EMA (Exponential Moving Average) Definition
The Exponential Moving Average (EMA) is a specific type of moving average used in technical analysis and trading that assigns greater weight to the most recent price data. EMA is commonly used by traders and analysts to identify short-term price trends in cryptocurrency, stocks, commodities, and others.
EMA Key Points
- EMA gives more weight to the recent prices, thus it reacts more quickly to price changes.
- Commonly used by traders to identify trend directions over different time periods.
- EMA can be applied to any time frame (daily, weekly, hourly), and thus fits all trading styles (long-term, short-term).
What is EMA (Exponential Moving Average)?
EMA or Exponential Moving Average is one of the many types of moving averages, a concept widely used in technical analysis. It is a statistical calculation that traders use to analyze data points over a period of time to identify potential trends and patterns. What distinguishes EMA from typical moving averages is its heavier weighting on recent data points.
Why is EMA used?
The primary reason traders and analysts use EMA is to identify the direction of a trend. By giving more weight to recent data, EMA allows traders to react more quickly to any changes in price trends. This is especially important in volatile markets like cryptocurrency where price swings are frequent and abrupt.
Where is EMA used?
EMA is used in a variety of markets including stocks, commodities, and most relevantly to our audience, cryptocurrency. It can be practiced on various time frames, making it relevant for different kinds of traders – short term day traders or longer-term position traders.
When is EMA used?
The EMA is used whenever a trader or analyst wishes to evaluate price trends over a period of time. Due to the adaptability of the EMA to different time frames, it can be utilised whenever trading or trend analysis is being performed.
How is EMA calculated?
The EMA is calculated by taking the closing price of a cryptocurrency (or any other asset), subtracting the EMA of the previous day, and then multiplying the result by a smoothing factor. Then, the calculated EMA is added to the previous day’s EMA to get the new EMA. The smoothing factor is usually calculated based on a selected period, for instance, a 10-day EMA will have a different smoothing factor than a 20-day EMA.
