Artificial Intelligence and Investing Essay

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Artificial Intelligence and Investing

Artificial intelligence can be defined as the ability of a computer to perform activities normally considered to require human intelligence. The techniques of this intelligence include knowledge-based, machine learning, and natural language processing techniques. Investing can be defined as the act of committing money to an endeavour with the exception of obtaining profit. Investing activities require data identification, asset valuation (the process of determining the worth of something), and risk management (the process of managing the uncertainty in investment decision-making). Artificial intelligence techniques can be applied to financial investing, especially in the areas of
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There is no specific “line” that a computer program must cross to be considered artificial intelligence, however an important factor is that the computerized solution should not be distinguishable form a human solution. This is referred to as the “Turing Test.”
Computer programming techniques that are commonly considered to be classified as being artificial intelligence includes: (1) knowledge-based techniques (ie: expert systems), (2) machine learning techniques (ie: genetic algorithms), and (3) sensory/monitor techniques (ie: natural language processing and image processing). First, an expert system is a program that uses knowledge and inferences to solve problems in a way that experts might. Next, neural networks are programs that simulate a network of communicating nerve cells to achieve a machine learning objective.
These methods can be applied to many fields of study. For our purpose, in accordance to investing, expert systems are used to predict things such as bankruptcy, neural networks are used to make important decisions such as the buying and selling of stock, and natural language processing programs are used to suggest a buy or sell signal of stock.
Artificial intelligence applies to many areas of investing. However, computational techniques are not always considered to be strictly artificially intelligent. Non-artificial intelligence areas may include numerical analyses, operations research, and probabilistic
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