Binary Options with Exponential Moving Averages
One of the best technical analysis tools once you get used to them are trading with exponential moving averages. They are a great indicator of the strength of the market and they also help a trader measure price trends. These moving averages reflect the average price of an asset as it appears in various time frames.
Exponential Moving Averages may be controlled at times which makes them ideal for use in technical analysis. The data they generate measures trends when it is compared with price. That is the reason why more recent data is considered stronger to base trades on when using exponential moving averages. They are widely considered a more powerful indicator than regular moving averages because a regular moving average tends to value all data the same.
An exponential moving average will usually make use of a thirty day exponential moving average and its association with a set of two time frames. The two time frames are never the same and the first time frame is always longer than the other. If a trader is using a twenty four hour chart and the asset price is above a thirty bar, it indicates a bullish trend. When below the thirty bar a bearish trend is indicated.
One thing to note; you have to be very aware of asset price as it relates to the long term trend. An example of this is if the price has been above the moving average for a long period of time, it may signal that resistance will take place in the very near future.
Once you have determined an underlying trend will likely not hit resistance, and then take a look at the thirty minute bars. Go back and look at price action over the past two weeks and see if you can determine if support and resistance levels the past two to three days can be verified. If a bullish trend is indicated it’s a good time to make the purchase when an asset price comes from below to cross a bar or has been above it and goes down a little.
Once you learn how to read it, you can trade very successfully when you using exponential moving averages.
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