Abstract
In theory, a gold futures possesses function of price discovery. However, futures including information must be disclosed by some effective way. This paper proposes a forecasting model which combines wavelet frame with Support vector regression (SVR). Wavelet frame is first used to decompose the series of gold futures price into sub-series with different scales, the SVR then uses the sub-series to build the forecasting model. Empirical research shows that the gold futures has the function of price discovery, and the two steps model is a good tool for making the price information clear and forecasting spot price. further research can try different basis function or other methods of disclosing information.
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Dai, W., Lu, CJ., Chang, T. (2010). Empirical Research of Price Discovery for Gold Futures Based on Compound Model Combing Wavelet Frame with Support Vector Regression. In: Wang, F.L., Deng, H., Gao, Y., Lei, J. (eds) Artificial Intelligence and Computational Intelligence. AICI 2010. Lecture Notes in Computer Science(), vol 6320. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16527-6_47
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DOI: https://doi.org/10.1007/978-3-642-16527-6_47
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-16526-9
Online ISBN: 978-3-642-16527-6
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