Using Genetic Programming to Model Volatility in Financial Time Series

Created by W.Langdon from gp-bibliography.bib Revision:1.7615

@InProceedings{chen:1997:GPmvfts,

• author = "Shu-Heng Chen and Chia-Hsuan Yeh",
• title = "Using Genetic Programming to Model Volatility in Financial Time Series",
• booktitle = "Genetic Programming 1997: Proceedings of the Second Annual Conference",
• editor = "John R. Koza and Kalyanmoy Deb and Marco Dorigo and David B. Fogel and Max Garzon and Hitoshi Iba and Rick L. Riolo",
• year = "1997",
• month = "13-16 " # jul,
• keywords = "genetic algorithms, genetic programming",
• pages = "58--63",
• address = "Stanford University, CA, USA",
• publisher_address = "San Francisco, CA, USA",
• publisher = "Morgan Kaufmann",
• ISBN = "1-55860-483-9",
• URL = "http://www.cs.ucl.ac.uk/staff/W.Langdon/ftp/papers/gp1997/chen_1997_GPmvfts.pdf",
• size = "6 pages",
• abstract = "RGP tested by using Nikkei 255 and S&P 500 as an example",
• notes = "GP-97 Fixed size sliding window of the original time series. BGP used to learn first window, then whole pop used with second window (ie as population seed). Fitness = sum of errors squared also serves to give estimate of volatility.",

}

Genetic Programming entries for Shu-Heng Chen Chia Hsuan Yeh

Citations