Forecasting stock market return with nonlinearity: a genetic programming approach
Created by W.Langdon from
gp-bibliography.bib Revision:1.7177
- @Article{Ding:2020:jaihc,
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author = "Shusheng Ding and Tianxiang Cui and Xihan Xiong and
Ruibin Bai",
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title = "Forecasting stock market return with nonlinearity: a
genetic programming approach",
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journal = "Journal of Ambient Intelligence and Humanized
Computing",
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year = "2020",
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month = "10 " # feb,
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note = "Published online",
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keywords = "genetic algorithms, genetic programming, Return
forecasting, Nonlinear models",
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URL = "
http://eprints.nottingham.ac.uk/60489/",
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URL = "
http://eprints.nottingham.ac.uk/60489/1/Forecasting%20stock%20market%20return%20with%20nonlinearity%20a%20genetic%20programming%20approach.pdf",
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DOI = "
doi:10.1007/s12652-020-01762-0",
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size = "13 pages",
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abstract = "The issue whether return in the stock market is
predictable remains ambiguous. This paper attempts to
establish new return forecasting models in order to
contribute on addressing this issue. In contrast to
existing literatures, we first reveal that the model
forecasting accuracy can be improved through better
model specification without adding any new variables.
Instead of having a unified return forecasting model,
we argue that stock markets in different countries
shall have different forecasting models. Furthermore,
we adopt an evolutionary procedure called Genetic
programming (GP), to develop our new models with
nonlinearity. Our newly-developed forecasting models
are testified to be more accurate than traditional
AR-family models. More importantly, the trading
strategy we propose based on our forecasting models has
been verified to be highly profitable in different
types of stock markets in terms of stock index futures
trading.",
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notes = "1 School of Business, Ningbo University, Ningbo, China
2 School of Computer Science, The University of
Nottingham Ningbo China, Ningbo, China 3 Department of
Mathematics, The London School of Economics and
Political Science, London, UK",
- }
Genetic Programming entries for
Shusheng Ding
Tianxiang Cui
Xihan Xiong
Ruibin Bai
Citations