Dynamic portfolio trading system is used to allocate one’s capital to a number of securities through time in a way to maximize the portfolio return and to minimize the portfolio risk. Genetic programming (GP) as an artificial intelligence technique has been used successfully in the financial field, especially for the forecasting tasks in the financial markets. In this paper, GP is used to devel...

The stock selection problem is one of the major issues in the investment industry, which is mainly solved by analyzing financial ratios. However, considering the complexity and imprecise patterns of the stock market, obvious and easy-to-understand investment rules, based on fundamental analysis, are difficult to obtain. Fundamental and technical analyses are two common methods for predicting th...

AI has long been applied to the problem of predicting financial markets. While AI researchers see financial forecasting as a fascinating challenge, predicting markets has powerful implications for financial economics – in particular the study of market efficiency. Recently economists have turned to AI for tools, using genetic algorithms to build trading strategies, and exploring the returns tho...

The stock selection problem is one of the major issues in the investment industry, which is mainly solved by analyzing financial ratios. However, considering the complexity and imprecise patterns of the stock market, obvious and easy-to-understand investment rules, based on fundamental analysis, are difficult to obtain. Fundamental and technical analyses are two common methods for predicting th...

OPTIMAL PAIRS TRADING RULES by Eric Mueller The University of Wisconsin-Milwaukee, 2016 Under the Supervision of Professor Chao Zhu This thesis derives an optimal trading rule for a pair of historically correlated stocks. When one stock's price increases and the other one's decreases, a trade of the pair is triggered. The idea is to short the winner and to long the loser with the hope that the ...

Automated Trading is the activity of buying and selling financial instruments for the purpose of gaining a profit, through the use of automated trading rules. This work presents an evolutionary approach for the design and optimization of artificial neural networks to the discovery of profitable automated trading rules. Experimental results indicate that, despite its simplicity, both in terms of...

In this paper, we visualize the behavior of a futures trading agent by using fuzzy if-then rules. The main aim of this paper is to graphically interpret how trading agents make decisions such as to buy or to sell a futures stock. Fuzzy ifthen rules are used for this aim because their antecedent part specifies the features of time series. The procedure for visualizing the behavior of trading age...