利用金融期货规避商品价格风险的研究

本文利用韩国综合股票价格指数期货对我国钢材进行了交叉套期保值研究,建立了基于随机波动模型下的利用国外金融期货对我国商品现货交叉套期保值风险度量模型,并通过实证分析认为.基于随机波动模型下的风险在险值基本能够刻画出基差风险状况.本研究为利用金融期货对商品现货交叉套期保值提供了理论依据,对我国推出金融期货后,企业规避商品价格风险扩大套期保值品种具有一定的借鉴意义.     

沪深300股指期货套期保值的实证研究

如果在现货资产中加入股指期货来进行套期保值,那么我们的收益会得到保障或者风险能够得到降低。本文便利用修正的ECM-GARCH模型来测算资产组合的最优套期保值比率,从而为投资者进行决策提供依据。     

我国股指期货套期保值效果的实证分析——基于下侧风险框架的分析

基于下偏矩风险法(LPMS)的套期保值侧重规避实际收益率低于目标收益率的情形,更符合投资者真实心理感受,能够通过设定不同的目标收益率而满足投资者不同的需求。通过构建沪深300股指期货和上证50ETF基金的套期保值组合,分别计算了基于LPMS和最小方差法(MV)下的套保比率及套保有效性。结果显示随着投资者风险偏好增加、目标收益率增加以及套保期限增加,LPMS下的套期保值有效性递减。与MV方法相比,LPMS方法能适应不同风险偏好和不同目标收益率特征的套期保值者。     

商品套期保值实现原理及其风险防范

商品套期保值以规避大宗商品特别是国际市场大宗商品过度波动的价格风险,而普遍受到企业尤其是大型实体企业和贸易企业的欢迎。通过期、现两个市场交易的反向操作进行对冲,实现商品套期保值,是建立在同一商品期货与现货市场价格走势趋于一致,以及合约交割日的临近,现货与期货价格走向趋同这一基石之上的。其基本的要义主要表现为"锁定四个对冲":一是锁定相同交割月份的期货合约对冲;二是锁定相同品种的期货合约对冲;三是锁定等量规模的期货合约对冲;四是锁定交易反向的期货合约对冲。商品套期保值的价值功能,主要表现在具有对冲现货价格大幅波动风险、锁定企业可持续发展预期、放大企业财务杠杆安全边界三个方面。其实现路径主要表现为买入套期保值和卖出套期保值。有效防范商品套期保值风险,需要多措并举,确定全方位积极应对策略,特别是要不断完善内部治理结构,强化风险防控责任,把握期现基差风险全部要义,严格执行"三位一体"操作规则,建立科学的预警防控机制。     

OLS和BVAR模型下最优套期保值比率的研究

以回避现货价格风险为目的进行的相反期货交易行为称为套期保值。套期保值的效果直接取决于股指期货头寸能否有效抵消现货头寸的风险。经过Eviews分析得出考虑了残差自相关的BVAR和OLS模型的最优套期保值比率相近。     

沪深300股指期货套期保值的实证研究

股指期货作为金融衍生产品的一个重要用途是套期保值,沪深300股指期货是我国推出的第一只股指期货,具有较强的开拓性和代表性。本文在基差风险不为零的前提下,运用GARCH模型研究沪深300股指期货的套期保值的可行性,以及最优套期保值比率,为风险厌恶型投资者提供有效规避现货市场系统性风险和非系统性风险的投资决策建议。     

国内外黄金市场的关联性研究

本文通过建立VEC模型,运用格兰杰因果检验与方差分解的方法对国内黄金期货、现货与伦敦黄金现货的关联性进行了分析,并进行了静态预测。结果表明:虽然序列不平稳,但三者间存在长期的协整关系;伦敦黄金现货对国内黄金期货、现货存在引导作用,短时间内,国内黄金期货会受到的更大冲击,而从长时间看,国内黄金现货受到的冲击更大;我国黄金期货尚不具备价格发现的作用,我国黄金市场仍然是黄金现货占主导地位;国内黄金现货市场与伦敦黄金现货市场相互影响程度更大;通过VEC模型的静态预测可以取得较好的预测效果。     

国内外黄金现货市场波动特征与风险度量

近十年来,国内外黄金现货市场收益率均表现出尖峰厚尾和波动聚集性特征。但与一般金融资产负的冲击具有非对称效应不同,黄金现货市场利好消息对波动的影响更大,且国内比国外市场有更显著的杠杆效应。在波动性特征方面,学生t分布对国内市场收益率描述效果更佳,而GED分布更适合国际市场;在市场风险度量方面,VaR-GJR-GED模型在国内和国际黄金现货市场风险研究上有很好的风险度量效果。     

沪深300股指期货在套期保值中的实证研究

本文介绍了沪深300股指期货在证券市场中的作用以及利用股指期货进行套期保值的两类方法,详细阐述了利用股指期货组建最小方差投资组合并得出了最小方差套期保值比率的计算公式。使用沪深300股指期货IF1012合约交易数据和上证50ETF交易数据,应用OLS模型估计套期保值比率进行实证研究,并将测算出的套期保值比率用于市场模拟的现货组合,测算了实际的套期保值效果。     

中国黄金期货的引入对黄金现货市场质量的影响

本文以上海黄金交易所成交最为活跃的AU9995黄金现货作为研究对象,采用EViews6.0软件对黄金期货上市前后各300个日交易数据进行处理分析,通过比较我国黄金期货引入前后黄金现货市场的流动性、波动性、效率性的变化情况,来研究黄金期货上市对现货市场质量所造成的影响。研究结果表明:黄金期货上市后,降低了黄金现货市场的流动性和效率性,增加了黄金现货市场的波动性,因此,黄金期货的引入并未能改善黄金现货市场质量,而是降低了黄金现货市场质量。通过本文的研究,也对我国推出股指期货有一定借鉴意义。     

中美玉米期货市场功能效率比较

价格发现与套期保值是期货市场的基本功能,能够反映期货市场的运行效率。通过对比中美贸易摩擦前后期货市场的价格发现和套期保值功能,分析中美玉米期货市场效率间的差距,探究我国玉米期货市场运行效率低的原因。利用格兰杰(Granger)因果分析、协整检验、分位信息份额模型、套期保值比率及绩效分析方法,定量对中美两国2013—2019年玉米期货及现货的数据进行分析,结果表明,中国玉米期货市场存在较强的价格发现功能,但套期保值绩效不佳。使用前沿分位信息份额模型和滚动格兰杰因果法分析中美两国期现货市场动态关系的区别,发现中国仅存期货市场对现货市场的单向引导,而美国在中美贸易摩擦前表现为玉米期现货市场具有相近的引导能力,套期保值效率较高,中美贸易摩擦增强了其现货市场对期货市场的引导能力,降低了期货市场运行效率。从期现货市场双向引导关系视角来看,中国玉米期货市场效率低的原因主要是现货市场的信息不完全、发展不完善,期现货市场缺少长期稳定的双向引导关系抑制了期货市场功能发挥。中国应全面加强期货市场建设,提升期货市场定价效率,推动农产品期货市场快速健康发展。     

Spot‐futures spread,time‐varying correlation,and hedging with currency futures

This article investigates the effects of the spot‐futures spread on the return and risk structure in currency markets. With the use of a bivariate dynamic conditional correlation GARCH framework, evidence is found of asymmetric effects of positive and negative spreads on the return and the risk structure of spot and futures markets. The implications of the asymmetric effects on futures hedging are examined, and the performance of hedging strategies generated from a model incorporating asymmetric effects is compared with several alternative models. The in‐sample comparison results indicate that the asymmetric effect model provides the best hedging strategy for all currency markets examined, except for the Canadian dollar. Out‐of‐sample comparisons suggest that the asymmetric effect model provides the best strategy for the Australian dollar, the British pound, the deutsche mark, and the Swiss franc markets, and the symmetric effect model provides a better strategy than the asymmetric effect model in the Canadian dollar and the Japanese yen. The worst performance is given by the naïve hedging strategy for both in‐sample and out‐of‐sample comparisons in all currency markets examined. © 2006 Wiley Periodicals, Inc. Jrl Fut Mark 26:1019–1038, 2006     

Optimal Futures Hedging Under Multichain Markov Regime Switching

Most of the existing Markov regime switching GARCH‐hedging models assume a common switching dynamic for spot and futures returns. In this study, we release this assumption and suggest a multichain Markov regime switching GARCH (MCSG) model for estimating state‐dependent time‐varying minimum variance hedge ratios. Empirical results from commodity futures hedging show that MCSG creates hedging gains, compared with single‐state‐variable regime‐switching GARCH models. Moreover, we find an average of 24% cross‐regime probability, indicating the importance of modeling cross‐regime dynamic in developing optimal futures hedging strategies. © 2012 Wiley Periodicals, Inc. Jrl Fut Mark 34:173–202, 2014     

A Markov regime switching approach for hedging stock indices

In this paper we describe a new approach for determining time‐varying minimum variance hedge ratio in stock index futures markets by using Markov Regime Switching (MRS) models. The rationale behind the use of these models stems from the fact that the dynamic relationship between spot and futures returns may be characterized by regime shifts, which, in turn, suggests that by allowing the hedge ratio to be dependent upon the “state of the market,” one may obtain more efficient hedge ratios and hence, superior hedging performance compared to other methods in the literature. The performance of the MRS hedge ratios is compared to that of alternative models such as GARCH, Error Correction and OLS in the FTSE 100 and S&P 500 markets. In and out‐of‐sample tests indicate that MRS hedge ratios outperform the other models in reducing portfolio risk in the FTSE 100 market. In the S&P 500 market the MRS model outperforms the other hedging strategies only within sample. Overall, the results indicate that by using MRS models market agents may be able to increase the performance of their hedges, measured in terms of variance reduction and increase in their utility. © 2004 Wiley Periodicals, Inc. Jrl Fut Mark 24:649–674, 2004     

A novel risk management framework for natural gas markets

This paper examines dynamic hedges in the natural gas futures markets for different horizons and explores the gains from devising risk management strategies. Despite the substantial progress made in developing hedging models, forecast combinations have not been explored. We fill this gap by proposing a framework for combining hedge-ratio predictions. Composite hedge ratios lead to significant reduction in portfolio risk, whether spot prices are partially predictable or not. We offer insights on hedging effectiveness across seasons, backwardation-contango conditions and the asymmetric profiles of long-short hedgers. We conclude that forecast combinations better reconcile realized performance with the hedging process, mitigating model instability.     

Optimal futures hedging for energy commodities: An application of the GAS model

This paper applies generalized autoregressive score-driven (GAS) models to futures hedging of crude oil and natural gas. For both commodities, the GAS framework captures the marginal distributions of spot and futures returns and corresponding dynamic copula correlations. We compare within-sample and out-of-sample hedging effectiveness of GAS models against constant ordinary least square (OLS) strategy and time-varying copula-based GARCH models in terms of volatility reduction and Value at Risk reduction. We show that the constant OLS hedge ratio is not inherently inferior to the time-varying alternatives. Nonetheless, GAS models tend to exhibit better hedging effectiveness than other strategies, particularly for natural gas.     

Volatility spillover effects and cross hedging in corn and crude oil futures

Using a volatility spillover model, we find evidence of significant spillovers from crude oil prices to corn cash and futures prices, and that these spillover effects are time‐varying. Results reveal that corn markets have become much more connected to crude oil markets after the introduction of the Energy Policy Act of 2005. Furthermore, when the ethanol–gasoline consumption ratio exceeds a critical level, crude oil prices transmit positive volatility spillovers into corn prices and movements in corn prices are more energy‐driven. Based on this strong volatility link between crude oil and corn prices, a new cross‐hedging strategy for managing corn price risk using oil futures is examined and its performance is studied. Results show that this cross‐hedging strategy provides only slightly better hedging performance compared with traditional hedging in corn futures markets alone. The implication is that hedging corn price risk in corn futures markets alone can still provide relatively satisfactory performance in the biofuel era. © 2010 Wiley Periodicals, Inc. Jrl Fut Mark     

The role of financial investors in determining the commodity futures risk premium

I develop and test a model to study the interaction between the commodity and stock markets. This study attempts to clarify the debate about the effect of financialization on commodity markets. Theoretically, the futures risk premium is determined by hedging pressure, stock market returns, and the commodity–equity correlation. Empirically, the effect of the stock market on the energy market became significantly greater for the futures risk premium in the period following the 2008 crisis. Furthermore, hedging pressure is a strong explanatory variable for the futures risk premium in various circumstances.     

Hedging in Futures and Options Markets with Basis Risk

This paper analyzes the hedging decisions for firms facing price and basis risk. Two conditions assumed in most models on optimal hedging are relaxed. Hence, (i) the spot price is not necessarily linear in both the settlement price and the basis risk and (ii) futures contracts and options on futures at different strike prices are available. The design of the first‐best hedging instrument is first derived and then it is used to examine the optimal hedging strategy in futures and options markets. The role of options as useful hedging tools is highlighted from the shape of the first‐best solution. © 2002 John Wiley & Sons, Inc. Jrl Fut Mark 22:59–72, 2002     

Production and hedging under Knightian uncertainty

This article introduces Knightian uncertainty into the production and futures hedging framework. The firm has imprecise information about the probability density function of spot or futures prices in the future. Decision‐making under such scenario follows the “max‐min” principle. It is shown that inertia in hedging behavior prevails under Knightian uncertainty. In a forward market, there is a region for the current forward price within which full hedge is the optimal hedging policy. This result may help explain why the one‐to‐one hedge ratio is commonly observed. Also inertia increases as the ambiguity with the probability density function increases. When hedging on futures markets with basis risk, inertia is established at the regression hedge ratio. Moreover, if only the futures price is subject to Knightian uncertainty, the utility function has no bearing on the possibility of inertia. © 2000 John Wiley & Sons, Inc. Jrl Fut Mark 20: 397–404, 2000