Moving Average
A Moving Average is a moving mean of data. In other words, Moving Averages perform a mathematical function where data within a selected period is averaged and the average ‘moves’ as new data is included in the calculation while older data is removed or lessened. Moving Averages essentially smooth data by removing ‘noise’. This smoothing of data makes Moving Averages popular tools in identifying price trends and trend reversals.

Simple Moving Average
Simple Moving Averages are the most common and popular form of moving average. The primary reason for this is the relative ease with which Simple Moving Averages are calculated. A Simple Moving Average is calculated by adding values over a set number of periods and then dividing the sum by the total number of values. As with other types of moving averages, Simple Moving Averages smooth the data by removing ‘noise’ over the selected period. The ability to smooth data makes them a useful tool in identifying price trends and trend reversals.

Exponential Moving Average
The Exponential Moving Average is similar to the Weighted Moving Average in that they both assign greater weight to the most recent data. Where they differ is that instead of dropping off the oldest data point in the selected period of the moving average, the Exponential Moving Average continues to maintain all the data. In other words, a 5 day Exponential Moving Average will contain more than 5 pieces of data information. Each observation becomes progressively less significant but still includes in its calculation all the price data in the life of the instrument.

The Exponential Moving Average is another method of weighting a moving average.

Weighted Moving Average
As with Simple Moving Averages, Weighted Moving Averages smooth the data by removing ‘noise’ over the selected period. However a Weighted Moving Average will be more sensitive to recent changes in data. This is because a Simple Moving Average gives all observations equal emphasis in its calculation, but a Weighted Moving Average assigns a greater weight to the most recent observations.

In this example you can see the three types of Moving Average, simple, weighted and exponential. For this analysis each moving average is using 14 as the averaging period.

In this example a Moving Average is being used to generate buy and sell signals. A close above the Moving Average is a buy signal and a close below the Moving Average is a sell signal. Note that this technique would have been most profitable in the second half of the analysis when the market was trending down.

In this example the 100period Moving Average is used to identify the trend and the 15period and 30period Moving Averages are used to give crossover buy and sell signals in the direction of the trend.

The 100 days Moving Average is sloping up and below prices indicating an up trend, for this reason only long positions are taken. For example when the 15 period Moving Average crosses above the 30 period Moving Average you would take a long position in the market, when the 15period Moving Average crosses below 30period Moving Average you would exit the long position but not enter a short position.

Open interest
Open Interest is the number of outstanding futures contracts that have not been offset by an opposite transaction.

In this example the volume and open interest are increasing in the first half of the analysis while the prices are decreasing, in the second half of the analysis the prices are increasing while the volume and open interest are decreasing. From this you could expect the market to turn and continue moving down as the up-move is losing momentum.

Parabolic Time Price
Developed by J. Welles Wilder and introduced in his book New Concepts in Technical Trading Systems, Parabolic Time Price is a system that always has a position in the market, either long or short. You would close out the current position and enter a reverse position when the price crosses the current Stop And Reverse (SAR) point. The SAR points resemble a parabolic curve as they begin to tighten and close in on prices once prices begin to trend, this explains the name - Parabolic Time Price.

Parabolic Time Price is usually charted with a bar analysis so that the stop and reverse points are easily identified. If you are long, the SAR points will be below the prices and the signal to go short will be when prices cross the current SAR point from above. If you are short, the SAR points will be above the prices and the signal to go long will be when prices cross the current SAR point from below.

When a new position is entered the SAR points will be positioned far enough away from the prices to permit some contra-trend price movement. As the market begins to trend the SAR points will move with prices and progressively tighten as the trend continues. This is accomplished by the use of an acceleration factor that increases up to a given limit each time a new extreme in the direction of the trend is reached.

In this analysis you can see the Parabolic Time Price SAR points plotted above and below the prices. The first buy and sell signals are marked on the chart. You can see that Parabolic Time Price would have been most effective when the market was in a trending phase, either to generate buy signals in the direction of the trend or to identify levels at which to place a trailing stop if you had a long position in the market.

Relative Strength Index (RSI)
Developed by J. Welles Wilder and introduced in his book New Concepts in Technical Trading Systems.

RSI calculates the difference in values between the closes over the Observation Period. These values are averaged, with an up-average, being calculated for periods with higher closes and a down-average being calculated for periods with lower closes. The up average is divided by the down average to create the Relative Strength. Finally, the Relative Strength is put into the Relative Strength Index formula to produce an oscillator that fluctuates between 0 and 100.

By calculating the RSI in this way Wilder was able to overcome two problems he had encountered with other momentum oscillators. Firstly, the RSI should avoid some of the erratic movements common to other momentum oscillators by smoothing the points used to calculate the oscillator. Secondly, the Y Axis scale for all instruments should be the same, 0 to 100. This would enable comparison between instruments and for objective levels to be used for overbought and oversold readings.

In this example the overbought and oversold zones are marked, above 70 and below 30 respectively, as well as examples of failure swings and bullish and bearish divergence.

Stochastic
Stochastic are an oscillator developed by George Lane and are based on the following observation:

As prices increase - closing prices tend to be closer to the upper end of the price range

As prices decrease - closing prices tend to be closer to the lower end of the price range

There are two types of Stochastic:
Slow Stochastic
Fast Stochastic

Each Stochastic uses two lines, %K and %D. The difference between Fast and Slow Stochastic is in the calculation of the %K and %D lines. Slow Stochastic is a slower and smoother form of Fast Stochastic.

Slow Stochastic
Slow Stochastic are based on Fast Stochastic but provides a slower and smoother response to price movements. It consists of two lines, %K and %D. The %K line in Slow Stochastic is the same as the %D line in Fast Stochastic and the %D line in Slow Stochastic is a Simple Moving Average of %K Slow Stochastic. This line is smoother than the %K and provides the signals for an overbought/oversold market.

Fast Stochastic
Fast Stochastic consists of two lines, %K and %D:
The %K line measures as a percentage where the current close is in relation to the lowest low over the observation period. This is shown on a scale of 0 to 100, where 0 is the observation period low and 100 is the observation period high. The %D line is a Simple Moving Average of the %K. This line is smoother than the %K and provides the signals for an overbought / oversold market.

In this chart both Fast and Slow Stochastic are charted, you can see that Slow Stochastic are smoother and slower to respond to price changes than Fast Stochastic.

In this chart the overbought and oversold areas are indicated, above 80 and below 20 respectively, also indicated are examples of Stochastic buy and sell signals where %K and %D have moved into the overbought or oversold zones, crossed and then moved out of the overbought or oversold zones.

This chart has examples of bullish and bearish divergence.

Volume
Volume is the total number of shares or futures contracts traded during the given period. Volume activity is normally viewed in relation to price activity and price range, where volume is used to confirm price trends and to warn of any weakening or change in the trend

This analysis displays volume and a moving average of the volume. The moving average of volume allows you to see if volume is high or low relative to the moving average. Point A on the analysis marks an attempt by the market to move to new highs on low volume (volume was below the moving average). You can see that the market failed to hold these new highs and in fact reversed to make new lows.At point B the market broke to new highs on increasing volume suggesting that this was a valid move and that the market would hold these new levels.At point C there was a high volume day with a strong close. This indicated that the market was going to make new highs.

Moving Average Convergence Divergence (MACD)

Moving Average Convergence Divergence or MACD as it is more commonly known, was developed by Gerald Appel to trade 26 and 12week cycles in the stock market. MACD is a type of oscillator that can measure market momentum as well as follow or indicate the trend.

MACD consists of two lines, the MACD Line and the Signal Line. The MACD Line measures the difference between a short Exponential Moving Average and a long Exponential Moving Average. The Signal Line is an Exponential Moving Average of the MACD Line. MACD oscillates above and below a zero line without upper and lower boundaries.

Buy and sell signals are generated using MACD when the MACD Line and Signal Lines cross, this occurred a number of times on this chart, however the most effective buy and sell signals will be after a divergence signal. This chart has examples of both, bullish and bearish divergences as well as the ensuing buy and sell signals.

Alpha-Beta Trend analysis
Alpha-Beta Trend analysis was developed by Anthony W Warren Ph.D. in 1984, and is an attempt to avoid some of the false signals associated with crossing moving averages. Three lines are plotted:

Upper trend channel line

Lower trend channel line

Trading filter

Together, the upper and lower lines define the uncertainty channel for trade decisions; the width of the channel varies with volatility.

In this example, the buy signal is given when the trading filter crosses to below the lower band. For the duration of the up-trend the trading filter is below the lower band. The signal to exit the long position is when the trading filter moves back within the bands.

Momentum
Momentum is an oscillator that measures the rate at which prices are changing over the Observation Period. It measures whether prices are rising or falling at an increasing or decreasing rate. The Momentum calculation subtracts the current price from the price a set number of periods ago. This positive or negative difference is plotted about a zero line.

In this example the Momentum line indicates that the market is overbought, this is followed by a bearish divergence signal, which indicates a weakening up trend. The confirmation that the trend has reversed is the break of the trend line.

The last signal from the Momentum line is that the market is oversold, this situation is corrected when the market rallies and the Momentum line moves back to zero.