The ZigZag feature on SharpCharts is not an indicator per se, but rather a means to filter out smaller price movements. A ZigZag set at 10% would ignore all price movements less than 10%. Only price movements greater than 10% would be shown. Filtering out smaller movements gives chartists the ability to see the forest instead of just trees. It is important to remember that the ZigZag feature has no predictive power because it draws lines base on hindsight. Any predictive power will come from applications such as Elliott Wave, price pattern analysis or indicators. Chartists can also use the ZigZag with retracements feature to identify Fibonacci retracements and projections.
Calculation
The ZigZag is based on the chart “type.” Line and dot charts, which are based on the close, will show the ZigZag based on closing prices. High-Low-Close bars (HLC), Open-High-Low-Close (OHLC) bars and candlesticks, which show the period's high-low range, will show the ZigZag based on this high-low range. A ZigZag based on the high-low range is more likely to change course than a ZigZag based on the close because the high-low range will be much larger and produce bigger swings.
The parameters box allows chartists to set the sensitivity of the ZigZag feature. A ZigZag with 5 in the parameter box will filter out all movements less than 5%. A ZigZag(10) will filter out movements less than 10%. If a stock traded from a reaction low of 100 to a high of 109 (+9%), there would not be a line because the move was less than 10%. If the stock advanced from a low of 100 to a high of 110 (+10%), there would be a line from 100 to 110. If the stock continued on to 112, this line would extend to 112 (100 to 112). The ZigZag would not reverse until the stock declined 10% or more from its high. From a high of 112, a stock would have to decline 11.2 points (or to a low of 100.8) to warrant another line. The chart below shows a QQQQ line chart with a 7% ZigZag. The early June bounce was ignored because it was less than 7% (black arrow). The two pullbacks in July were ignored because they were much less than 7% (red arrows).
Be careful with the last ZigZag line. Astute chartists will notice that the last ZigZag line is up even though QQQQ advanced just 4.13% (43.36 to 45.15). This is just a temporary line because QQQQ has yet to reach the 7% change threshold. A move to 46.40 is needed for a gain of 7%, which would then warrant a permanent ZigZag line. Should QQQQ fail to reach the 7% threshold on this bounce and then decline below 43, this temporary line would disappear and the prior ZigZag line would continue from the early August high.
Elliott Wave Counts
The ZigZag feature can be used to filter out small moves and make Elliott Wave counts more straight-forward. The chart below shows the S&P 500 ETF with a 6% ZigZag to filter moves less than 6%. After a little trial and error, 6% was deemed the threshold of importance. An advance or decline greater than 6% was deemed significant enough to warrant a wave for an Elliott count. Keep in mind that this is just an example. The threshold and the wave count are subjective and dependent on individual preferences. Based on the 6% ZigZag, a complete cycle was identified from March 2009 until July 2010. A complete cycle consists of 8 waves, 5 up and 3 down.
Retracements and Projections
Sharpcharts users can choose between the normal “ZigZag” and “ZigZag (Retrace.).” As shown in the examples above, the normal ZigZag shows lines that move at least a specific percentage. The ZigZag (Retrace.) connects the reaction highs and lows with labels that measure the prior move. The numbers on the dotted lines reflect the difference between the current Zigzag line and the ZigZag line immediately before it. For example, the chart below shows Altera (ALTR) with the 15% ZigZag (Retrace.) feature. Three ZigZag lines have been labeled (1, 2 and 3). The dotted line connecting the low of Line 1 with the low of Line 2 shows a box with 0.638. This means Line 2 is .638 (63.8%) of Line 1. A number below 1 means the line is shorter than the prior line. The dotted line connecting the high of Line 2 with the high of Line 3 shows a box with 1.646. This means Line 3 is 1.646 (164.6%) of Line 2. A number above 1 means the line is longer than the prior line.
As you may have guessed, seeing these lines as a percentage of the prior lines makes it possible to assessFibonacci retracements Fibonacci projections. The August decline (Line 2) retraced around 61.8% of the June-July advance (Line 1). This is a classic Fibonacci retracement. The advance from early September to early November was 1.646 times the August decline. In this sense, the ZigZag (Retrace.) can be used to project the length of an advance. Again, 1.646 is close to the Fibonacci 1.618, which is the Golden Ratio used in many projection estimates. See our ChartSchool article for more on Fibonacci retracements.
Conclusions
The ZigZag and ZigZag (Retrace.) filter price action and do not have any predictive power. The ZigZag lines simply react when prices move a certain percentage. Chartists can apply an array of technical analysis tools to the ZigZag. Chartists can perform basic trend analysis by comparing reaction highs and lows. Chartists can also overlay the ZigZag feature to look for price patterns that might not be as visible on a normal bar or line chart. The ZigZag has a way of highlighting the important movements and ignoring the noise. When using the ZigZag feature, don't forget to measure the last line to determine if it is temporary or permanent. The last ZigZag line is temporary if the current price change is less than the ZigZag parameter. The last line is permanent when the price change is greater than or equal to the ZigZag parameter.
SharpCharts
The ZigZag and ZigZag (Retrace.) can be found in SharpCharts as a price overlay in the Chart Attributes section or as an addition to an indicator. Upon selecting the Zigzag feature from the drop down box, the parameters window will appear empty. Five (5%) is the default parameter, but this can change depending on a security's price characteristics. Some securities produce too few Zigzag lines at 5% so the default is set lower (e.g. 3.75%). Some securities produce too many zigzag lines at 5% so the default is set higher (e.g. 6.25%). The Zigzag parameter can be seen in the upper left corner of the chart. Once the Zigzag feature is applied, chartists can adjust the parameter to suit their charting needs. A lower number will make the feature more sensitive, while a higher number will make it less sensitive. Click here for a live chart with the Zigzag (Retrace.) feature.
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Many people believe that the markets are random. In fact, one of the most prominent investing books out there is "A Random Walk Down Wall Street" (1973) by Burton G. Malkiel, who argues that throwing darts at a dartboard is likely to yield results similar to those achieved by a fund manager (and Malkiel does have many valid points).
However, many others argue that although prices may appear to be random, they do in fact follow a pattern in the form of trends. One of the most basic ways in which traders can determine such trends is through the use of fractals. Fractals essentially break down larger trends into extremely simple and predictable reversal patterns. This article will explain what fractals are and how you might apply them to your trading to enhance your profits.
What Are Fractals? When many people think of fractals in the mathematical sense, they think of chaos theory and abstract mathematics. While these concepts do apply to the market (it being a nonlinear, dynamic system), most traders refer to fractals in a more literal sense. That is, as recurring patterns that can predict reversals among larger, more chaotic price movements.
These basic fractals are composed of five or more bars. The rules for identifying fractals are as follows:
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A bearish turning point occurs when there is a pattern with the highest high in the middle and two lower highs on each side.
A bullish turning point occurs when there is a pattern with the lowest low in the middle and two higher lows on each side.
The fractals shown in Figure 1 are two examples of perfect patterns. Note that many other less perfect patterns can occur, but the basic pattern should remain intact for the fractal to be valid.
Figure 1
The obvious drawback here is that fractals are lagging indicators - that is, a fractal can't be drawn until we are two days into the reversal. While this may be true, most significant reversals last many more bars, so most of the trend will remain intact (as we will see in the example below).
Applying Fractals to Trading Like many trading indicators, fractals are best used in conjunction with other indicators or forms of analysis. Perhaps the most common confirmation indicator used with fractals is the "Alligator indicator", a tool that is created by using moving averages that factor in the use of fractal geometry. The standard rule states that all buy rules are only valid if below the "alligator's teeth" (the center average), and all sell rules are only valid if above the alligator's teeth.
Figure 2 is an example of such a setup:
Figure 2
As you can see, the primary drawback to this system is the large swings that take place. Notice, for example, that the latest fractal had a drawdown of over 100 pips and still has not hit an exit point. However, there are countless other techniques that can be applied in conjunction with fractals to produce profitable trading systems.
Figure 3 shows a forex trading setup that uses a combination of fractals (multiple time frames), Fibonacci-based moving averages (placed at 89, 144, 233, 377 and their inverses) and a momentum indicator. Let's look at a recent trade setup for the GBP/USD currency pair to see how fractals can help:
Figure 3
Here is a basic rule setup that is used when using a chart with a four-hour time frame:
Initiate a position when the price has hit the farthest Fibonacci band, but only after a daily (D1) fractal takes place.
Exit a position after a daily (D1) fractal reversal takes place.
Notice how the fractals pinpoint meaningful tops and bottoms? This helps to take the guesswork out of deciding at which Fibonacci level to trade - all we have to do is check to see if the daily fractal occurred. We should also note that the trend strength began increasing at the sell fractal, and topped at the buy fractal. Although we lose some pips with the confirmation, it saves us from losing out on mere market noise - 139 pips certainly isn't bad for three days! (For further reading, see Trading Without Noise.)
Things to Consider Here are a few things to remember when using fractals:
They are lagging indicators. They are best used as confirmation indicators to help confirm that a reversal did take place. Real-time tops and bottoms can be surmised with other techniques.
The longer the time period (i.e. the number of bars required for a fractal), the more reliable the reversal. However, you should also remember that the longer the time period, the lower the number of signals generated.
It is best to plot fractals in multiple time frames and use them in conjunction with one another. For example, only trade short-term fractals in the direction of the long-term ones. Along these same lines, long-term fractals are more reliable than short-term fractals.
Always use fractals in conjunction with other indicators or systems. They work best as decision support tools, not as indicators on their own.
Conclusion As you can see, fractals can be extremely powerful tools when used in conjunction with other indicators and techniques, especially when used to confirm reversals. The most common usage is with the "Alligator indicator"; however, there are other uses too, as we've seen here. Overall, fractals make excellent decision support tools for any trading method.
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In the world of short-term trading, experiences are defined by a trader's ability to anticipate a certain move in the price of a financial asset. There are many different indicators used to predict an asset's future direction, but few have proved to be as useful and easy to interpret as the parabolic SAR. In this article, we'll take a look at the basics of this indicator and show you how you can incorporate it into your trading strategy.
The Indicator
The parabolic SAR is a technical indicator that is used by many traders to determine the direction of an asset's momentum and the point in time when this momentum has a higher-than-normal probability of switching directions. Sometimes known as the "stop and reversal system", the parabolic SAR was developed by the famous technician Welles Wilder, creator of the relative strength index, and it is shown as a series of dots placed either above or below an asset's price on a chart.
One of the most important aspects to keep in mind is that the positioning of the "dots" is used by traders to generate transaction signals depending on where the dot is placed relative to the asset's price. A dot placed below the price is deemed to be a bullish signal, causing traders to expect the momentum to remain in the upward direction. Conversely, a dot placed above the prices is used to illustrate that the bears are in control and that the momentum is likely to remain downward. (For further reading, see How is the parabolic SAR used in trading?)
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The first entry point on the buy side occurs when the most recent high price of an issue has been broken; it is at this time that the SAR is placed at the most recent low price. As the price of the stock rises, the dots will rise as well, first slowly and then picking up speed and accelerating with the trend. This accelerating system allows the investor to watch the trend develop and establish itself. The SAR starts to move a little faster as the trend develops and the dots soon catch up to the price action of the issue. As you can see in Figure 1, the indicator works extremely well when a stock is trending, but it can lead to many false signals when the price moves sideways or is trading in a choppy market.
Parabolic SAR and the Short Sale
The parabolic SAR is extremely valuable because it is one of the easiest methods available for strategically setting the position of a stop-loss order. As you become more acquainted with technical indicators, you'll find that the parabolic SAR has built up quite the positive reputation for its role in helping many traders lock-in paper profits that have been realized in a trending environment. You can also see that professional traders whoshort the market will use this indicator to help determine the time to cover their short positions. (For more, see Trailing-Stop Techniques.)
It is important to note that this indicator is extremely mechanical and will always assume that the trader is holding a long or short position. The ability for the parabolic SAR to respond to changing conditions removes all human emotion and allows the trader to be disciplined. On the other hand, the disadvantage of using this indicator can also be seen in Figure 1. Notice how the signals can lead to many false entries during periods of consolidation. Being whipsawed in and out of trades can often be extremely frustrating, even for the most successful traders.
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Developed by John Bollinger, Bollinger Bands® are volatility bands placed above and below a moving average. Volatility is based on the standard deviation, which changes as volatility increases and decreases. The bands automatically widen when volatility increases and narrow when volatility decreases. This dynamic nature of Bollinger Bands also means they can be used on different securities with the standard settings. For signals, Bollinger Bands can be used to identify M-Tops and W-Bottoms or to determine the strength of the trend. Signals derived from narrowing BandWidth are discussed in the chart school article on BandWidth.
Note: Bollinger Bands® is a registered trademark of John Bollinger.
SharpCharts Calculation
* Middle Band = 20-day simple moving average (SMA)
* Upper Band = 20-day SMA + (20-day standard deviation of price x 2)
* Lower Band = 20-day SMA - (20-day standard deviation of price x 2)
Bollinger Bands consist of a middle band with two outer bands. The middle band is a simple moving average that is usually set at 20 periods. A simple moving average is used because the standard deviation formula also uses a simple moving average. The look-back period for the standard deviation is the same as for the simple moving average. The outer bands are usually set 2 standard deviations above and below the middle band.
Settings can be adjusted to suit the characteristics of particular securities or trading styles. Bollinger recommends making small incremental adjustments to the standard deviation multiplier. Changing the number of periods for the moving average also affects the number of periods used to calculate the standard deviation. Therefore, only small adjustments are required for the standard deviation multiplier. An increase in the moving average period would automatically increase the number of periods used to calculate the standard deviation and would also warrant an increase in the standard deviation multiplier. With a 20-day SMA and 20-day Standard Deviation, the standard deviation multiplier is set at 2. Bollinger suggests increasing the standard deviation multiplier to 2.1 for a 50-period SMA and decreasing the standard deviation multiplier to 1.9 for a 10-period SMA.
Signal: W-Bottoms
W-Bottoms were part of Arthur Merrill's work that identified 16 patterns with a basic W shape. Bollinger uses these various W patterns with Bollinger Bands to identify W-Bottoms. A “W-Bottom” forms in a downtrend and involves two reaction lows. In particular, Bollinger looks for W-Bottoms where the second low is lower than the first, but holds above the lower band. There are four steps to confirm a W-Bottom with Bollinger Bands. First, a reaction low forms. This low is usually, but not always, below the lower band. Second, there is a bounce towards the middle band. Third, there is a new price low in the security. This low holds above the lower band. The ability to hold above the lower band on the test shows less weakness on the last decline. Fourth, the pattern is confirmed with a strong move off the second low and a resistance break.
Chart 2 shows Nordstrom (JWN) with a W-Bottom in January-February 2010. First, the stock formed a reaction low in January (black arrow) and broke below the lower band. Second, there was a bounce back above the middle band. Third, the stock moved below its January low and held above the lower band. Even though the 5-Feb spike low broke the lower band, Bollinger Bands are calculated using closing prices so signals should also be based on closing prices. Fourth, the stock surged with expanding volume in late February and broke above the early February high. Chart 3 shows Sandisk with a smaller W-Bottom in July-August 2009.
Signal: M-Tops
M-Tops were also part of Arthur Merrill's work that identified 16 patterns with a basic M shape. Bollinger uses these various M patterns with Bollinger Bands to identify M Bottoms. According to Bollinger, tops are usually more complicated and drawn out than bottoms. Double tops, head-and-shoulders patterns and diamonds represent evolving tops.
In its most basic form, an M-Top is similar to a double top. However, the reaction highs are not always equal. The first high can be higher or lower than the second high. Bollinger suggests looking for signs of non-confirmation when a security is making new highs. This is basically the opposite of the W-Bottom. A non-confirmation occurs with three steps. First, a security forges a reaction high above the upper band. Second, there is a pullback towards the middle band. Third, prices move above the prior high, but fail to reach the upper band. This is a warning sign. The inability of the second reaction high to reach the upper band shows waning momentum, which can foreshadow a trend reversal. Final confirmation comes with a support break or bearish indicator signal.
Chart 4 shows Exxon Mobil (XOM) with an M-Top in April-May 2008. The stock moved above the upper band in April. There was a pullback in May and then another push above 90. Even though the stock moved above the upper band on an intraday basis, it did not CLOSE above the upper band. The M-Top was confirmed with a support break two weeks later. Also notice that MACD formed a bearish divergence and moved below its signal line for confirmation.
Chart 5 shows Pulte Homes (PHM) within an uptrend in July-August 2008. Price exceeded the upper band in early September to affirm the uptrend. After a pullback below the 20-day SMA (middle Bollinger Band), the stock moved to a higher high above 17. Despite this new high for the move, price did not exceed the upper band. This flashed a warning sign. The stock broke support a week later and MACD moved below its signal line. Notice that this M-top is more complex because there are lower reaction highs on either side of the peak (blue arrow). This evolving top formed a small head-and-shoulders pattern.
Signal: Walking the Bands
Moves above or below the bands are not signals per se. As Bollinger puts it, moves that touch or exceed the bands are not signals, but rather “tags”. On the face of it, a move to the upper band shows strength, while a sharp move to the lower band shows weakness. Momentum oscillators work much the same way. Overbought is not necessarily bullish. It takes strength to reach overbought levels and overbought conditions can extend in a strong uptrend. Similarly, prices can “walk the band” with numerous touches during a strong uptrend. Think about it for a moment. The upper band is 2 standard deviations above the 20-period simple moving average. It takes a pretty strong price move to exceed this upper band. An upper band touch that occurs after a Bollinger Band confirmed W-Bottom would signal the start of an uptrend. Just as a strong uptrend produces numerous upper band tags, it is also common for prices to never reach the lower band during an uptrend. The 20-day SMA sometimes acts as support. In fact, dips below the 20-day SMA sometimes provide buying opportunities before the next tag of the upper band.
Chart 6 shows Air Products (APD) with a surge and close above the upper band in mid July. First, notice that this is a strong surge that broke above two resistance levels. A strong upward thrust is a sign of strength, not weakness. Trading turned flat in August and the 20-day SMA moved sideways. The Bollinger Bands narrowed, but APD did not close below the lower band. Prices, and the 20-day SMA, turned up in September. Overall, APD closed above the upper band at least five times over a four month period. The indicator window shows the 10-period Commodity Channel Index (CCI). Dips below -100 are deemed oversold and moves back above -100 signal the start of an oversold bounce (green dotted line). The upper band tag and breakout started the uptrend. CCI then identified tradable pullbacks with dips below -100. This is an example of combining Bollinger Bands with a momentum oscillator for trading signals.
Chart 7 shows Monsanto (MON) with a walk down the lower band. The stock broke down in January with a support break and closed below the lower band. From mid January until early May, Monsanto closed below the lower band at least five times. Notice that the stock did not close above the upper band once during this period. The support break and initial close below the lower band signaled a downtrend. As such, the 10-period Commodity Channel Index (CCI) was used to identify short-term overbought situations. A move above +100 is overbought. A move back below +100 signals a resumption of the downtrend (red arrows). This system triggered two good signals in early 2010.
Conclusions
Bollinger Bands reflect direction with the 20-period SMA and volatility with the upper/lower bands. As such, they can be used to determine if prices are relatively high or low. According to Bollinger, the bands should contain 88-89% of price action, which makes a move outside the bands significant. Technically, prices are relatively high when above the upper band and relatively low when below the lower band. However, relatively high should not be regarded as bearish or as a sell signal. Likewise, relatively low should not be considered bullish or as a buy signal. Prices are high or low for a reason. As with other indicators, Bollinger Bands are not meant to be used as a stand alone tool. Chartists should combine Bollinger Bands with basic trend analysis and other indicators for confirmation.
Bands and SharpCharts
Bollinger Bands can be found in SharpCharts as a price overlay. As with a simple moving average, Bollinger Bands should be shown on top of a price plot. Upon selecting Bollinger Bands, the default setting will appear in the parameters window (20,2). The first number (20) sets the periods for the simple moving average and the standard deviation. The second number (2) sets the standard deviation multiplier for the upper and lower bands. These default parameters set the bands 2 standard deviations above/below the simple moving average. Users can change the parameters to suit their charting needs. Bollinger Bands (50,2.1) can be used for a longer timeframe or Bollinger Bands (10,1.9) can be used for a shorter timeframe.
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Developed by J. Welles Wilder, the Average True Range (ATR) is an indicator that measures volatility. As with most of his indicators, Wilder designed ATR with commodities and daily prices in mind. Commodities are frequently more volatile than stocks. They were are often subject to gaps and limit moves, which occur when a commodity opens up or down its maximum allowed move for the session. A volatility formula based only on the high-low range would fail to capture volatility from gap or limit moves. Wilder created Average True Range to capture this “missing” volatility. It is important to remember that ATR does not provide an indication of price direction, just volatility.
Wilder features ATR in his 1978 book, New Concepts in Technical Trading Systems. This book also includes the Parabolic SAR, RSI and the Directional Movement Concept (ADX). Despite being developed before the computer age, Wilder's indicators have stood the test of time and remain extremely popular.
True Range
Wilder started with a concept called True Range (TR), which is defined as the greatest of the following:
Method 1: Current High less the current Low
Method 2: Current High less the previous Close (absolute value)
Method 3: Current Low less the previous Close (absolute value)
Absolute values are used to ensure positive numbers. After all, Wilder was interested in measuring the distance between two points, not the direction. If the current period's high is above the prior period's high and the low is below the prior period's low, then the current period's high-low range will be used as the True Range. This is an outside day that would use Method 1 to calculate the TR. This is pretty straight forward. Methods 2 and 3 are used when there is a gap or an inside day. A gap occurs when the previous close is greater than the current high (signaling a potential gap down or limit move) or the previous close is lower than the current low (signaling a potential gap up or limit move). The image below shows examples of when methods 2 and 3 are appropriate.
Example A: A small high/low range formed after a gap up. The TR equals the absolute value of the difference between the current high and the previous close.
Example B: A small high/low range formed after a gap down. The TR equals the absolute value of the difference between the current low and the previous close.
Example C: Even though the current close is within the previous high/low range, the current high/low range is quite small. In fact, it is smaller than the absolute value of the difference between the current high and the previous close, which is used to value the TR.
Calculation
Typically, the Average True Range (ATR) is based on 14 periods and can be calculated on an intraday, daily, weekly or monthly basis. For this example, the ATR will be based on daily data. Because there must be a beginning, the first TR value is simply the High minus the Low, and the first 14-day ATR is the average of the daily TR values for the last 14 days. After that, Wilder sought to smooth the data by incorporating the previous period's ATR value.
Current ATR = [(Prior ATR x 13) + Current TR] / 14
- Multiply the previous 14-day ATR by 13.
- Add the most recent day's TR value.
- Divide the total by 14
In the spreadsheet example, the first True Range value (.91) equals the High minus the Low (yellow cells). The first 14-day ATR value (.56)) was calculated by finding the average of the first 14 True Range values (blue cell). Subsequent ATR values were smoothed using the formula above. The spreadsheet values correspond with the yellow area on the chart below. Notice how ATR surged as QQQQ plunged in May with many long candlesticks.
For those trying this at home, a few caveats apply. First, ATR values depend on where you begin. The first True Range value is simply the current High minus the current Low and the first ATR is an average of the first 14 True Range values. The real ATR formula does not kick in until day 15. Even so, the remnants of these first two calculations linger to slightly affect ATR values. Spreadsheet values for a small subset of data may not match exactly with what is seen on the price chart. Decimal rounding can also slightly affect ATR values.
Absolute ATR
ATR is based on the True Range, which uses absolute price changes. As such, ATR reflects volatility as absolute level. In other words, ATR is not shown as a percentage of the current close. This means low priced stocks will have lower ATR values than high price stocks. For example, a $20-30 security will have much lower ATR values than a $200-300 security. Because of this, ATR values are not comparable. Even large price movements for a single security, such as a decline from 70 to 20, can make long-term ATR comparisons impractical. Chart 4 shows Google with double digit ATR values and chart 5 shows Microsoft with ATR values below 1. Despite different values, their ATR lines have similar shapes.
Conclusions
ATR is not a directional indicator, such as MACD or RSI. Instead, ATR is a unique volatility indicator that reflects the degree of interest or disinterest in a move. Strong moves, in either direction, are often accompanied by large ranges, or large True Ranges. This is especially true at the beginning of a move. Uninspiring moves can be accompanied by relatively narrow ranges. As such, ATR can be used to validate the enthusiasm behind a move or breakout. A bullish reversal with an increase in ATR would show strong buying pressure and reinforce the reversal. A bearish support break with an increase in ATR would show strong selling pressure and reinforce the support break.
SharpCharts
Listed as “Average True Range”, ATR is on the Indicators drop-down menu. The “parameters” box to the right of the indicator contains the default value, 14, for the number of periods used to smooth the data. To adjust the period setting, highlight the default value and enter a new setting. Wilder often used 8 period ATR. SharpCharts also allows users to position the indicator above, below, or behind the price plot. A moving average can be added to identify upturns or downturns in ATR. Click “advanced options” to add a moving average as an indicator overlay. Click here for a live example of ATR.
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