Exponential Moving Average

Exponential Moving Average Quotes

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Moving Average Quotes


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Moving averages are one of the most basic and frequently used indicators in technical analysis. The moving averages smoothes data by making it easier to analyze, especially in volatile markets. They also are used in creating many other technical indicators and overlays.


Delayed Quotes - U.S. Market open in 2 hours and 5 minutes.
IndexTime (ET)LastChange5-day
MA
10-day
MA
20-day
MA
50-day
MA
130-day
MA
260-day
MA
Charts
Exchange Indexes
05/21/2013 16:002,435.3410.292,433.022,435.842,422.332,399.592,391.022,380.22Chart
05/21/2013 16:009,598.5610.829,560.449,506.879,380.629,188.498,830.718,386.12Chart
DOW Indexes
05/21/2013 16:005,257.9512.775,243.065,209.265,154.785,065.424,773.094,588.42Chart
05/21/2013 16:0015,388.5852.9215,317.1315,219.7115,023.6114,760.2013,991.5813,490.73Chart
05/21/2013 16:006,519.008.016,513.156,450.026,310.136,196.995,795.755,433.55Chart
05/21/2013 16:00515.480.81515.01514.49522.75514.50482.66479.14Chart
S&P Indexes
05/21/2013 16:00832.441.34820.52814.77800.59788.84761.55728.93Chart
05/21/2013 16:00199.870.51198.45195.63191.33185.72174.85162.21Chart
05/21/2013 16:00748.901.61745.44739.68729.15713.52682.42658.78Chart
05/21/2013 16:001,214.812.561,208.901,199.221,176.791,151.401,090.431,024.76Chart
05/21/2013 16:001,669.182.911,662.131,648.771,623.131,586.401,510.991,447.92Chart
05/21/2013 16:00562.510.82558.87553.26541.05530.04503.78260.59Chart
05/21/2013 16:00578.552.67576.80573.03561.96543.93507.30478.36Chart
05/21/2013 16:00415.550.06418.20415.62412.97404.54377.16363.59Chart
05/21/2013 16:00493.995.04491.82487.83481.94471.07435.24410.78Chart
05/21/2013 16:00442.860.47439.52435.48425.86418.16400.57379.53Chart
05/21/2013 16:00434.410.78433.34430.58423.34414.92402.62388.23Chart
05/21/2013 16:00320.570.89319.80317.66312.34305.70297.81295.88Chart
05/21/2013 16:00404.410.45404.20403.11408.41401.06376.79372.87Chart
Russell Indexes
05/21/2013 16:00926.081.64921.87914.78900.58880.48837.95800.74Chart
05/21/2013 16:00998.780.84993.37983.79964.15946.72899.18850.82Chart
05/21/2013 16:00992.511.68987.93980.19964.64943.43897.71857.21Chart
Sector Indexes
05/21/2013 16:00253.747.23254.80266.40272.85304.55368.88409.77Chart
05/21/2013 16:001,420.520.801,405.251,397.031,379.871,353.801,309.051,253.52Chart
05/21/2013 16:0083.820.0483.8983.4182.8482.7281.2681.33Chart
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About Moving Averages

There are two types of moving averages - simple moving average (SMA or MA) and exponential moving average (EMA).

A simple moving average is the average price of a security over a specified number of periods. Thus, MA (5) represent the average security price over the last 5 bars, MA (20) is the average security price over the last 20 bars, etc.

An exponential moving average can be calculated as a percent-based EMA or as a period-based EMA. The formula for an exponential moving average is:

Current EMA = (Current Price - Previous EMA)  x Multiplier + Previous EMA

For a percentage-based EMA, the "Multiplier" is equal to the EMA's specified percentage. For a period-based EMA, the "Multiplier" is equal to 2 / (1 + N) where N is the specified number of periods.

In the quotes table above, we have period-based exponential moving averages that are calculated by following formulas:

EMA(5) = (2/(5 +1)) x (Close - Previous EMA) + Previous EMA
EMA(10) = (2/(10+1)) x (Close - Previous EMA) + Previous EMA
EMA(20) = (2/(20+1)) x (Close - Previous EMA) + Previous EMA
EMA(50) = (2/(50+1)) x (Close - Previous EMA) + Previous EMA
EMA(130) = (2/(130+1)) x (Close - Previous EMA) + Previous EMA
EMA(260) = (2/(260+1)) x (Close - Previous EMA) + Previous EMA

In selection of the bar period for the exponential moving average in the quotes table above, the following principles were used:

One calendar week has 5 trading days and a 5-day exponential moving average would represent a 1-week trend analysis.
EMA (10) would represent 2 weeks of trend analysis.
EMA (20) would represent a 4-week or approximately 1 month trend analysis.
EMA (50) would represent a 10-week or approximately 2 months trend analysis.
EMA (130) would represent a 26-week or approximately 6 months trend analysis.
EMA (260) would represent a 52-week or approximately a 1-year trend analysis.

Furthermore, the quotes table above would cover technical analyses from short-term trends up to 1-year long-term trends.

How to Use Moving Averages

Moving averages are the simplest tools in technical analysis. One of the basic ways to analyze a moving average is to define its direction. If the moving average is rising, the analyzed security is considered to be in an up-trend up. If the moving average is declining, the analyzed security is considered to be in a down-trend.

Another way of doing technical analysis based on the moving average is to identify a moving average location in relation to the price. This is one of the most commonly used techniques to define a basic trend. If the price moves above the moving average, the price trend is considered to be bullish (an up-trend). Conversely, if the price moves below the moving average, the trend is considered to be bearish (a down-trend). In our quotes table above, we use this method - the green exponential moving average value (quote) indicates that the EMA is located below the index price and point to a Bullish sentiment. Specifically, the red exponential moving average value (quote) indicates that the EMA is located above the index price by pointing to the Bearish sentiment.

A third way of using moving averages in technical analysis involves identifying the location of the fast (shorter-term) moving average in relation to the slow (longer-term) moving average. If the fast moving average moves above the slow moving average, the trend is considered to be Bullish. If the fast moving average is below the slow moving average, the trend is considered to be Bearish. This technique is equivalent to the MACD analysis. The MACD is calculated as the difference between fast and slow moving averages. While analysis of two moving averages could be done visually, the MACD analysis enables you to do it visually and have a numerical representation of the fast moving average location in relation to the slow moving average.

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