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Moving Average

A moving average is a plot of the average price of the security over time. A moving average makes it easier to see the actual trend in the prices. The average can be computed over different intervals. A 30 day simple moving average uses an average over the previous 30 days. Thus, moving averages are a smoothing of the recent price history. They are used as short-term, intermediate-term, and long-term trend indicators.

Moving Averages are also used to generate buy or sell signals when prices cross over the moving average or when one moving average crooses over another moving average. When prices, which were below the moving average, close above it, a buy signal is generated. When prices, which were above the moving average, close below it, a sell signal is generated. However, traders must be careful that they don't get whiplashed by false signals as prices oscillate around the moving average in a consolidation phase. The use of longer term moving averages helps to minimize this efect, but at the cost of delayed buy and sell signals. If the trend doesn't last more than twice the length of the moving average, you can lose money by trading this method.

Moving averages fall into different categories depending on the type of filtering that is used. When using moving average cossovers, a buy signal is generated when the fast (shorter term) moving average crosses above the slow (longer term) moving average. Similarly, a sell signal is generated when the fast MA crosses below the slow MA. Whiplash in MA crossovers can be minimized by increasing the difference in the time frames of the moving averages that are used.

A simple moving average gives equal weight to each price point. A 30-day simple moving average computes the average closing price over the last 30 days (Add the last thirty closing prices and divide by 30). A simple moving average is easy to understand and compute, which makes it widely used. However, it gives as much importance to past prices as recent price history, which can give a distorted picture if the moving average is over a long period of time or when it covers a large price movement during the period of interest. With a simple moving average, a past price can have a large impact when it is dropped from the moving average at the end of the moving average period.

A weighted moving average improves the simple moving average, by giving more weight to recent data. Thus, it appropriately gives more importance to recent price action while still accounting for the price history that produced the recent prices. It is still easy to understand. It is a little more difficult to compute, but there are many internet sites that do this for you. Since past data is weighted less, there is less of an impact when a data point is dropped from the moving average, but there is still an impact.

An exponential moving average improves the weighted moving average by weighting past history less and less, without ever removing the data completely. So it eliminates the impact when a data point is dropped from the moving average. It still appropriately gives the highest weighting to most recent data. However, this moving average is harder to understand than the simple moving average, so it is not as widely used.

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