Technical analysis is an integral part of trading and one of the most common concepts of technical analysis is the moving averages. But did you know there are many types of moving averages that can be used to make a thorough analysis of the securities and the market as a whole? Thats right. While the terms Simple Moving Average and Exponential Moving Average are quite common, traders also use the DMA to understand the price movements in the markets. Learn more about DMA and how it is different from your classic EMA and enhance your technical analysis concepts.
Read More: What is MACD – All you need to know
What is DMA?
Displaced Moving Average (DMA) is a technical analysis tool that traders can use to analyze price trends. It’s a variation of the standard moving average indicator, which helps identify potential trends and changes in the market. DMA involves shifting or displacing the regular moving average line either to the left or right on the price chart. This adjustment allows traders to anticipate potential price movements more effectively. By moving the moving average, traders can essentially project what the moving average would have been at a specific point in the past or future.
How is DMA calculated?
In order to calculate the DMA, the primary step is to calculate the moving average. The calculation of DMA is explained hereunder.
Calculating the moving averages
The starting point is the calculation of the standard moving average. This involves summing up the closing prices of a stock or index over a specific period and then dividing this sum by the number of periods to arrive at an average.
Calculating DMA
DMA is an extension of MA that introduces the capability to shift the moving average line on the chart. The steps in calculating DMA include,
- Select MA Period – Determine the desired number of periods for the moving average, such as 20 days.
- Choose Displacement Value – Decide the number of periods by which the MA line is to be shifted. For example, shifting by 5 periods to the right would mean projecting the DMA average of the past 20 days forward by 5 days on the chart.
- Calculating DMA – the next step is to take the closing price of the selected periods. If displacement is involved, traders need to adjust the prices according to the displacement value. Finally, traders need to calculate the average of these adjusted prices to obtain the DMA value.
What is 20DMA and 50 DMA?
The terms “20DMA” and “50DMA” refer to the “20-day Moving Average” and “50-day Moving Average,” respectively. They represent the average closing prices of a stock or index over the past 20 and 50 trading days, providing insights into short-term and medium-term price trends.
What is the difference between moving average and DMA?
The main difference between a moving average and Displaced Moving Average (DMA) lies in their calculation methods: a moving average calculates the average of a specified number of periods, while DMA shifts the moving average line left or right on the chart to project historical trends onto different time points for analysis.
What is Exponential Moving Average?
The Exponential Moving Average (EMA) is a unique type of moving average that gives more weight to recent price data, making it very responsive to recent market changes. This sets it apart from the Simple Moving Average (SMA), which treats all prices within a specific timeframe equally. EMA’s responsiveness is achieved by emphasizing recent data while diminishing the significance of older data points, allowing it to quickly adapt to evolving market conditions. EMA’s dynamic nature makes it popular for capturing emerging trends quickly, but it also requires careful use due to its sensitivity to noise and false signals.
The formula to calculate EMA is,
Current EMA = [Closing Price – EMA (Previous Time Period)] x Multiplier + EMA (Previous Time Period)
Where,
Multiplier = 2 / (Chosen Time Period + 1)
What are the differences between DMA and EMA?
Some of the key differences between the DMA and EMA are tabled hereunder.
| Category | DMA | EMA |
| Calculation Method | DMA involves shifting the moving average line left or right on the chart, projecting past trends onto different points in time. | EMA gives more weight to recent price data, resulting in greater responsiveness to current market conditions. |
| Sensitivity to Price Moves | DMA’s sensitivity is influenced by the chosen displacement and the period under consideration. | EMA exhibits high sensitivity to recent price fluctuations, reacting swiftly to shifts in the market. |
| Weighting of Data Points | DMA applies the same weighting to all data points within the chosen period, regardless of their chronological order. | EMA assigns higher significance to recent data points, making it particularly responsive to immediate changes. |
| Trend Identification | DMA is advantageous for projecting historical trends onto different timeframes, offering insights into potential shifts. | EMA is effective for identifying short-term trends and potential reversals in the market due to its rapid responsiveness. |
| Smoothness of Curve | DMA curve may appear jagged due to the shifting of data points, reflecting the displaced nature of the calculation. | EMA generally presents a smoother curve due to the consistent adjustment of weightings for recent data. |
| Application Scope | DMA finds utility when historical trends need to be projected onto various timeframes for analysis. | EMA is favoured for short-term analysis as it promptly reflects current market conditions and price changes. |
Which day moving average is best?
The choice of the best moving average depends on the trader’s goals and time horizon; the Exponential Moving Average (EMA) is often preferred for short-term analysis due to its quicker response to recent price changes, while the Simple Moving Average (SMA) is popular for longer-term trends due to its smoother calculation.
Conclusion
The use of DMA is the refined version of understanding the moving averages and thereby the security or the stock markets as a whole. DMA is a technical analysis concept and therefore, for its correct use and implementation, it is necessary to understand it in its true sense and account for its limitations too.
