Moving averages in cryptocurrency trading is a trend indicator that provides a clearer insight into an asset price movement by displaying its average value within a given timeframe. It is a very important tool if you want to know when to enter and exit the market.
Although there are many indicators in the market, a moving average or MA is the most popular and vital technical indicator in crypto trading. This technical indicator works in any timeframe, but to get the highest benefits from this tool, you need to know its best uses. Many other indicators like MACD, Bollinger bands, and CME Bitcoin Gaps also partly rely on moving averages theory.
This moving averages in crypto trading guide cover the following:
- What is a Moving Average?
- How to calculate moving averages in cryptocurrency trading
- Types of moving averages in crypto trading
- Moving average strategy in cryptocurrency trading
What is a Moving Average?
A Moving Average is a trend indicator that helps highlight the average value of an asset within a given period of time. Remember, the moving average won’t tell you the future movements of the price. Instead, moving averages confirm established trends. Moving averages sharpens the price fluctuations. It also reduces the market noise.
So when market noise is removed, you will better understand what is happening in the market and the possible future movements of the price. Although it is not possible to predict the market, the fact is that with the help of an MA, you can easily analyze the market perfectly.
How Can You Calculate the Crypto Moving Average?
First, aggregate the “x” number of past data or previous Candle’s value and divide it by X. Ok, let me give you a real example, and then you will understand it more clearly.
Suppose you want to know about the 34 moving average periods. Then, a 34-period moving average is derived by aggregating the previous 34 periods and then dividing by 34.
Isn’t that easy? Now we move on from the simple moving average example here to the EMA and WMA calculations that will be somewhat different. This is as it relates to moving averages in trading.
How Many Types of Moving Averages Are There in Crypto Trading?
Simple moving average
The simple moving average is a solid long-term indicator that works in any timeframe. The simple moving average calculates an average of the last n prices.
Where Px represents the price…
5 periods of moving average calculation will be like this
SMA = (P1+P2+P3+p4+p5)/5
The fun fact is that you won’t need to calculate these complex equations manually. Just apply the SMA to your chart on your trading platforms and then adjust as you wish. You will see a blank option to input your desired number.
Most of the time, traders use 20,50,100 SMA periods.
Exponential moving average or EMA
Exponential moving average focuses or gives more weight to recent price data. This type of moving average is faster than a simple moving average. Short-term traders and scalpers love to use these types of MA.
An exponential moving average gives a more influential output which works best for finding short-term trends and catching little swings in the market.
The formula for EMA will be = (2/n+1)* (close-previous EMA )+ Previous EMA
Weighted moving average or WMA
WMA gives more weight to the last period. WMA is faster than SMA but not as fast as EMA. Professional crypto traders use a weighted moving average.
Moving Average Strategy in Cryptocurrency Trading
The moving average can be used as support and resistance. In general, the support level is where buyers willingly wait to buy, and the resistance level is where sellers wait to sell.
Just check out the chart above. How beautifully BTCUSD or Bitcoin respects the 34 WMA/Every time it comes near the support line, it bounces from it. Suppose if we paid close attention to these WMA support zones, we could find profitable setups. But remember, you need to wait for the perfect time, the ideal shot. If you rush to enter the market, you will lose your money in this volatile market.
Take a look at another example, and this time, I will show you how you sell using 34 WMA.
Our WMA here is acting as strong resistance levels. When the price breaks the WMA line, we will prepare to find any rejection or bounce from the resistance zone. See, every time the price goes near the 34 WMA; the market gives us an opportunity. If we sold these areas, then we could make huge profits.
The fact is that does the market respect all the WMA? No, If things were so easy, then everyone would be rich. Most of the time, markets tend to respect 34 WMA. And hardly any trader knows this secret.
Exponential moving average crossover strategy
If one moving average moves another moving average, it creates a great opportunity. But we need to be patient until the perfect crossover happens. We will use 50 EMA and 200 EMA for the crossover strategy because big banks and institutional traders use these crossover types. That’s why traders call this crossover a golden cross.
See here 5 EMA crosses 200 EMA aggressively, and then we find a strong bullish candle. Now, this is very important, folks. If you find a golden crossover with no robust bullish candle, you will not take that trade. Without any bullish candle, that setup will be void.
If we took this trade, how much profit could we make? But the irony is that most of the time, we make mistakes by hurrying in taking our trades or entering the market. If you enter the trade just because there is a golden cross, then the time is very near that you will lose all your money.
To sell, you need to apply the same rules. You need to find a crossover where 50 EMA will cross 200 EMA from upside to down, and then you need to find a robust bearish candle. If you get these two things simultaneously, you can blindly take a short setup. But if one is missing, then avoid taking trades.
Using EMA, SMA, and WMA to predict the market and enter the trade can be profitable if you are a patient trader. Approximately 50/55 million traders actively trade cryptocurrency, and if you ask which indicators they use most of the time, the answer will be the moving average.
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