Moving Average - Crossovers

Moving average crossovers are an important tool in the arsenal of any trader. Moving Average Convergence Divergence (MACD) one of the most popular indicator depends on them. Crossovers mark important shifts in momentum and support/resistance regardless of holding period. Many traders can therefore just stick with the major averages and find out most of what they need to know. The most popular settings draw charts with a 20-day for the short-term trend, a 50-day for the intermediate trend and a 200-day for the big picture. Long-term crossovers carry more weight than short-term events.

However, when trading with these crossovers, you should know this that these averages are lagging indicators. What this means is that they are giving a signal about the past price action something that has already taken place. These averages work very well in a trending market but do not work well in non trending or choppy markets.

Major types of Crossovers are Price Crossover, Double Moving Average Crossover and Triple Moving Average Crossover.

Price Crossover

Moving Averages can 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.

Chart given below 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.

Double Moving Average Crossover

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.

When using double moving average crossover as a technical indicator, you should be long when the short average is above the longer period average. And when it is below, you should be short. The crossovers of these short and longer averages provide the trading signal to act as they indicate that the momentum is shifting from one direction to another.

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. The Golden Cross represents a major shift from the bears to the bulls. It triggers when the 50-day average breaks above the 200-day average. Conversely, the Death Cross restores bear power when the 50-day falls back beneath the 200-day. The 200-day average becomes major resistance after the 50-day average drops below it, and major support after breaking above it. When price gets trapped between the 50-day and 200-day averages, it can whipsaw repeatedly between their price extremes. This pinball action marks a zone of opportunity for swing trades.

The chart below of the S&P Depository Receipts Exchange Traded Fund (SPY) shows the 50-day Simple Moving Average and the 200-day Simple Moving Average; this Moving Average pair is often looked at by big financial institutions as a long range indicator of market direction.

Note how the long-term 200-day Simple Moving Average is in an uptrend; this is a signal that the market is quite strong. Generally, a buy signal is established when the shorter-term 50-day SMA crosses above the 200-day SMA and contrastly, a sell signal is indicated when the 50-day SMA crosses below the 200-day SMA.

In the chart above of the S&P 500, both buy signals would have been extremely profitable, but the one sell signal would have caused a small loss. Keep in mind, that the 50-day, 200-day Simple Moving Average crossover is a very long-term strategy.

Triple Moving Average Crossover

The triple moving average crossover system is also used to generate buy and sell signals. Its buy signals come early in the development of a trend, and its sell signals are generated early when a trend ends. The third moving average can be used in combination with the other two moving averages to confirm or deny the signals that they generate. It thereby reduces the chance that the investor will be acting on false signals.

The shorter the moving average, the more closely it will follow the price trend. When a stock begins an uptrend, short-term moving averages will begin rising far earlier than longer-term moving averages. For example, if a stock declines by equal amounts each day for 50 days, and then begins to rise by the same amount each day for 50 days, the 5-day moving average will start to rise on the third day after the change in direction, the 10-day average will begin to rise on the sixth day after the change, and the 20-day average will begin to rise on the eleventh day. The longer a trend has persisted, the more likely it is to continue persisting, up to a point. Waiting too long to enter a trend can result in missing most of the gain. Entering the trend too early can mean entering on a false start and having to sell at a loss. Traders have addressed this problem by waiting for three moving averages to verify a trend by aligning in a certain way.

To illustrate, we’ll use the 5-day, 10-day, and 20-day moving averages. When an uptrend begins, the 5-day moving average will start rising first. Traders view this as interesting but of no major significance. As the upside momentum increases, longer moving averages gradually begin to follow suit.

A buying alert takes place when the 5-day crosses above both the 10 and the 20. That is, the average price of the stock over the last five days is greater than its average over both the last ten days and the last twenty days. This shows a short-term shift in trend. A buy signal is confirmed when the 10-day then crosses above the 20-day. The 10-day average price of a stock is more meaningful than the 5-day average price. If the average price over the last ten days is greater than the average price over the last twenty days, the shift in momentum is considered to be much more significant.

Conversely, when an uptrend changes to a downtrend, the first thing that happens is that the 5-day declines below the 10-day and 20-day averages. This constitutes an alert that a sell signal may be forthcoming. The confirmed sell signal occurs when the 10-day crosses below the 20-day resulting in an alignment in which the 5-day average is below the 10-day average and the 10-day average is below the 20-day average.

Investors and traders might be wise to incorporate another indicator into their decision-making. To increase the reliability of the signals given by the system outlined above, it might be wise to use the 50-day moving average as a context and reference. The best and most profitable time to buy a stock is early in a new trend. Later buy signals carry greater risk that the stock will soon decline (because stocks don’t go up forever). Therefore, if the 50-day average has been in a significant decline and is now leveling off or just beginning to rise, a buy signal using the triple crossover method outlined above has a greater chance of success than if the 50-day average has been rising for a long time, or is beginning to level off or decline after a prolonged advance. In other words, the intermediate-term 50-day average can be used to confirm and "support" the signals given by the shorter-term moving averages. Generally, it's better to avoid buying a stock if its 50-day moving average is in decline. A short-term trader might make an exception to this general policy in order to profit from a snap-back toward the declining 50-day average from an extreme oversold condition.

An example of triple moving average crossover is shown in the chart below of Wal-Mart (WMT) stock. The first crossover of the quickest SMA (in the example above, the 10-day SMA) across the next quickest SMA (20-day SMA) acts as a warning that prices are reversing trend; however, usually a buy or sell order is not placed yet. The second crossover of the quickest SMA (10-day) and the slowest SMA (50-day) finally triggers the buy or sell signal. A more conservative approach is to wait until the middle SMA (20-day) crosses over the slower SMA (50-day).

Limitations of Crossovers

Moving Averages Crossovers add horsepower to many types of trading strategies. But try to limit their use to trending markets. They work best in trending markets, where an uptrend or downtrend is firmly in place, but they generate many false signals in choppy, sideways markets. Moving averages emit false signals during the "negative feedback" of sideways markets. Keep in mind these common indicators measure directional momentum. They lose power in markets with little or no price change.

Moving Averages crossovers produce relatively late signals. After all, the system employs two lagging indicators. Moving Averages are lagging indicators because they use historical information. Using them as indicators will not get you in at the bottom and out at the top but will get you in and out somewhere in between. 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.

For years, technicians have tried to filter crossover systems through trend-recognition formulas in order to reduce whipsaws. You can try this for yourself, or just look for price patterns that tell you the crossovers are worthless. Take a look at a chart of any market with a strong trend. You will see that the moving averages are not crossing back and forth repeatedly. They will be moving in the same general direction in a more or less parallel fashion. Now look at a chart of a non-trending market. As this market moves sideways the moving averages will be crossing back and forth very frequently. Look at the implications of this simple examination of the charts. If we are trading the crossovers we will be trading most frequently in non-trending markets and trading most infrequently in strongly trending markets.

With a little thought and effort I’m sure we can design some reliable entry signals that are based on moving averages but avoid the typical crossover signals. For example we could measure the slope of several moving averages and when all the averages slope upward we would have a buy signal.We could also measure the distance between several moving averages and implement our trades when the averages are all headed in the same direction but start getting farther apart. This procedure would give us a series of entry signals within the same original trend. This should provide an excellent entry and re-entry strategy.

Persistent rangebound markets limit the usefulness of all types of average information. All moving averages eventually converge toward a single price level in dead markets. This flatline behavior yields few clues about market direction. So stop using averages completely when this happens, and move to oscillators (such as Stochastics) to predict the next move.

Major Uses of Moving Averages

Moving averages are the basis of chart and time series analysis. Simple moving averages and the more complex exponential moving averages help visualize the trend by smoothing out price movements. Charting analysis can be traced back to 18th Century Japan, yet how and when moving averages were first applied to market prices remains a mystery. It is generally understood that simple moving averages (SMA) were used long before exponential moving averages(EMA), because EMAs are built on SMA framework and the SMA continuum was more easily understood for plotting and tracking purposes.

Some of the primary functions of moving averages are to identify current trends and trend reversals, measure the strength of an asset's momentum and determine potential areas where an asset will find support or resistance.

Trend Identification

Identifying trends is one of the key functions of moving averages, which are used by most traders who seek to "make the trend their friend". Moving averages are lagging indicators, which means that they do not immediately predict new trends, but confirm trends once they have been established. A stock is deemed to be in an uptrend when the price is above a moving average and the average is sloping upward. Many traders will only consider holding a long position in an asset when the price is trading above a moving average whereas he will use a price below a downward sloping average to confirm a downtrend. This simple rule can help ensure that the trend works in the traders' favor. As you can see in the Figure given below, 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 signals a downtrend.

Another method of determining trend 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.

Trend Reversal

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 the Figure given below, 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 the Figure given below, 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.

Momentum

Many beginner traders ask how it is possible to measure momentum and how moving averages can be used to tackle such a feat. The simple answer is to pay close attention to the time periods used in creating the average, as each time period can provide valuable insight into different types of momentum. In general, short-term momentum can be gauged by looking at moving averages that focus on time periods of 20 days or less. Looking at moving averages that are created with a period of 20 to 100 days is generally regarded as a good measure of medium-term momentum. Finally, any moving average that uses 100 days or more in the calculation can be used as a measure of long-term momentum. Common sense should tell you that a 15-day moving average is a more appropriate measure of short-term momentum than a 200-day moving average.

One of the best methods to determine the strength and direction of an asset's momentum is to place three moving averages onto a chart and then pay close attention to how they stack up in relation to one another. The three moving averages that are generally used have varying time frames in an attempt to represent short-term, medium-term and long-term price movements. In the Figure given below, strong upward momentum is seen when shorter-term averages are located above longer-term averages and the two averages are diverging. Conversely, when the shorter-term averages are located below the longer-term averages, the momentum is in the downward direction.

Support and Resistance

Another major way in which moving averages are used is to identify support and resistance levels. Moving averages act as a support in an uptrend and resistance in a downtrend. 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. Many traders anticipate a "bounce off" of major moving averages and use other technical indicators as confirmation of the expected move.

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.

However a move through a major moving average is often used as a signal by technical traders that the trend is reversing and once the price of an asset falls below an influential level of support, such as the 200-day moving average, it is not uncommon to see the average act as a strong barrier that prevents investors from pushing the price back above that average. Hence, what was acting as a major support in an uptrend is now a major resistance. This resistance is often used by traders as a sign to take profits or to close out any existing long positions. Many short sellers will also use these averages as entry points because the price often bounces off the resistance and continues its move lower.

Below chart 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.

The support and resistance characteristics of moving averages make them a great tool for managing risk. The ability of moving averages to identify strategic places to set stop-loss orders allows traders to cut off losing positions before they can grow any larger. As you can see in the below Figure, traders who hold a long position in a stock and set their stop-loss orders below influential averages can save themselves a lot of money. Using moving averages to set stop-loss orders is key to any successful trading strategy.

Limitations of Using Moving Averages

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. Don't 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.

SMA vs. EMA

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. The simple moving average may sound, perhaps, too simple. The exponential moving average is considerably more complicated. The basic concept is that it weights the most recent price data most heavily.

Moving averages are lagging indicators, and therefore, by definition, will give late signals. By weighting recent price data more heavily, exponential moving averages attempt to speed up the signal given. The disadvantage of doing this, of course, is that this more-rapid signal can sometimes be premature and therefore give the swing trader a false indication to trade. 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 time frames to find the best fit. Below Chart 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.

Which moving average you use will depend on your trading and investing style and preferences. Some traders prefer to use exponential moving averages for shorter time periods to capture changes more quickly. Some investors prefer simple moving averages over the duration of long time periods to identify long-term trend changes. Many traders plot several different moving averages to give them both sides of the story. They might use a longer period simple moving average to find out what the overall trend is, and then use a shorter period exponential moving average to find a good time to enter a trade.

Ultimately, it comes down to your experience and even the character of a given security – some tend to ‘work’ better with SMAs while others do so with EMAs – it takes practice and experience to find the balance that works for you. A 50-day SMA might work great for identifying support levels in the NASDAQ, but a 100-day EMA may work better for the Dow Transports, for instance. Moving average type and length of time will depend greatly on the individual security and how it has reacted in the past.

Exponential Moving Average (EMA)

This moving average calculation uses a smoothing factor to place a higher weight on recent data points. 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 above, a 15-period EMA rises and falls faster than a 15-period SMA. This slight difference doesn’t seem like much, but it is an important factor to be aware of since it can affect returns.

The exponential moving average has been refined and more commonly used since the 1960s, thanks to earlier practitioners' experiments with the computer. The new EMA would focus more on most recent prices rather than on a long series of data points, as the simple moving average required.

EMA 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 period's 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.

SMA: 10 period sum / 10

Multiplier: (2 / (Time periods + 1) ) = (2 / (10 + 1) ) = 0.1818 (18.18%)

EMA: {Close - EMA(previous day)} x multiplier + EMA(previous day).

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/(20+1) = .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.

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. As you can see in the figure above, 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.

Simple moving averages became the preferred method for tracking market prices because they are quick to calculate and easy to understand. Early market practitioners operated without the use of the sophisticated chart metrics in use today, so they relied primarily on market prices as their sole guides. They calculated market prices by hand, and graphed those prices to denote trends and market direction. This process was quite tedious, but proved quite profitable with confirmation of further studies.

SMA 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.

Daily Closing Prices: 11,12,13,14,15,16,17

First day of 5-day SMA: (11 + 12 + 13 + 14 + 15) / 5 = 13

Second day of 5-day SMA: (12 + 13 + 14 + 15 + 16) / 5 = 14

Third day of 5-day SMA: (13 + 14 + 15 + 16 + 17) / 5 = 15

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.

Limitations of SMA

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.

Moving Averages

Introduction

Most chart patterns show a lot of variation in price movement. This can make it difficult for traders to get an idea of a security's 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 security's 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. 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.

Moving averages are termed "moving" because the group of prices used in the calculation move according to the point on the chart. This means old days are dropped in favor of new closing price days, so a new calculation is always needed corresponding to the time frame of the average employed. So, a 10-day average is recalculated by adding the new day and dropping the 10th day, and the ninth day is dropped on the second day.

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 two most popular types ofmoving averages are the Simple Moving Average(SMA) and the Exponential Moving Average(EMA). Thesemoving averages can be used to identify the direction of the trend or define potential support and resistance levels.

The Lag Factor

The longer the moving average, the more the lag. A 10-day 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 200-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 200-day moving average to change course. Below chart shows the S&P CNX Nifty with a 10-day SMA closely following prices and a 200-day EMA grinding higher. The 50-day EMA fits somewhere between the 10 and 200 day moving averages when it comes to the lag factor.

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.

BEARISH CONTINUATION CANDLESTICK PATTERNS

BEARISH CONTINUATION PATTERNS

BEARISH REVERSAL CANDLESTICK PATTERNS



BEARISH REVERSAL PATTERNS



BULLISH CONTINUATION CANDLESTICK PATTERNS

BULLISH CONTINUATION PATTERNS

CANDLESTICKS PATTERN - BULLISH DRAGONFLY DOJI

BULLISH DRAGONFLY DOJI

Type:	Reversal
Relevance:	Bullish
Prior Trend:	Bearish
Reliability:	Medium
Confirmation:	Suggested
No. of Sticks:	1

The Bullish Dragonfly Doji Pattern is a single candlestick pattern that occurs at the bottom of a trend or during a downtrend. The Bullish Dragonfly Doji Pattern is very similar to the Bullish Hammer Pattern mentioned above. The distinction between the two is if there is a body or not. In case of Bullish Dragonfly Doji Pattern, the opening and closing prices are identical and there is no body. On the other hand the Bullish Hammer Pattern has a small real body at the upper end of the trading range.

Recognition Criteria:

1. There is an overall downtrend in the market.
2. Then we see a Doji at the upper end of the trading range.
3. The doji has an extremely long lower shadow.
4. However the doji does not have any upper shadow.

Explanation:

The market is in an overall bearish mood characterized by a downtrend. Then market opens and sells off sharply. However, the sell-off is suddenly abated and the prices reverse direction and start going up for the rest of the day closing at or near the day’s high thus leading to the long lower shadow. The failure of the market to continue in the selling side reduces the bearish sentiment. Now the shorts are increasingly uneasy with their bearish positions. If the market opens higher next day, many shorts will have a strong incentive to cover their short positions.

Important Factors:

The Bullish Dragonfly Doji Pattern is a more bullish signal than a Bullish Hammer Pattern. Its reliability is also higher than the Bullish Hammer Pattern. 

However, a confirmation of the trend reversal implied by this pattern by either a white candlestick, a large gap up or a higher close on the next trading day is still suggested, to be on the safe side.