金属跨期现市场操纵机理及预警研究

The mechanism and early warning of metal spot and futures cross-market manipulation

金融化程度的不断提高使得金属资源价格的竞争逐渐转向贸易金融联动的综合市场,期、现货市场联动性增强,跨市场操纵的风险增大。在此背景下,如何预警、防范价格操纵风险,成为提高我国金属资源安全的一项紧迫任务。对此,本文基于系统动力学,以铜为例构建了金属跨期现市场操纵仿真模型,探索跨期现市场操纵对金属价格的影响程度和影响路径,在此基础上,构建了基于QFD的跨期现市场操纵预警质量屋模型。实证结果表明:(1)现货市场操纵不仅在操纵期内对铜价有较大影响,操纵期结束后对铜价的影响仍然持续较长时间,且通过控制库存使铜价上涨的操纵方式更有效。(2)期货市场的操纵只在操纵期内对铜价造成巨大波动,但操纵期结束后铜价迅速趋于基准水平,且通过操纵基金持仓使铜价下降的操纵方式更有效。(3)实时监测综合预警指标体系,同时尽快建立完备的跨市场风险防范体系,完善跨市场监管和信息交流机制等都能有效防范金属跨期现市场操纵。

With the development of financial globalization, the price competition of metal resources gradually shifts from the areas of primary resource and product markets to the comprehensive market of trade-finance linkage. The linkage between the metal spot and futures price is increasing. The price of metal has not only been subject to the impact of supply and demand fundamentals. Besides, the international capital speculation, the international currency exchange rate changes, interest rates changes, oil price, and other financial factors also affect the metal’s price fluctuations. Speculative behavior and price manipulation in financial processes increase the possibility of cross-market manipulation of metal resources and make price manipulation more implicit and difficult to identify or avoid. In this context, how to realize early warning and prevent against price manipulation risk has become an important and urgent task to improve the safety of China's metal resources. Metal resources cross-market manipulation mechanism is a typical complex system. This paper explores the influence level and path of price manipulation on metal price by constructing the dynamic simulation model of metal cross-market manipulation system. In the specific analysis, since copper is a relatively mature metal resource in China, this paper takes copper as an example to establish the system dynamics model and designs three simulation scenarios: the spot market manipulation, the futures market manipulation, and the cross-market manipulation. By observing the copper price of spot market relative to the baseline level (no price manipulation of the scenario), we can learn the impact of manipulation on copper price. On this basis, the key index system of spot and futures cross-market early warning is extracted, and the early warning model of spot and futures cross-market manipulation based on QFD is established. In this paper, the validity of the model has been demonstrated by the combination of operational and historical tests. The simulation results show that the model fits well with the fluctuation rule of copper price in the Chinese copper market. According to the output result of system simulation and the warning model, the following conclusions are drawn:(1) Spot market manipulation can control prices mainly by the monopoly of supply and inventory control. The spot market manipulation not only has a large effect on the copper price during the control period but also has a continuous effect on the copper price for a long time after the control period. In addition, the manipulation of increasing the copper price by controlling the inventory is more effective.(2) Futures market manipulation mainly takes advantage of the impact of speculative factors on copper demand to manipulate copper prices. In this situation, the manipulation can only cause significant price volatility during the control period, and then the copper price will approach the benchmark level rapidly after the control period. In the case of futures market manipulation, the way of manipulating fund positions to make copper prices fell is more effective.(3) The cross-market manipulation manipulates copper prices by controlling supply on spot market and positions on the futures market. Comparing with the two scenarios above, the influence on copper prices is greater. Furthermore, the impact can last longer.(4) It is important to design real-time monitoring and early warning index system. The system is composed of positions, trading volume, supply, basis, and the closing price. Thus, a comprehensive cross-market risk prevention system can be constructed to improve cross-market regulation and information exchange mechanisms.