What Is a Bar Graph?

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What Is a Bar Graph?

A bar graph is a graphical representation of information. It uses bars that extend to different heights to depict value.

Bar graphs can be created with vertical bars, horizontal bars, grouped bars (multiple bars that compare values in a category), or stacked bars (bars containing multiple types of information).

Bar graphs are commonly used in business and financial analysis to display often complicated data. They can convey information quickly and effectively. In the financial industry, a volume chart is a commonly used vertical bar graph.

Key Takeaways

  • Bar graphs can display data in visual ways.
  • Bar graphs have an x-axis and a y-axis and can be used to compare one or more categories of data.
  • Data is presented via vertical or horizontal bars.
  • Bars can represent one or more labeled variables.
  • Bars can also be grouped together for comparative purposes.

Understanding a Bar Graph

The purpose of a bar graph is to convey relational information quickly in a visual manner. The bars display the value for a particular category of data.

The vertical axis on the left or right side of the bar graph is called the y-axis. The horizontal axis at the bottom of a bar graph is called the x-axis.

The height or length of the bars represents the value of the data. The value corresponds to levels on the y-axis.

The values on the x-axis can be any variable, such as time, earnings per share (EPS), revenue, or cash flow. Bar graphs are often used to depict trading volume for a security. They appear in a panel below a security’s price chart.

Image by Sabrina Jiang © Investopedia 2021


Bar Graph Properties

Certain aspects of a bar graph separate them from other types of graphs and charts.

  • The bars on a bar graph have equal width and interval spacing.
  • Bars can run vertically or horizontally.
  • Bars share the same starting point or base. In other words, all bars will start at the bottom of the graph and extend upward (vertically) or they’ll start at the side of the graph and extend across (horizontally).
  • The y-axis of a bar graph is the side or vertical axis.
  • The x-axis of a bar graph is the bottom or horizontal axis.
  • Data value is defined on the y-axis; data type is defined on the x-axis.
  • Bar height or extension corresponds to the value of data.
  • The higher or longer a bar, the greater the value.
  • If colors are used, a bar graph may include a legend that defines them.

Bar Graph Types

Vertical Bar Graph

A vertical bar graph contains data that’s displayed vertically using rectangular bars that represent a measure of data. The rectangular bars start and extend from the bottom x-axis. The y-axis allows users to measure the height of the bars against specific levels of value inscribed on it. Usually, the higher the bar, the greater the value.

Horizontal Bar Graph

A horizontal bar graph contains data that’s displayed horizontally using rectangular bars that represent a measure of data. The rectangular bars start and extend from the side y-axis, In this case, the x-axis allows users to measure the length of the bars against specific levels of value inscribed on it. Usually, the longer the bar, the greater the value.

Grouped Bar Graph

Grouped bar graphs, also called clustered bar graphs, represent discrete values for more than one item in the same category. The separate, rectangular bars are grouped together. Essentially, they break down the overall value (or items) for (or within) the category. A grouped bar graph could display more than one category, each with its separate rectangular bars. The information can be depicted vertically or horizontally.

Stacked Bar Graph

Stacked bar graphs, also known as composite bar graphs, divide a total into parts. These parts are typically identified using different colors within the same rectangular bar. So, a single rectangular bar that represents a total will display several parts and colors. The parts need to be labeled for identification. The information can be depicted vertically or horizontally.

Bar Graph Uses

  • A bar graph is used to present data visually
  • It can be used by industries to convey complicated information easily
  • It can compare different variables and values
  • It can reveal and facilitate the study of patterns over time
  • It can compare various sets of data
  • It can display categories and sub-categories
  • It can display results of surveys

In technical analysis, a volume bar chart shows how much trading volume there was on a particular day. The x-axis displays days, while a bar extending up from any day depicts the amount of volume, as measured by the y-axis.

When a bar graph has a well-defined zero point and the data set has both positive and negative values in relation to this point, both ranges of values can be displayed. Bars above the zero line typically represent positive values, while bars below the zero line typically show negative values.

Example of a Bar Graph

Many traders employ a moving average convergence divergence (MACD) histogram, which is a popular technical indicator that illustrates the difference between the MACD line and the signal line.

The following daily price chart for Apple stock shows three types of bar graphs.

Image by Sabrina Jiang © Investopedia 2021


Extending from the right is price by volume, a type of horizontal bar graph which shows volume dispersion based on price.

Along the bottom of the chart, volume is shown using a vertical bar graph. It displays bars representing the number of shares traded per day.

Finally, the MACD histogram at the very bottom shows the separation between the MACD and the signal line. When the histogram crosses the zero line it means the MACD and signal line have crossed, which some traders use as a trade signal.

Bar Graph vs. Bar Chart

A bar graph shows data in columns, while a bar chart is a technical analysis tool that displays the open, high, low, and close prices for a particular security during a specific time period (such as a day or week) using a vertical bar. Small horizontal lines extend to the left and right of the vertical bar to show the open and close prices. The top and bottom of each bar represent the high and low prices for the period.

Unlike the bar graph, the price bar chart only covers relevant prices and does not extend all the way up from the x-axis.

Bar Graph vs. Histogram

The most immediately noticeable difference between a bar graph and a histogram is that the bars in a bar graph typically don’t touch each other (other than in a grouped bar graph). A histogram is a type of bar graph where the bars have no gaps between them.

A histogram is used to depict the frequency distribution of variables in a data set. A bar graph depicts a comparison of discrete or categorical variables. Furthermore, a histogram displays distribution frequency as a two-dimensional figure: the height and width of rectangles have specific meanings. Both can vary. A bar graph is one-dimensional. The height of the rectangular bars represents something specific while the width is meaningless.

Bar Graph Limitations

A bar graph is a way to display information. How the data is chosen to be displayed could affect its interpretation. For example, if too large of a scale is chosen, then the data may appear insignificant when in actuality, it’s not. The scale doesn’t allow for an appropriate comparison.

In addition, bar graphs may make data look compelling when it actually lacks substance. For example, looking at only a few days worth of volume data in a stock doesn’t provide much relevant information. Yet comparing recent volume to volume over the last year can provide a technical trader with useful information for trading decisions.

What Are Some Benefits of a Bar Graph?

A bar graph can be of great use when you have to explain the meaning of complex data. It allows you to compare different sets of data among different groups easily. It instantly demonstrates this relationship using two axes, where the categories are on one axis and the various values are on the other. A bar graph can also illustrate important changes in data throughout a period of time.

Why Are Bar Graphs Used?

They’re used to present data, or a concept involving data, in a visual way. This can make it easier for people to quickly understand the meaning of the data. In addition, presenting data graphically rather than through text or the spoken word can be an efficient and faster way to communicate.

What Are the Types of Bar Graphs?

There are horizontal and vertical bar graphs. There are also stacked and grouped bar graphs. While histograms are similar in appearance to bar graphs, they represent data in a different way.

The Bottom Line

A bar graph can be a very useful business tool that helps deliver complicated data and concepts in a way that’s easy to understand.

The overall relationship of the data (and, thus, the main point that a company is making with its presentation) is illustrated using the y-axis (values) and the x-axis (categories).

Traders use volume bar graphs every day. These can measure, for example, the number of trades executed over a certain time period (such as a day) for different securities. Or, they can indicate the volume of trades at particular prices for a security.

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Technical Analysis That Indicates Market Psychology

Written by admin. Posted in Technical Analysis

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The principles of market psychology underlie every technical indicator, so a good understanding of crowd behavior is crucial to your comprehension of the fundamentals of certain technical indicators. The psychology of the market is hard to predict, but several trusted indicators make it easier for traders and investors to better estimate directional changes based on shifting sentiment.

Here, we look at several technical indicators that are driven by the psychology of the market.

Key Takeaways

  • Select technical indicators are used by market participants to better understand market psychology and behavior.
  • This is because price and volume action can be thought of as a history of changes and shifts in sentiment such as fear and greed.
  • Here, we look at how market psychology informs several such indicators including the MACD, ADX, RoC, and Williams %R.

MACD

The moving average convergence divergence (MACD) is simply a tool that measures shifts in consensus from bullishness to bearishness, and vice versa. Extending the basic MACD to a deeper level, we find the MACD-histogram, which is actually a tool for determining the difference between long-term and short-term consensus of value. The measure tracks the difference between the fast MACD line (short-term consensus) and the slow signal line (longer-term consensus).

The Directional System

The directional system was developed by J. Welles Wilder, Jr., as a means of identifying trends that are strong enough to be valid and useful indicators for traders. Directional lines are constructed to determine whether trends are bullish or bearish: When a positive directional line is above the negative line, bullish traders possess greater strength (and a bullish signal is given). The opposite situation indicates bearishness. More telling is the average directional indicator (ADX), which rises when the spread between the positive and negative lines increases. When the ADX rises, profitable investments are getting ever stronger, and losers are getting weaker; furthermore, the trend is likely to continue.

Momentum and Rate of Change (RoC)

Momentum indicators measure changes in mass optimism or pessimism by comparing today’s consensus of value (price) to an earlier consensus of value. Momentum and RoC are specific measures against which actual prices are compared: When prices rise but momentum or rate of change falls, a top is likely near. If prices reach a new high but momentum or RoC reach a lower top, a sell signal is realized. These rules also apply in the opposite situation, when prices fall or new lows are reached.

Smoothed Rate of Change

The smoothed rate of change compares today’s exponential moving average (average consensus) to the average consensus of some point in the past. The smoothed rate of change is simply an enhanced version of the RoC momentum indicator—it is intended to alleviate the RoC’s potential for errors in determining the market’s attitude of bullishness or bearishness.

Williams %R (Wm%R)

Wm%R, a measure focusing on closing prices, compares each day’s closing price with a recent consensus range of value (range of closing prices). If on a particular day, bulls are able to push the market to the top of its recent range, Wm%R issues a bullish signal, and a bearish signal is issued if bears can push the market to the bottom of its range.

Stochastics

Similar to Wm%R, stochastics measure closing prices against a range. If bulls push prices up during the day but cannot achieve a close near the top of the range, stochastic turns down, and a sell signal is issued. The same also holds true if bears push prices down but cannot achieve a close near the low, in which case a buy signal is issued.

Relative Strength Index (RSI)

RSI also measures market psychology in a fundamentally similar way to that of Wm%R. RSI is almost always measured with a computer, typically over a seven- or nine-day range, producing a numerical result between 0 and 100 that points to oversold or overbought situations; the RSI, therefore, gives a bullish or bearish signal, respectively.

Volume

The total volume of shares traded is an excellent way in which to ascertain the psychology of the market. Volume is actually a measure of investors’ emotional state: While a burst of volume will cause sudden pain to poorly-timed investments and immediate elation for those who made wise investments, low volume will likely not result in a significant emotional response.

The longest-lasting trends generally occur when emotion is the lowest. When volume is moderate and both shorts and longs do not experience the roller coaster ride of emotion, the trend can reasonably be expected to continue until the emotion of the market changes. In a longer-term trend such as this, small price changes either up or down do not precipitate much emotion, and even a series of small changes occurring day after day (enough to create a major, gradual trend) will generally not generate severe emotional reactions.

In the case of short selling, a market rally may serve to flush out those individuals holding short positions, causing them to cover and subsequently push the market higher. The same principle holds true on the flip side: when the longs give up and bailout, the decline pulls more poorly timed investments with it. At the most fundamental level of market volume, both short and long investors who lose money, who collectively exit their positions, are the primary drivers behind significant volume trends.

Frequently Asked Questions

How do technical indicators and market psychology fit together?

Technical analysis looks at price charts to find patterns that indicate trends and reversals. Technicians believe that these patterns are the result of market psychology. A price chart, then, can be thought of as a graphical representation of emotions such as fear, greed, optimism and pessimism, and human behavior, such as herd instinct. Price charts illustrate how market participants react to future expectations.  

What do the MACD and ADX reveal about market sentiment?

The moving average convergence divergence (MACD) demonstrates the shift in consensus between bullishness and bearishness. The directional system uses directional lines to indicate whether trends are bullish or bearish, including the average directional indicator (ADX).

What do RoC and Williams %R reveal about market sentiment?

Momentum and the Rate of Change (RoC) demonstrate sentiment and the likelihood of tops or bottoms forming by looking at current price levels versus an earlier consensus of price. The smoothed rate of change looks at the current average consensus versus the consensus of a previous point.

Williams %R assesses closing prices versus a recent range of closing prices; stochastics look at closing prices versus a range; the relative strength index (RSI) looks at prices over a seven- or nine-day range.

How can volume indicators uncover trader psychology?

The total volume of shares speaks to the so-called conviction and emotional state of traders, with moderate volume often correlated to less volatility and higher volume often tied to greater volatility. Volume also helps confirm the legitimacy of a trend and identify support and resistance levels. For instance, if a price has fallen to a resistance level and volume increases without much price movement, it can indicate consolidation, often interpreted as market indecisiveness. 

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Anticipate Trends to Find Profits

Written by admin. Posted in Technical Analysis

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Technical analysis is a useful tool that allows a trader to anticipate certain market activity before it occurs. These anticipations are drawn from previous chart patterns, probabilities of certain trade setups and a trader’s previous experience. Over time, anticipation can eliminate the need for over-analyzing market direction as well as identifying clear, objective areas of significance. It isn’t as hard as it sounds. Read on to find out how to anticipate the direction of a market trend and follow it through to a profit.

Anticipation vs. Prediction

Technical analysis is often referred to as some sort of black magic used to time the market. However, what many outside of the financial world don’t realize is that traders don’t try to predict the future. Instead, they create strategies that have a high probability of succeeding—situations where a trend or market movement can be anticipated.

Let’s face it: if traders could pick tops and bottoms on a consistent basis, they would be spending more time out in a Ferrari F430 convertible enjoying a nice stretch of highway than they would hunched over their computer screen. Many of you have probably tried picking tops and bottoms in the past and are through with the game. Perhaps you’re already following in the footsteps of many professional traders who attempt to find situations where they can anticipate a move and then take a portion of that move when the setups occur.

The Power of Anticipation

When deciding on whether or not to make a trade, you likely have your own strategies for entering and exiting the market. (If you don’t, you should decide on them before clicking the buy/sell button.) Technical traders use certain tools such as the moving average convergence divergence (MACD), the relative strength index (RSI), stochastic, or the commodity channel index (CCI), along with recognizable chart patterns that have occurred in the past with a certain measured result.

Experienced traders will probably have a good idea of what the outcome of a trade will be as it plays out. If the trade is going against them as soon as they enter and it doesn’t turn around within the next few bars, odds are that they weren’t correct on their analysis. However, if the trade does go in their favor within the next few bars, then they can begin to look at moving the stops up to lock in gains as the position plays out. (“Bars” are used as a generic term here, as some of you may use candlesticks or line charts for trading.)

The figure below is an example of a trade taken on the British pound/U.S. dollar (GBP/USD) currency pair. It uses an exponential moving average (EMA) crossover to determine when to be long and when to be short. The blue line is a 10-period EMA, and the red is a 20-period EMA. When the blue line is over the red, you are long, and vice versa for shorts. In a trending market, this is a powerful setup to take because it allows you to participate in the large move that often follows this signal. The first arrow shows a false signal, while the second shows a very profitable signal.

Image by Sabrina Jiang © Investopedia 2021


This is where the power of anticipation comes into play. The active trader typically monitors open positions as they play out to see if any adjustments need to be made. Once you had gone long at the first arrow, within three bars, you would already be down more than 100 pips. By placing your stop at the longer-term trend moving average, you will probably want to be out of that trade anyway, as a potential reversal might be signaled.

On the second arrow, once you were long, it would only take a few days before this trade went in your favor. The trade management comes into play by trailing your stop up to your personal trading style. In this case, you could have used a close under the blue line as your stop, or waited for a close underneath the red line (longer-term moving average). By being active in position management—by following the market with your stops and accepting them when they are hit—you are far more likely to have greater returns in the long run than you would be if you removed the stop right before the market blasted through it.

The above figure illustrates the difference between anticipation and prediction. In this case, we are anticipating that this trade will have a similar result based on the results of previous trades. After all, this pattern was nearly identical to the one that worked before, and all other things remaining equal, it should have a decent enough chance to work in our favor.

So did we make a prediction about what would happen in this case? Absolutely not. If we had, we wouldn’t have put our stop-loss in place at the same time the trade was sent. Unlike anticipation, which uses past results to determine the probability of future ones, making an accurate prediction often involves a combination of luck and conjecture, making the results much less, well, predictable.

Limited Emotion

By monitoring the trade(s) in real-time and adjusting accordingly, we ensure that emotions aren’t able to get the better of us and cause a deviation from the original plan. Our plan originated before the position was taken (and thus had no conflict of interest), so we use this to look back on when the trade is active.

Since we already have a plan that involves no emotion, we are able to do as much as possible to stick to that plan during the heat of battle. Make a point of minimizing emotion, but not completely removing it. You’re only human, after all, and trading like a robot is nearly impossible for most traders, no matter how successful they are. We know what the market will look like if our anticipation both does and does not occur.

Therefore, by using the chart above, you can see where the signals clearly did and did not work as they were happening based on the price action of each bar and its relation to the moving averages. The key is to take ownership of your trades and act based on your trading plan time and time again.

The Bottom Line

Objectivity is essential to trading survival. Technical analysis provides many views of anticipation in a clear and concise manner, but as with everything else in life, it doesn’t provide a guarantee of success. However, by sticking to a trading plan day in and day out, our emotions are minimized and we can greatly increase the probability of making a winning trade. With time and experience, you can learn to anticipate the direction of your trades and improve your chances of achieving better returns.

Investopedia does not provide tax, investment, or financial services and advice. The information is presented without consideration of the investment objectives, risk tolerance, or financial circumstances of any specific investor and might not be suitable for all investors. Investing involves risk, including the possible loss of principal.

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The Pioneers of Technical Analysis

Written by admin. Posted in Technical Analysis

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Whether you consider yourself a technical analyst or not, there are very few investing techniques that do not at least give a nod to the technical side of investing. Some investing styles use nothing but technical analysis, with their practitioners often claiming that they know nothing of stock fundamentals because all they need is in the charts. This segment of investing didn’t sprout from nothing. In this article, we will look at the men that pioneered the field of technical analysis. (See also: Technical Analysis.)

All Things Flow From Dow

Charles Dow occupies a huge place in the history of finance. He founded The Wall Street Journal – the benchmark by which all financial papers are measured – and, more importantly for our purpose, he created the Dow Jones Industrial Index. In doing so, Dow opened the door to technical analysis. Dow recorded the highs and lows of his average daily, weekly and monthly, correlating the patterns with the ebb and flow of the market. He would then write articles, always after the fact, pointing out how certain patterns explained and predicted previous market events.

However, Dow can’t take all – or even a majority of – the credit for the theory bearing his name. Dow Theory would have only acted as a hindsight confirmation of loose principals if it weren’t for William P. Hamilton. (See also: Giants of Finance: Charles Dow.)

First One Into the Water: William P. Hamilton

Dow Theory was a collection of market trends linked heavily to oceanic metaphors. The fundamental, long-term trend of four or more years was the tide of the market – either rising (bullish) or falling (bearish). This was followed by shorter-term waves that lasted between a week and a month. And, lastly, there were the splashes and tiny ripples of choppy water insignificant day-to-day fluctuations.

Hamilton used these measures in addition to a few rules – such as the railroad average and the industrial average confirming each other’s direction – to call bull and bear markets with laudable accuracy. Although he did call the 1929 crash too early (1927, 1928), he made a final appeal on Oct. 21, 1929, three days before the crash and mere weeks before his death at the age of 63.

The Practitioner: Robert Rhea

Robert Rhea took Dow Theory and turned it into a practical indicator for going long or short in the market. He literally wrote the book on the topic: “The Dow Theory” (1932). Rhea was successful at using the theory to call tops and bottoms – and able enough to profit from those calls. Very soon after mastering Dow Theory, Rhea didn’t need to trade on his knowledge. He only had to write it down.

After calling the market bottom in 1932 and a top in 1937, the fortunes made by subscribers to Rhea’s investment letter, Dow Theory Comments, brought in thousands more subscribers. As with Hamilton, however, Rhea’s life as a market prognosticator was short – he died in 1939. (See also: Dow Theory Tutorial.)

The Wizard: Edson Gould

Perhaps the most accurate forecaster with the longest track record, Edson Gould, was still making calls up to 1983 at the age of 81. Gould also made most of his money from writing newsletters rather than investing, selling subscriptions for $500 in 1930. He caught all of the major bull and bear market points, making several eerily accurate predictions, such as the Dow rising 400 points in a 20-year bull market, that the Dow would top 1,040 in 1973 and so on.

Gould used charts, market psychology and indicators including the Senti-Meter – the DJIA divided by the dividends per share of the companies. Gould was so good at his trade that he continued to make accurate calls from beyond the grave. Gould died in 1987, but in 1991, the Dow hit 3,000, as he’d predicted. At the time of his prediction in 1979, the Dow had yet to break 1,000.

[The work of these pioneers formed the foundation for a huge array of technical tools used by traders today to develop profitable trading strategies. To learn more, check out the Technical Analysis course on the Investopedia Academy, which includes interactive content and real-world examples to boost your trading skills.]

The Chartist: John Magee

John Magee wrote the bible of technical analysis, “Technical Analysis of Stock Trends” (1948). Magee was one of the first to trade solely on the stock price and its pattern on the historical charts. Magee charted everything: individual stocks, averages, trading volumes – basically anything that could be graphed. He then poured over these charts to identify broad patterns and specific shapes like weak triangles, flags, bodies, shoulders and so on.

Unfortunately for Magee, early on, he was better at looking after his clients than his own portfolio, often selling out in his own portfolio based on gut feelings despite strong hold signals from his charts. From his 40s to his death at 86, however, Magee was one of the most disciplined technical analysts around, refusing to even read a current newspaper lest it interfere with the signals of his charts. (For more, see: Analyzing Chart Patterns.)

The Omissions

There is bound to be some controversy with a list like this. Where is the infamous Jesse Livermore, the trader whose gut calls on price ticks are arguably the first successful technical trades? What about R. N. Elliott? What about WD Gann?

Well, Livermore did little in the area of theorizing and died broke. Elliott tweaked technical analysis with his own hypothesis, but his theories are difficult to test and even harder to trade – involving something of mysticism piled on top of numbers. Similarly, Gann’s lines, while seemingly useful in concept, are so sensitive to error that their practicality is questionable. Both of these men were purported to have made fortunes trading on their theories, but there is no solid record to back that up as there is for Livermore. Certainly no multi-million-dollar estate was left behind by either.

The Bottom Line

Dow, Hamilton, Rhea, Gould and Magee are on the main track of technical analysis, each carrying the theory and practice a little further. There are of course, many branching side paths that, while interesting detours, didn’t advance this main thrust. Every time an investor – fundamental or technical – talks about getting in low or picking entry and exit points, they are paying homage to these men and the techniques for which they laid the foundation. (See also: Introduction to Types of Trading: Technical Traders.)

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