Capacity Planning with Financial and Operational Hedging in Low‐Cost Countries

The authors of this article outline a capacity planning problem in which a risk‐averse firm reserves capacities with potential suppliers that are located in multiple low‐cost countries. While demand is uncertain, the firm also faces multi‐country foreign currency exposures. This study develops a mean‐variance model that maximizes the firm's optimal utility and derives optimal utility and optimal decisions in capacity and financial hedging size. The authors show that when demand and exchange rate risks are perfectly correlated, a risk‐averse firm, by using financial hedging, will achieve the same optimal utility as a risk‐neutral firm. In this study as well, a special case is examined regarding two suppliers in China and Vietnam. The results show that if a single supplier is contracted, financial hedging most benefits the highly risk‐averse firm when the demand and exchange rate are highly negatively related. When only one hedge is used, financial hedging dominates operational hedging only when the firm is very risk averse and the correlation between the two exchange rates have become positive. With both theoretical and numerical results, this study concludes that the two hedges are strategic tools and interact each other to maximize the optimal utility.     

需求-汇率风险聚集下的汇率风险对冲与批发价激励

以一个由上游制造商和下游零售商组成的二级供应链为建模背景,在汇率风险和需求风险聚集(pooling)在下游零售商的情况下,分别建立了有无批发价激励情形下的两个动态博弈模型,获得了相应的均衡。通过分析相应的均衡,结果表明,(1)在两种情形下,零售商的汇率风险对冲行为具有稳定供应链生产行为的作用,但批发价激励能够提高零售商的汇率风险对冲比例和供应链节点企业间的交易价格;(2)与无批发价激励的情形相比,有批发价激励时的制造商利润较高,从而制造商有使用批发价激励零售商对冲汇率风险的动机;(3)在风险聚集下,"通过较低的批发价来激励零售商对冲汇率风险"这一策略能够实现供应链盈利水平与风险承担之间的权衡:需求和汇率风险增加均会使得供应链节点企业和供应链整体的盈利水平降低,同时也将降低风险聚集处的节点企业和供应链整体的利润方差。     

中国商品期货市场风险溢价及其影响因素测度研究:基于套期保值压力效应的视角

本文基于套期保值压力效应的视角主要从商品期货合约本身的套期保值压力和交叉套期保值压力两个方面对我国农产品、能源化工和金属商品期货的风险溢价进行测度和分析.实证研究表明:当控制系统风险后,商品期货本身的套期保值压力与存在于组内的交叉套期保值压力均显著地影响期货的风险溢价.最后,本文引入价格压力变量以检验期货风险溢价模型的稳健性,当控制价格压力后,这两种套期保值压力效应仍然显著地存在.     

期望效用视角下的风险对冲效率

与传统文献将风险下降比率作为风险对冲效率指标不同,本文引入期望效用理论来比较最小方差对冲策略、最小在险价值(VaR)对冲策略和最小条件在险价值(CVaR)对冲策略的对冲效率,从而将人们的风险态度同对冲策略选择联系起来,以实现不同风险态度的投资者选择不同风险对冲策略的目的。借用风险中性效用函数、二次效用函数和CARA效用函数,本文严格证明:在这三种对冲策略中,最小方差对冲策略过于保守,最小VaR对冲策略最为激进,风险厌恶程度大的投资者偏好最小方差对冲策略,风险中性投资者和风险厌恶程度小的投资者更偏好最小VaR对冲策略,最小CVaR对冲策略介于二者之间。     

模型的复杂性与期货套期保值效率:基于环境突变样本区间的检验

本文从模型风险的角度,选取环境突变样本区间,对“模型的复杂性和期货套期保值效率”这一问题进行研究.采用随机系数马尔科夫体制转换(RCMRS)模型对期货最优套期保值比进行估计.并将RCMRS模型套期保值效率和OLS、VAR、VECM及GARCH等模型进行比较和分析.样本内比较发现,复杂的动态模型并未带来明显优于静态模型的套期保值表现.样本外比较则显示,动态模型的套期保值效率明显劣于静态模型.当环境突变,模型存在明显的误设时,由于复杂模型较简单模型涉及到更多变量和假定,模型(误设)风险较简单模型更大.再加上复杂模型较简单模型包含更多噪音,估计风险更大,综合来看,复杂模型的总风险明显大于简单模型,这直接导致复杂模型的套期保值效率劣于简单模型.     

关于货币风险套期保值方法的描述与比较

本文借助一个传统的无摩擦的国际金融市场模型,讨论了三种假设前提下贴现债券价格的变化率。在此基础上,导出了远期合约的价格以及相关的期货交割价格,并对此作了比较。     

基于时变Copula函数的下偏矩最优套期保值效率测度方法研究

由于下偏矩测度方法具有明显优于最小方差风险度量方法的特征,因此是更为合理的套期保值效率测度准则。本文针对已有的计算最小下偏矩套期保值比率的非参数方法与参数方法存在的局限性问题,提出使用时变Copula函数来估计现货与期货收益率的联合密度函数,然后通过数值方法计算最小下偏矩套期保值比率的新方法。并且运用上海期货交易所交易的铜期货合约价格与上海金属网公布的铜现货价格数据进行实证检验,发现使用具有随时间变化的相关系数的Copula函数,与非参数方法相比,可以得到更小下偏矩的套期保值率。     

基于价格调整的长寿风险自然对冲策略

在长寿风险对冲框架下,通过引入外生的产品价格,构建了基于价格调整的自然对冲模型。首先运用最优化理论得到了模型最优产品配比的解析式,然后在实际的销售配比与模型的最优配比相等的约束下,推导出了寿险产品和年金产品的最优定价。该定价能够使得模型的最优配比真正被实现,即销售的配比刚好是使产品组合长寿风险最小化的最优配比。最后通过数值算例,阐述了基于价格调整的自然对冲策略的效果,并进一步分析了利率、承保年龄、性别等因素对自然对冲策略的影响。     

不完全市场中相关性风险的对冲策略研究

随着我国资本市场的进一步完善,以及市场波动的更加剧烈,投资者对于相关性风险的关注日益增强,如何对冲相关性风险是一个亟待解决的重要课题。本文在基于跳跃的不完全市场中,以带有跳跃的价格过程为基础,引入相关性随机过程,依据期权的希腊字母对冲原理,构建相关性风险的对冲策略——卖出一份股票指数看跌期权同时买入若干份对应个股的看跌期权和若干份标的股票,使投资组合保持资产波动率以及价格跳跃风险中性,进而通过卖出组合中指数期权的相关性风险溢价来对冲个股组合的相关性风险。本文选取2007年3月到2013年3月香港恒生指数及其成份股期权的日数据用以实证分析,结果表明:该策略能够对冲个股投资组合的相关性风险,且在大部分情况下获得显著为正的收益。本文对事前构建对冲策略以规避极端事件发生时的相关性风险具有重要的参考价值。     

基于风险分解的股指期货套期保值策略研究

本文构建了基于方差分解的股指期货套期保值模型,并求解了相应的最优套期保值比率。将总体风险分解为系统风险与非系统风险,根据套保目标,通过在两类风险之间分配不同的权重可以提高组合整体表现。研究表明,方差分解套期保值模型更能有效地反映投资者对于风险类别的不同偏好,克服了H-D模型及MV模型的不足,具有良好的概括能力且更有利于套保目标的实现。     

套期保值, 估计风险与贝叶斯统计——基于中国铜期货市场的经验研究

针对期货最优套期保值策略估计中可能存在的估计风险问题,本文对单变量线性回归模型(OLS模型)和多变量线性回归模型(VAR模型和EC-VAR模型)进行贝叶斯分析,并采用Gibbs抽样方法对中国铜期货市场的最优套期保值策略进行了实证分析。本文还同时估计了基于频率统计方法的最优套期保值策略,并对贝叶斯统计下和频率统计下的最优套期保值策略进行了分析比较。实证结果清楚表明,估计风险对模型结果有重要影响。在处理估计风险方面,贝叶斯统计较频率统计方法有明显优势。     

国际投资汇率风险的综合套保策略研究

国际组合投资涉及多币种汇率风险,分别使用双边货币期货进行套保要承担较高套保成本。参考美元指数期货的实践,本文提出基于人民币指数期货的综合套保策略。实证结果表明,无论对于单个货币资产还是分散化投资的国际股指、债指组合,引入人民币指数期货能够显著降低收益率波动,提高抵御汇率波动的能力,同时拓展收益空间,是有效的汇率风险综合套保工具;人民币指数期货套保效率显著优于货币期货篮子,在发达国家股指市场表现更加突出。采用基于指数加权移动平均模型（EWMA）的动态套保策略,使得人民币指数期货收益对股指或债指市场波动敏感度降低,在市场极端状况时仍能保持相对中性。     

Financial Hedging and Optimal Procurement Policies under Correlated Price and Demand

We consider a firm that procures an input commodity to produce an output commodity to sell to the end retailer. The retailer's demand for the output commodity is negatively correlated with the price of the output commodity. The firm can sell the output commodity to the retailer through a spot, forward or an index‐based contract. Input and output commodity prices are also correlated and follow a joint stochastic price process. The firm maximizes shareholder value by jointly determining optimal procurement and hedging policies. We show that partial hedging dominates both perfect hedging and no‐hedging when input price, output price, and demand are correlated. We characterize the optimal financial hedging and procurement policies as a function of the term structure of the commodity prices, the correlation between the input and output prices, and the firm's operating characteristics. In addition, our analysis illustrates that hedging is most beneficial when output price volatility is high and input price volatility is low. Our model is tested on futures price data for corn and ethanol from the Chicago Mercantile Exchange.     

Shareholders' Wealth‐Maximizing Operating Decisions and Risk Management Practices in a Mixed Contracts Economy

This paper establishes a critically important positive role for operations management practices and financial hedging. We show that operations management decisions and financial hedging are intertwined, and we advance a framework that can identify their combined effects on investors' wealth. We show that: (a) firms (publicly traded corporations) will optimally hold adequate riskless working capital (e.g., cash) to minimize the cost of obtaining non‐financial inputs, and the magnitude of this cash holding depends on operating details, and (b) operations management and financial hedging can lower firms' cash requirements, and boost productivity, defined as the wealth created in the firm per dollar of invested capital. Productivity‐enhancing practices—by “freeing up” some of the firm's cash—can maximize the investors' wealth. We show that these results obtain because firms' contracts with many of the providers of non‐financial inputs are not traded, and because investors can invest not just in public corporations but also in businesses “outside the markets” (e.g., proprietorships, partnerships, and private equity).     

Operational Hedging and Diversification under Correlated Supply and Demand Uncertainty

When facing supply uncertainty caused by exogenous factors such as adverse weather conditions, firms diversify their supply sources following the wisdom of “not holding all eggs in one basket.” We study a firm that decides on investment and production levels of two unreliable but substitutable resources. Applying real options thinking, production decisions account for actual supply capabilities, whereas investment decisions are made in advance. To model triangular supply and demand correlations, we adapt the concepts of random capacity and stochastic proportional yield while using concordant ordered random variables. Optimal profit decreases monotonically in supply correlation and increases monotonically in supply–demand correlation. Optimal resource selection, however, depends on the trivariate interplay of supply and demand and responds non‐monotonically to changing correlations. Moreover, supply hedges (i.e., excess capacity at alternative sources) can be optimal even if supply resources are perfectly positively correlated. To accommodate changing degrees of correlation, the firm adjusts the lower margin capacities under random capacity; but under stochastic proportional production capability, it uses either low‐ or high‐margin capacities to create tailored “scale hedges” (i.e., excess capacity at one source which can partially substitute for diversification).     

同种商品不同月份期货组合风险评价模型研究及应用

以期货合约的每一交易日的对数涨跌率来反映市场风险,借助VaR风险价值法,运用加权核估计技术(WKDE)和指数加权滑动模型(EWMA),建立了基于期货组合中持有头寸不同且可以进行风险对冲的期货组合市场风险非线性叠加评价模型,解决了同种商品、不同月份期货组合每一交易日最大损失的确定问题,并通过实证研究验证了模型的实用性.该模型的特点一是借助WKDE法预测组合中单个合约每一交易日涨跌率最大日亏损值,充分体现了期货合约涨跌率的实际走势,使VaR估计更加精确.二是通过动态迁移相关系数矩阵的计算保证了模型的精确性.采用EWMA模型预测动态变化的方差-协方差矩阵,从实证的角度得到更精准的动态迁移相关系数矩阵.三是考虑了组合中多头和空头不同头寸之间的风险对冲,避免了实际中期货组合风险的线性相加而造成放大风险或减少风险的不准确性,从而能较好地保证了模型的预测精度及准确性.四是通过基于风险非线性叠加建立的期货组合风险评价模型解决了SPAN系统中期货组合风险的线性叠加问题,从而得到更合理的组合风险预测值.     

基于动态规划多期期货套期保值优化模型研究

通过对套期保值者头寸价值变化量的分析,采用动态规划方法,建立了多期套期保值动态模型,推导出多期套期保值进行动态跟踪调整的策略。该模型的特点一是反映了期货交易费用在套期保值中的作用,解决了现有期货套期保值策略忽略交易费用的不足,提高了模型的准确性。二是考虑保证金对期货套期保值的影响。把期货交易保证金的机会损失纳入套期保值策略内,从而使套期保值直接反映了期货保证金无利息收入、而存在机会成本的真实情况,弥补了现有研究不考虑期货交易保证金的机会损失的缺陷。三是体现了套期保值者收益最大化的原则。解决了现有模型只考虑了规避期货和现货组合的价格波动风险,忽略组合的收益的弊端,增加了模型的实用性和适用性。     

Quantile Uncertainty and Value‐at‐Risk Model Risk

This article develops a methodology for quantifying model risk in quantile risk estimates. The application of quantile estimates to risk assessment has become common practice in many disciplines, including hydrology, climate change, statistical process control, insurance and actuarial science, and the uncertainty surrounding these estimates has long been recognized. Our work is particularly important in finance, where quantile estimates (called Value‐at‐Risk) have been the cornerstone of banking risk management since the mid 1980s. A recent amendment to the Basel II Accord recommends additional market risk capital to cover all sources of “model risk” in the estimation of these quantiles. We provide a novel and elegant framework whereby quantile estimates are adjusted for model risk, relative to a benchmark which represents the state of knowledge of the authority that is responsible for model risk. A simulation experiment in which the degree of model risk is controlled illustrates how to quantify Value‐at‐Risk model risk and compute the required regulatory capital add‐on for banks. An empirical example based on real data shows how the methodology can be put into practice, using only two time series (daily Value‐at‐Risk and daily profit and loss) from a large bank. We conclude with a discussion of potential applications to nonfinancial risks.     

Risk Characterization for Nanotechnology

Nanotechnology is a broad term that encompasses materials, structures, or processes that utilize engineered nanomaterials, which can be defined as materials intentionally designed to have one or more dimensions between 1 and 100 nm. Historically, risk characterization has been viewed as the final phase of a risk assessment process that integrates hazard identification, dose‐response assessment, and exposure assessment. The novelty and diversity of materials, structures, and tools that are covered by above‐defined “nanotechnology” raise substantial methodological issues and pose significant challenges for each of these phases of risk assessment. These issues and challenges culminate in the risk characterization phase of the risk assessment process, and this article discusses several of these key issues and approaches to developing risk characterization results and their implications for risk management decision making that are specific to nanotechnology.