Artificial Intelligence in Financial Investments

von: Andreas Cseh

Table of Contents

Introduction

Stock Trading
Artificial intelligence in stock trading
How current AI systems work
Software Tools in the Market
The Impact of AI systems on Businesses, Traders and Individuals
Risks and strategy
Conclusion

Bibliography

Web links

Introduction:

Warren Buffet is known as the ultimate investor in this age. For instance, if you invested $10,000 in Berkshire Hathaway in 1965 when he took it over, you will now be sitting on more than $50 million by 2003. So good is he, in fact, that an artificial intelligence software developed in Carnegie Mellon that predicts stock movements was named after him by. But can machines really take the place of human traders, much less surpass them? When Deep Blue defeated Chess Grandmaster Kasparov in 1997, AI was propelled into the limelight. Indeed, if a machine can whiz through the intricacies of the ultimate game of strategy, why not beat man in other fields as well – thereby facilitating work, decreasing costs and errors and increasing productivity and quality. This study focuses on applying AI in Finance, particularly in stock trading. In the field of Finance, artificial intelligence has long been used. Some applications of Artificial Intelligence, as mentioned by Medsker, et al. [1996] include:

• Credit authorization screening
• Mortgage risk assessment
• Project management and bidding strategy
• Financial and economic forecasting
• Risk rating of exchange-traded, fixed income investments
• Detection of regularities in security price movements
• Prediction of default and bankruptcy

Some prospective corporate financial applications that ANN can enhance (Hsieh,1993) are:

• Financial simulation
• Predicting investor behavior
• Evaluation
• Credit approval
• Security/and or Asset Portfolio Management

Artificial intelligence types used in finance include neural networks, fuzzy logic, genetic algorithms, expert systems and intelligent agents. They are often used in combination with each other. When AI first appeared a decade ago, it generated mass media hype but delivered inconsistent results. A number of those who praised its ability were paralyzed in the end. One such case is Fidelity Investments. In this paper, we set the stage by describing how traditional stock trading differs from AI-powered stock trading. We define the various AI systems available and also explore the various solutions available in the market, their IT foundations and how salient they are. Then, we move into how AI systems for stock trading will affect traders, companies and individuals. Benefits, risks and competitive strategy will be defined and real-world examples cited, as grounding for our recommendations in the end. Recommendations include getting management buy-in, implementing the system and managing the whole structure to succeed.

Stock-Trading

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