{"id":15267,"date":"2021-12-20T17:25:29","date_gmt":"2021-12-20T17:25:29","guid":{"rendered":"https:\/\/www.5paisa.com\/finschool\/?p=15267"},"modified":"2025-03-26T16:22:12","modified_gmt":"2025-03-26T10:52:12","slug":"technical-analysis-understanding-moving-averages","status":"publish","type":"post","link":"https:\/\/www.5paisa.com\/finschool\/technical-analysis-understanding-moving-averages\/","title":{"rendered":"Technical Analysis: Understanding Moving Averages"},"content":{"rendered":"\t\t
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Moving Averages<\/span><\/strong><\/h5>
  • Moving average is a widely used technical indicator of stock prices\u00a0that helps to smooth out\u00a0the volatility in the price action\u00a0by filtering out the noise from random price fluctuations. A moving average is a trend-follow lagging indicator as it is calculated taking past data into consideration. \u00a0As its name suggests, a moving average is an average that moves as old values are dropped out as new values become available. Moving averages can be employed to identify the current trend in a script.<\/span><\/li><\/ul>
    Types of moving averages<\/span><\/strong><\/h5>

    There are 3 types of moving averages<\/span><\/p>

    a)\u00a0Simple moving average\u00a0(SMA)<\/span><\/strong><\/p>

    • It is obtained by computing the simple average of price data over a defined period of time. In general, we compute the simple moving average based on the closing price of the security as it is considered to have more significance as compared to the rest of price points (Namely open\/high\/low price for the day). Thus, a 5-day SMA is calculated by adding the closing price of 5 days and dividing this sum by the total number of days (in this case, five).<\/span><\/li><\/ul>

      For example, the 5 days SMA of ITC is calculated as follows:<\/span><\/strong><\/span><\/p>

      • While calculating the Moving Average after the close of the trading session on July 7, 2017, we can compute the SMA value by taking the closing price of the last 5 trading session, including July 7, 2017, and dividing the same by 5. At close of the next trading session on July 10, 2017, SMA is calculated by excluding the Closing Price of July 3, 2017 by adding the new data point. (Closing Price of July 10, 2017).<\/span><\/li>
      • As illustrated in the example below, prices gradually decreases from 342.5 to 328.85 over a period of eight days in the same timeframe the 5 Period SMA decreases from 336.44 to 332.79, indicating a lag associated with the Moving Averages. Hence, larger the time period, larger is the lag.<\/span><\/li><\/ul>

        \u00a0<\/span><\/p>

        Date<\/span><\/p><\/td>

        Close Price<\/span><\/p><\/td>

        5 Period SMA<\/span><\/p><\/td><\/tr>

        03-Jul-17<\/span><\/p><\/td>

        342.5<\/span><\/p><\/td>

        \u00a0<\/span><\/p><\/td><\/tr>

        04-Jul-17<\/span><\/p><\/td>

        337.25<\/span><\/p><\/td>

        \u00a0<\/span><\/p><\/td><\/tr>

        05-Jul-17<\/span><\/p><\/td>

        331.05<\/span><\/p><\/td>

        \u00a0<\/span><\/p><\/td><\/tr>

        06-Jul-17<\/span><\/p><\/td>

        337.10<\/span><\/p><\/td>

        \u00a0<\/span><\/p><\/td><\/tr>

        07-Jul-17<\/span><\/p><\/td>

        334.30<\/span><\/p><\/td>

        336.44<\/span><\/p><\/td><\/tr>

        10-Jul-17<\/span><\/p><\/td>

        333.30<\/span><\/p><\/td>

        334.60<\/span><\/p><\/td><\/tr>

        11-Jul-17<\/span><\/p><\/td>

        330.40<\/span><\/p><\/td>

        333.23<\/span><\/p><\/td><\/tr>

        12-Jul-17<\/span><\/p><\/td>

        328.85<\/span><\/p><\/td>

        332.89<\/span><\/p><\/td><\/tr><\/tbody><\/table>

        7TH July SMA = 336.44=\u00a0(342.50+337.25+331.05+337.10+334.30)
        \u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a05\u00a0<\/span><\/p>

        10th July SMA =334.6=\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0(337.25+331.05+337.10+334.30+333.30)
        \u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a05\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0
        11th July SMA= 333.23= \u00a0\u00a0(331.05+337.10+334.30+333.30+330.40)
        \u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a05
        12th July WMA= 332.89= \u00a0\u00a0\u00a0(337.10+334.30+333.30+330.40+328.85)
        \u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a05<\/span><\/p>

        b)\u00a0Weighted moving average\u00a0(WMA)<\/strong>
        <\/span><\/p>

        • Weighted moving average moves a step ahead from simple moving average. Here, we assign a weight to each value, with a bigger weight assigned to the most recent data points as they are more relevant than historical data points. The sum of weights should add up to 1 (or 100%). As new data points are added, the new weights will align accordingly. In contrast, in simple moving average, each value is assigned the same weight. Ideally, traders calculate WMA on the basis of closing price.<\/span><\/li>
        • The weighted moving average is calculated by multiplying the given price by its assigned weight and then dividing the sum by total number of days. The weights assigned are subjective in nature, and it is based on the discretion of the trader. Because of its calculation methodology, WMA will follow prices more closely than a corresponding SMA. The WMA reduces the lag effect to an extent.<\/span><\/li><\/ul>

          \u00a0<\/span><\/p>


          Date<\/span><\/span><\/p><\/td>

          Close Price<\/span><\/p><\/td>

          Weights<\/span><\/p><\/td>

          WMA<\/span><\/p><\/td><\/tr>

          03-Jul-17<\/span><\/p><\/td>

          342.5<\/span><\/p><\/td>

          0.07<\/span><\/p><\/td>

          \u00a0<\/span><\/p><\/td><\/tr>

          04-Jul-17<\/span><\/p><\/td>

          337.25<\/span><\/p><\/td>

          0.13<\/span><\/p><\/td>

          \u00a0<\/span><\/p><\/td><\/tr>

          05-Jul-17<\/span><\/p><\/td>

          331.05<\/span><\/p><\/td>

          0.20<\/span><\/p><\/td>

          \u00a0<\/span><\/p><\/td><\/tr>

          06-Jul-17<\/span><\/p><\/td>

          337.10<\/span><\/p><\/td>

          0.27<\/span><\/p><\/td>

          \u00a0<\/span><\/p><\/td><\/tr>

          07-Jul-17<\/span><\/p><\/td>

          334.30<\/span><\/p><\/td>

          0.33<\/span><\/p><\/td>

          335.34<\/span><\/p><\/td><\/tr>

          10-Jul-17<\/span><\/p><\/td>

          333.30<\/span><\/p><\/td>

          \u00a0<\/span><\/p><\/td>

          334.29<\/span><\/p><\/td><\/tr>

          11-Jul-17<\/span><\/p><\/td>

          330.40<\/span><\/p><\/td>

          \u00a0<\/span><\/p><\/td>

          332.89<\/span><\/p><\/td><\/tr>

          12-Jul-17<\/span><\/p><\/td>

          328.85<\/span><\/p><\/td>

          \u00a0<\/span><\/p><\/td>

          331.43<\/span><\/p><\/td><\/tr><\/tbody><\/table>

          \u00a0<\/span><\/p>

          7TH July WMA = 335.34=\u00a0(342.50*0.07+337.25*0.13+331.05*0.20+337.10*0.27+334.3*0.33)
          \u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a05<\/span><\/p>

          10th July WMA =334.29=\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0(337.25*0.07+331.05*0.13+337.10*0.20+334.3*0.27+333.3*0.33)
          \u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a05
          11th July WMA= 332.89= \u00a0\u00a0(331.05*0.07+337.10*0.13+334.30*0.20+333.3*0.27+330.4*0.33)
          \u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a05
          12th July WMA= 331.43= \u00a0\u00a0\u00a0(337.1*0.07+334.30*0.13+333.30*0.20+330.4*0.27+328.85*0.33)
          \u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a05<\/span><\/p>

          C)\u00a0Exponential moving average\u00a0(EMA)<\/strong><\/p>