## Moving Averages: What You Need to Know

Knowing when to open and close a trade can be one of the best ways to increase your earnings and avoid trading collapse. To achieve this, you will be needing some technical indicators designed to help investors determine the trend direction of securities. One of the useful tools that can assist you with this technical analysis is looking at Moving Averages.

A moving average is an important tool that every investor should consider using today. With a moving average, you can be able to predict the market flow and the direction of trends easily. But what exactly is a moving average and how do you use them?

Read on to learn what they are, how they are calculated, types and benefits.

### What is a Moving Average?

A moving average is a data analysis approach that involves calculating the averages of distinct subsets of the complete data set. It is a technical indicator that creates a single trend line by combining the price points of an instrument over a set time frame. Dividing the sum by the number of data points will give you the moving average you can use to predict the next market movement.

Additionally, it’s a lagging indicator that uses a strategy to acquire a general sense of the trends in a data set, but what is a trend? A trend, as you would want to know, refers to market trading research of previous market movements. It allows you to anticipate what will happen to the market in the future.

### Types of Moving Averages

The simple and the exponential moving average are the common types of moving average.

#### Simple Moving Average

A **Simple Moving Average** is created by finding the arithmetical mean for a group of variables at different intervals over a specified period. The formula for calculating the security’s simple moving average is as follows:

SMA= A1 +A2 +…+An / n

where:

A=Average in period n

n=Number of periods

#### Exponential Moving Average

On the other hand, the **Exponential Moving Average (EMA**) provides considerable value to recent prices to make it more sensitive to fresh data.

In comparison to a simple moving average, the EMA provides more weight to recent data points. Calculate the simple moving average (SMA) over a given period before calculating the EMA.

The formula for calculating an exponential moving average is as follows:

EMA = K x ( C.P – P.EMA) + P.EMA

Where K = 2/(n+1), with “n” the selected time period.

C.P = current price

P.EMA = previous exponential moving average

### Calculating a Simple Moving Average

You can calculate a moving average by adding stock prices and dividing the amount by the number of periods yields. You can understand this as obtaining the average mean of a dataset.

Consider the case below: You have a sales dataset that spans the years 2012 through 2020. If you want to create a moving average for this data collection, you may specify the intervals for the moving average. Let’s compute the three-year moving interval using this dataset example.

Year |
Price($m) |

2012 |
6 |

2013 |
4 |

2014 |
5 |

2015 |
3 |

2016 |
7 |

2017 |
4 |

2018 |
8 |

2019 |
7 |

2020 |
5 |

At any moment in time, the formula for a simple moving average can be calculated by taking the average of a specific number of periods up to that point.

Using;

M.A = (A1 + A2 + …… + An) / n

Where A = prices per year

three-year years

**First interval**

Choosing a three year interval = 2012, 2013, 2014

M.A = 6 + 4 + 5 / 3

**M.A** = 5.0

**Second interval**

Choosing another three-year interval= 2015, 2016, 2017

M.A = 3 + 7 + 4 / 3

**M.A** = 4.7

**Third interval**

2018, 2019, 2020

M.A = 8 + 7 + 5 / 3

**M.A** = 6.7

**Note**: You may simply estimate the likely market direction of the next three years’ interval using these moving averages: **5.0**, **4.7**, and **6.7.0**

### Conclusion

In technical stock market analysis, a moving average can benefit you more because it smooths data and provides a clearer visual picture of the current trend.

### Some links that may help you

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