What Is a Bullish Engulfing Pattern?

A bullish engulfing pattern is a white candlestick that closes higher than the previous day’s opening after opening lower than the previous day’s close. It can be identified when a small black candlestick, showing a bearish trend, is followed the next day by a large white candlestick, showing a bullish trend, the body of which completely overlaps or engulfs the body of the previous day’s candlestick.

A bullish engulfing pattern may be contrasted with a bearish engulfing pattern.

Understanding a Bullish Engulfing Pattern

The bullish engulfing pattern is a two-candle reversal pattern. The second candle completely ‘engulfs’ the real body of the first one, without regard to the length of the tail shadows.

This pattern appears in a downtrend and is a combination of one dark candle followed by a larger hollow candle. On the second day of the pattern, the price opens lower than the previous low, yet buying pressure pushes the price up to a higher level than the previous high, culminating in an obvious win for the buyers.

What Does a Bullish Engulfing Pattern Tell You?

A bullish engulfing pattern is not to be interpreted as simply a white candlestick, representing upward price movement, following a black candlestick, representing downward price movement. For a bullish engulfing pattern to form, the stock must open at a lower price on Day 2 than it closed at on Day 1. If the price did not gap down, the body of the white candlestick would not have a chance to engulf the body of the previous day’s black candlestick.

Because the stock both opens lower than it closed on Day 1 and closes higher than it opened on Day 1, the white candlestick in a bullish engulfing pattern represents a day in which bears controlled the price of the stock in the morning only to have bulls decisively take over by the end of the day.

The white candlestick of a bullish engulfing pattern typically has a small upper wick, if any. That means the stock closed at or near its highest price, suggesting that the day ended while the price was still surging upward.

This lack of an upper wick makes it more likely that the next day will produce another white candlestick that will close higher than the bullish engulfing pattern closed, though it’s also possible that the next day will produce a black candlestick after gapping up at the opening. Because bullish engulfing patterns tend to signify trend reversals, analysts pay particular attention to them.

Bullish Engulfing Pattern vs. Bearish Engulfing Pattern

These two patterns are opposites of one another. A bearish engulfing pattern occurs after a price moves higher and indicates lower prices to come. Here, the first candle, in the two-candle pattern, is an up candle. The second candle is a larger down candle, with a real body that fully engulfs the smaller up candle.

Example of a Bullish Engulfing Pattern

As a historical example, let’s consider Philip Morris (PM) stock. The company’s shares were a great long in 2011 and remained in an uptrend. In 2012, though, the stock was retreating.

On January 13, 2012, a bullish engulfing pattern occurred; the price jumped from an open of $76.22 to close out the day at $77.32. This bullish day dwarfed the prior day’s intraday range where the stock finished down marginally. The move showed that the bulls were still alive and another wave in the uptrend could occur.

Bullish Engulfing Candle Reversals

Investors should look not only to the two candlesticks which form the bullish engulfing pattern but also to the preceding candlesticks. This larger context will give a clearer picture of whether the bullish engulfing pattern marks a true trend reversal.

Bullish engulfing patterns are more likely to signal reversals when they are preceded by four or more black candlesticks. The more preceding black candlesticks the bullish engulfing candle engulfs, the greater the chance a trend reversal is forming, confirmed by a second white candlestick closing higher than the bullish engulfing candle.

Acting on a Bullish Engulfing Pattern

Ultimately, traders want to know whether a bullish engulfing pattern represents a change of sentiment, which means it may be a good time to buy. If volume increases along with price, aggressive traders may choose to buy near the end of the day of the bullish engulfing candle, anticipating continuing upward movement the following day. More conservative traders may wait until the following day, trading potential gains for greater certainty that a trend reversal has begun.

Limitations of Using Engulfing Patterns

A bullish engulfing pattern can be a powerful signal, especially when combined with the current trend; however, they are not bullet-proof. Engulfing patterns are most useful following a clean downward price move as the pattern clearly shows the shift in momentum to the upside. If the price action is choppy, even if the price is rising overall, the significance of the engulfing pattern is diminished since it is a fairly common signal.

The engulfing or second candle may also be huge. This can leave a trader with a very large stop loss if they opt to trade the pattern. The potential reward from the trade may not justify the risk.

Establishing the potential reward can also be difficult with engulfing patterns, as candlesticks don’t provide a price target. Instead, traders will need to use other methods, such as indicators or trend analysis, for selecting a price target or determining when to get out of a profitable trade.

What Is the Average True Range (ATR)?

The average true range (ATR) is a technical analysis indicator introduced by market technician J. Welles Wilder Jr. in his book New Concepts in Technical Trading Systems that measures market volatility by decomposing the entire range of an asset price for that period.

The true range indicator is taken as the greatest of the following: current high less the current low; the absolute value of the current high less the previous close; and the absolute value of the current low less the previous close. The ATR is then a moving average, generally using 14 days, of the true ranges.

Traders can use shorter periods than 14 days to generate more trading signals, while longer periods have a higher probability to generate fewer trading signals.

The Average True Range (ATR) Formula

The formula to calculate ATR for an investment with a previous ATR calculation is :

$\begin{aligned}&\frac{ \text{Previous ATR} ( n – 1 ) + \text{TR} }{ n } \\&\textbf{where:} \\&n = \text{Number of periods} \\&\text{TR} = \text{True range} \\\end{aligned}$​nPrevious ATR(n−1)+TR​where:n=Number of periodsTR=True range​

If there is not a previous ATR calculated, you must use:

$\begin{aligned}&\Big ( \frac{ 1 }{ n } \Big ) \sum_{i}^{n} \text{TR}_i \\&\textbf{where:} \\&\text{TR}_i = \text{Particular true range, such as first day’s TR,} \\&\text{then second, then third} \\&n = \text{Number of periods} \\\end{aligned}$​(n1​)i∑n​TRi​where:TRi​=Particular true range, such as first day’s TR,then second, then thirdn=Number of periods​

You must first use the following formula to calculate the true range:

$\begin{aligned}&\text{ TR } = \text{ Max } [ ( \text{H} – \text{L} ), | \text{H} – \text{C}_p |, | \text{L} – \text{C}_p | ] \\&\textbf{where:} \\&\text{H} = \text{Today’s high} \\&\text{L} = \text{Today’s low} \\&\text{C}_p = \text{Yesterday’s closing price} \\&\text{Max} = \text{Highest value of the three terms} \\&\textbf{so that:} \\&( \text{H} – \text{L} ) = \text{Today’s high minus the low} \\&| \text{H} – \text{C}_p | = \text{Absolute value of today’s high minus} \\&\text{yesterday’s closing price} \\&| \text{L} – \text{C}_p | = \text{Absolute value of today’s low minus} \\&\text{yesterday’s closing price} \\\end{aligned}$​ TR = Max [(H−L),∣H−Cp​∣,∣L−Cp​∣]where:H=Today’s highL=Today’s lowCp​=Yesterday’s closing priceMax=Highest value of the three termsso that:(H−L)=Today’s high minus the low∣H−Cp​∣=Absolute value of today’s high minusyesterday’s closing price∣L−Cp​∣=Absolute value of today’s low minusyesterday’s closing price​

How to Calculate the ATR

The first step in calculating ATR is to find a series of true range values for a security. The price range of an asset for a given trading day is its high minus its low. To find an asset’s true range value, you first determine the three terms from the formula.

Suppose that XYZ’s stock had a trading high today of $21.95 and a low of $20.22. It closed yesterday at $21.51. Using the three terms, we use the highest result:

$( \text{H} – \text{L}) = \$21.95 – \$20.22 = \$1.73$(H−L)=$21.95−$20.22=$1.73

$| ( \text{H} – \text{C}_p ) | = | \$21.95 – \$21.51 | = \$0.44$∣(H−Cp​)∣=∣$21.95−$21.51∣=$0.44

$| ( \text{L} – \text{C}_p ) | = | \$20.22 – \$21.51 | = \$1.29$∣(L−Cp​)∣=∣$20.22−$21.51∣=$1.29

The number you’d use would be $1.73 because it is the highest value.

Because you don’t have a previous ATR, you need to use the ATR formula:

$\begin{aligned}\Big ( \frac{ 1 }{ n } \Big ) \sum_{i}^{n} \text{TR}_i\end{aligned}$(n1​)i∑n​TRi​​

Using 14 days as the number of periods, you’d calculate the TR for each of the 14 days. Assume the following prices from the table.

What Is the Arithmetic Mean?

The arithmetic mean is the simplest and most widely used measure of a mean, or average. It simply involves taking the sum of a group of numbers, then dividing that sum by the count of the numbers used in the series. For example, take the numbers 34, 44, 56, and 78. The sum is 212. The arithmetic mean is 212 divided by four, or 53.

People also use several other types of means, such as the geometric mean and harmonic mean, which comes into play in certain situations in finance and investing. Another example is the trimmed mean, used when calculating economic data such as the consumer price index (CPI) and personal consumption expenditures (PCE).

How the Arithmetic Mean Works

The arithmetic mean maintains its place in finance, as well. For example, mean earnings estimates typically are an arithmetic mean. Say you want to know the average earnings expectation of the 16 analysts covering a particular stock. Simply add up all the estimates and divide by 16 to get the arithmetic mean.

The same is true if you want to calculate a stock’s average closing price during a particular month. Say there are 23 trading days in the month. Simply take all the prices, add them up, and divide by 23 to get the arithmetic mean.

The arithmetic mean is simple, and most people with even a little bit of finance and math skill can calculate it. It’s also a useful measure of central tendency, as it tends to provide useful results, even with large groupings of numbers.

Limitations of the Arithmetic Mean

The arithmetic mean isn’t always ideal, especially when a single outlier can skew the mean by a large amount. Let’s say you want to estimate the allowance of a group of 10 kids. Nine of them get an allowance between $10 and $12 a week. The tenth kid gets an allowance of $60. That one outlier is going to result in an arithmetic mean of $16. This is not very representative of the group.

In this particular case, the median allowance of 10 might be a better measure.

The arithmetic mean also isn’t great when calculating the performance of investment portfolios, especially when it involves compounding, or the reinvestment of dividends and earnings. It is also generally not used to calculate present and future cash flows, which analysts use in making their estimates. Doing so is almost sure to lead to misleading numbers.

Arithmetic vs. Geometric Mean

For these applications, analysts tend to use the geometric mean, which is calculated differently. The geometric mean is most appropriate for series that exhibit serial correlation. This is especially true for investment portfolios.

Most returns in finance are correlated, including yields on bonds, stock returns, and market risk premiums. The longer the time horizon, the more critical compounding and the use of the geometric mean becomes. For volatile numbers, the geometric average provides a far more accurate measurement of the true return by taking into account year-over-year compounding.

The geometric mean takes the product of all numbers in the series and raises it to the inverse of the length of the series. It’s more laborious by hand, but easy to calculate in Microsoft Excel using the GEOMEAN function.

The geometric mean differs from the arithmetic average, or arithmetic mean, in how it’s calculated because it takes into account the compounding that occurs from period to period. Because of this, investors usually consider the geometric mean a more accurate measure of returns than the arithmetic mean.

Example of the Arithmetic vs. Geometric Mean

Let’s say that a stock’s returns over the last five years are 20%, 6%, -10%, -1%, and 6%. The arithmetic mean would simply add those up and divide by five, giving a 4.2% per year average return.

The geometric mean would instead be calculated as (1.2 x 1.06 x 0.9 x 0.99 x 1.06)^1/5 -1 = 3.74% per year average return. Note that the geometric mean, a more accurate calculation in this case, will always be smaller than the arithmetic mean.