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.

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.

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.)

Starting out in the trading game? Looking for the best technical indicators to follow the action is important. It affects how you’ll interpret trends—both on positions and in the broad averages—as well as the type of opportunities that pop up in your nightly research. Choose wisely and you’ve built a solid foundation for success in speculation. Choose poorly and predators will be lining up, ready to pick your pocket at every turn.

Novice Trading Strategies

Most novices follow the herd when building their first trading screens, grabbing a stack of canned indicators and stuffing as many as possible under the price bars of their favorite securities. This “more is better” approach short circuits signal production because it looks at the market from too many angles at once. It’s ironic because indicators work best when they simplify the analysis—cutting through the noise and providing usable output on-trend, momentum, and timing.

Instead, take a different approach by breaking down the types of information you want to follow during the market day, week, or month. In truth, nearly all technical indicators fit into five categories of research. Each category can be further subdivided into leading or lagging. Leading indicators attempt to predict where the price is headed while lagging indicators offer a historical report of background conditions that resulted in the current price being where it is.

• Trend indicators (lagging) analyze whether a market is moving up, down, or sideways over time.
• Mean reversion indicators (lagging) measure how far a price swing will stretch before a counter impulse triggers a retracement.
• Relative strength indicators (leading) measure oscillations in buying and selling pressure.
• Momentum indicators (leading) evaluate the speed of price change over time.
• Volume indicators (leading or lagging) tally up trades and quantify whether bulls or bear are in control.

So, how can a beginner choose the right setting at the start and avoid months of ineffective signal production? The best approach in most cases is to begin with the most popular numbers—while adjusting one indicator at a time—and seeing if the output helps or hurts your performance. Using this method, you’ll quickly grasp the specific needs of your level.

Now that you understand the five ways that indicators dissect market action, let’s identify the best ones in each category for novice traders.

Trend Indicators

50-Day EMA and 200-Day EMA

We’ll start with two indicators that are embedded within the same panel as the daily, weekly, or intraday price bars. Moving averages look back at price action over specific time periods, subdividing the total to create a running average that’s updated with each new bar. The 50- and 200-day exponential moving averages (EMAs) are more responsive versions of their better-known cousins, simple moving averages (SMAs). In a nutshell, the 50-day EMA is used to measure the average intermediate price of a security, while the 200-day EMA measures the average long term price.

U.S. Oil Fund (USO)’s 50- and 200-day EMAs rose steadily into the summer of 2014, while the instrument pushed up to a 9-month high. The 50-day EMA turned lower in August, with the 200-day EMA following suit one month later. The shorter-term average then crossed over the longer-term average (indicated by the red circle), signifying a bearish change in trend that preceded a historic breakdown.

Mean Reversion Indicators

Bollinger Bands

USO buying and selling impulses stretch into seemingly hidden levels that force counter waves or retracements to set into motion. Bollinger bands (20, 2) try to identify these turning points by measuring how far price can travel from a central tendency pivot—the 20-day SMA in this case—before triggering a reversionary impulse move back to the mean.

The bands also contract and expand in reaction to volatility fluctuations, showing observant traders when this hidden force is no longer an obstacle to rapid price movement.

Relative Strength Indicators

Stochastics

Market movement evolves through buy-and-sell cycles that can be identified through stochastics (14,7,3) and other relative strength indicators. These cycles often reach a peak at overbought or oversold levels and then shift in the opposite direction, with the two indicator lines crossing over. Cycle alternations don’t automatically translate into higher or lower security prices as you might expect. Rather, bullish or bearish turns signify periods in which buyers or sellers are in control of the ticker tape. It still takes volume, momentum, and other market forces to generate price change.

SPDR S&P Trust (SPY) oscillates through a series of buy-and-sell cycles over a 5-month period. Look for signals where:

1. A crossover has occurred at or near an overbought or oversold level
2. Indicator lines then thrust toward the center of the panel.

This two-tiered confirmation is necessary because stochastics can oscillate near extreme levels for long periods in strongly trending markets. And, while 14,7,3 is a perfect setting for novice traders, consider experimenting to find the setting that best fits the instrument you are analyzing. For example, experienced traders switch to faster 5,3,3 inputs.

Momentum Indicators

MACD

Moving average convergence divergence (MACD) indicator, set at 12, 26, 9, gives novice traders a powerful tool to examine rapid price change. This classic momentum tool measures how fast a particular market is moving while it attempts to pinpoint natural turning points. Buy or sell signals go off when the histogram reaches a peak and reverses course to pierce through the zero line. The height or depth of the histogram, as well as the speed of change, all interact to generate a variety of useful market data.

SPY shows four notable MACD signals over a 5-month period. The first signal flags waning momentum, while the second captures a directional thrust that unfolds right after the signal goes off. The third signal looks like a false reading but accurately predicts the end of the February–March buying impulse. The fourth triggers a whipsaw that’s evident when the histogram fails to penetrate the zero line. 

Volume Indicators

On-Balance-Volume (OBV)

Keep volume histograms under your price bars to examine current levels of interest in a particular security or market. The slope of participation over time reveals new trends—often before price patterns complete breakouts or breakdowns. You can also place a 50-day average of volume across the indicator to see how the current session compares with historic activity.

Now add on-balance volume (OBV), an accumulation-distribution indicator, to complete your snapshot of transaction flow. The indicator adds up buying and selling activity, establishing whether bulls or bears are winning the battle for higher or lower prices. You can draw trendlines on OBV, as well as track the sequence of highs and lows. It works extremely well as a convergence-divergence tool. For example, between January and April, Bank of America (BAC) proved this when prices hit a higher high while OBV hit a lower high, signaling a bearish divergence preceding a steep decline.

The Bottom Line

Choosing the right technical indicators is daunting but can be managed if novice traders focus the effects into five categories of market research: trend, mean reversion, relative strength, momentum, and volume. Once they’ve added effective indicators for each category, they can begin the long but satisfying process of tweaking inputs to match their trading styles and risk tolerance.