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Simple Moving Averages Make Trends Stand Out Moving averages (MA) are one of the most popular and often-used technical indicators. The moving average is easy to calculate and, once plotted on a chart, is a powerful visual trend-spotting tool. You will often hear about three types of moving average: simple. exponential and linear. The best place to start is by understanding the most basic: the simple moving average (SMA). Lets take a look at this indicator and how it can help traders follow trends toward greater profits. (For more on moving averages, see our Forex Walkthrough .) Trendlines There can be no complete understanding of moving averages without an understanding of trends. A trend is simply a price that is continuing to move in a certain direction. There are only three real trends that a security can follow: An uptrend. or bullish trend, means that the price is moving higher. A downtrend. or bearish trend, means the price is moving lower. A sideways trend. where the price is moving sideways. The important thing to remember about trends is that prices rarely move in a straight line. Therefore, moving-average lines are used to help a trader more easily identify the direction of the trend. (For more advanced reading on this topic, see The Basics Of Bollinger Bands and Moving Average Envelopes: Refining A Popular Trading Tool .) Moving Average Construction The textbook definition of a moving average is an average price for a security using a specified time period. Lets take the very popular 50-day moving average as an example. A 50-day moving average is calculated by taking the closing prices for the last 50 days of any security and adding them together. The result from the addition calculation is then divided by the number of periods, in this case 50. In order to continue to calculate the moving average on a daily basis, replace the oldest number with the most recent closing price and do the same math. No matter how long or short of a moving average you are looking to plot, the basic calculations remain the same. The change will be in the number of closing prices you use. So, for example, a 200-day moving average is the closing price for 200 days summed together and then divided by 200. You will see all kinds of moving averages, from two-day moving averages to 250-day moving averages. It is important to remember that you must have a certain number of closing prices to calculate the moving average. If a security is brand new or only a month old, you will not be able to do a 50-day moving average because you will not have a sufficient number of data points. Also, it is important to note that weve chosen to use closing prices in the calculations, but moving averages can be calculated using monthly prices, weekly prices, opening prices or even intraday prices. (For more, see our Moving Averages tutorial.) Figure 1: A simple moving average in Google Inc. Figure 1 is an example of a simple moving average on a stock chart of Google Inc. (Nasdaq:GOOG ). The blue line represents a 50-day moving average. In the example above, you can see that the trend has been moving lower since late 2007. The price of Google shares fell below the 50-day moving average in January of 2008 and continued downward. When the price crosses below a moving average, it can be used as a simple trading signal. A move below the moving average (as shown above) suggests that the bears are in control of the price action and that the asset will likely move lower. Conversely, a cross above a moving average suggests that the bulls are in control and that the price may be getting ready to make a move higher. (Read more in Track Stock Prices With Trendlines .) Other Ways to Use Moving Averages Moving averages are used by many traders to not only identify a current trend but also as an entry and exit strategy. One of the simplest strategies relies on the crossing of two or more moving averages. The basic signal is given when the short-term average crosses above or below the longer term moving average. Two or more moving averages allow you to see a longer term trend compared to a shorter term moving average it is also an easy method for determining whether the trend is gaining strength or if it is about to reverse. (For more on this method, read A Primer On The MACD .) Figure 2: A long-term and shorter term moving average in Google Inc. Figure 2 uses two moving averages, one long-term (50-day, shown by the blue line) and the other shorter term (15-day, shown by the red line). This is the same Google chart shown in Figure 1, but with the addition of the two moving averages to illustrate the difference between the two lengths. Youll notice that the 50-day moving average is slower to adjust to price changes. because it uses more data points in its calculation. On the other hand, the 15-day moving average is quick to respond to price changes, because each value has a greater weighting in the calculation due to the relatively short time horizon. In this case, by using a cross strategy, you would watch for the 15-day average to cross below the 50-day moving average as an entry for a short position. Figure 3: A three-month The above is a three-month chart of United States Oil (AMEX:USO ) with two simple moving averages. The red line is the shorter, 15-day moving average, while the blue line represents the longer, 50-day moving average. Most traders will use the cross of the short-term moving average above the longer-term moving average to initiate a long position and identify the start of a bullish trend. (Learn more about applying this strategy in Trading The MACD Divergence .) Support is established when a price is trending downward. There is a point at which the selling pressure subsides and buyers are willing to step in. In other words, a floor is established. Resistance happens when a price is trending upward. There comes a point when the buying strength diminishes and the sellers step in. This would establish a ceiling. (For more explanation, read Support amp Resistance Basics .) In either case, a moving average may be able to signal an early support or resistance level. For example, if a security is drifting lower in an established uptrend, then it wouldnt be surprising to see the stock find support at a long-term 200-day moving average. On the other hand, if the price is trending lower, many traders will watch for the stock to bounce off the resistance of major moving averages (50-day, 100-day, 200-day SMAs). (For more on using support and resistance to identify trends, read Trend-Spotting With The AccumulationDistribution Line .) Conclusion Moving averages are powerful tools. A simple moving average is easy to calculate, which allows it to be employed fairly quickly and easily. A moving averages greatest strength is its ability to help a trader identify a current trend or spot a possible trend reversal. Moving averages can also identify a level of support or resistance for the security, or act as a simple entry or exit signal. How you choose to use moving averages is entirely up to you. An initial bid on a bankrupt company039s assets from an interested buyer chosen by the bankrupt company. From a pool of bidders. Article 50 is a negotiation and settlement clause in the EU treaty that outlines the steps to be taken for any country that. Beta is a measure of the volatility, or systematic risk, of a security or a portfolio in comparison to the market as a whole. A type of tax levied on capital gains incurred by individuals and corporations. Capital gains are the profits that an investor. An order to purchase a security at or below a specified price. A buy limit order allows traders and investors to specify. An Internal Revenue Service (IRS) rule that allows for penalty-free withdrawals from an IRA account. The rule requires that. Technical Analysis: Moving Averages Most chart patterns show a lot of variation in price movement. This can make it difficult for traders to get an idea of a securitys overall trend. One simple method traders use to combat this is to apply moving averages. A moving average is the average price of a security over a set amount of time. By plotting a securitys average price, the price movement is smoothed out. Once the day-to-day fluctuations are removed, traders are better able to identify the true trend and increase the probability that it will work in their favor. (To learn more, read the Moving Averages tutorial.) Types of Moving Averages There are a number of different types of moving averages that vary in the way they are calculated, but how each average is interpreted remains the same. The calculations only differ in regards to the weighting that they place on the price data, shifting from equal weighting of each price point to more weight being placed on recent data. The three most common types of moving averages are simple. linear and exponential. Simple Moving Average (SMA) This is the most common method used to calculate the moving average of prices. It simply takes the sum of all of the past closing prices over the time period and divides the result by the number of prices used in the calculation. For example, in a 10-day moving average, the last 10 closing prices are added together and then divided by 10. As you can see in Figure 1, a trader is able to make the average less responsive to changing prices by increasing the number of periods used in the calculation. Increasing the number of time periods in the calculation is one of the best ways to gauge the strength of the long-term trend and the likelihood that it will reverse. Many individuals argue that the usefulness of this type of average is limited because each point in the data series has the same impact on the result regardless of where it occurs in the sequence. The critics argue that the most recent data is more important and, therefore, it should also have a higher weighting. This type of criticism has been one of the main factors leading to the invention of other forms of moving averages. Linear Weighted Average This moving average indicator is the least common out of the three and is used to address the problem of the equal weighting. The linear weighted moving average is calculated by taking the sum of all the closing prices over a certain time period and multiplying them by the position of the data point and then dividing by the sum of the number of periods. For example, in a five-day linear weighted average, todays closing price is multiplied by five, yesterdays by four and so on until the first day in the period range is reached. These numbers are then added together and divided by the sum of the multipliers. Exponential Moving Average (EMA) This moving average calculation uses a smoothing factor to place a higher weight on recent data points and is regarded as much more efficient than the linear weighted average. Having an understanding of the calculation is not generally required for most traders because most charting packages do the calculation for you. The most important thing to remember about the exponential moving average is that it is more responsive to new information relative to the simple moving average. This responsiveness is one of the key factors of why this is the moving average of choice among many technical traders. As you can see in Figure 2, a 15-period EMA rises and falls faster than a 15-period SMA. This slight difference doesnt seem like much, but it is an important factor to be aware of since it can affect returns. Major Uses of Moving Averages Moving averages are used to identify current trends and trend reversals as well as to set up support and resistance levels. Moving averages can be used to quickly identify whether a security is moving in an uptrend or a downtrend depending on the direction of the moving average. As you can see in Figure 3, when a moving average is heading upward and the price is above it, the security is in an uptrend. Conversely, a downward sloping moving average with the price below can be used to signal a downtrend. Another method of determining momentum is to look at the order of a pair of moving averages. When a short-term average is above a longer-term average, the trend is up. On the other hand, a long-term average above a shorter-term average signals a downward movement in the trend. Moving average trend reversals are formed in two main ways: when the price moves through a moving average and when it moves through moving average crossovers. The first common signal is when the price moves through an important moving average. For example, when the price of a security that was in an uptrend falls below a 50-period moving average, like in Figure 4, it is a sign that the uptrend may be reversing. The other signal of a trend reversal is when one moving average crosses through another. For example, as you can see in Figure 5, if the 15-day moving average crosses above the 50-day moving average, it is a positive sign that the price will start to increase. If the periods used in the calculation are relatively short, for example 15 and 35, this could signal a short-term trend reversal. On the other hand, when two averages with relatively long time frames cross over (50 and 200, for example), this is used to suggest a long-term shift in trend. Another major way moving averages are used is to identify support and resistance levels. It is not uncommon to see a stock that has been falling stop its decline and reverse direction once it hits the support of a major moving average. A move through a major moving average is often used as a signal by technical traders that the trend is reversing. For example, if the price breaks through the 200-day moving average in a downward direction, it is a signal that the uptrend is reversing. Moving averages are a powerful tool for analyzing the trend in a security. They provide useful support and resistance points and are very easy to use. The most common time frames that are used when creating moving averages are the 200-day, 100-day, 50-day, 20-day and 10-day. The 200-day average is thought to be a good measure of a trading year, a 100-day average of a half a year, a 50-day average of a quarter of a year, a 20-day average of a month and 10-day average of two weeks. Moving averages help technical traders smooth out some of the noise that is found in day-to-day price movements, giving traders a clearer view of the price trend. So far we have been focused on price movement, through charts and averages. In the next section, well look at some other techniques used to confirm price movement and patterns. How to Use Moving Averages Moving averages help us to first define the trend and second, to recognize changes in the trend. Thats it. There is nothing else that they are good for. Any thing else is just a waste of time. I wont be getting into the gory details about how they are constructed. There are about a zillion websites that will explain the mathematical make-up of them. Ill let you do that on your own one day when you are extremely bored out of your mind But all you really have to know is that a moving average line is just the average price of a stock over time . Thats it. The two moving averages I use two moving averages: the 10 period simple moving average (SMA) and the 30 period exponential moving average (EMA). I like to use a slower one and a faster one. Why Because when the faster one (10) crosses over the slower one (30), it will often signal a trend change. Lets look at an example: You can see in the chart above how these lines can help you define trends. On the left side of the chart the 10 SMA is above the 30 EMA and the trend is up . The 10 SMA crosses down below the 30 EMA in mid August and the trend is down . Then, the 10 SMA crosses back up through the 30 EMA in September and the trend is up again - and it stays up for several months thereafter. Here are the rules: Focus on long positions only when the 10 SMA is above the 30 EMA. Focus on short positions only when the 10 SMA is below the 30 EMA. It doesnt get any simpler than that and it will ALWAYS keep you on the right side of the trend Note that moving averages only work well when a stock is trending - not when they are in a trading range. When a stock (or the market itself) becomes sloppy then you can ignore moving averages - they wont work Here are the important things to remember (for long positions - reverse for short positions.): The 10 SMA must be above the 30 EMA. There must be plenty of space in between the moving averages. Both moving averages must be sloping upward. The 200 period moving average The 200 SMA is used to separate bull territory from bear territory. Studies have shown that by focusing on long positions above this line and short positions below this line can give you a slight edge. You should add this moving averages to all of your charts in all time frames. Yes. weekly charts, daily charts, and intra-day (15 min, 60 min) charts. The 200 SMA is the most important moving average to have on a stock chart. You will be surprised at how many times a stock will reverse in this area. Use this to your advantage Also, when writing scans for stocks, you can use this as an additional filter to find potential long setups that are above this line and potential short setups that are below this line. Support and resistance Contrary to popular belief, stocks do not find support or run into resistance on moving averages. Many times you will hear traders say, Hey, look at this stock It bounced off of the 50 day moving average Why would a stock suddenly bounce off of a line that some trader put on a stock chart It wouldnt. A stock will only bounce (if you want to call it that) off of significant price levels that occurred in the past - not a line on a chart. Stocks will reverse (up or down) at price levels that are in close proximity to popular moving averages but they do not reverse at the line itself. So, suppose you are looking at a chart and you see the stock pulling back to, lets say, the 200 period moving average. Look at the price levels on the chart that proved to be significant support or resistance areas in the past. Those are the areas where the stock will likely reverse. Moving Averages - Simple and Exponential Moving Averages - Simple and Exponential Introduction Moving averages smooth the price data to form a trend following indicator. They do not predict price direction, but rather define the current direction with a lag. Moving averages lag because they are based on past prices. Despite this lag, moving averages help smooth price action and filter out the noise. They also form the building blocks for many other technical indicators and overlays, such as Bollinger Bands. MACD and the McClellan Oscillator. The two most popular types of moving averages are the Simple Moving Average (SMA) and the Exponential Moving Average (EMA) . These moving averages can be used to identify the direction of the trend or define potential support and resistance levels. Here039s a chart with both an SMA and an EMA on it: Simple Moving Average Calculation A simple moving average is formed by computing the average price of a security over a specific number of periods. Most moving averages are based on closing prices. A 5-day simple moving average is the five day sum of closing prices divided by five. As its name implies, a moving average is an average that moves. Old data is dropped as new data comes available. This causes the average to move along the time scale. Below is an example of a 5-day moving average evolving over three days. The first day of the moving average simply covers the last five days. The second day of the moving average drops the first data point (11) and adds the new data point (16). The third day of the moving average continues by dropping the first data point (12) and adding the new data point (17). In the example above, prices gradually increase from 11 to 17 over a total of seven days. Notice that the moving average also rises from 13 to 15 over a three day calculation period. Also notice that each moving average value is just below the last price. For example, the moving average for day one equals 13 and the last price is 15. Prices the prior four days were lower and this causes the moving average to lag. Exponential Moving Average Calculation Exponential moving averages reduce the lag by applying more weight to recent prices. The weighting applied to the most recent price depends on the number of periods in the moving average. There are three steps to calculating an exponential moving average. First, calculate the simple moving average. An exponential moving average (EMA) has to start somewhere so a simple moving average is used as the previous period039s EMA in the first calculation. Second, calculate the weighting multiplier. Third, calculate the exponential moving average. The formula below is for a 10-day EMA. A 10-period exponential moving average applies an 18.18 weighting to the most recent price. A 10-period EMA can also be called an 18.18 EMA. A 20-period EMA applies a 9.52 weighing to the most recent price (2(201) .0952). Notice that the weighting for the shorter time period is more than the weighting for the longer time period. In fact, the weighting drops by half every time the moving average period doubles. If you want to us a specific percentage for an EMA, you can use this formula to convert it to time periods and then enter that value as the EMA039s parameter: Below is a spreadsheet example of a 10-day simple moving average and a 10-day exponential moving average for Intel. Simple moving averages are straight forward and require little explanation. The 10-day average simply moves as new prices become available and old prices drop off. The exponential moving average starts with the simple moving average value (22.22) in the first calculation. After the first calculation, the normal formula takes over. Because an EMA begins with a simple moving average, its true value will not be realized until 20 or so periods later. In other words, the value on the excel spreadsheet may differ from the chart value because of the short look-back period. This spreadsheet only goes back 30 periods, which means the affect of the simple moving average has had 20 periods to dissipate. StockCharts goes back at least 250-periods (typically much further) for its calculations so the effects of the simple moving average in the first calculation have fully dissipated. The Lag Factor The longer the moving average, the more the lag. A 10-day exponential moving average will hug prices quite closely and turn shortly after prices turn. Short moving averages are like speed boats - nimble and quick to change. In contrast, a 100-day moving average contains lots of past data that slows it down. Longer moving averages are like ocean tankers - lethargic and slow to change. It takes a larger and longer price movement for a 100-day moving average to change course. The chart above shows the SampP 500 ETF with a 10-day EMA closely following prices and a 100-day SMA grinding higher. Even with the January-February decline, the 100-day SMA held the course and did not turn down. The 50-day SMA fits somewhere between the 10 and 100 day moving averages when it comes to the lag factor. Simple vs Exponential Moving Averages Even though there are clear differences between simple moving averages and exponential moving averages, one is not necessarily better than the other. Exponential moving averages have less lag and are therefore more sensitive to recent prices - and recent price changes. Exponential moving averages will turn before simple moving averages. Simple moving averages, on the other hand, represent a true average of prices for the entire time period. As such, simple moving averages may be better suited to identify support or resistance levels. Moving average preference depends on objectives, analytical style and time horizon. Chartists should experiment with both types of moving averages as well as different timeframes to find the best fit. The chart below shows IBM with the 50-day SMA in red and the 50-day EMA in green. Both peaked in late January, but the decline in the EMA was sharper than the decline in the SMA. The EMA turned up in mid February, but the SMA continued lower until the end of March. Notice that the SMA turned up over a month after the EMA. Lengths and Timeframes The length of the moving average depends on the analytical objectives. Short moving averages (5-20 periods) are best suited for short-term trends and trading. Chartists interested in medium-term trends would opt for longer moving averages that might extend 20-60 periods. Long-term investors will prefer moving averages with 100 or more periods. Some moving average lengths are more popular than others. The 200-day moving average is perhaps the most popular. Because of its length, this is clearly a long-term moving average. Next, the 50-day moving average is quite popular for the medium-term trend. Many chartists use the 50-day and 200-day moving averages together. Short-term, a 10-day moving average was quite popular in the past because it was easy to calculate. One simply added the numbers and moved the decimal point. Trend Identification The same signals can be generated using simple or exponential moving averages. As noted above, the preference depends on each individual. These examples below will use both simple and exponential moving averages. The term moving average applies to both simple and exponential moving averages. The direction of the moving average conveys important information about prices. A rising moving average shows that prices are generally increasing. A falling moving average indicates that prices, on average, are falling. A rising long-term moving average reflects a long-term uptrend. A falling long-term moving average reflects a long-term downtrend. The chart above shows 3M (MMM) with a 150-day exponential moving average. This example shows just how well moving averages work when the trend is strong. The 150-day EMA turned down in November 2007 and again in January 2008. Notice that it took a 15 decline to reverse the direction of this moving average. These lagging indicators identify trend reversals as they occur (at best) or after they occur (at worst). MMM continued lower into March 2009 and then surged 40-50. Notice that the 150-day EMA did not turn up until after this surge. Once it did, however, MMM continued higher the next 12 months. Moving averages work brilliantly in strong trends. Double Crossovers Two moving averages can be used together to generate crossover signals. In Technical Analysis of the Financial Markets. John Murphy calls this the double crossover method. Double crossovers involve one relatively short moving average and one relatively long moving average. As with all moving averages, the general length of the moving average defines the timeframe for the system. A system using a 5-day EMA and 35-day EMA would be deemed short-term. A system using a 50-day SMA and 200-day SMA would be deemed medium-term, perhaps even long-term. A bullish crossover occurs when the shorter moving average crosses above the longer moving average. This is also known as a golden cross. A bearish crossover occurs when the shorter moving average crosses below the longer moving average. This is known as a dead cross. Moving average crossovers produce relatively late signals. After all, the system employs two lagging indicators. The longer the moving average periods, the greater the lag in the signals. These signals work great when a good trend takes hold. However, a moving average crossover system will produce lots of whipsaws in the absence of a strong trend. There is also a triple crossover method that involves three moving averages. Again, a signal is generated when the shortest moving average crosses the two longer moving averages. A simple triple crossover system might involve 5-day, 10-day and 20-day moving averages. The chart above shows Home Depot (HD) with a 10-day EMA (green dotted line) and 50-day EMA (red line). The black line is the daily close. Using a moving average crossover would have resulted in three whipsaws before catching a good trade. The 10-day EMA broke below the 50-day EMA in late October (1), but this did not last long as the 10-day moved back above in mid November (2). This cross lasted longer, but the next bearish crossover in January (3) occurred near late November price levels, resulting in another whipsaw. This bearish cross did not last long as the 10-day EMA moved back above the 50-day a few days later (4). After three bad signals, the fourth signal foreshadowed a strong move as the stock advanced over 20. There are two takeaways here. First, crossovers are prone to whipsaw. A price or time filter can be applied to help prevent whipsaws. Traders might require the crossover to last 3 days before acting or require the 10-day EMA to move abovebelow the 50-day EMA by a certain amount before acting. Second, MACD can be used to identify and quantify these crossovers. MACD (10,50,1) will show a line representing the difference between the two exponential moving averages. MACD turns positive during a golden cross and negative during a dead cross. The Percentage Price Oscillator (PPO) can be used the same way to show percentage differences. Note that MACD and the PPO are based on exponential moving averages and will not match up with simple moving averages. This chart shows Oracle (ORCL) with the 50-day EMA, 200-day EMA and MACD(50,200,1). There were four moving average crossovers over a 2 12 year period. The first three resulted in whipsaws or bad trades. A sustained trend began with the fourth crossover as ORCL advanced to the mid 20s. Once again, moving average crossovers work great when the trend is strong, but produce losses in the absence of a trend. Price Crossovers Moving averages can also be used to generate signals with simple price crossovers. A bullish signal is generated when prices move above the moving average. A bearish signal is generated when prices move below the moving average. Price crossovers can be combined to trade within the bigger trend. The longer moving average sets the tone for the bigger trend and the shorter moving average is used to generate the signals. One would look for bullish price crosses only when prices are already above the longer moving average. This would be trading in harmony with the bigger trend. For example, if price is above the 200-day moving average, chartists would only focus on signals when price moves above the 50-day moving average. Obviously, a move below the 50-day moving average would precede such a signal, but such bearish crosses would be ignored because the bigger trend is up. A bearish cross would simply suggest a pullback within a bigger uptrend. A cross back above the 50-day moving average would signal an upturn in prices and continuation of the bigger uptrend. The next chart shows Emerson Electric (EMR) with the 50-day EMA and 200-day EMA. The stock moved above and held above the 200-day moving average in August. There were dips below the 50-day EMA in early November and again in early February. Prices quickly moved back above the 50-day EMA to provide bullish signals (green arrows) in harmony with the bigger uptrend. MACD(1,50,1) is shown in the indicator window to confirm price crosses above or below the 50-day EMA. The 1-day EMA equals the closing price. MACD(1,50,1) is positive when the close is above the 50-day EMA and negative when the close is below the 50-day EMA. Support and Resistance Moving averages can also act as support in an uptrend and resistance in a downtrend. A short-term uptrend might find support near the 20-day simple moving average, which is also used in Bollinger Bands. A long-term uptrend might find support near the 200-day simple moving average, which is the most popular long-term moving average. If fact, the 200-day moving average may offer support or resistance simply because it is so widely used. It is almost like a self-fulfilling prophecy. The chart above shows the NY Composite with the 200-day simple moving average from mid 2004 until the end of 2008. The 200-day provided support numerous times during the advance. Once the trend reversed with a double top support break, the 200-day moving average acted as resistance around 9500. Do not expect exact support and resistance levels from moving averages, especially longer moving averages. Markets are driven by emotion, which makes them prone to overshoots. Instead of exact levels, moving averages can be used to identify support or resistance zones . Conclusions The advantages of using moving averages need to be weighed against the disadvantages. Moving averages are trend following, or lagging, indicators that will always be a step behind. This is not necessarily a bad thing though. After all, the trend is your friend and it is best to trade in the direction of the trend. Moving averages insure that a trader is in line with the current trend. Even though the trend is your friend, securities spend a great deal of time in trading ranges, which render moving averages ineffective. Once in a trend, moving averages will keep you in, but also give late signals. Don039t expect to sell at the top and buy at the bottom using moving averages. As with most technical analysis tools, moving averages should not be used on their own, but in conjunction with other complementary tools. Chartists can use moving averages to define the overall trend and then use RSI to define overbought or oversold levels. Adding Moving Averages to StockCharts Charts Moving averages are available as a price overlay feature on the SharpCharts workbench. Using the Overlays drop-down menu, users can choose either a simple moving average or an exponential moving average. The first parameter is used to set the number of time periods. An optional parameter can be added to specify which price field should be used in the calculations - O for the Open, H for the High, L for the Low, and C for the Close. A comma is used to separate parameters. Another optional parameter can be added to shift the moving averages to the left (past) or right (future). A negative number (-10) would shift the moving average to the left 10 periods. A positive number (10) would shift the moving average to the right 10 periods. Multiple moving averages can be overlaid the price plot by simply adding another overlay line to the workbench. StockCharts members can change the colors and style to differentiate between multiple moving averages. After selecting an indicator, open Advanced Options by clicking the little green triangle. Advanced Options can also be used to add a moving average overlay to other technical indicators like RSI, CCI, and Volume. Click here for a live chart with several different moving averages. Using Moving Averages with StockCharts Scans Here are some sample scans that StockCharts members can use to scan for various moving average situations: Bullish Moving Average Cross: This scans looks for stocks with a rising 150-day simple moving average and a bullish cross of the 5-day EMA and 35-day EMA. The 150-day moving average is rising as long as it is trading above its level five days ago. A bullish cross occurs when the 5-day EMA moves above the 35-day EMA on above average volume. Bearish Moving Average Cross: This scans looks for stocks with a falling 150-day simple moving average and a bearish cross of the 5-day EMA and 35-day EMA. The 150-day moving average is falling as long as it is trading below its level five days ago. A bearish cross occurs when the 5-day EMA moves below the 35-day EMA on above average volume. Further Study John Murphy039s book has a chapter devoted to moving averages and their various uses. Murphy covers the pros and cons of moving averages. In addition, Murphy shows how moving averages work with Bollinger Bands and channel based trading systems. Technical Analysis of the Financial Markets John Murphy