生产成本信息不对称下零售商风险厌恶的回购契约

探索在市场价格随机条件下,生产成本信息不对称零售商风险厌恶时,采用回购契约协调二级供应链的内在规律.构建新的条件下的回购契约模型并求解,分析信息不对称和风险厌恶对供应链上各决策变量的影响.通过算例仿真进行了验证,研究结果发现:在市场价格随机条件下,不管生产成本信息是否对称,只要零售商存在风险厌恶,供应链上各决策变量都会发生分岔突变的现象;不管零售商是否风险厌恶,生产成本信息不对称都会给供应商带来额外的收益,但会损害零售商与整个供应链的收益;信息越不对称,供应链上的各种决策变量在分岔突变区域的振幅越大.结论是:分岔突变现象是价格随机条件下,参与者风险厌恶时存在的一种特有现象;供应商能够通过隐瞒私人信息带来额外的收益,但损害零售商和供应链的利益;零售商应对生产成本信息不对称的最好办法就是以最低的成本使生产成本信息透明;零售商以平稳的心态面对各种外部风险,更有利于科学决策.     

存货质押融资中螺纹钢风险价值的控制

针对钢材市场中存货质押融资业务的价格风险问题,以螺纹钢现货的价格为样本数据,采用经验值方法计算风险率与效率损失率,并与基于VaR历史模拟法的计算结果进行比较.结果表明,样本期间长度的选择对历史模拟法计算结果的优劣有一定影响,历史模拟法适合短期限的存货质押融资贷款.用回顾测试对计算结果进行检验,表明用VaR方法设定的质押率对控制螺纹钢价格风险更有效.     

Short‐term salmon price forecasting

This study establishes a benchmark for short‐term salmon price forecasting. The weekly spot price of Norwegian farmed Atlantic salmon is predicted 1–5 weeks ahead using data from 2007 to 2014. Sixteen alternative forecasting methods are considered, ranging from classical time series models to customized machine learning techniques to salmon futures prices. The best predictions are delivered by k‐nearest neighbors method for 1 week ahead; vector error correction model estimated using elastic net regularization for 2 and 3 weeks ahead; and futures prices for 4 and 5 weeks ahead. While the nominal gains in forecast accuracy over a naïve benchmark are small, the economic value of the forecasts is considerable. Using a simple trading strategy for timing the sales based on price forecasts could increase the net profit of a salmon farmer by around 7%.     

Modeling eBay price using stochastic differential equations

Online auctions have become increasingly popular in recent years. There is a growing body of research on this topic, whereas modeling online auction price curves constitutes one of the most interesting problems. Most research treats price curves as deterministic functions, which ignores the random effects of external and internal factors. To account for the randomness, a more realistic model using stochastic differential equations is proposed in this paper. The online auction price is modeled by a stochastic differential equation in which the deterministic part is equivalent to the second‐order differential equation model proposed in Wang et al. (Journal of the American Statistical Association, 2008, 103, 1100–1118). The model also includes a component representing the measurement errors. Explicit expressions for the likelihood function are also obtained, from which statistical inference can be conducted. Forecast accuracy of the proposed model is compared with the ODE (ordinary differential equation) approach. Simulation results show that the proposed model performs better.     

Financial volatility modeling: The feedback asymmetric conditional autoregressive range model

An implied assumption in the asymmetric conditional autoregressive range (ACARR) model is that upward range is independent of downward range. This paper scrutinizes this assumption on a broad variety of stock indices. Instead of independence, we find significant cross‐interdependence between the upward range and the downward range. Regression test shows that the cross‐interdependence cannot be explained by leverage effect. To include the cross‐interdependence, a feedback asymmetric conditional autoregressive range (FACARR) model is proposed. Empirical studies are performed on a variety of stock indices, and the results show that the FACARR model outperforms the ACARR model with high significance for both in‐sample and out‐of‐sample forecasting.     

Can online search data improve the forecast accuracy of pork price in China?

Online search data provide us with a new perspective for quantifying public concern about animal diseases, which can be regarded as a major external shock to price fluctuations. We propose a modeling framework for pork price forecasting that incorporates online search data with support vector regression model. This novel framework involves three main steps: that is, formulation of the animal diseases composite indexes (ADCIs) based on online search data; forecast with the original ADCIs; and forecast improvement with the decomposed ADCIs. Considering that there are some noises within the online search data, four decomposition techniques are introduced: that is, wavelet decomposition, empirical mode decomposition, ensemble empirical mode decomposition, and singular spectrum analysis. The experimental study confirms the superiority of the proposed framework, which improves both the level and directional prediction accuracy. With the SSA method, the noise within the online search data can be removed and the performance of the optimal model is further enhanced. Owing to the long-term effect of diseases outbreak on price volatility, these improvements are more prominent in the mid- and long-term forecast horizons.     

The industrial asymmetry of the stock price prediction with investor sentiment: Based on the comparison of predictive effects with SVR

As a representative emerging financial market, the Chinese stock market is more prone to volatility because of investor sentiment. It is reasonable to use efficient predictive methods to analyze the influence of investor sentiment on stock price forecasting. This paper conducts a comparative study about the predictive performance of artificial neural network, support vector regression (SVR) and autoregressive integrated moving average and selects SVR to study the asymmetry effect of investor sentiment on different industry index predictions. After studying the relevant financial indicators, the results divide the Shenwan first-class industries into two types and show that the industries affected by investor sentiment are composed of young companies with high growth and high operative pressure and there are a great number of investment bubbles in those companies.     

考虑等待时间的网约车与出租车均衡定价研究

针对网约车和出租车的出行服务竞争,用等待时间刻画影响需求的服务质量,考虑网约车服务质量高于/低于出租车服务质量两种情景,探讨两种服务共存的条件及均衡定价策略.研究结果表明:当总网络外部性为正时,两种服务需较高差异化才能实现共存;而当总网络外部性为负时,无需其他条件约束,两种服务皆可共存.通过算例分析,分析了网约车服务等待时间对消费者剩余的影响以及参数对两种服务共存条件的影响.此外,借鉴参照依赖理论描述出租车司机在竞争市场中的获利感知,提出基于服务质量差异的网约车管制措施.研究结论为网约车服务定价和监管策略提供了一定的管理启示.     

生产率提高和产业结构变化对住房价格的影响

通过构建劳动力和住房市场均衡模型,探究了生产率提高和产业结构变化对住房市场和劳动力市场均衡状态的影响,并利用我国35个大中城市2002—2012年的数据建立动态面板模型进行了实证分析.结果表明,生产率提高会引起房价上涨,且第三产业的效应强于第二产业;产业结构优化升级是房价上涨的动力.住房价格上涨是生产率提高和产业结构优化的必然结果,中央政府建立"稳定房价工作责任制"的调控措施不符合市场的发展规律.政府应当重点引导产业和劳动力向中小城镇流动,促进中小城镇与大城市产业和劳动力市场的均衡发展,建设以市场自我稳定为目标的长效机制.     

我国精炼铜行业现状及发展趋势浅析

综述了近几年我国铜冶炼行业的生产、分布、贸易及供需平衡情况;阐述了国内产能规模在40万t以上的大型精炼铜生产商情况及发展动态;分析了过去10年中国精铜的价格走势及主要影响因素,对未来一段时期内的铜冶炼行业发展及价格趋势进行了初步预判,指出中短期内,我国铜冶炼行业将始终处于供大于求的态势,原料对外依存度提高、环保要求日趋严格、完全成本上涨等将成为制约我国铜冶炼行业发展的主要因素,预计未来一段时期内铜价将继续保持震荡走低的态势.