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What Are the Different Tools for Technical Analysis?

By Ray Hawk
Updated May 16, 2024
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The tools for technical analysis of stocks center around data collected on price fluctuations for the stock and the volume of shares that are traded over specific periods of time. The market data is compiled in charts and graphs that track a stock's movement. These changes incorporate tools for technical analysis, such as candlestick signals, Fibonacci retracements, moving averages, and pivot points to determine when a stock is going to change price direction as well as predict how much higher or lower it is likely to move based on past performance.

Technical security analysis is a form of quantitative analysis of the stock market that relies entirely on mathematical models and past data that has been gathered on a stock itself or the market sector in which it is traded. This is significantly different from fundamental analysis, which attempts to gauge the true value of a company and its products based on its competition and broad economic factors, such as national economies and industrial conditions. The tools for technical analysis, therefore, can be very precise in charting a range of changes that the stock may go through based on decades of historical data, and supply-versus-demand forces that affect the stock. While a technical stock trader may use some behavioral economics principles to understand general emotional factors in a market that can drive a stock up or down, the overall goal when using tools for technical analysis is to look for mathematically-predictable patterns in market trends that drive a stock price. A technical analyst, therefore, is looking at the effects of market trends in stock charts, whereas a fundamental analyst is more concerned with the causes of such trends.

Candlestick signals can be traced back to the 18th century and Homma Munehisa, who is credited with inventing the concept of technical analysis. Munehisa was a Japanese rice merchant who created a combination line and bar chart to track the overall movement of a product's price on the market with a line, while simultaneously tracking its opening and closing prices with bars, making the chart look like an array of candlestick figures that progress across a page. As the price of the stock goes outside of the normal opening and closing trading prices, these are referred to as “candlestick shadows,” which are more lightly-colored in the chart to give emphasis to the major range of movement. The complexity of the chart gives it the ability to convey information on short-term or immediate trading conditions and long-term price fluctuations quickly, and has made it one of the most important tools for technical analysis of stocks.

Fibonacci retracement charts calculate when a stock price goes above or below price stop settings for its normal movement, known as a “support” when it rises above predicted values and a “resistance” when it falls below them. The chart is one of the important tools for technical analysis because it can tell a trader what the optimal point is for placing a trade based on movement values. The calculations in the chart are based on Fibonacci numbers, which are a sequence of integers discovered by Leonardo Fibonacci, a 12th century Italian mathematician. Fibonacci number sets have many uses in modern computing, and biological and economic calculations, as they represent a predictable branching nature that seems to be common throughout living and technological systems.

Many other indicators exist as tools for technical analysis, all of which can be charted in some manner to predict price and volume movement, from Bollinger Bands that show price volatility to the Williams % R Oscillator for volume, which shows whether a stock is currently being oversold or overbought. Each method focuses on a unique way of looking at price and volume changes. A Price Activity (PAC) chart, for instance, directly compares volume levels to prices as the price of the stock changes, whereas a Moving Average Convergence-Divergence (MACD) chart instead focuses on the oscillating nature of prices in the moving average by subtracting the longer moving average from the shorter moving average without regard to volume.

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