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Wednesday, February 25, 2009

Technical Analysis

By Walter Fox

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.

Fundamental analysis, in contrast, creates a comprehensive company profile to determine future trend patterns. Historically, technical analysts have claimed that any relevant company specific data would affect stock price or volume, and would therefore be included in the technical analysis.

The objective of technical analysis is to increase an investoras profit by predicting future market trends instead of guessing. Using similar data in a different way, fundamental analysis creates the same result. The goal of technical analysis is to provide a simple mathematic gauge to help make investment decisions easier.

"Head and Shoulders," a graph pattern that shows two equal peaks with a high center peak, is one of the typical patterns a professional technical analyst will utilize in making trading decisions. Some criticize that these patterns are a result of the humanas predisposition to form patterns in the geographically random environment, and are not mathematically valid.

While Technical Analysis seeks to use a purely quantitative measure for predicting market trends, it is limited by a number of factors: Technical analysts traditional ignore a lot of quantitative data. Analysts tend to adhere to particular paradigms, which favor different charting methods and attribute more or less weight to particular statistical patterns as market indicators, which reveals a subjective bias on the part of the Analyst.

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.

Whether machine learning will replace Technical Analysis, or will be used as a tool to improve it, it is likely that many existing analytical paradigms will become less relevant as our tools become better, and reveal the shortcomings of our prior techniques.

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