Long memory of price-volume correlation in metal futures market based on fractal features

An empirical test on long memory between price and trading volume of China metals futures market was given with MF-DCCA method. The empirical results show that long memory feature with a certain period exists in price-volume correlation and a fittther proof was given by analyzing the source of multifractal feature. The empirical results suggest that it is of important practical significance to bring the fractal market theory and other nonlinear theory into the analysis and explanation of the behavior in metal futures market.

Prediction of metal futures price volatility and empirical analysis based on symbolic time series of high-frequency

The metal futures price fluctuation prediction model was constructed based on symbolic high-frequency time series using high-frequency data on the Shanghai Copper Futures Exchange from July 2014 to September 2018,and the sample was divided into 194 histogram time series employing symbolic time series.The next cycle was then predicted using the K-NN algorithm and exponential smoothing,respectively.The results show that the trend of the histogram of the copper futures earnings prediction is gentler than that of the actual histogram,the overall situation of the prediction results is better,and the overall fluctuation of the one-week earnings of the copper futures predicted and the actual volatility are largely the same.This shows that the results predicted by the K-NN algorithm are more accurate than those predicted by the exponential smoothing method.Based on the predicted one-week price fluctuations of copper futures,regulators and investors in China’s copper futures market can timely adjust their regulatory policies and investment strategies to control risks.

Volatility forecasting in Chinese nonferrous metals futures market

This paper seeks to model and forecast the Chinese nonferrous metals futures market volatility and allows new insights into the time-varying volatility of realized volatility and leverage effects using high-frequency data.The LHAR-CJ model is extended and the empirical research on copper and aluminum futures in Shanghai Futures Exchange suggests the dynamic dependencies and time-varying volatility of realized volatility,which are captured by long memory HAR-GARCH model.Besides,the findings also show the significant weekly leverage effects in Chinese nonferrous metals futures market volatility.Finally,in-sample and out-of-sample forecasts are investigated,and the results show that the LHAR-CJ-G model,considering time-varyingvolatility of realized volatility and leverage effects,effectively improves the explanatory power as well as out-of sample predictive performance.

Volatility-volume relationship of Chinese copper and aluminum futures market

Following Bessembinder and Seguins,trading volume is separated into expected and unexpected components.Meanwhile,realized volatility is divided into continuous and discontinuous jump components.We make the empirical research to investigate the relationship between trading volume components and various realized volatility using1min high frequency data of Shanghai copper and aluminum futures.Moreover,the asymmetry of volatility-volume relationship is investigated.The results show that there is strong positive correlation between volatility and trading volume when realized volatility and its continuous component are considered.The relationship between trading volume and discontinuous jump component is ambiguous.The expected and unexpected trading volumes have positive influence on volatility.Furthermore,the unexpected trading volume,which is caused by arrival of new information,has a larger influence on price volatility.The findings also show that an asymmetric volatility-volume relationship indeed exists,which can be interpreted by the fact that trading volume has more explanatory power in positive realized semi-variance than negative realized semi-variance.The influence of positive trading volume shock on volatility is larger than that of negative trading volume shock,which reflects strong arbitrage in Chinese copper and aluminum futures markets.