Genetic Programming Prediction of Stock Prices
Computational Economics
Modeling Exchange Rate Behaviorwith a Genetic Algorithm
Computational Economics
Paul Wilmott Introduces Quantitative Finance
Paul Wilmott Introduces Quantitative Finance
An Introduction to Natural Computing in Finance
EvoWorkshops '09 Proceedings of the EvoWorkshops 2009 on Applications of Evolutionary Computing: EvoCOMNET, EvoENVIRONMENT, EvoFIN, EvoGAMES, EvoHOT, EvoIASP, EvoINTERACTION, EvoMUSART, EvoNUM, EvoSTOC, EvoTRANSLOG
Modesty is the best policy: automatic discovery of viable forecasting goals in financial data
EvoCOMNET'10 Proceedings of the 2010 international conference on Applications of Evolutionary Computation - Volume Part II
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This paper introduces a new data set for use in the financial prediction domain, that of quantified News Sentiment. This data is automatically generated in real time from the Dow Jones network with news stories being classified as either Positive, Negative or Neutral in relation to a particular market or sector of interest. We show that with careful consideration to fitness function and data representation, GP can be used effectively to find non-linear solutions for predicting large intraday price jumps on the S&P 500 up to an hour before they occur. The results show that GP was successfully able to predict stock price movement using these news alone, that is, without access to even current market price.