Empirical Research of Price Discovery for Gold Futures Based on Compound Model Combing Wavelet Frame with Support Vector Regression

摘要

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.