我国黄金期货市场有效性的实证分析

黄金因为其兼有货币、商品和金融三大属性的特征历来受到人们的重视.自黄金期货在上海期货交易所上市,填补了我国长期缺乏金融期货的空白.管理层与市场各参与主体对黄金期货给予很高的期望与关注,因此研究上海黄金期货市场的有效性具有重要意义.本文通过运用游程检验、ADF单位根检验、协整检验与计量经济学的方法,对上海期货交易所黄金期货市场的有效性进行了实证分析.结果表明,上海黄金期货市场尚未达到有效,并且黄金现货价格单向引导期货价格,我国黄金期货市场还有待改善.     

基于ARIMA模型对我国黄金期货价格分析与预测

本文基于ARIMA模型,对黄金期货建立了价格预测模型,并对2016年1月18日至2017年1月10日内共241个交易日的上海期货交易所的黄金期货的结算价数据的变动规律和短期趋势进行了预测.实证结果表明:ARIMA模型可以对黄金期货价格走势做出短期预测,能够大体上反映出黄金期货价格的波动情况,并为投资者以及企业在进行相关决策时提供有价值的参考.然而预测误差随着预测时间的增加而变大.     

中美期货市场联动机理分析——以白糖期货市场为例

在世界经济全球化和金融自由化的背景下,国内外期货市场联动性的判断成为期货市场研究热点。文章选取我国郑州商品交易所(ZCE)白糖期货价格和美国洲际交易所(ICE)白糖期货作为研究对象,以两个交易所的白糖日间收盘价格数据作为变量,从流动性指标和相关程度的角度,运用统计学、相关性检验、Granger因果检验和VAR模型等计量经济方法衡量中美白糖期货市场运行效率和成熟程度。研究结果表明:美国白糖期货流动性高于中国白糖期货流动性,中美白糖期货交易制度的内外盘期货标准合约不同、内外盘期货交易制度差异、涨跌停板制度和持仓报告制度等存在差异。中美白糖期货价格存在长期协整关系和双向引导关系,美国白糖期货在相互作用中处于主导地位。     

国内、国际期货市场期货价格之间的关联研究

该文利用协整检验和Granger因果检验等技术,首次对国内和国际期货市场的铜、铝、大豆和小麦的期货价格之间的动态关系进行了实证研究.结果显示:上海期货交易所与伦敦金属交易所铜、铝的期货价格之间存在长期均衡关系,大连商品交易所与芝加哥期货交易所大豆的期货价格之间存在协整关系;相对而言,国外市场的影响力较大;郑州商品交易所与芝加哥期货交易所小麦期货价格之间不存在协整关系.     

沪铝与伦铝指数价格协整关系与引导关系的实证分析

文章利用协整分析和Granger因果关系检验等统计方法,对上海期货交易所沪铝指数价格和伦敦期货交易所综合铝价格之闻的长期均衡关系和引导关系进行实证研究。结果表明两市的铝期货价格之间存在长期的均衡关系;伦铝价格对沪铝价格具有引导作用,而沪铝价格对伦铝价格的影响却不大。这说明中国在铝期货价格上缺乏定价权。     

纽约黄金期货价格波动对我国期货市场收益率的影响研究

随着我国期货市场的迅速发展,商品期货逐步显示出金融属性。本文运用自回归分布滞后模型结合GARCH族模型对纽约黄金期货价格波动与我国上海期货交易所沪铜、沪铝、沪锌、天然橡胶、燃料油期货价格波动之间的动态关系展开研究,以考察宏观经济运行对我国期货市场的影响。     

上海铝期货市场有效性的实证研究

本文利用单位根检验、协整检验对上海期货交易所铝期货市场的有效性进行了实证研究,结果显示:沪铝期货市场已经达到弱式有效,且当期货价格与最后交易日的现货价格间的时间跨度不超过4个月时,金属铝的期货价格和现货价格之间存在协整关系。     

中国黄金期货与黄金现货价格的实证分析

意旨探索中国黄金现货价格对黄金期货价格形成的作用机制。借助ADL模型和共同因子贡献法进行实证分析,研究了中国黄金期货价格与黄金现货价格的关系。研究表明,中国黄金期货价格与现货价格长期趋势是一致的,但是短期存在比较大的偏差,同时中国黄金期货和现货价格波动率序列之间有较高的依存度。由此中国黄金期货市场已具备一定规避风险的功能。     

上海期铜价格有效性研究

文章根据BGS检验模型对上海期货交易所铜期货最近二年的交易数据进行有效性的实证分析,分析结果显示四周内的铜期货价格基本上是交割日的现货无偏估计。     

不同趋势下股指期货价格发现功能研究

本文利用沪深300指数和沪深300股指期货当月主合约的5分钟高频数据,采用线性和非线性Granger因果检验方法,对股指期货价格发现功能进行了研究。研究结果表明,在上涨趋势中股指期货收益变化领先于现货市场收益变化,股指期货具备价格发现功能;而在下跌趋势中,股指期货收益与现货收益互为Granger因果关系,股指期货市场收益与现货市场收益存在相互引导的关系。     

Information Linkages between Chinese and World Copper Futures Markets

In this paper, we examine the price discovery process and volatility spillover effects in informationally linked futures markets. Using synchronous trading information from the Shanghai Futures Exchange (SHFE), the New York Mercantile Exchange (NYMEX), and the London Metal Exchange (LME) for copper futures from 2000 to 2012, we show that the cointegration relationships of these futures markets changed during 2006–2008. The results indicate that there is a bidirectional relationship in terms of price and volatility spillovers between the LME and NYMEX and the SHFE, with a stronger effect from the LME and NYMEX to the SHFE (versus the effect from the SHFE to the LME and NYMEX) prior to 2006. Our results also highlight the increasingly prominent role of the SHFE in the price formation process and cross-volatility spillover effects since 2008. Finally, we show that volatility spillover has important implications for constructing optimized portfolios for copper investors.     

沪铜期货市场价格发现的动态贡献——基于状态空间模型的实证研究

商品期货价格与现货价格的相互关系一直是学术界研究的热点,但大都基于静态的模型。本文从期货定价的持有成本理论出发,通过误差修正方程构建状态空间模型,利用卡尔曼滤波算法从动态的角度研究了2004-2012年期间我国沪铜期货市场价格发现的贡献。实证结果显示:2004-2012年,我国沪铜期货市场价格发现的贡献随着时间的变化而变化。2004-2008年逐步增强;2008年金融危机后,逐步下滑,到2010年,落后于现货市场;之后又有回升趋势。总体来看,沪铜期货市场在价格发现中处于主导地位,但具有明显的波动性。     

基于LM算法的石油期货价格预测研究

石油价格的走势一直是世界各国所研究和关注的焦点,石油期货是世界石油交易的一种重要方式,准确预测石油期货价格的走势,对于政府宏观政策取向和相关企业经营决策具有重要意义。本文利用BP神经网络的自适应学习能力,建立基于LM算法的石油期货价格预测模型,并使用MATLAB7．0编程实现,针对纽约商业交易所的石油期货价格数据进行了训练和测试。研究结果表明,将基于LM算法的BP神经网络模型应用于石油期货价格预测中,运算速度快,预测精度高,具有推广应用的价值。     

Volatility–volume co-movements: evidence from China metal markets

This article investigates the interactional relationship between price volatility and futures trading activity for three heavily traded metal products on the Shanghai Metal Exchange and the Shanghai Futures Exchange. Using models based on vector autoregression and generalized method of moments, we show, in particular, that futures trading activity has a strong impact on both spot and futures price volatility in copper and aluminium markets. Futures trading activity leads spot market volatility in copper and aluminium markets which suggests that futures markets have a destabilizing effect. In order to disentangle the effect of different traders’ types on asset price movements, we decompose futures trading into speculators’ and hedgers’ trading and investigate their contributions to volatility. As a robustness check, we investigate the impact of endogenous structural breaks on the interactional relationship between price volatility and futures trading.     

我国商品期货价格指数与宏观经济指标关系的实证研究简

通过考察我国商品期货价格指数与主要宏观经济变量之间的相互影响关系,发现商品期货价格指数对物价、国内生产总值、利率、人民币汇率均有明显的引导作用和直接影响,并且能够领先CPI指标约5-7个月。商品期货价格指数作为CPI的先行指标具有一定的可行性。     

Dynamic Relationships among GCC Stock Markets and Nymex Oil Futures

Daily relationships among stock markets of the Gulf Cooperation Council (GCC) members, excluding Qatar, form two equilibrium relationships with varying predictive power. The Saudi market leads, followed by Bahrain and United Arab Emirates. Kuwait, which is dominated by momentum traders, and Oman have the weakest links with the other GCC markets. Only the Saudi index can predict—and be predicted by—New York Mercantile Exchange oil futures prices. Therefore these markets are candidates for diversified regional portfolios at the country level. The trading day effect is weak for all GCC markets and oil futures prices but remains consistent with findings for the U.S. stock market. (JEL C22 , F3 , Q49 )     

Modeling the volatility of futures return in rubber and oil—A Copula-based GARCH model approach

This paper attempts to make use of a Copula-based GARCH (Generalized AutoRegressive Conditional Heteroskedasticity) Model to find out the relationships between the volatility of rubber futures returns in the Agricultural Futures Exchange of Thailand (AFET) and other four main markets, namely, the volatility of rubber futures returns in the Singapore Commodity Exchange (SICOM), the volatility of rubber futures returns, crude oil returns, and gas oil returns in the Tokyo Commodity Exchange (TOCOM). The results illustrate that the Student-t dependence only shows better explanatory power than the Gaussian dependence structure and the persistence pertaining to the dependence structure between rubber futures returns in AFET and oil futures returns, namely, crude oil futures returns and gas oil futures returns in TOCOM. Whereas, the Gaussian dependence shows better explanatory ability between rubber futures returns in AFET and other rubber futures returns, namely, the volatility of rubber futures in SICOM and TOCOM. For the multivariate Copula model, all the parameters between AFET and other variables are significant. Based on these results, with the liberalization of agricultural trade and the withdrawal of government support to agricultural producers, there is in many countries a new need for price discovery and even physical trading mechanisms, a need that can often be met by commodity futures exchanges. Hence, this paper recommends that the government supports the hedge mutual funds that can be invested in every commodities futures exchange in the world. It can also put the funds together that will contribute farmers to invest in each commodities futures market.