The double exponential moving average (DEMA) indicator is a technical indicator that is calculated using a combination of single and double exponential moving averages (EMAs) to eliminate the lag time typically associated with other moving averages.

This means that it is faster than typical moving averages (MAs), making it more responsive to price changes than normal MAs. The DEMA is used in much the same way as typical moving averages to identify the current trend and pinpoint potential trade entry and exit positions.

*Chart 1: GBP/AUD 4-hour chart with 21-period DEMA and MA*

The above chart demonstrates how the DEMA tracks prices more closely than the MA.

**Calculating the simple MA**

A major difference between the double EMA and normal MAs relates to the way we calculate their values. The simple moving average is usually calculated by taking the closing price of the last X periods and finding their average.

For example, calculating the 20-period moving average typically involves adding up the closing prices of the last 20 periods and then finding their average. As each period ends, we add the closing price of the latest period to the previous 19 periods to get the new 20-period MA; these values make up the 20-period MA line.

**Calculating the double exponential moving average (DEMA)**

As expected, the double exponential moving average (DEMA) is calculated via a more complicated formula shown below:

DEMA = 2 × EMA_{N} − EMA of EMA_{N}

Where: N = Look-back period

- The first step is to determine a look-back period, which could be 5, 10, 20, or 100 periods.
- Next, you calculate the EMA for the chosen look-back period, which becomes EMA
_{N}. - Then apply the EMA formula for a similar look-back period to EMA
_{N}to get a smooth EMA. - Multiply EMA
_{N}by 2 and then subtract the smoothed EMA from step 3.

The complicated nature of the DEMA formula means that traders need more data to calculate DEMA values, but this can be automated on most charting platforms.

**Trading the DEMA and MA crossovers **

One of the most popular uses of moving averages is the MA crossover, which is used by most trend traders to identify trade entry and exit points. The DEMA eliminates a significant portion of the time lag associated with traditional MAs, as shown in the example below.

Two double EMAs and two standard MAs have been applied to the GBP/AUD four-hour chart below, with the aim of trading the 21-period and 55-period crossovers of the DEMAs and the MAs.

*Chart 2: GBP/AUD 4-hour char**t with two DEMAs and two normal MAs*

*Chart 3: Chart with marked DEMA and MA crossovers*

The first DEMA crossover occurred at 1.7887, triggering a bearish move that could have resulted in a short trade lasting up to 1.7707 when the second crossover occurred and leading to a new bullish move. A person who took this short trade would have booked an 80-pip profit based solely on the DEMA crossover signals.

The normal moving averages missed the entire move and could have generated a false signal when the faster MA (21-period MA) tried to cross above the slower MA (55-period), which almost resulted in a buy signal shortly before the DEMA crossover triggered a sell signal.

The last two circles also show a similar trend, where the DEMA crossover identified a potential long trade at 1.7820 with a nice entry position a candle later at 1.7781, while the normal MA crossover caught the same move 11 periods later (44 hours late) at 1.7934 since this is a four-hour chart.

In this scenario, a trader following the standard MA crossover would have missed over 100 pips profit on a bullish move and would have gotten into the trade when the move was almost exhausted if they were solely relying on the MA crossover.

The chart above shows that on multiple occasions, the DEMA crossover occurred hours before the MA crossover took place. In one case, the MA crossover did not happen, which means that traders waiting for the crossover could have missed a significant downtrend.

**A word of caution**

Keep in mind that the DEMA is a much faster moving average. It usually generates more trading signals, but it can also generate false trading signals, especially in choppy market conditions.

The stochastic RSI is different from the stochastic oscillator in the sense that it is calculated by applying the formula used to calculate the stochastic oscillator to the relative strength index (RSI) indicator, while the stochastic oscillator is a standalone momentum indicator.

**The stochastic oscillator**

The stochastic oscillator is a technical indicator typically used to generate buy and sell signals by highlighting extremely oversold and overbought conditions. The indicator operates under the assumptions that:

- An uptrend is made up of a series of prices that are higher or equal to the closing price of each prior period.
- A downtrend is made up of a series of prices that are lower or equal to the closing prices of the previous periods.

The stochastic oscillator was created by George Lane in the late 1950s as a way to track price changes (momentum). Lane strongly believed that before the price of an asset changes course, it first has to lose momentum, similar to the way rockets behave.

He used the analogy of how a rocket blasts off from Earth with a lot of momentum, then begins losing momentum at its peak before suddenly falling back to Earth. He said asset prices behave in a similar manner to rockets because they lose momentum at their peak before reversing direction.

*Chart 1: EUR/USD chart with stochastic **oscillator*

**How to calculate the stochastic oscillator**

The stochastic oscillator is made up of two lines. The faster line is referred to as the %K line and reflects the current price as compared to the highs and lows of a prior defined period, typically 14 periods.

The second line is known as the %D line and is a simple moving average (MA) of the first line. The indicator has a default value of (14, 3, 3) representing the 14 periods used in the first line and the 3 periods used to calculate the SMA line (%D line).

**The stochastic RSI**

The stochastic relative strength index (RSI) indicator uses RSI values instead of actual price values in its calculations, which means that the indicator effectively tracks RSI values instead of price values, also categorized as “an indicator of an indicator.”

The stochastic RSI is a modified version of the stochastic oscillator that was created by Stanley Kroll and Tushar Chande in 1994 with the main goal of tracking RSI values instead of actual price values.

This means that the %K line of the indicator tracks RSI values and compares them to the previous highs and lows of the past 14 periods, and the %D line is the three-period SMA of the first line representing RSI values.

*Chart 2: EUR/USD chart with stochastic RSI indicator*

**What is the stochastic RSI used for?**

The main reason behind the creation of the stochastic RSI was to generate more overbought and oversold signals; the normal RSI typically generates few sell and buy signals.

By forcing the stochastic oscillator to track RSI values, the indicator is more likely to generate more signals because the newly formed indicator will be extremely sensitive to RSI movements.

**How the RSI works**

The relative strength index (RSI) indicator is a momentum indicator that tracks the magnitude of recent changes in the price of an asset to determine whether oversold or overbought conditions are present at any given time.

The RSI is plotted as an oscillator on a scale ranging from 0 to 100, with values over 70 indicating that an asset’s price is in overbought territory and values below 30 indicating that prices are currently oversold.

The indicator is calculated by finding the RS (relative strength), which is the figure found when you divide the average gain by the average loss over a specific time period (typically 14 periods). The RSI is then calculated using the following formula:

RSI = 100 – (100 / (1 + RS)

RS = average gain / average loss

**The bottom line**

The stochastic oscillator is generally a much faster indicator than the stochastic RSI indicator, which is derived from another indicator and is a lagging indicator. This means that the stochastic oscillator typically generates sell and buy signals much earlier than the stochastic RSI, which could be very useful for traders who trade shorter timeframes. However, swing and position traders may prefer to focus on signals generated by the stochastic RSI given the longer holding periods.

The Aroon indicator is used by traders to identify the strength of an existing price trend and identify points where a current trend is likely to reverse. The indicator keeps track of the number of higher highs made in an uptrend as well as the number of lower lows made in a downtrend. The indicator is composed on an “up line” that tracks bullish trends and a “down line” that tracks bearish price trends.

**Can the Aroon indicator be used to analyse crypto charts?**

Because it is a technical indicator that can be applied to any price chart regardless of the asset being traded, it can indeed be used for analysing crypto charts. However, as with most technical indicators, there are certain conditions in which an indicator’s effectiveness may decline, just as there are certain situations where an indicator performs at peak accuracy.

This means that in theory, you can apply any of the many technical indicators on a price chart and expect the typical results associated with the indicator, regardless of the asset whose price you are tracking.

However, this couldn’t be further from the truth in reality. Every indicator works best under certain ideal conditions and may not perform as well under other conditions. For example, many indicators do not work in extremely volatile market conditions where price is moving rapidly from highs to lows in an erratic manner.

Therefore, if you want to determine whether the Aroon indicator can work on crypto charts, you must first analyse the typical conditions that exist within the crypto markets.

**How do the crypto markets behave?**

One of the defining characteristics of crypto markets is that they are known to be extremely volatile, with prices swinging between extreme lows and extreme highs on a daily basis. The significant price swings witnessed in the crypto markets, especially on the lower timeframes, make it difficult for most lagging indicators to work on crypto charts.

This means that in most cases, it may not be prudent to use the Aroon indicator on crypto charts that track price changes on time intervals lower than one hour, such as the five-minute, 15-minute, and 30-minute charts.

However, you could use the Aroon indicator on the one-hour, four-hour, and daily timeframe charts and get pretty good signals. This can be quite accurate, as shown by the two charts below.

*Chart 1: Applying the Aroon indicator to the one-minute bitcoin chart*

*Chart 2: Applying the Aroon indicator to the one-hour bitcoin chart*

**How the Aroon indicator works on crypto charts**

The above charts are a good example of how the Aroon indicator looks on the one-minute and one-hour bitcoin charts. However, the screenshots were taken during period of relative calm in the crypto markets, as evidenced by the one-minute chart, which shows subdued price action.

In this scenario, the Aroon indicator seems to work quite fine on both charts as the indicator has pinpointed all of the new highs and lows on the chart during the sustained price declines as well as the sustained price rallies.

For example, on the one-hour chart, the up line has crossed the down line at several points where the trend was about to reverse in favour of buyers, and the same has also been witnessed whenever the price has shifted in favour of the sellers.

Moreover, this is a chart of bitcoin, which happens to be the largest cryptocurrency by market value and is traded by most crypto investors. However, many other crypto assets are less popular, which means that they are traded by fewer investors and subject to significant price swings.

**The bottom line**

The effectiveness of any indicator when applied to a particular asset’s price chart depends on many other factors, such as the asset’s liquidity and typical price patterns. Always consider such factors when drawing conclusions from the Aroon indicator whenever you apply it to a crypto asset. Such assets are associated with extreme volatility, which could invalidate the conclusions you have drawn from your analysis, leading to significant losses. Always apply proper risk management to all your trades.

**Brief definition of the average true range (ATR) indicator**

The average true range indicator is an indicator that measures and displays how much the price of an asset has moved, on average, over a specific time period.

Given that the ATR tracks the price movements of an asset, it also displays values as actual currency values, and in the case of forex pairs, the values are displayed as pips.

For example, the ATR indicator tracking a stock will typically display values in dollars such as 0.50, which stands for $0.50, while the ATR indicator tracking a forex pair is likely to display price as 0.0050, representing 50 pips.

Figure 1: A chart showing the ATR indicator at the bottom

**How the ATR is calculated**

Firstly, the term average true range means that the indicator is a type of average, which in this case means that it is an average of a series of true ranges calculated for each individual unit of time in a larger time period.

Therefore, the first step to calculating the average true range is to calculate the true range (TR) of each time period.

The true range is defined as:

- The current high minus the current low
- The current low minus the previous close
- The current high minus the previous close

The ATR uses absolute values, which means that it does not recognise negative values, but converts each of the three figures above into positive values and then picks the highest value as the true range.

The ATR is calculated as follows when it is applied to a chart:

The true range of each time period is calculated, after which the average of the chosen group of time periods is determined. For example, the ATR for a 14-period timeframe is calculated as follows:

ATR = [(Prior ATR x 13) + Current TR] / 14

- First, multiply the previous 14-period ATR by 13
- Then, add the TR value of the current day
- Finally, divide the total by 14

**Why does the true range use absolute values?**

The true range indicator uses absolute values as it is only interested in measuring the distance between the highest and lowest prices achieved in a given time period.

The use of absolute values is mostly applied when calculating the true range from:

- The current low minus the previous close
- The current high minus the previous close

This is because these calculations could easily result in negative values as they are typically used when there is a gap-up or a gap-down from the previous closing prices, as illustrated by the image below.

Figure 2: Instances where the true range uses absolute values

**Image A:** Shows the formation of a small bar after a gap-up. In this case, the true range is not calculated from the high and low of the current candle, but from the difference between the current high and the previous close, which is the true price range.

**Image B:** Displays a small candle formed from a gap-down in price. In this scenario, the true range is calculated from the difference between the current low and the previous close, instead of the highs and lows of the small candle.

**Image C:** Is unique in that the highs and lows of the current candle are within the highs and lows of the previous candle. However, the current candle is much smaller than the absolute value of the difference between the current high and the previous close, which becomes the true range.

**How to calculate the ATR by yourself**

In case you are wondering how you can calculate the ATR value on a particular chart if you do not have the previous 14-day ATR, you can do it in this manner.

Once you have chosen a point in time when you want to start your ATR calculations, simply calculate the true range values for 14 time periods from your chosen starting point.

Next, calculate the average of the true range values that you have calculated for the 14 time periods and use that as the value for your previous 14-day ATR. Remember that the ATR is a literal average and the figure you get from the above calculations is quite accurate.

You will only start using the ATR formula described in the first section from the 15th day, when you have your first 14-day ATR value.