Moving average option trading

Moving Averages Strategy for Binary Options.

Improve your binary options trading style by learning and implementing the moving averages strategy. We’ve already talked about chart patterns and what their significance to technical analysis is. However, it’s really important to clear out that in most cases things aren’t as clear as in the examples we’ve presented. In many cases there are lots of price fluctuations and different movements, making it notoriously difficult for an analyst to deduce the correct trend of an asset every single time.

One of the most interesting methods traders use to mitigate the effects of this phenomenon is to apply moving averages. Moving average is just a fancy way of saying that they calculate the average price of the asset for a predetermined period of time. This way they are able to observe the data more clearly, thus identifying genuine trends and increasing the probability of things working out well for them in the end.

Types of Moving Averages.

There are many types of moving averages, but three of them are the most popular, commonly known and most widely used. These three types are simple, linear and exponential. There may be differences in the way the average is calculated, but the interpretations remain the same. Most of the variables come from the fact that there is different emphasis put on different data points. In some cases more emphasis is placed on recent movements, while in other instances the price fluctuations of the whole period of equal importance.

Simple Moving Average (SMA)

As the name suggests, the simple moving average (SMA) is one of the simplest methods to calculate the moving average. As such, it is also very popular and commonly used by many traders and analysts. The method is as simple as they get – in order to calculate a moving average using this method, one needs to take the sum of all the closing prices of the certain period and then divide it by the number of prices taken. To make this more clear, here’s an example. Let’s say we want to calculate the moving average for a 10-day period. In this case, we take the closing price of all 10 days, sum them together and divide them by 10. This way the strength of the trends can be measured and become more apparent. With all the illusions removed, the trader can make sound choices concerning his finances and not be worried about the outcome. Look at the example below and everything will make sense.

A large number of analysts and traders speculate that the data presented by the SMA is not detailed and relevant enough to be taken seriously. For them, recent price movements are much more essential and they believe that this aspect of the price movement should be given the proper attention and weight. Since simple moving average takes everything into consideration with the same importance, it’s easy to see why this argument would be held. Certainly, for many traders, recent movements are much more important and if that is not reflected in the average, they feel the average, itself, is not accurate enough. This is what lead to the creation of other methods of calculating the averages.

Linear Weighted Average (LWA)

Some experts strongly believe that the SMA isn’t adequate enough to serve their needs, which is why they look elsewhere for reassurance. Where SMA is lacking in respect of relevance for these traders, linear weighted average more than makes up for. The problem is solved by adding more emphasis on more recent data. This is done by introducing more complicated calculations. Instead of simply taking the closing prices, exerts instead take the closing prices for a period of time, then multiply the closing price based on its place in the chronological progression.

For example, if we have a three day linear weighted average, then every day would be a data point, in which case we take the different closing prices and multiply them by the place of the data point. The first day’s closing price will then be multiplied by one, the second by two and the third by three. Then all the values are summed up and divided by the sum of multipliers (in this case it would be 3+2+1=6), essentially giving us the average with more emphasis on the third day than the first. Of course, if we were to choose a longer time window, the rules would apply all the same and it would not matter how many days we’ve picked. This is the basis of the principle.

Exponential Moving Averages (EMA)

Like LWA, EMA strives to put more emphasis on the more recent prices in the time frame. However, it does so in a bit more complicated and perhaps more refined manner, unlike the rudimentary nature of the LWA. To many the exponential moving average is much more efficient and preferred. In most cases you don’t even have to know how the different calculations are performed because the data is laid down for you in most charting packages, meaning that you won’t have to compute the averages, yourself. Everything you require is laid down before you and all you need to do is make sense of it (which can sometimes be a bit harder than it looks).

As a more advanced technique, EMA is used much more frequently used than LWA. Even though it has its critics, SMA is still very popular, leaving the LWA as the most rarely used of the trio. EMA is much more sensitive to new information than the SMA is. This is one of the reasons why it is preferred to the much simpler alternatives – because it delivers satisfactory enough information to many of the traders who employ technical analysis. If you take a look at the same chart from two different perspectives – that of the SMA and that of EMA, you will notice that as the different values rise and fall, the EMA corrects itself much faster than its simpler counterpart. The differences may be subtle, but they can be important enough to influence decisions in different ways.

Major Uses of Moving Averages.

As we’ve already said before, moving averages are used to dispel any illusions and deceptive factors in the data. This means that their primary objective is to assist technical analysts and traders to more easily identify trends and make decisions based on a more general data. Sometimes the information in the short-term can lead us to believe that the market conditions are different form what they actually are and moving averages help us to deal with possible misconceptions. They also help us to set up the levels of support and resistance, which are important as well, if you remember.

It’s easy to identify a trend based on the direction of a moving average. If a moving average is going up and the price is above it, then we are talking about a definite uptrend. If, however, the moving average is going down and the price movements are below it, we can clearly see a downtrend.

Another way we can determine a movement in a trend is to have a look at the relationship between two moving averages. If we have a long-term average below a short-term one, then we are talking about an uptrend. If the short-term average is below the long-term average, then we are witnessing a downtrend.

Moving averages can also help us spot trend reversals. There are two main signals for a trend reversal, both of them characterized as crossovers. The first one is when we have a crossover between the moving average and the price. If that should happen, then we are possibly talking about a trend reversal. This is just a signal, of course, which means that this isn’t the case 100% of the time. However, the signal is strong enough and accurate in enough cases as to require caution. If there is indeed a change in the trend, it will be reflected in the moving average shortly.

The other signal is the crossover between two moving averages. If we see this, then we can almost always be sure that there will be a trend reversal. If the moving averages are both short-term, then we might be talking about short-term trend reversal. Logically, enough, if we see a crossover between two long-term moving averages, then this definitely speaks of long-term trend reversal.

Just as crossovers are used to signal a trend reversal, moving averages can be used as a tool to determine the support or resistance levels. Long-term moving averages are especially useful in this respect. There many cases when the price of a security would go down until it reaches the moving average, and then go back up. In this case, the moving average serves as a level of support. We know that the price will probably not break it and if it does, this signals of a trend so we will be prepared and will know what to do based on the current status of market.

Moving averages are very useful for technical analysts and help them clear out the “noise” and irrelevant (or less relevant) data they don’t really want to pay attention to. They can help predict or confirm trends and give us a nice overview of the situation on the market.

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How To Use A Moving Average To Buy Stocks.

The moving average (MA) is a simple technical analysis tool that smooths out price data by creating a constantly updated average price. The average is taken over a specific period of time, like 10 days, 20 minutes, 30 weeks, or any time period the trader chooses. There are advantages to using a moving average in your trading, as well options on what type of moving average to use. Moving average strategies are also popular and can be tailored to any time frame, suiting both long term investors and short-term traders. (see "The Top Four Technical Indicators Trend Traders Need to Know.")

Why Use a Moving Average.

A moving average can help cut down the amount of "noise" on a price chart. Look at the the direction of the moving average to get a basic idea of which way the price is moving. Angled up and price is moving up (or was recently) overall, angled down and price is moving down overall, moving sideways and the price is likely in a range.

A moving average can also act as support or resistance. In an uptrend a 50-day, 100-day or 200-day moving average may act as a support level, as shown in the figure below. This is because the average acts like a floor (support), so the price bounces up off of it. In a downtrend a moving average may act as resistance; like a ceiling, the price hits it and then starts to drop again.

The price won't always "respect" the moving average in this way. The price may run through it slightly or stop and reverse prior to reaching it.

As a general guideline, if the price is above a moving average the trend is up. If the price is below a moving average the trend is down. Moving averages can have different lengths though (discussed shortly), so one may indicate an uptrend while another indicates a downtrend.

[ Moving averages are a great way to identify areas of support or resistance, but they shouldn't be the only strategy that you use to identify potential trades. If you want to learn how other technical analysis strategies, Investopedia Academy's Technical Analysis Course is an excellent starting point. ]

Types of Moving Averages.

A moving average can be calculated in different ways. A five-day simple moving average (SMA) simply adds up the five most recent daily closing prices and divides it by five to create a new average each day. Each average is connected to the next, creating the singular flowing line.

Another popular type of moving average is the exponential moving average (EMA). The calculation is more complex but basically applies more weighting to the most recent prices. Plot a 50-day SMA and a 50-day EMA on the same chart, and you'll notice the EMA reacts more quickly to price changes than the SMA does, due to the additional weighting on recent price data.

Charting software and trading platforms do the calculations, so no manual math is required to use a MA.

One type of MA isn't better than another. An EMA may work better in a stock or financial market for a time, and at other times an SMA may work better. The time frame chosen for a moving average will also play a significant role in how effective it is (regardless of type).

Common moving average lengths are 10, 20, 50, 100 and 200. These lengths can be applied to any chart time frame (one minute, daily, weekly, etc), depending on the traders trade horizon.

The time frame or length you choose for a moving average, also called the "look back period", can play a big role in how effective it is.

An MA with a short time frame will react much quicker to price changes than an MA with a long look back period. In the figure below the 20-day moving average more closely tracks the actual price than the 100-day does.

The 20-day may be of analytical benefit to a shorter-term trader since it follows the price more closely, and therefore produces less "lag" than the longer-term moving average.

Lag is the time it takes for a moving average to signal a potential reversal. Recall, as a general guideline, when the price is above a moving average the trend is considered up. So when the price drops below that moving average it signals a potential reversal based on that MA. A 20-day moving average will provide many more "reversal" signals than a 100-day moving average.

A moving average can be any length, 15, 28, 89, etc. Adjusting the moving average so it provides more accurate signals on historical data may help create better future signals.

Trading Strategies - Crossovers.

Crossovers are one of the main moving average strategies. The first type is a price crossover. This was discussed earlier, and is when the price crosses above or below a moving average to signal a potential change in trend.

Another strategy is to apply two moving averages to a chart, one longer and one shorter. When the shorter MA crosses above the longer term MA it's a buy signal as it indicates the trend is shifting up. This is known as a "golden cross."

When the shorter MA crosses below the longer term MA it's a sell signal as it indicates the trend is shifting down. This is known as a "dead/death cross"

Moving averages are calculated based on historical data, and nothing about the calculation is predictive in nature. Therefore results using moving averages can be random--at times the market seems to respect MA support/resistance and trade signals, and other times it shows no respect.

One major problem is that if the price action becomes choppy the price may swing back and forth generating multiple trend reversal/trade signals. When this occurs it's best to step aside or utilize another indicator to help clarify the trend. The same thing can occur with MA crossovers, where the MAs get "tangled" for a period of time triggering multiple (liking losing) trades.

Moving averages work quite well in strong trending conditions, but often poorly in choppy or ranging conditions.

Adjusting the time frame can aid in this temporarily, although at some point these issues are likely to occur regardless of the time frame chosen for the MA(s).

A moving average simplifies price data by smoothing it out and creating one flowing line. This can make isolating trends easier. Exponential moving averages react quicker to price changes than a simple moving average. In some cases this may be good, and in others it may cause false signals. Moving averages with a shorter look back period (20 days, for example) will also respond quicker to price changes than an average with a longer look period (200 days). Moving average crossovers are a popular strategy for both entries and exits. MAs can also highlight areas of potential support or resistance. While this may appear predictive, moving averages are always based on historical data and simply show the average price over a certain time period.

Moving Averages.

Moving averages are among the most simple technical indicators available. They are used to smooth the price pattern of the stock, and provide an easy-to-see indication whether the stock is currently trending (moving up or down) or in a trading range (moving sideways). As the name implies, moving averages are based on the averages of the stock's price (most commonly its closing price).

A 20-day average will take the average of the stock's closing price for the 20 most recent trading days. The next day, the new day's stock price will be added to the average, and the oldest price of the previous 20 days will be taken out. This will create a slowly-moving trend of the stock's price, in this case a 20-day moving average, as seen in the chart below.

As seen above, the actual price pattern of the stock is very volatile, with a single day's price changing by over $3. However, once we apply a 20-day indicator to it, the pattern is smoothed, and we can see a trend develop. As can be seen in early February, even though the stock's price jumped more than $5, the moving average did not change much, since it took into account the last 20 days worth of data, and smoothed the trendline.

For example, in mid February, just looking at the stock's price pattern, it seemed that the stock had stopped its upwards trend and was beginning to go down. However, the moving averages indicated that the stock was still in a strong uptrend which would continue till early March. Heeding the moving averages would have kept investors in the stock during the rally in late February.

Likewise, the spike in the stock price in late May and early June might have tempted investors to buy into the stock again. However, the moving averages told a different story. The moving average was flat and indicated that an uptrend had not developed. True enough, the stock started trading downwards from early June right into July.

What we covered above are called Simple Moving Averages, or just Moving Averages. Another form of averaging is known as Exponential Moving Averages or EMA for short. In simple moving averages, say a 20-Day moving average, each of the 20 days' prices have equal weight in calculating the average. However, in exponential moving averages, the most recent prices have more weight than the earliest ones.

As such, during a surprise rally, the exponential moving average will respond faster and start to trend upwards earlier. Take the chart below for example. The simple moving average is marked in blue, and the exponential moving average is marked in red. In late May, there was a sudden surge in RYL's stock price. The exponential moving average, being more sensitive, reacted quickly and started trending upwards. On the other hand, the simple moving average still took into account the previous down days, and did not even register an upward trend till the rally was almost over!

So which type of moving average is better? Both have their own merit. The simple moving average is less prone to whipsaws and false alarms, and will only indicate trends when the price pattern is more pronounced, while the exponential moving average might register false alarms.

On the other hand, exponential moving averages are more sensitive to sudden price changes and are able to react faster. Since we are dealing with option trading, we would tend to follow the exponential moving averages, since their sensitivity and quick movement are ideal for the short-term and volatile nature of option trading.

So, how do we use moving averages? As has beem mentioned, both simple and exponential moving averages are primarily meant to indicate whether the stock is in an uptrend, downtrend or sideways trading range. This can help prevent investors from buying into a stock that is stuck in a trading range or starting to trend downwards.

Another common way of using both simple and exponential moving averages is by noticing when the stock price crosses above or below the moving average. This shows that the trend (either up or down) has reversed, and a new trend is developing.

Looking at the RYL chart above, the stock price crossed upwards from below the exponential moving average in late Februrary and late May, indicating that investors are starting to buy the stock and the trend is moving upwards. These would be good times to buy call options or any bullish option strategy on the stock. Conversely, at the end of March and early July, the stock price crossed below the exponential moving average, indicating that it was time to implement bearish option strategies.

However, it can be seen that the stock price crossed the exponential moving average many times in those 6 months, creating a lot of false alarms. Heeding every crossover would have been a very painful and costly experience. The reason for that is that a 20-Day exponential moving average is probably too sensitive and erratic. The moving average can be modified to accomodate different periods or date ranges. For example, the chart below presents both the 20-Day (in blue) and 50-Day exponential moving averages for CAT.

As can be seen, the 50-Day exponential moving average (in red) is much smoother than the 20-Day, and therefore can indicate trends better. In addition, the stock price crosses it less often, producing less false signals. However, by the time the stock price crosses the 50-Day exponential moving average, the rally or crash is almost over. In other words, the longer the period being averaged, the less sensitive it is, and the slower it is to react.

So what period moving averages should we choose? This depends on the individual's risk profile and investment strategies. Someone with a low risk profile and long-term strategies might choose slower moving averages, while someone willing to risk more might go for faster moving averages. The most common ones are 20-Day, 50-Day and 200-Day simple and exponential moving averages; for short-term to long-term strategies, in that order. Since most option strategies are volatile and short-term in nature, shorter moving averages (though more risky with more false alarms) are needed to "catch the wave". Some options investors compromise by using a slightly slower moving average such as the 24-Day and 30-Day averages.

Please be reminded that this indicator should not be used on its own, but rather with one or two additional indicators, in order to confirm any signals.

Other Topics in this Guide.

Other Topics in this Guide.

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Moving Average in Binary Options.

In binary options trading, it is essential for the binary options trader to have a basis on a Call or Put action. Different techniques are used to make an informed decision. Some may rely on just financial news and world market trends. Others employ more sophisticated formulas to predict the movement of the price of a specific asset. No matter what technique is used, the risk of a binary options trader is greatly reduced when proper analysis is made.

Technical analysis has been used by binary options brokers since it came to the market a few years back. Traders have seen the invention of hundreds of indicators which they factor when they purchase binary options. Some technical indicators are more popular than others. Some may be objective to some traders. But reliable and useful analysis techniques such as the moving average is preferred over the others by newer binary options traders.

Moving average is exactly what its name implies. It denotes the average of the price movement of an asset for a specific period of time. Moving averages have different derivatives. But, their underlying purpose remains the same. The purpose of moving averages (hereon referred to as MA) is to help binary options traders track the trends of financial assets by smoothing out the day-to-day price fluctuations, also called noise. When the daily fluctuations are disregarded, a more direct trend results, and a general action or direction can be traced from the curve.

By identifying trends using MA, traders are able to make those trends work in their favor and increase the number of winning trades. A clear understanding of why moving averages are important is what the binary options trader needs in order to appreciate the technique. How they are calculated is what will be discussed here.

Simple Moving Average.

Moving averages are a common way to gauge the direction of a current trend. Every type of MA is a mathematical result that is calculated by averaging the number of past data points. Once the average is determined, it is then plotted into a chart. This would allow binary options traders to look at smoothened data rather getting confused with the the day-to-day price fluctuations that are inherent in all financial markets.

The simplest form of a moving average is aptly known as a simple moving average (SMA). This type of moving average is computed by taking the arithmetic mean of a given set of values. For example, to calculate a basic 10-day moving average you would add up the closing prices from the past 10 days and then divide the result by 10.

Say we have these following value points:

12, 10, 7, 8, 7, 10, 10, 8, 9, 13, 7, 6, 9.

From the above given set of values, the sum of the prices for the past 10 days counting from the rightmost value (9) is 87.

8 + 7 + 10 + 10 + 8 + 9 + 13 + 7 + 6 + 9 = 87.

This sum is divided by the number of days (10) to arrive at the 10-day average.

If a binary options trader wishes to see a 50-day average instead, the same procedure would be made, but the sum would be divided into 50 to include the prices over the past 50 days. The resulting average from our example, 8.7, takes into account the past 10 data points. This gives the binary options trader an idea of how an asset is priced relative to the past 10 days.

So why is it called a “moving” average if it’s just plain average. Because, as new values arrive, older data points will be dropped from the set to make way for the new values. Thus, the data set is constantly “moving” to account for new data as they becomes available.

This method of computation ensures that only the most current information is being accounted for. Here’s the continuation of our example. Say a trading day closed adding a new value (12) to our history.

12, 10, 7, 8, 7, 10, 10, 8, 9, 13, 7, 6, 9, 12.

Once the new value of 12 is added to the set, the past 10 data points now includes the 12 and drops the first 8. The new count of 10 data points now start from 12, changing the sum.

7 + 10 + 10 + 8 + 9 + 13 + 7 + 6 + 9 + 12 = 91.

Because of the relatively larger value of 12 replacing the lower value 8, a binary options trader would expect to see the average of the data set increase. In our example, the SMA went from 8.7 to 9.1.

After obtaining the different SMAs, they are plotted in a chart and connected together to create a moving average line. You will be able to find these curving lines on charts that technical traders use.

Exponential Moving Average.

The Exponential Moving Average (EMA) is a type of moving average that gives more weight to recent prices to make them more responsive to new information. Don’t get intimidated by the equation as it is widely used and mastering it is not really necessary since nearly all charting platforms do the computations for you. However, for purposes of discussion, the EMA equation is:

EMA = (P * a) + (Previous EMA * (1 — a) )

From the formula, we notice that when we calculate the first point of the EMA, there is no value available for the Previous EMA. This can be resolved by obtaining an SMA and continuing on with the above formula for EMA. Traders usually use simple spreadsheets that are available in the Internet that includes real-life examples of how to calculate both a SMAs and EMAs.

Also, by looking at how the EMA is calculated, it can be found that more emphasis is placed on more recent data points, making it a type of weighted average. EMA responds more quickly to the changing of prices. This means that for a certain time period, the EMA has already forecasted that a price would go down while the SMA would still need to go through more periods for find the prices falling. This responsiveness is the main reason why more binary options traders prefer to use the EMA over the SMA.

The use of EMA charts has helped binary options traders forecast trends and directions based on moving average values. The EMA is used in many strategies, so it is recommended to master reading EMA charts. How to use these values to set up trend forecasts is what many charting platforms provide.

Some binary options brokers also provide charts that show moving averages. See our list of binary options brokers, and choose one that you are most comfortable with. Let us help you in your way to success.

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