# Influencing Factors Analysis of Crude Oil Futures Price Volatility Based on Mixed-Frequency Data
## 6 Conclusions
According to this theory, the sequence-related information arrival process causes the ARCH behavior in the futures rate of return, namely the continuity of volatility, and the futures contract transaction volume can be used as a proxy indicator of information arrival, explaining the time-varying nature of the variance of the return rate. Investors can take advantage of the fact that there is a correlation between futures price fluctuations and trading volume, and using the joint information between crude oil futures price fluctuations and trading volume can improve the accuracy and effectiveness of analysis and inference; it also helps to understand the role of trading volume and open interest in futures price fluctuations, and strengthen risk management in the crude oil futures market. Based on the above conclusions, the fundamental reason for crude oil price fluctuations is the increasing diversification of dominant forces, and the direct cause is that the game of pricing power has triggered the structural disorder of the crude oil supply and demand system. A historical investigation of the structural transformation process of the crude oil market found that: spatial isolation between scarcity and supply and demand, small demand elasticity and supply which is vulnerable to be monopolized, the contradiction between supply and demand caused by strong demand growth, the gap control of storage, supply, demand, and inventory in the transaction process, changes in the price of petrodollars, excessive speculations by traders, and the impact of emergencies all have triggered violent and frequent fluctuations in crude oil prices. Crude oil futures prices are the combination of natural laws (laws of sustainable development), micro-market laws, financial market laws, and emergencies and policy regulations in different time and space. According to the scope of action, degree of influence, and frequency of occurrence, the main controlling factors that affect crude oil futures price fluctuations are mainly divided into three categories: First, the basic factors that affect the medium and long-term trend, mainly including crude oil supply, crude oil demand and crude oil transaction settlement currency, while basic factors have a direct impact on the international crude oil futures prices; second, structural factors that affect the short-term trend, mainly include crude oil inventories in the spot market and changes in the prices of substitutes (natural gas, coal), changes in positions (arbitrage and speculation, etc.) on the financial market (future market); third, incidental factors that trigger short-term fluctuations, mainly including international political turbulence, geopolitical events, wars, and sudden climate changes. In the market, the various factors and categories of crude oil prices are independent and interactive with each other, showing integrity, organic correlation, dynamic development, orderliness, and complexity, forming a \"transaction-market-environment\" system. In this system, supply, demand, and crude oil transaction settlement currency are the underlying factors of crude oil as a commodity transaction, interacting in the transaction subsystem of the system; crude oil spot inventory in the commodity market, alternatives to coal and natural gas, on-site factors such as hedging and speculation in the crude oil futures market complete the structural activities in the market subsystem; international politics and economic turmoil, conflicts and wars in major oil producing areas, and extreme abnormal climates constitute the external environmental subsystem in which information is fully exchanged, therefore triggered sharp fluctuations in crude oil futures prices. Regarding high-frequency and low-frequency combined effects, although the results of single-factor and multifactor models are different, there is no significant difference in general. The research results are basically the same, reflecting the advantages of the mixed effect model of high and low-frequency data in the stability of the estimation results.