EWMA Implied Volatility based on Historical Volatility

Volatility is the most common measure of risk.

Volatility in this sense can either be historical volatility (one observed from past data), or it could implied volatility (observed from market prices of financial instruments.)

The main objective of EWMA is to estimate the next-day (or period) volatility of a time series and closely track the volatility as it changes.

The EWMA model allows one to calculate a value for a given time on the basis of the previous day's value.
The EWMA model has an advantage in comparison with SMA , because the EWMA has a memory.
The EWMA remembers a fraction of its past by a factor A, that makes the EWMA a good indicator of the history of the price movement if a wise choice of the term is made.

Full details regarding the formula :

In this scenario, we are looking at the historical volatility using the anual length of 252 trading days and a monthly length of 21.
Once we apply all of that we are going to get the yearly volatility .
After that we just have to divide that by the square root of number of days in a year, or weeks in a year or months in a year in order to get the daily/weekly/monthly expected volatility .

Once we have the expected volatility , we can estimate with a high chance where the market top and bottom is going to be and continue our analysis on that premise.

If you have any questions, please let me know !

Open-source script

In true TradingView spirit, the author of this script has published it open-source, so traders can understand and verify it. Cheers to the author! You may use it for free, but reuse of this code in a publication is governed by House Rules. You can favorite it to use it on a chart.


The information and publications are not meant to be, and do not constitute, financial, investment, trading, or other types of advice or recommendations supplied or endorsed by TradingView. Read more in the Terms of Use.

Want to use this script on a chart?