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28 March 2023 Cointegration identification with metric learning
Zeyu Xia, Changle Lin
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Proceedings Volume 12566, Fifth International Conference on Computer Information Science and Artificial Intelligence (CISAI 2022); 125661U (2023) https://doi.org/10.1117/12.2667621
Event: Fifth International Conference on Computer Information Science and Artificial Intelligence (CISAI 2022), 2022, Chongqing, China
Abstract
Cointegration is an important topic for time series analysis, especially in finance pair trading and hedging area. Cointegration is a kind of structure in which a linear combination of two (or more) time series is stationary. Traditional way to identify cointegration is to use the OLS estimator, firstly run a regression and secondly run a unit root test on residuals. But such method is easy to lead to ambiguous and unstable result. Therefore, we developed a dimensionality reduction model based on automatically calculated common factors and adopted the Metric Learning method to find a method that can quickly reduce the dimensionality and test the cointegration relationship of stock pairs.
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Zeyu Xia and Changle Lin "Cointegration identification with metric learning", Proc. SPIE 12566, Fifth International Conference on Computer Information Science and Artificial Intelligence (CISAI 2022), 125661U (28 March 2023); https://doi.org/10.1117/12.2667621
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KEYWORDS
Machine learning
Neural networks
Data modeling
Time series analysis
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