A technique used to forecast the movement of stock prices based on past market data is called technical analysis. Though some have claimed positive results simply considering the variables of price and volume, academic mathematicians scrutinize this as an incomplete analysis of market trends and statistics.

Over the past years, technical analysts have argued that a company’s specific data affects the price and value of their stocks, therefore making fundamental analysis unnecessary. The method of fundamental analysis utilizes a comprehensive company profile to predict future trends.

The purpose of Technical Analysis is to take the guesswork out of investing. It seeks to increase profits by predicting the future of the markets and trading against those predictions. Fundamental Analysis does the same thing but prefers to use different data, or use data differently. Perhaps more than Fundamental Analysis, Technical Analysis seeks to automate the decision making process by producing a purely quantitative measure of future trends.

Professional Technical Analysts will likely identify atypical patternsa such as the aHead and Shoulders Patterna. When looking at a graph, this pattern depicts three peaks with the center peak the highest, and the other two approximately the same. Patterns such as this, serve as graphic indicators by which an analyst will make trading decisions. Critics argue that these patterns are not mathematically valid, but rather are the result of humanas psychological predisposition to finding patterns in an otherwise random graphical environment.

The method of measuring and predicting market trends using quantitative methods may be limited. Subjective bias is evident when analysts give more or less consideration for certain statistical patterns or favor certain charting methods. Therefore, technical analysts traditionally ignore a great deal of quantitative data.

The promise of artificial intelligence and machine learning will impact the future of both technical analysis and fundamental analysis. This technology will automate the decision-making process of investing without the limitation of how much data can be physically processed by an individual.

Machine learning has no predisposition to identifying false patterns, and it is able to include disparate data, which on the surface appears to have no correlation to the trends being analyzed. Furthermore, machine learning will identify patterns at any scale. While Analysts tend to look for large (significant) trends, at the machine level, any scale is significant if a trend can truly be identified.

While it is plausible that many existing analytical paradigms will become obsolete as our tools improve, it is unknown whether machines will replace technical analysis or merely reveal the shortcomings of our prior techniques and help us to improve them.