| Energy price fluctuations produce a significant effect on the domestic price level through direct or indirect action. A recent survey showed that coal in the proportion of primary energy consumption in the whole has been fallen slightly, at the same time, the high coal consumption should not be ignored. Statistics show that the proportion of coal in primary energy consumption was about 64.2% in 2014. So far the effective forecast system of energy prices has not been established, as a result, the risk of volatility in energy price could not be avoided effectively. As the significant constituent in energy consumption, the fluctuation of coal price can have negative effects on commodity prices, production costs, corporate profits, and all of those factors could release their negative impact on steady economic growth.Under the above background, the coal price volatility and transmission effect is studied. In theoretical research, the future trend of coal price is researched from short-term and medium-to-long term views. The author analysis the transmission effect of coal price integrated the conduction instantly with the conduction under time delay, based on the qualitative analysis about the transmission mechanism of coal price. It has scientific merit as part of the research on energy price. To study the coal price, not only has the theory significance, but also the practical significance. The VAR model is used to realize the multi-step forecast. Besides, the author specifically program the short-term and medium-to-long term features of coal price into the application using Kalman filtering algorithm and gray theory. The results show that the methods to forecast coal price are effectively and accurately. The forecast methods can be generalized widely for those characteristics of practical and great maintainability.The main contents and methods of the research are summarized as follows:(1) The main factors which influence the coal price. These factors are analyzed from three different perspectives. From micro angle, the factors include supply and demand, substitutes, technical level, the coal futures, etc. From the macroscopic point of view, the factors include the level of economic development, the government’s macro-regulatory functions, interest rate, money supply, the policy environment, etc. From the perspective of rational expectations, the research is performed using prosperity index.(2) Movement characteristics of coal price. The HP filter algorithm is used to separate trend and periodicity from the long-term movement of coal price. The method of structural breakpoints is applied to study the long-term movement characteristics of coal price. The theory of co-integration is used to research the integrations of regional coal market, and the validity of coal market is denoted by the convergence of coal price in different coal market.(3) To predict coal price. Considering the importance of forecasting the coal price in theory and practice in China, different methods are used to predict the coal price. The Kalman filter algorithm is applied to realize the short-term forecasting, and the gray theory is used to forecast medium-to-long term coal price.(4) Coal price transmission effect. The transmission mechanism of coal price in industry chains has been studied by the qualitative approach. Input-output model has been used to analysis the instant effect which is due to coal price fluctuations in three industries. The VAR model has been applied to research the lag time of the transmission in electric power industry, metallurgical industry, chemical industry, building materials industry, agriculture, service industry.The conclusion indicates:(1) The long cycle of coal price movement is about 14 years; there are no enough reasons to admit the structural breakpoints in coal price movement; the difference of coal price among different areas is relatively stable, which means that the integration in coal market is better. (2) The Kalman filter algorithm is better to trace and forecast the short-term coal price. The gray theory has a clear advantage in medium-to-long term coal price prediction when the data quality is poor. The results show the coal price could be down by 15.81% from the first quarter of 2015 to the first quarter of 2016 with other conditions unchanged. (3) When the coal price fluctuates, the order of influence timely is the secondary, tertiary, primary industry. Once the coal price fluctuates by 100%, the prices of the primary, secondary, tertiary will fluctuate by 0.056%,4.715%,0.170% or so separately. The coal price fluctuations have a direct or indirect impact on all kinds of price levels, and the lag time has been studied. The response time in the national economy is about 2 years; the response time in electric power industry, metallurgical industry, chemical industry, building materials industry is about 18 months; the response time of agriculture is about 12 months; and the response time of service industry is about 6 months.The innovation points of the dissertation:(1) The system theory about coal price fluctuation has been proposed. The coal price fluctuation has been researched from four angles:influence factor, fluctuation characteristics, future trends, transmission effect. All these researches has formed an organic whole process, and avoided the disadvantages of unsystematic studies. (2) The fluctuation characteristics of coal price in China have been revealed through these studies:long-term trend and periodic fluctuation of coal price, structural breakpoints, and coal market integrations. (3) The Kalman filter algorithm has been applied in short-term prediction of coal price. The results show that the covariance of predicted value has always being maintained in [1.4621e-4,0.2643]. The lower covariance ensures the stationary of prediction accuracy. (4) The coal price transmission has been dissected from immediate effects and effects of lag time based on input-output price model and VAR model, as a result, the paper has gotten a more comprehensive view of the coal price transmission.
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