# Relations Of The 20 And 100 Week Moving Averages : CryptoCurrency

One of the most popular simple moving averages is the 200-day SMA. However, there is a danger to following the crowd. As The Wall Street Journal explains, since thousands of traders base their strategies around the 200-day SMA, there is a chance that these predictions could become self-fulfilling and limit price growth.

## Relations of the 20 and 100 week moving averages : CryptoCurrency

Traders use simple moving averages (SMAs) to chart the long-term trajectory of a stock or other security, while ignoring the noise of day-to-day price movements. This allows traders to compare medium- and long-term trends over a larger time horizon. For example, if the 200-day SMA of a security falls below its 50-day SMA, this is usually interpreted as a bearish death cross pattern and a signal of further declines. The opposite pattern, the golden cross, indicates potential for a market rally.

While a simple moving average gives equal weight to each of the values within a time period, an exponential moving average places greater weight on recent prices. Exponential moving averages are typically seen as a more timely indicator of a price trend, and because of this, many traders prefer using this over a simple moving average. Common short-term exponential moving averages include the 12-day and 26-day. The 50-day and 200-day exponential moving averages are used to indicate long-term trends.

A moving average is a statistic that captures the average change in a data series over time. In finance, moving averages are often used by technical analysts to keep track of price trends for specific securities. An upward trend in a moving average might signify an upswing in the price or momentum of a security, while a downward trend would be seen as a sign of decline.

The moving average convergence divergence (MACD) is used by traders to monitor the relationship between two moving averages, calculated by subtracting a 26-day exponential moving average from a 12-day exponential moving average. The MACD also employs a signal line that helps identify crossovers, and which itself is a nine-day exponential moving average of the MACD line that is plotted on the same graph. The signal line is used to help identify trend changes in the price of a security and to confirm the strength of a trend.

Moving averages are without a doubt the most popular trading tools. Moving averages are great if you know how to use them but most traders, however, make some fatal mistakes when it comes to trading with moving averages. In this article, I show you what you need to know when it comes to choosing the type and the length of the perfect moving average and the 3 ways how to use moving averages when making trading decisions.

You have to stick to the most commonly used moving averages to get the best results. Moving averages work when a lot of traders use and act on their signals. Thus, go with the crowd and only use the popular moving averages.

Swing traders have a very different approach and they typically trade on the higher time frames (4H, Daily +) and also hold trades for longer periods of time. Thus, swing-traders should first choose a SMA and also use higher period moving averages to avoid noise and premature signals. Here are 4 moving averages that are particularly important for swing traders:

Now that you know about the differences between the moving averages and how to choose the right period setting, we can take a look at the 3 ways moving averages can be used to help you find trades, ride trends and exit trades in a reliable way.

But even as swing traders, you can use moving averages as directional filters. The Golden and Death Cross is a signal that happens when the 200 and 50-period moving average cross and they are mainly used on the daily charts.

The second thing moving averages can help you with is support and resistance trading and also stop placement. Because of the self-fulfilling prophecy we talked about earlier, you can often see that the popular moving averages work perfectly as support and resistance levels.

The screenshot below shows a price chart with a 50 and 21 period moving average. You can see that during the range, moving averages completely lose their validity, but as soon as the price starts trending and swinging, they perfectly act as support and resistance again.

You might wonder if there are also 21-day moving averages, or perhaps 10-day moving averages, and yes, you can make it anything you want. We use multiples of 7 because we have 7 days in a week, and this means every day is in the series once, twice, etc. For COVID cases, this can be very important: we know on Sundays a lot of laboratories close, so they cannot report. If we used a 10-day moving average, it would include Sundays twice sometimes, and sometimes only have one Sunday. This would cause little dips whenever you have a 10 day period where two Sundays are incorporated. I tried this to satisfy your possible curiosity. Notice how it softens the peaks and valleys a little, but that every few days, the valleys are actually deeper? Those are when two Sundays are incorporated or, in one case, even two Sundays and a holiday. For that reason, we generally use multiples of 7 for moving averages of days.

You can imagine that some things do not use a weekly schedule as we do: a bee does not care that it is Sunday when it goes to find a flower, for example, so logging a 7-day moving average might not be as useful as using the weather patterns.But in general, and especially for things that need humans to log the numbers, we will use a multiple of 7 for a moving average.

A moving average doesn't predict price direction. Instead, it defines the current direction. However, a moving average tends to lag because it's based on past prices. Despite this, investors use moving averages to help smooth price action and filter out the noise.

The two most popular types of moving averages are the simple moving average (SMA) and the exponential moving average (EMA). Simple moving averages (SMAs) are an average of prices over the specified timeframe, while exponential moving averages (EMAs) give more weight to recent prices. Other specialty types of moving averages available in our charting tools include DEMA, Hull Moving Average, KAMA, and TEMA.

Because moving averages are based on past data, they tend to lag behind price data. The longer the moving average, the more the lag. In addition, the type of moving average affects the lag: EMAs with the more recent data weighted more heavily will lag less than an SMA, which gives equal weight to data further in the past.

The chart above shows the SPDR S&P 500 ETF (SPY) 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.

Keep the lag factor in mind when choosing the right moving average for your chart. Your moving average preferences will depend on your objectives, analytical style, and time horizon. Try experimenting with both types of moving averages, different timeframes, and different securities to find the best fit.

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; for example, 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 becomes available, causing the average to move along the time scale. The example below shows a 5-day moving average evolving over three days.

Exponential moving averages (EMAs) 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. EMAs differ from simple moving averages in that a given day's EMA calculation depends on the EMA calculations for all the days prior to that day. You need far more than 10 days of data to calculate a reasonably accurate 10-day EMA.

When adding a moving average to your chart, the first choice to make is whether to use an exponential or a simple moving average. Even though there are clear differences between simple moving averages and exponential moving averages, one is not necessarily better than the other. Choosing the right type of moving average depends on your trading objectives.

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.

The length of the moving average depends on the trader's time horizon and 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.

Moving averages can be used to identify the trend, as well as support and resistance levels. Crossovers with price or with another moving average can provide trading signals. Chartists may also create a Moving Average Ribbon with more than one moving average to analyze the interaction between multiple MAs at once.

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. 350c69d7ab