Syntax
public static ExpDev Series(DataSeries ds, int period, bool useEMA)
public ExpDev(DataSeries ds, int period, bool useEMA, string description)
Parameter Description
| ds | DataSeries used to build ExpDev |
| period | Lookback period |
| useEMA | Uses SMA if unchecked, or EMA if checked |
Description
Standard Deviation is the statistical measure of market volatility. If prices trade in a tight narrow trading range then
StdDev will return a low value indicating volatility is low. Conversely if prices swing wildly up and down then
StdDev returns a high value indicating volatility is high. What it does is measure how widely prices are dispersed from the average or mean price.
What makes ExpDev (exponential deviation) different is the use of exponential smoothing (
EMA) vs. simple averaging that takes place inside the indicator. This is believed to make the Exponential Deviation bands more sensitive to the market action.
Interpretation
- Standard deviation rises as prices become more volatile. As price action calms, standard deviation heads lower.
- Market tops accompanied by increase volatility over short periods of time, indicate nervous and indecisive traders. Or market tops with decreasing volatility over long time frames, indicate maturing bull markets.
- Market bottoms accompanied by decreased volatility over long periods of time, indicate bored and disinterested traders. Or market bottoms with increasing volatility over relatively sort time periods, indicate panic sell off.
Remarks
- Avoid testing ExpDev of a Standard Price Series (Bars.Open, Bars.Close, etc.) for an absolute value since these series can be adjusted (split) in the future, which will change their historic deviations. Instead, normalize the test by dividing both StdDev and the value (or series) by the DataSeries value.
Correct/* Normalized */
double C = Closebar;
if( ( ExpDev.Series( C, 20 )bar / C ) < ( 1.5 / C ) )...
Calculation
Initial exponential deviation: Mean deviation (subtract the N-period average of the price from each period's price, take the absolute values of these numbers, sum the absolute values, and divide by the total number of periods (N))
- Period deviation (PD) = Absolute value of each period's deviation (close less SMA or EMA)
- Multiplier (MLTP) = 2 / (Time periods + 1)
- Exponential deviation (ED) = PD * MLTP + ED (previous day) * (1-MLTP)
Example
Please refer to
July 2019 Traders' Tip article's code.