EMA and SMA - Moving Averages Explained

 Simple and Exponential Moving Averages

We all are taught the basic average in our early school days. However, there are more advance methods of calculating averages like Simple Moving Averages (SMA), Daily Moving Averages (DMA), Exponential Moving Averages (EMA), particularly used time series data. Stock prices are example of time series data as each stock has a price associated with it at any given time and with time the price changes.

The moving averages are building blocks for various technical indicators used in stock market analysis like MACD (Moving Average Convergence Divergence), Moving Averages Crossovers, Bollinger Bands etc. Moreover, moving averages can be used to estimate one of the Support and Resistance levels. 

Simple Moving Average

For time series data, we often use moving averages i.e. taking averages in a time window (like hourly, daily, etc) and the time window moves with time. This moving average on a rolling window is called Simple Moving Average (SMA). When the moving average is calculated on a daily basis it is called Daily Moving Average (DMA).

Let us understand with an example what do we mean with moving time window. Suppose you have 30 day data (like closing price of a stock) and you want to calculate the 5 day moving average of the closing price. Since its a 5 day moving average (DMA), the average will start from the 5th day and it will be (Sum of 1st 5 days closing price / 5), similarly on 6th day the 5-DMA will be (Sum of closing price from 2nd day to 6th day / 5), on 7th day the 5-DMA will be (Sum of closing price from 3rd day to 7th day / 5) and so on until 30th day. 

 

As the DMA, which is calculated on daily basis, SMA can be calculated for a time window like 15-minutes, 1-hour, 4-hours rolling window.

StoxFactor provides multiple window DMA data for all the future and options stocks and indexes in the dashboard.

 

Exponential Moving Average

In case of simple moving averages, all the time frames like days in case of DMA are given equal weight or are treated equally. However, in case of Exponential Moving Average (EMA), the latest time frame is given more weight compared to older data. For example, in case of 5 day EMA, the 5th day will have more weight or importance compared to 1st day in the time window. 

EMA assigns more importance to the most recent stock price. In stock market any recent events or forthcoming events are priced in, therefore EMA makes more sense in case of analyzing stock prices.

The mathematical calculation for EMA is simple but time consuming, therefore StoxFactor provides pre-computed EMA data for stocks and indexes.

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