting Williams %R is to buy when the indicator rises above 80 or sell when the indicator falls below 20.
The ZLEMA indicator or zero lag exponential moving average is a technical analysis indicator originally created by Ric Way and John Ehlers.
The goal of the indicator is to try to eliminate the inherent lag of all trend following indicators which average prices over time such as the simple or exponential moving averages.
Instead of applying the exponential moving average on the regular data (usually the close price), the indicator applies it to a de-lagged data, which is the original data removed from the "lag" days.
Usually, a stock is considered bullish when the zero lag EMA is above the original EMA and bearish when the zero lag EMA is below the original EMA.