What is Technical Analysis?
Ä Note: It is not necessary to read this section in order to use TradingSolutions. However, understanding the concepts used in the program can help you to get the most out of the intermediate and advanced features.
Technical Analysis involves using past stock prices, volume, and other related data to forecast future price movements. There are three basic premises that a technical analyst believes in. First, technical analysts believe that the price of a stock is driven by supply and demand. Stocks are not always worth the price that they are selling for. They often trade higher or lower based upon a large demand or a lack thereof. This ties into the second belief of the technical analyst: stocks move in trends that usually last for a detectable period of time. In other words, price movements are not simply random variations. The final belief of a technical analyst is that these detectable trends often repeat themselves. By detecting a repeating pattern in the early stages, a technical analyst is able to profit from the stock price movement if it behaves in the same manner that it did in the past.
There are two main types of technical analysis. The first type is based upon the recognition and interpretation of chart patterns. This type of technical analysis is more of an art than a science and can be very subjective since it relies on the technical analysts' judgment for determining whether a pattern exists or not. Common techniques utilized in this type of technical analysis involve drawing trendlines on the chart, interpreting a Japanese candlestick chart, and using other line studies such as Fibonacci Arcs, Gann Fans, etc. One major problem with this type of technical analysis is that it does not easily lend itself to historical backtesting. Because pattern recognition is subjective and since each pattern must be recognized manually by the analyst, historical backtesting is almost prohibitively laborious. See figure 1, below, for an example of how a trendline might be drawn on a recognized trend.
Figure 1: Demonstration of a Trend line. Notice the distinct upward trend in the CSCO chart from November 5th to December 13th. This type of trend can be exploited by purchasing the stock after the trend has lasted for so many days and selling the stock once the trend appears to be broken.
The second type of technical analysis uses mechanical indicators based on price, volume and other data to predict future price movements and/or to determine when to buy or sell. The data used to create an indicator can be technical (or even date-based fundamental) data taken from the stock being analyzed, a related stock or stocks, or from various general market data sources. This data is then applied to a mathematical formula to generate the indicator. Some indicators can be used directly to make trading decisions. Other indicators must first be processed by a series of rules to generate an entry/exit signal. The underlying formulas for many indicators are based upon moving averages, oscillators, etc. and use price data, volume data, and market data such as breadth as the inputs. Because this type of technical analysis is mechanical in nature and uses mathematical formulas, historical backtesting is possible. This allows the technical analyst to gain confidence in the indicators and any resulting entry/exit signals before actually trading. See figure 2, below, for an example of an indicator.
Figure 2: Demonstration of the classic Moving Average Convergence/Divergence (MACD) indicator. When the MACD is increasing, this indicates that prices are trending higher. Whereas a decreasing MACD indicates that prices are trending lower. The MACD is typically traded at the crossover points of its 9-day exponential moving average (not shown).
Neural networks have recently become a very popular technology for technical analysis. They most closely fall within the bounds of this second type of technical analysis. A neural network can be viewed as a very powerful and flexible "formula" whose output can be used directly for making trading decisions or to produce entry/exit signals. However, the neural network goes far beyond a typical indicator, because it has the ability to learn from the data itself. This powerful tool for technical analysis is at the core of TradingSolutions and is discussed in detail in a later section.
& Continue to the next section, What are the differences between trading and investing?, or return to the Overview for this chapter.