Analysis and Prediction of the Characteristics of Time Periods of Fluctuations in Chinese Crude Oil Futures Prices
Research on forecasting the price volatility of crude oil futures has focused primarily on foreign markets.Crude oil futures contracts in China are divided into three trading sessions within a single trading day,which differs greatly from those in foreign markets.The segmentation of trading hours may lead to differences in the structure of volatility between the Chinese market and foreign markets.Through the heterogeneous autoregressive realized volatility(HAR-RV)model framework and high-frequency futures contract trading data sampled at a half-second frequency,this paper studies the structural characteristics of price volatility and forecasting issues.It verifies the feasibility of forecasting over smaller time scales from daily to intraday trading session scales in the Chinese market.It is found that Chinese crude oil futures price volatility exhibits interval volatility characteristics,and the inclusion of interval features significantly improves the predictive performance of the model.In addition,it is also found that reducing the forecast horizon facilitates improved stability of the realized volatility series.This paper expands HAR-RV model research to non-stationary time series,and the volatility forecasts can enable investors and risk managers to develop more precise risk management tools tailored to the Chinese crude oil futures market.
Chinese crude oil futuresheterogeneous autoregressive-realized volatility(HAR-RV)modeltime period characteristicspredictionhigh-frequency data
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