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# Moving Average for Crypto: The Technical analyst indicator

Did you know that you require a **technical analysis** regarding the investment and the returns on it in order to be a successful investor? Yes, You do. Investing and trading is not a child’s play, it is a complex process that requires speculation, calculation, and estimation. And in order to do that, one needs to be familiar with concepts that revolve around the finance market. One such necessary theory is ‘Moving Average’. “*Successful investment is about managing risk, not avoiding it”*. And moving averages surely help you to calculate your investment and manage your risk by eliminating the chances of failure.

What we are going to learn?

## What is the Moving Average ?

Moving averages are **price based market indicators** that help to find out the average price of a cryptocurrency over a period of time. It is commonly used to assess investments and recognise trading opportunities by analysing the statistics of the previous market conditions. By this technical analysis, one can identify the areas of threat and chances. The Moving Average extracts information from the price and volume of a crypto relating to the previous time period in order to interpret the position of a crypto in the market. The main aim of calculating Moving Average is to level out the price chart by forming a constantly updated average price data. With the help of this average, any investor or trader can identify the trend direction of a particular crypto before or after investing.

This is precisely why Moving Average is also called **“Lagging indicator”** because it reacts to the previous prices or forms an analysis based on the preceding data. This reactive indicator forms a basis for other familiar technical analysis tools such Bollinger Bands and the MACD. The calculation of moving averages diminishes short-term instability in the price trend of a Crypto market. The statistics resulting after calculation of the moving average shows the change in the crypto market over a set period of time.

## Features of The Moving Average

To calculate the moving average you need to know some basics about it. Let’s see what they are :

- Moving Average gives out the average price of a set of data regarding a crypto from the past time period.
- The moving average is not restricted to a certain tenure. It is a customisable indicator.
- Moving Average causes lag irrespective of the time period. The greater the time period is, the bigger the lag.
- Shorter time frames in a moving average implies more price sensitive and vice versa.

## Uses of The Moving Average

Moving Average is an indicator that analyses the trend of a crypto in the present or the future using the past data. This helps the trader in understanding the kind of returns or profits they would avail from their investments, movements or patterns in the crypto market. Each move made in the trade market counts.

Some important functions of the Moving Average are :

**Reactive Tool**: The Moving Average is a lagging technical analysis indicator that reacts, analyses or works based on the previous information from the prices and volume of the cryptocurrency. It does not predict any solid results about the future, rather interprets the past information and helps the investor get an idea about the type of crypto he’s willing to invest in. The Moving Average is a trend following indicator and not a trend making one.**Helps to gauge momentum**: Momentum measures the rate of rise and fall in the prices of cryptocurrency. With the help of Moving Average, one can foresee the trend in the volume and prices of a crypto. This helps in making a sound and safe investment for the traders. With the momentum indicator, the strength and weakness and the support and resistance level of a crypto can be determined.**Trading signals**: The tenure of the moving average decides the degree of lag. Longer time period implements greater lag and vice versa. A 200 day moving average yields a greater lag as compared to a 20 day moving average. The traders use these average figures as trading signals which either initiates them to buy or sell a crypto based on the price average.**Customisable indicator**: An investor can customise his Moving Average indicator according to his needs. The trader has the choice to choose the time period for which they intend on finding the moving average. The moving average calculated for shorter tenures will be more price sensitive. The longer the time period used to calculate the Average, the less sensitive it will be to price changes.**Trend Analysis**: The basic purpose of calculating the Moving Average is to foresee the trend based on past data. It does not mean that the moving averages form any trend. Any rising moving average shows that the crypto is in an uptrend and is doing well in the market. Similarly any decreasing average shows that the crypto is in a downtrend and is not doing so well in the market.

## Types of Moving Average

There is a wide range of indicators in the market benefitting the traders to plan their next move regarding their investment in Cryptocurrency. Various types of moving averages have been developed over time to smoothen the trading experience of investors. Some examples of Moving Average are :

- Double Exponential Moving Average (DEMA)
- Fractal Adaptive Moving Average (FRAMA)
- Volume Weighted Moving Average (VWMA)
- Smoothed Moving Average (SMMA)
- Weighted Moving Average (WMA)
- Hull Moving Average (HMA)
- Exponential Moving Average (EMA)
- Kaufman’s Adaptive Moving Average (KAMA)
- Simple Moving Average (SMA)
- Variable Index Dynamic Average (VIDYA)

Among the wide variety of Moving Averages, the most used and notable ones are Simple Moving Average (SMA), Exponential Moving Average (EMA), and Weighted Moving Average (WMA). Let’s have a brief look at how these Moving Averages function.

### Simple Moving Average (SMA)

As you can guess by the name, Simple Moving Average is the most easy and simple method of calculating Moving Average. It is an unweighted moving average which implies that weight assigned to the data sets is constant for every day (The data sets differ from each other). With each passing day, the most obsolete data is replaced with the fresh data. The SMA is calculated by adding a set of periods together and then dividing that by the number of periods.

SMA Calculation :

**SMA : X1+X2+X3+X4……….Xn / n **

Where : X : The average periods (n)

n : Number of periods

### Weighted Moving Average (WMA)

As the name suggests, Weighted Moving Average gives more weight or value to the recent data points. It is similar to SMA, in which the old data is replaced by the new one. Each data point is assigned a multiplier which decides the significance of the data in the set. The largest multiplier is assigned to the new data and then it does on decreasing as the data gets old. This signifies that the new data is more relevant and useful. The calculation of WMA is similar to SMA, only here the weights are different for each data.

WMA Calculation :

**WMA : Sum of period values /Number of period**

Where:

Sum of period values = Price * weights

### Exponential Moving Average (EMA)

This moving average focuses more or gives more value and weightage to the current price in order to make the speculation relevant and responsive to fresh data. It is a type of Weighted Moving Averages (WMA). In EMA, more weight is assigned to the new data, that doesn’t mean that the old data is completely discarded. The old data is also considered, but they retain a multiplier. To calculate EMA, one needs to find out SMA and the smoothing factor.

EMA calculation :

- Calculate Simple Moving Average for the data ( The average periods/Number of periods)
- Calculate the Multiplier [2/(selected time period + 1)].
- Use the smoothing factor to calculate EMA
- EMA = {Close – EMA(previous day)} x multiplier + EMA(previous day)

**EMA(T) = [ Vt X ( s/ 1+d)] + EMA(Y) X [ 1-( s/1+d)] **

Where :

EMA(T) : EMA today

Vt : Value Today

s : smoothing

d : Number of days

EMA(Y) : EMA yesterday

There are other complex ways to calculate Moving Average, but these 3 are the most simple and preferable one.

## SMA vs EMA ( A comparison )

#### Simple Moving Average

- Values
*each data*set equally *Slow response*to changing prices- Has a lower value when prices are rising and falls slowly when prices are declining
- Weights are
*equally distributed* - Oldest data is replaced by the newest one

**Exponential Moving Average **

- Puts more emphasis on the
*recent data*set. *Responds very quickly*to changing prices- Has a higher value when price is rising and falls faster when prices are declining
- Weights are given according to the
*relevance of the data.*New data gets more preference - The newest data is added but the old data is not thrown out

## Frequently Asked Questions

1. Why are moving averages calculated ?

Moving averages are calculated to analyse and comprehend the past position of a Crypto before investing or making a move in the market in order to save yourself from major losses.

2. What are examples of Moving Average ?

There are various kinds of Moving Averages. Some of them are SMA, WMA and EMA. Among these also, there are different time periods, like 10 day moving average or 50 day moving average.

3. What are examples of Moving Average indicators ?

Bollinger Band and MACD.

4. Is the trend analysis valid ?

The basic aim of moving average is to estimate the trend of a crypto. The method is basic but effective. Moving averages has been a go-to choice for investors due to it’s effective results and an excellent tool for trend confirmations. A long term moving average confirms a bullish trend whereas a short term moving average implies a bearish trend.

5. How does the moving average identify support and resistance?

An uptrend moving average shows support, i.e. good position of crypto in the market. A downtrend moving average gives resistance, i.e. the crypto market is falling.

## Moving Average: Should you trust the Indicator?

Moving Average is a technical analyst indicator so it is always advisable to use it with caution. No indicator promises to bear 100% effective results. Any knowledgeable and experienced technical analyst would know not to completely trust the moving average to make their next trading move. But this doesn’t justify the usefulness of moving averages. They are helpful to an extent and can sometimes give out the best results. It’s just a game of price, volume and time.