What is Simple Moving Average?

Trend is your best Friend

What is simple moving average?

A Simple moving average  is a tool used in technical analysis to know about the nature of the trend. As they say trend is your best friend therefore awareness regarding the same helps in accurate buying and selling opportunities in the stock market.

How to Use Simple Moving Average?

A Simple Moving Average (SMA) helps you see the trend’s direction. If the price is above the SMA, it suggests an uptrend, so you might consider buying stocks. Conversely, if the price is below the SMA, it suggests a downtrend, so you might think about selling stocks short.

But remember, while SMAs can be helpful, especially long-term ones, they’re not perfect. Long-term SMAs smooth out random ups and downs, making them more reliable. However, short-term SMAs might give you false signals to buy or sell because they’re influenced by more immediate price changes. So, use SMAs as a guide, but don’t rely on them entirely.

Sure, here’s a simpler explanation:

Long-term Simple Moving Averages (like 50 or 100-day SMAs) are better at giving reliable signals because they smooth out fluctuations in prices over a longer period. They’re like a slow-moving ship that gives you a steady indication of where the market is heading.

On the other hand, short-term SMAs react more quickly to recent price changes, which means they can give signals more often. However, this can also lead to more false signals because they’re easily influenced by short-term fluctuations.

But here’s the catch: Short-term SMAs are less likely to lag behind the current market conditions compared to long-term SMAs. Long-term SMAs might be slower to catch up with sudden market movements because they’re looking at a broader picture of price movements over a longer period.

So, when you see a trend already starting strongly, the shorter-term SMAs might catch on quicker, while the longer-term SMAs might take a bit longer to show the same trend.

What are the types of moving average?

Simple moving average

A Simple Moving Average (SMA) is a way to figure out the average price of something over a certain period. You do this by adding up the recent prices and then dividing that total by the number of time periods you’re looking at.

Weighted average

In a weighted average, all the closing prices aren’t treated equally. We give more importance to the most recent ones. For example, if we’re calculating a weighted average over 10 days, we multiply the 10th day’s closing price by 10, and the 9th day’s closing price by 9, and so on.

Exponential average

EMA stands for Exponential Moving Average. It’s a type of moving average that gives more weight to recent data points, making it more responsive to recent price changes compared to a simple moving average (SMA).

In simple terms, EMA calculates the average price of a stock, currency, or any other financial asset over a certain period of time, but it gives more importance to the most recent prices. This means that as new data comes in, the EMA reacts more quickly to reflect any changes in the trend of the asset’s price.

EMA is widely used in technical analysis to identify trends, reversals, and potential entry or exit points for trading. It’s calculated using a formula that takes into account the smoothing factor, the previous EMA value, and the current closing price.

Calculation Of EMA

To calculate the Exponential Moving Average (EMA) for a series of data points, follow these steps:

1. Choose a period: Decide on the number of periods you want to consider for your EMA calculation. This could be 10 days, 20 days, etc.

2. Calculate the SMA: Start by calculating the Simple Moving Average (SMA) for the first period. This is done by adding up the closing prices of the first N periods and dividing by N, where N is the number of periods.

3. Calculate the smoothing factor (SF): The smoothing factor is calculated based on the chosen number of periods. It’s typically 2 divided by N+1. For example, if you’re using a 10-day EMA, the smoothing factor would be 2/(10+1) = 0.1818.

4. Calculate the EMA for subsequent periods; For each new data point after the first one, use the following formula:

   – EMA(today) = (Closing price(today) – EMA(yesterday)) * SF + EMA(yesterday)

   Where:

   – EMA(today) is the Exponential Moving Average for today’s period.

   – Closing price(today) is the closing price for today’s period.

   – EMA(yesterday) is the Exponential Moving Average from the previous period.

   – SF is the smoothing factor calculated in step 3.

5. Repeat step 4 for each new data point: Continue this process for each subsequent period in your dataset, using the EMA calculated for the previous period as part of the calculation for the current period.

6. Interpret the results: The resulting series of EMA values will give you a smoothed representation of the data, with more weight given to recent prices. This can help identify trends and changes in the underlying data more effectively than a simple moving average.

Calculation through Example.

Sure, let’s calculate the 5-day Exponential Moving Average (EMA) for a series of closing prices:

Closing prices:

Day 1: 20

Day 2: 22

Day 3: 21

Day 4: 24

Day 5: 23

We’ll use a smoothing factor (SF) of 0.33, which is calculated as 2 / (5 + 1).

1. Calculate the Simple Moving Average (SMA) for the first 5 days:

   SMA = (20 + 22 + 21 + 24 + 23) / 5

       = 110 / 5

       = 22

2. Use the SMA as the EMA for the first period:

   EMA(1) = SMA = 22

3. Now, let’s calculate the EMA for subsequent periods:

   Day 2:

   EMA(2) = (Closing price(2) – EMA(1)) * SF + EMA(1)

          = (22 – 22) * 0.33 + 22

          = 0 * 0.33 + 22

          = 22

   Day 3:

   EMA(3) = (Closing price(3) – EMA(2)) * SF + EMA(2)

          = (21 – 22) * 0.33 + 22

          = (-1) * 0.33 + 22

          = 21.67

   Day 4:

   EMA(4) = (Closing price(4) – EMA(3)) * SF + EMA(3)

          = (24 – 21.67) * 0.33 + 21.67

          = 2.33 * 0.33 + 21.67

          = 0.769 + 21.67

          = 22.439

   Day 5:

   EMA(5) = (Closing price(5) – EMA(4)) * SF + EMA(4)

          = (23 – 22.439) * 0.33 + 22.439

          = 0.561 * 0.33 + 22.439

          = 0.185 + 22.439

          = 22.624

So, the 5-day Exponential Moving Averages are:

Day 1: 22

Day 2: 22

Day 3: 21.67

Day 4: 22.439

Day 5: 22.624

Note—You don’t have to perform these tedious and exhausting calculation ,Just launch your trading platform and type EMA and you will have a curve plotted on chart.

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