Automatic Creation of Stock Trading Rules on the Basis of Decision Trees
نویسندگان
چکیده
The main task of any trader is the selection of profitable strategies for trading a financial instrument. One of the simplest ways to represent trading rules is binary decision trees based on the comparison of current values of technical indicators with some absolute values. This approach simplifies the creation of trading systems but their validity is limited to short-term intervals of trade. This paper represents an approach for generating more universal trade rules in the form of binary decision trees based on the comparison of the current values of technical indicators with relative levels. The ranges of these levels are recalculated on a daily basis which allows the trading rule to remain relevant within a long term. The proposed system analyzes the historical price data for a long period and using the genetic algorithm causes trading strategies optimized relatively to the Sharpe ratio.
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