The Moving Average indicator gives you the average or mean value of the price for a specific period of time. There are four different types of Moving Averages that are commonly considered. Traders use the following Moving Averages to guide their buying and selling decisions:

- Linear weighted
- Simple or arithmetic
- Exponential
- Smoothed

The Moving Average indicator is helpful because it allows you to average the price for an asset for a given period. This gives you a better picture of what’s happening than data on prices that may seem initially, to be within a large range.

You can use the Moving Average indicator with any type of data set, as long as that data set is sequential. This includes opening and closing prices or even trading volume. Moving Averages of different types can diverge from each other but only in cases where different weight coefficients are used.

Traders always compare the price line to its Moving Averages. When the price line moves above the Moving Average indicator that is interpreted as a signal to buy. If the price falls below its Moving Average indicator, that’s a sell signal.

The Moving Average indicator is not used to tell you the best time to enter or exit. However, they help you to conduct transactions and benefit from the trend. This means that you can sell soon after prices have reached their peak, although you won’t be able to sell at the exact peak because of the inherent delay in a Moving Average.

## Simple Moving Average (SMA)

The Simple Moving Average is the arithmetic average that’s calculated by adding the recent price data and dividing that by the number of periods. For example, a five-day simple Moving Average adds the five most recent closing prices and divides that by five. This provides you with a new average for each day during the period that you’re analyzing.

### Calculation of Simple Moving Average (SMA)

When calculating SMA, you’ll notice that short-time averages are able to react more quickly when the underlying security changes price.

The following formula is used to calculate Simple Moving Average (SMA)

:SMA = SUM(CLOSE, N) / N

This symbol is used in the Simple Moving Average (SMA) formula:

N – is the number of calculation periods.

## Exponential Moving Average (EMA)

The Exponential Moving Average indicator uses the exponential window function to smooth time series data. There’s another important difference between it and the SMA. The SMA gives equal weight to each past observation. However, the EMA assigns different weights to each, These weights decrease exponentially over time.

### Calculation of Exponential Moving Average (EMA)

The following formula is used to calculate Exponential Moving Average (EMA) indicator:

EMA = (CLOSE(i) * P) + (EMA(i – 1) * (100 – P))

These symbols are used in the Exponential Moving Average (EMA) formula:

CLOSE(i) – the price of the current period closure;

EMA(i-1) – Exponentially Moving Average of the previous period closure;

P – the percentage of using the price value.

## Smoothed Moving Average (SMMA)

The Smoothed Moving Average (SMMA) indicator aims to reduce noise. It does this by using a long lookback period and by considering all of the prices during that time.

### Calculation of Smoothed Moving Average indicator

The following formula is used to calculate Smoothed Moving Average indicator :

The Smoothed Moving Average formula can be simplified as a result of arithmetic manipulations: SMMA (i) = (SMMA(i – 1) * (N – 1) + CLOSE (i)) / N

The smoothed moving average uses several succeeding simple moving averages. The first moving average is calculated as the simple moving average (SMA): SUM1 = SUM(CLOSE, N) SMMA1 = SUM1/N

The second and succeeding moving averages are calculated according to this formula:

PREVSUM = SMMA(i – 1) * N

SMMA(i) = (PREVSUM – SMMA(i – 1) + CLOSE(i)) / N

These symbols are used in the simplified formula and the calculation of each Simple Moving Average indicator:

SUM1 – is the total sum of closing prices for N periods;

PREVSUM – smoothed sum of the previous bar;

SMMA1 – is the smoothed moving average of the first bar;

SMMA(i) – is the smoothed moving average of the current bar (except for the first one);

CLOSE(i) – is the current closing price;

N – is the smoothing period.

## Linear Weighted Moving Average (LWMA)

The Linear Weighted Moving Average indicator lets you calculate the average price of the instrument over time. It gives more weight to recent data than older data and helps you to analyze the trend in the market.

Traders use this indicator to confirm an uptrend. If the price is above the LMMA but the LMMA is rising, that means the market is in an uptrend. If the price is under the LMMA and the LMMA is going down, the market is in a downtrend.

Traders should always be alert to points when the lines cross. if the LMMA line crosses the price line, it could mean that the trend is about to change. The lookback period that’s being used will tell you how closely the indicator is tracking movements in the market.

For example, a lookback period of five usually tracks price very closely. In this context, even small price fluctuations will cause the lines to cross. If you have a 100-period lookback, you’ll be more likely to determine longer-term trends or long-term changes in the current trends.

### Calculation of Linear Weighted Moving Average (LWMA)

Linear Weighted Moving Average (LWMA) indicator applies more weight to more recent data than previous data. It does this by multiplying the closing prices by a weighted coefficient.

The following formula is used to calculate Linear Weighted Moving Average (LWMA) indicator:

LWMA = SUM(Close(i)*i, N) / SUM(i, N)

These symbols are used in the formula:

SUM(i, N) – is the total sum of weight coefficients.