Study On Short - Term Forecast Model Of Shanghai Copper Price Based On Time Series

With the non-ferrous metal copper Chinese industrial production and the broader needs ofthe domestic copper consumption has been among the first in the world, copper futures hasgradually become an important investment and hedging instruments. However, due to theinterference of various factors, frequent fluctuations in the copper market, prices are difficult topredict, increasing the risk of futures trading. Operating rules on jurisdiction and effectivelygrasp the future trends in copper futures investors can find and request additional information,and to avoid the risk of a certain degree of international trade. This paper aims to explore theinner workings of the impact of copper in copper run rule and the establishment of model timeseries models to predict the future price of copper, in order to be able to fundamentals domesticcopper producers a brief analysis and provide investors with valuable decisions.This paper reviews the basic method of time series analysis, time series model introducesdeterministic and stochastic time series model. From autoregressive model (AR model), themoving average model (MA model), autoregressive moving average model (ARMA model),autoregressive moving average model (ARIMA model) evolution, and emphasizes the effect ofARCH sequence analysis, logical reasoning high when the role of frequency. Finally, the useof copper daily data and monthly data, respectively, using the method to determine thecombination of the stochastic model for Chinese copper price trends in the types of analog dataGARCH model, the empirical results show that the prediction model has better forecast results.