Fundamental Factors Investment Strategy Design Of Shanghai Copper Futures

Copper is a very important industrial metal,and China’s rapid economic development is inseparable from this metal.Shanghai Copper Futures has maintained a considerable scale after going through the storm since its listing in the last issue.Its price has become the authoritative quotation for domestic copper metal,and is increasingly valued by enterprises and investors.Studying the influencing factors of the Shanghai copper futures market will not only enrich academic research in the field of commodity futures in China,but also help expand investment strategies in the commodity futures market,and increase the participation of copper industry chain-related companies and financial institutions in China’s Shanghai copper futures market.The research object of this article is Shanghai Copper Futures.First,it introduces the development of Shanghai Copper Futures and qualitatively analyzes the fundamental factors affecting the Shanghai Copper Futures market.Then use continuous time series data to build a VAR model to analyze the impact of fundamental variables on the return of Shanghai Copper Futures,and then further construct the GARCH model with dummy variables and the GARCH-MIDAS model to explore the influencing factors of Shanghai copper futures yield volatility.Finally,based on theoretical and empirical research,two types of monthly return models for Shanghai copper futures are established,and investment strategies are designed for backtesting.The fundamental factors affecting the Shanghai copper futures market include copper supply and demand,macroeconomic conditions,and exchange rate markets.This paper first uses VAR model,Granger causality test,impulse response analysis and variance decomposition to realize the dynamic impact analysis of Shanghai copper futures yield and each fundamental variable.After empirical research,it was found that the lagging terms of the change rate of refined copper stocks（STOCK）at the end of the international period of ICSG,the change rate of the PMI of Chinese manufacturing purchasing managers,and the change rate of the real effective exchange rate index of RMB（REER＿IDX）on the monthly yield of Shanghai copper futures It has a significant effect,and these three fundamental variables are Granger causes of return at a significance level of 5%,which have a predictive effect on them.In order to study the volatility of the Shanghai copper futures market,this article then builds a GARCH model with dummy variables to analyze the differences between the Shanghai copper futures market fluctuations before and after the Shanghai copper options are listed.The research results show that the volatility of Shanghai copper futures yields has dropped significantly after the introduction of Shanghai copper options.In addition,in order to further explore the influence of fundamental factors on the volatility of Shanghai copper futures,this paper constructs a GARCH-MIDAS model,using low-frequency（monthly）fundamental variables as high-frequency（daily）long-term fluctuation components of Shanghai copper futures yield,and the long-term and short-term fluctuations of Shanghai copper futures returns are analyzed.The research results show that the volatility of Shanghai copper futures,ICSG global ending refined copper inventory volatility（VSTOCK）and China Manufacturing Purchasing Manager Index Volatility（VPMI）have very significant positive volatility in Shanghai copper futures returns.influences.In order to enrich the fundamental and quantitative investment strategies of China’s commodity futures market,based on the theoretical analysis and empirical research of the influencing factors of the Shanghai copper futures market,this paper establishes two types of Shanghai copper futures based on traditional linear regression prediction models and support vector machine prediction models.Yield prediction model,and design corresponding investment strategies to guide transactions.After back-testing research on two types of strategies,it was found that:（1）Among the first-type strategies based on traditional linear regression prediction models,strategies 2,3,and 4 can obtain better back-testing returns,which combined with ICSG Global Fine Copper Inventory change rate（STOCK）,China Manufacturing Purchasing Managers Index Change Rate（PMI）and RMB Real Effective Exchange Rate Index Change Rate（REER＿IDX）are three fundamental factors.Strategy 4 During the backtest period,the total return reached 13.45%,and the annualized return It is 10.94%,the Sharpe ratio is0.814,and the maximum retracement is 4.43%;（2）In the second type of strategy based on the support vector machine prediction model,strategies 5 and 6 can obtain good backtesting returns,which only includes Statistically significant lag terms of each fundamental factor(STOCK_t-5、STOCK_t-6、PMI_t-1、PMI_t-3、PMI_t-5、REER＿IDX_t-5)The backtest performance of strategy 6 is very outstanding,and its total return during the backtest Up to 28.80%,annualized return rate is up to 23.13%,Sharpe ratio is up to2.253,the maximum retracement is only 3.02%,and the robustness of the strategy is better,less affected by slippage and handling fees.