Technical indicators are the tools used by traders to aid them in the decisions of when to enter and exit a trade. They vary from oscillators, moving averages, and trend lines to complex mathematical formulas. Indicators are divided into two categories: leading and lagging. Generally speaking, oscillators like RSI and Stochastic are considered leading indicators, while indicators derived from moving averages, like MACD are considered lagging indicators. Lagging indicators get you into the trade late and leading indicators are prone to false signals. There are more than 100 different technical indicators available to traders, but you could spend all the time and money in the world learning these and you would not be much better off than when you started. You may be able to understand what Jim Kramer’s guests are saying when they say the RSI shows oversold and MACD just made a bullish crossover, and you may have a cool looking screen, but it will not make you a better trader.

An analogy to this would be trying to predict the weather. The following comes straight from Wikipedia.

Weather forecasting is the application of science and technology to predict the state of the atmosphere for a given location. Human beings have attempted to predict the weather informally for millennia, and formally since the nineteenth century. Weather forecasts are made by collecting quantitative data about the current state of the atmosphere on a given place and using scientific understanding of atmospheric processes to project how the atmosphere will evolve on that place. Once an all-human endeavor based mainly upon changes in barometric pressure, current weather conditions, and sky condition, weather forecasting now relies on computer-based models that take many atmospheric factors into account. Human input is still required to pick the best possible forecast model to base the forecast upon, which involves pattern recognition skills, teleconnections, knowledge of model performance, and knowledge of model biases. The chaotic nature of the atmosphere, the massive computational power required to solve the equations that describe the atmosphere, error involved in measuring the initial conditions, and an incomplete understanding of atmospheric processes mean that forecasts become less accurate as the difference in current time and the time for which the forecast is being made (the range of the forecast) increases. The use of ensembles and model consensus help narrow the error and pick the most likely outcome.

Sound familiar? In my part of the country, weather predictions are usually about 50% accurate. If you are new to trading, there is a better way. If you are a seasoned trader and you disagree with me, you can still apply the concepts you learn in this series of articles to improve your percentage of successful trades while still utilizing your favorite indicators.

I am sure there are some technical traders that consistently make money, but they are the exception and not the rule. The reason these traders are successful has nothing to do with technical indicators, but everything to do with risk management. The best professional traders stick to their trading plan and never deviate from it.

If you used the same strict risk management rules and your trading plan stated, “I only buy in an uptrend after a pullback and short in a downtrend after a pullback,” I would argue that you could still achieve the same results.
In many cases, amateur traders use technical indicators in the same way superstitious gamblers commit to absurd rituals. Have you ever played in a craps game at a casino? From time to time, dealers will go on break and be replaced by a new set of dealers. This is apparently “bad luck,” according to the superstitious gamblers. Whenever this happens, you will witness one of the strangest phenomena—these players will suddenly take back all their bets and sit out. If the dice shooter’s next roll is a seven, causing everyone to lose, which will happen one in six rolls, these players immediately attribute it to the new dealers coming in. If the dice shooter’s next roll is not a seven, they will jump back in because they weathered the storm. Obviously nothing changed—the roll will be a seven 16.7% of the time no matter what—but they are confident that they have some sort of control over the whole thing.
There are many psychological terms for this—confirmation bias, gambler’s fallacy—but the point is that people are behaving irrationally.

This might seem ridiculous to you, but it happens in trading, too. A trader might look for a MACD crossover before making a buy, and then if that trade turns out to be profitable, the trader will credit the MACD crossover. If the trade turns out not to be profitable, they will blame that on some other externality.

Another negative of using technical indicators is that professional traders know what technical indicators are telling people. This makes you a target for professional stop hunters. How many times have you entered a perfect trade set up only to be stopped out right before the price turned and went in the direction of your original trade? Professional traders know what strategies are popular, and they know how to exploit that. They also know where the nearest supply or demand zone is, and if it is far enough away from the current price, they have more than enough capital to move the market against you and take out all the stops, allowing them to enter at a better price. By always placing your stop below a demand zone or above a supply zone, it makes you more immune to stop hunters.