Using Rough Set to Support Investment Strategies of Rule-Based Trading with Real-Time Data in Futures Market

Using Rough Set to Support Investment Strategies of Rule-Based Trading with Real-Time Data in Futures Market

Investment strategies in stock market have gained unprecedented popularity in major financial markets around the world. However, it is a very difficult problem because of the fluctuation of the stock market. This study presents usefulness of rough set on the rule base to develop real-time investment...

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Hauptverfasser: Suk Jun Lee, Jae Joon Ann, Kyong Joo Oh, Tae Yoon Kim, Hyoung Yong Lee, Chi Woo Song
Format: Tagungsbericht
Sprache:eng
Schlagworte:
Data mining
Expert systems
Fluctuations
Humans
Industrial engineering
Investments
Profitability
Real time systems
Statistics
Stock markets
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Jae Joon Ann
Kyong Joo Oh
Tae Yoon Kim
Hyoung Yong Lee
Chi Woo Song
description Investment strategies in stock market have gained unprecedented popularity in major financial markets around the world. However, it is a very difficult problem because of the fluctuation of the stock market. This study presents usefulness of rough set on the rule base to develop real-time investment strategies using technical analysis in futures market. This study consists of four phases. In the first phase, meaningful technical indicators are selected to reflect market movements. In the second phase, rough set is used to extract trading rules for identification of buy and sell patterns in the stock market. In the third phase, the investment strategies are developed in order to apply selected trading rules using rule-based reasoning to unpredictable stock market. Finally, investment strategies on the basis of rule base are evaluated by real-time trading. This study then examines the profitability of the proposed model.
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subjects Data mining
Expert systems
Fluctuations
Humans
Industrial engineering
Investments
Profitability
Real time systems
Statistics
Stock markets
title Using Rough Set to Support Investment Strategies of Rule-Based Trading with Real-Time Data in Futures Market
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