- ADX (Directional Movement System)
- Accumulative Swing Index
- Aroon
- Aroon Oscillator
- Chaikin Money Flow
- Chaikin Volatility
- Chande Momentum Oscillator
- Commodity Channel Index
- Comparative Relative Strength
- Detrended Price Oscillator
- Ease Of Movement
- Fractal Chaos Oscillator
- High Minus Low
- Historical Volatility
- Linear Regression RSquared
- Linear Regression Slope
- MACD
- MACD Histogram
- Mass Index
- Median Price
- Momentum Oscillator
- Money Flow Index
- Negative Volume Index
- On Balance Volume
- Performance Index
- Positive Volume Index
- Price Oscillator
- Price ROC
- Price Volume Trend
- Prime Number Oscillator
- Rainbow Oscillator
- Relative Strength Index
- Standard Deviation
- Stochastic Momentum Index
- Stochastic Oscillator
- Swing Index
- Trade Volume Index
- TRIX
- True Range
- Ultimate Oscillator
- Vertical Horizontal Filter
- VIDYA
- Volume Oscillator
- Volume ROC
- Williams Accumulation Distribution
- Williams PctR

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Variable Moving Average, often abbreviated as VMA, is an Exponential Moving Average. It was developed by Tushar S. Chande in 1991. VMA automatically adjusts its smoothing constant on the basis of Market Volatility. The Sensitivity of Variable Moving Average keeps growing provided the volatility of data considered is increasing. A major flaw in all forms of moving averages is that, they are unable to function properly and predict future trend during Trending and Non-Trending movements of Stocks occurring one after another. Similarly, when moving averages are determined over a longer period of time, Moving Averages are unable to respond to trend reversals. This may lead to disastrous trade signals. Variable Moving Averages distinguishes itself from other moving averages on the basis of sensitivity. VMA functions far better than other moving averages because it adjusts its smoothing constant according to market conditions like Market Volatility.

If data provided is more volatile then latest figures are given more weight. VMA not only shortens it average time period when market is trending but it also increases its length if market is non-trending highly volatile markets. Any Tool can be used to determine Volatility in Variable Moving Average. Most Common Tool to determine Volatility is a 9 Period Chande Momentum Oscillator. Chande presented the idea of using Volatility Index to determine the smoothing period. In order to function properly, the Volatility Index must catch up the pace of market trend. If it is highly trending, the Volatility Index must adjust its length to determine price trends of immense importance. Another recent development in CMO is the use of Absolute CMO to determine Volatility Index.

In order to Calculate Variable Moving Average, we must determine a method to calculate
Volatility Index. Standard Deviation or Chande Momentum Oscillator are frequently
used by Traders to determine Volatility Index.

Following is a formula to determine VMA with Chande Momentum Oscillator:

The basic difference between Variable Moving Average and other Moving Averages is
that, VMA doesn’t have any upper boundary to its Smoothing Constant.

Variable Moving Average has no upper limit to its Smoothing Constant. Volatility
Index can reach zero mark. At this point, the Average will not go further and will
match the previous Variable Moving Average. Similarly, when Volatility Index approaches
1, the Smoothing Period would be equivalent to ‘n’ as illustrated below.
The Value of CMO ranges between -100 and 100. In order to take Absolute value of
CMO, Divide the outcome by 100.

Traders often use VIDYA and VMA interchangeably. Actually, that’s not true. VIDYA was introduced by Chande in 1992 in “TECHNICAL ANALYSIS OF STOCKS AND COMMODITIES”. After 3 years, in 1995, he Developed Chande Momentum Oscillator. In the 1995 edition of “TECHNICAL ANALYSIS OF STOCKS AND COMMODITIES”, Chande used CMO to calculate VIDYA and named it Variable Moving Average. In order to use it in an Indicator, traders prefer Absolute value of Chande Momentum Oscillator. This can be obtained by dividing the output of CMO by 100. When we use AbsCMO to calculate Volatility Index, it is knows as variable moving average. On the other hand, if we use standard Deviation to determine Volatility Index, it is called as Variable Index Dynamic Average.

The main purpose of every Moving Average is to determine trends, smooth data fluctuations, generate long and short signals. These attributes make a moving average most frequently used technique by Traders. Three Different Averages can be utilized to exhibit a Normal Crossover Trading Scheme. Traders use three varying moving averages on the basis of length i.e. Short, Medium, and Long Run. A common example of Trading System would be of 4, 9, and 18 time intervals. The parameter of length i.e. Months, Weeks, Days or Minutes primarily depends on the nature of chart used in determining trade signals.

Trade Signals in a 3 Period Moving Average is explained below:

- A buy signal is triggered when Short and Medium Run Averages cross Long Run Average from below.
- Conversely, a sell signal is generated when Short and Medium Run Averages cross Long Run Average from above.
- Long Position Signals are generated when Closing Price is greater than Moving Average. Conversely, Short Position Signal is generated when Closing Price is less than Moving Average.

- All most all of the Moving Averages deploy fixed number of days to determine the Volatility Index. Unlike other Moving Averages, VMA adjusts its length according to the Market Volatility.
- VMA speeds up when the prices are moving rapidly and slows down when the prices are showing slight or marginal difference from their previous positions.
- VMA allows its users to adjust instruct their trading style while determining future trends. The Range of VMA is highly dynamic, this allows the traders to adjust the number of days to be included and which days to be excluded.
- The Chande Momentum Oscillator can be utilized along with VMA to form an active average specifically designed to determine market momentum.
- VMA helps its users plan for more accurate contingencies. One can initiate new positions, set stops, or close old ones on the basis of a range of outcomes chalked out by the trading plan.
- The Responsiveness of VMA is far better then other Indicators during times of High Volatility and Price Movements.

- VMA doesn’t predict precise change from the actual. The Purpose of VMA is to give an estimated trend direction on the basis of past days.
- A disadvantage or rather threat of using VMA is that in majority of the cases, the majority of technical indicator including VMA have failed to predict future trends in some specific markets. The use of VMA in such markets is not only useless but it can be costly as well.
- Using VMA or any other moving average may not be as much fruitful as a weighted average would be. The only evidence for it is that it considers more situations then a single moving average.
- VMA doesn’t consider any scenario other then the one provided to it within the Number of days in consideration.