Technical Analysis
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.
Historically, Technical Analysis stood in contrast with fundamental analysis, which prefers to make a more comprehensive profile of a company before predicting future trends. Technical Analysts argued that if specific company data was relevant, it would have already effected the price or volume of their stocks, and is therefore inherently included in the technical analysis anyway.
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.
One of the typical graph patterns used by professional technical analysts to make trading decisions is the, aHead and Shoulders.a Two similar-sized peaks with a higher center peak are graphic indicators. These patterns may not be mathematically valid, argue some critics, but the result of the psychological predisposition of humans to form patterns in a random geographical area.
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 future of Technical Analysis, and Fundamental Analysis too, is giving way to the power and promise of machine learning and artificial intelligence. Machine learning does what all analysis systems attempted "automate the decision-making process" but without the limitation of how much data could be physical processed.
Unlike an analyst, a computer can pick up miniscule details that on the surface seem unrelated to the trend being evaluated. Additionally, is not predisposed to identify false patterns. Computers can identify trends of any size, though analysts tend to look for just the larger trends.
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.
Historically, Technical Analysis stood in contrast with fundamental analysis, which prefers to make a more comprehensive profile of a company before predicting future trends. Technical Analysts argued that if specific company data was relevant, it would have already effected the price or volume of their stocks, and is therefore inherently included in the technical analysis anyway.
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.
One of the typical graph patterns used by professional technical analysts to make trading decisions is the, aHead and Shoulders.a Two similar-sized peaks with a higher center peak are graphic indicators. These patterns may not be mathematically valid, argue some critics, but the result of the psychological predisposition of humans to form patterns in a random geographical area.
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 future of Technical Analysis, and Fundamental Analysis too, is giving way to the power and promise of machine learning and artificial intelligence. Machine learning does what all analysis systems attempted "automate the decision-making process" but without the limitation of how much data could be physical processed.
Unlike an analyst, a computer can pick up miniscule details that on the surface seem unrelated to the trend being evaluated. Additionally, is not predisposed to identify false patterns. Computers can identify trends of any size, though analysts tend to look for just the larger trends.
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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