有色金属价格波动预警仿真研究
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摘要
摘要：随着经济迅猛发展,我国已成为世界有色金属生产、消费大国。有色金属作为重要的基础原材料产业,其价格的剧烈波动不仅能产生极大的市场不确定性,导致生产者、消费者以及其他利益相关者面临巨大的市场风险,也将严重影响中国整体经济的平稳态势。对于有色金属行业来说,有色金属价格波动通过在上下游行业和国民经济各部门的传导,会给有色金属工业带来了极大的困难和挑战,也严重影响和约束了行业的稳定与发展。对使用有色金属作为原料的企业来说,有色金属价格波动具有显著不良影响,因为价格波动可以转化为原材料成本的波动,波动的原材料成本会削弱企业的盈利能力,限制原材料的选择决策。因此,为了应对不良的价格波动,企业、行业整体甚至国家提前收集价格波动信息,预警价格波动,控制价格波动风险,具有重要的现实意义。
在这一背景下,本文试图寻找有色金属价格波动的根源,运用系统动力学对铜价波动进行预警仿真,主要工作如下：
本文以铜为例,深入分析研究有色金属的关键性因素,并进一步收集了大量的与铜价以及铜产品上下游行业相关的经济指标,筛选出铜价波动预警初选指标。然后运用时差相关分析构成铜价波动的先行指标、一致指标和滞后指标,并采用主成分分析法,得到先行指标的三个主成分为：进出口价格因子、投机与原材料因子和建筑材料价格因子；一致指标的三个主成分分别为：工业品出厂价格因子、成本与产量因子和出口因子消费；滞后指标的两个主成分为：需求因子和废铜进口因子。最后在此基础上,计算得出铜价波动预警的先行致综合指数、一致综合指数和滞后综合指数,并分别比较先行、一致和滞后综合指数与铜价波动趋势,预警铜价波动风险。
将系统动力学方法引入到对有色金属价格的波动行为的研究中,分析铜价波动各影响因素的因果反馈关系,绘制系统因果回路图,通过系统的价格模块、需求模块、成本模块、产能利用率模块和库存模块分析铜价波动动力学结构,构建系统流图,并设置参数,仿真我国铜价波动趋势,通过比较1996年至2012年模拟铜价和历史价格,检验模型的可靠性。
对铜价波动进行情景模式仿真,分别从市场结构、经济周期、投机影响、突发事件和产业政策五个方面的不同情景模式下,首先验证历史时期不同情景下的铜价波动趋势,以及价格波动的影响程度和影响路径,再以2014年为变化起始时间,分别分析不同情景变化时2014年至2020年价格变化趋势,结果表明,在垄断性市场结构下,产量受到生产商控制,价格更易大幅波动；经济周期对铜价影响具有滞后效应,处于宏观经济上行周期时模拟价格高于基准水平,宏观经济处于下行周期时模拟价格低于基准水平,并且经济上行周期对价格的影响大于经济下行周期；对于投机因素的分析,持仓量增加时,模拟价格上涨,持仓量减少时,模拟价格下跌；对突发事件,不同影响程度的突发事件,对价格的影响时间以及影响幅度不同；对于产业政策的模拟仿真,表明合理的产业政策有利于稳定价格。
Abstract:With the rapid economic development, China has become a main production and consumption country of non-ferrous metal in the world. As an important basic raw material, the price volatility for non-ferrous metals leads to the market uncertainty, even causes the huge market risks for producers, consumers and other stakeholders, and these factors will seriously affect the overall Chinese economy steady trend. For non-ferrous metals industry, its price volatility through upstream and downstream industries and economic sectors conduction, will give non-ferrous metal industry has brought great difficulties and challenges, but also seriously affect and constrain the industry's stability and development. The use of non-ferrous metal as a raw material for businesses, non-ferrous metal price fluctuations have a significant adverse impact, because the price fluctuations can be converted to fluctuations in the cost of raw materials, fluctuations in raw material costs will undermine corporate profitability, limiting raw material selection decisions. Therefore, in response to adverse price volatility, industry, enterprise, industry and even the country collects information of price volatility in advance, early warning the price volatility, control the risks of price volatility.
Under the background, this paper tries to find out the root causes of non-ferrous metals price volatility, and starts from determine the key influence factors of non-ferrous metals price volatility.
In this paper, copper, for example, in-depth analysis of the key factors of non-ferrous metals, and further collected a large number of economic indicators related to copper price and the upstream and downstream industries of copper products, filter out the primary indicators for early warning of copper prices volatility. Then the research constitutes the leading indicators, consistent indicators and lagging indicators of copper price volatility by using the time difference correlation analysis, and uses principal component analysis to obtain the following main components:the three main components for leading indicators are import and export price factor, speculation and raw materials factor, and building materials price factor; the three main components for consistent indicators are:producer's price for manufactured products factor, cost factor and yield factor, and export factor consumption; lagging indicators include two main components which are demand factor and scrap copper import factor. Finally, base on above results, calculates the leading composite index, consistent composite index and lagging composite index for early warning of copper price volatility, then compares every index with the copper price volatility trend, to warn the related risks.
The system dynamics method is used in the study of non-ferrous metals price volatility activities, to determine the feedback causal relationship for each influence factor of copper price fluctuations, draw causal loop diagram of copper system, and analyze the dynamic structure of copper price volatility through the price module, the demand module, the cost module, capacity utilization module and inventory module, then build the system flow diagram, set the parameters, and simulation the trend of fluctuations in copper prices volatility. By comparing the historical and forecasting copper price from1996to2012, the results show that the simulated copper forecasting price trend remains consistent with its historical price, which tests the reliability of the model.
This research simulates the copper price volatility in scenario modes, and discusses the cooper price volatility in different scenario modes from five aspects which are market structure, economic cycles, speculative effects, emergencies and industrial policy. Firstly, the research verifies the trends of volatility in copper prices, the influence extent of price volatility and impact path under different scenarios in the past, then regards2014as the start time, respectively analyzing price changes from2014to2020under different scenarios. The result shows that the price is more sharply volatility when production controlled by the manufacturer with monopolistic market structure; the economic cycles influence on copper prices have lagged effects, on macroeconomic upward cycle, the simulated price is higher than baseline levels, and in the downward cycle the prices below the benchmark level, and the economic upward cycle influence is greater than the downward one. The analysis of the speculative factors shows that when open interest increasing, the simulated price rises, open interest reducing, the simulated prices falls; different unexpected events have various periods and extents of impact on the price; the simulation of industry policy shows that the rational industrial policy is conducive to stabilize the price.
在这一背景下,本文试图寻找有色金属价格波动的根源,运用系统动力学对铜价波动进行预警仿真,主要工作如下：
本文以铜为例,深入分析研究有色金属的关键性因素,并进一步收集了大量的与铜价以及铜产品上下游行业相关的经济指标,筛选出铜价波动预警初选指标。然后运用时差相关分析构成铜价波动的先行指标、一致指标和滞后指标,并采用主成分分析法,得到先行指标的三个主成分为：进出口价格因子、投机与原材料因子和建筑材料价格因子；一致指标的三个主成分分别为：工业品出厂价格因子、成本与产量因子和出口因子消费；滞后指标的两个主成分为：需求因子和废铜进口因子。最后在此基础上,计算得出铜价波动预警的先行致综合指数、一致综合指数和滞后综合指数,并分别比较先行、一致和滞后综合指数与铜价波动趋势,预警铜价波动风险。
将系统动力学方法引入到对有色金属价格的波动行为的研究中,分析铜价波动各影响因素的因果反馈关系,绘制系统因果回路图,通过系统的价格模块、需求模块、成本模块、产能利用率模块和库存模块分析铜价波动动力学结构,构建系统流图,并设置参数,仿真我国铜价波动趋势,通过比较1996年至2012年模拟铜价和历史价格,检验模型的可靠性。
对铜价波动进行情景模式仿真,分别从市场结构、经济周期、投机影响、突发事件和产业政策五个方面的不同情景模式下,首先验证历史时期不同情景下的铜价波动趋势,以及价格波动的影响程度和影响路径,再以2014年为变化起始时间,分别分析不同情景变化时2014年至2020年价格变化趋势,结果表明,在垄断性市场结构下,产量受到生产商控制,价格更易大幅波动；经济周期对铜价影响具有滞后效应,处于宏观经济上行周期时模拟价格高于基准水平,宏观经济处于下行周期时模拟价格低于基准水平,并且经济上行周期对价格的影响大于经济下行周期；对于投机因素的分析,持仓量增加时,模拟价格上涨,持仓量减少时,模拟价格下跌；对突发事件,不同影响程度的突发事件,对价格的影响时间以及影响幅度不同；对于产业政策的模拟仿真,表明合理的产业政策有利于稳定价格。
Abstract:With the rapid economic development, China has become a main production and consumption country of non-ferrous metal in the world. As an important basic raw material, the price volatility for non-ferrous metals leads to the market uncertainty, even causes the huge market risks for producers, consumers and other stakeholders, and these factors will seriously affect the overall Chinese economy steady trend. For non-ferrous metals industry, its price volatility through upstream and downstream industries and economic sectors conduction, will give non-ferrous metal industry has brought great difficulties and challenges, but also seriously affect and constrain the industry's stability and development. The use of non-ferrous metal as a raw material for businesses, non-ferrous metal price fluctuations have a significant adverse impact, because the price fluctuations can be converted to fluctuations in the cost of raw materials, fluctuations in raw material costs will undermine corporate profitability, limiting raw material selection decisions. Therefore, in response to adverse price volatility, industry, enterprise, industry and even the country collects information of price volatility in advance, early warning the price volatility, control the risks of price volatility.
Under the background, this paper tries to find out the root causes of non-ferrous metals price volatility, and starts from determine the key influence factors of non-ferrous metals price volatility.
In this paper, copper, for example, in-depth analysis of the key factors of non-ferrous metals, and further collected a large number of economic indicators related to copper price and the upstream and downstream industries of copper products, filter out the primary indicators for early warning of copper prices volatility. Then the research constitutes the leading indicators, consistent indicators and lagging indicators of copper price volatility by using the time difference correlation analysis, and uses principal component analysis to obtain the following main components:the three main components for leading indicators are import and export price factor, speculation and raw materials factor, and building materials price factor; the three main components for consistent indicators are:producer's price for manufactured products factor, cost factor and yield factor, and export factor consumption; lagging indicators include two main components which are demand factor and scrap copper import factor. Finally, base on above results, calculates the leading composite index, consistent composite index and lagging composite index for early warning of copper price volatility, then compares every index with the copper price volatility trend, to warn the related risks.
The system dynamics method is used in the study of non-ferrous metals price volatility activities, to determine the feedback causal relationship for each influence factor of copper price fluctuations, draw causal loop diagram of copper system, and analyze the dynamic structure of copper price volatility through the price module, the demand module, the cost module, capacity utilization module and inventory module, then build the system flow diagram, set the parameters, and simulation the trend of fluctuations in copper prices volatility. By comparing the historical and forecasting copper price from1996to2012, the results show that the simulated copper forecasting price trend remains consistent with its historical price, which tests the reliability of the model.
This research simulates the copper price volatility in scenario modes, and discusses the cooper price volatility in different scenario modes from five aspects which are market structure, economic cycles, speculative effects, emergencies and industrial policy. Firstly, the research verifies the trends of volatility in copper prices, the influence extent of price volatility and impact path under different scenarios in the past, then regards2014as the start time, respectively analyzing price changes from2014to2020under different scenarios. The result shows that the price is more sharply volatility when production controlled by the manufacturer with monopolistic market structure; the economic cycles influence on copper prices have lagged effects, on macroeconomic upward cycle, the simulated price is higher than baseline levels, and in the downward cycle the prices below the benchmark level, and the economic upward cycle influence is greater than the downward one. The analysis of the speculative factors shows that when open interest increasing, the simulated price rises, open interest reducing, the simulated prices falls; different unexpected events have various periods and extents of impact on the price; the simulation of industry policy shows that the rational industrial policy is conducive to stabilize the price.
引文
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