Price formation in the German biodiesel supply chain: a Markov‐switching vector error‐correction modeling approach

Changing linkages between agricultural and energy markets have attracted considerable attention in research and policy discussions during recent years. As one of the largest biofuel markets worldwide, the German biodiesel market is of particular interest. It has grown rapidly since the beginning of the new millennium, with this growth being driven mainly by political interventions. Vertical price transmission channels along the biodiesel supply chain are analyzed in this study. We examine the relationship between diesel and biodiesel prices, and between rapeseed oil, soy oil, and biodiesel prices between 2002 and 2008. Due to pronounced changes in market conditions and the policy framework, a regime‐dependent Markov‐switching vector error‐correction model is used. The regimes are characterized by markedly different price adjustment behaviors. Before 2005 and from late 2007 onward, a regime characterized by the strong orientation of biodiesel prices toward diesel prices dominates. Between 2005 and 2007, biodiesel and rapeseed oil prices are mutually interdependent. Frequent switches between the regimes of the price dynamics during this period indicate a high extent of uncertainty and instability in the market.     

基于局域网的实时语音通信时延研究

在局域网中语音通信时延是影响语音质量的重要因素。为了最大限度地降低局域网中语音通信时延,提高语音质量,以采用低阶音频函数和UDP协议实现语音传输系统为基础,通过实验并分析了造成局域网中语音通信时延的主要因素,提出了在局域网中最大限度地降低实时语音通信时延的解决策略,实验数据证明,时延的分析是正确的,降低时延的策略是有效的。     

Reference Dependent Preference and Labor Supply: Evidence from China

This paper investigates the daily labor supply decisions of Hangzhou cabdrivers. We find that Hangzhou cabdrivers’ wage elasticity is significantly positive, their working decisions are largely affected by shift time, and crude proxy variables for income; hours targets can hardly explain their working behavior. Nevertheless, Hangzhou cabdrivers are still affected by reference dependent preference. Using new empirical strategies, we show that cabdrivers are more likely to continue working when wage rates are unexpectedly low and more likely to quit when wage rates are unexpectedly high.     

延期支付下部分价格折扣的变质物品订货模型

一般的延期支付库存模型将产品采购价视为固定不变的,而实际商业活动中,价格折扣是供应商促销的一种常用手段。本文在进一步考虑"数量界限"的价格折扣问题的基础上,建立了一个延期支付下部分价格折扣的变质物品经济订购批量模型,分析了两种情况下订货商的最优订货策略,并用算例进行了说明。     

基于技术进步的浙江省能源消费回弹效应研究

基于技术进步对经济增长的贡献和环境负荷分解模型,对浙江省1990年以来技术进步对GDP增长的贡献、能源消费回弹效应及能源回弹量进行实证分析。其中,对技术进步的测定采用城镇单位在岗职工工资总额和农村居民纯收入作为劳动因素,以期更合理地体现劳动对经济增长的贡献,同时对多元回归模型的多重共线性进行滞后差分变换,以期得到更为精确的实证数据。     

奇异摄动延迟积分微分方程RK方法的渐近稳定性

基于延迟积分微分方程稳定性理论,将Pouzet-Runge-Kutta方法应用于奇异摄动延迟积分微分方程,并讨论了该方法的渐近稳定性.     

The use of limited dependent variable techniques in strategy research: issues and methods

Strategy researchers are increasingly turning their attention from examining the impact of strategic choices on firm performance to examining the factors that determine strategic choices at the firm level. This shift of research orientation has meant that researchers are increasingly faced with a limited dependent variable (LDV) that takes a limited number of usually discrete values, for which LDV methods such as logit or probit are required. Despite their growing popularity, there appears to be widespread problems in the use of LDV methods. This research note complements recent studies that offer general guidelines by presenting and illustrating the practical steps needed to implement the methods essential for analyzing and interpreting the results from LDV models. Copyright © 2009 John Wiley & Sons, Ltd.     

内部控制、中期审计与年报审计延迟

年报审计延迟影响了会计信息的及时性,是衡量审计效率的重要变量;内部控制质量及中期财务报告审计是影响年报审计延迟的重要因素。以2007—2012年A股上市公司为研究对象,研究内部控制质量与中期财务报告审计对年报审计延迟的影响,并探讨了在降低年报审计延迟上,内部控制在中期审计和未进行中期审计的公司中的作用有何不同。研究表明：良好的内部控制有助于降低年报审计延迟,上市公司审计了中期财务报告也能降低年报审计延迟。在降低年报审计延迟方面,相较于中期审计的公司,中期未审计公司其内部控制质量的提高对年报审计延迟具有显著的降低作用。     

Stock return predictability of the cumulative abnormal returns around the earnings announcement date: Evidence from China

We find that cumulative abnormal returns adjusted by size, book-to-market, and momentum around the earnings announcement date (DGTW_CAR3 hereafter) significantly and positively predict stock returns in the 6-month period from May 2005 to October 2020 in the China's A-shares market. The monthly equally-weighted DGTW_CAR3 premiums are 0.47% and 0.67% after risk adjustment. Although stock price delay fails to fully account for the DGTW_CAR3 premium, we find that the DGTW_CAR3 premium is more significant for illiquid stocks and during periods with high investor sentiment. This result suggests that market inefficiency explains the DGTW_CAR3 premium. Further analysis shows that, in addition to earnings information, the optimism reflected in the management discussion and analysis section of the annual or half-year report also contributes to the DGTW_CAR3 premium. This finding implies that DGTW_CAR3 may contain new fundamental information that correlates significantly and positively with future stock performance. Finally, we find that the institutional ownership change of a stock associated with DGTW_CAR3 also significantly and positively predicts the stock's return, suggesting that institutional investors adjust their holdings according to DGTW_CAR3 and consequently influence the demand for the stock in the China's A-shares market.     

A Continuity Correction for Discrete Barrier Options

The payoff of a barrier option depends on whether or not a specified asset price, index, or rate reaches a specified level during the life of the option. Most models for pricing barrier options assume continuous monitoring of the barrier; under this assumption, the option can often be priced in closed form. Many (if not most) real contracts with barrier provisions specify discrete monitoring instants; there are essentially no formulas for pricing these options, and even numerical pricing is difficult. We show, however, that discrete barrier options can be priced with remarkable accuracy using continuous barrier formulas by applying a simple continuity correction to the barrier. The correction shifts the barrier away from the underlying by a factor of exp(bet sig sqrt dt), where bet approx 0.5826, sig is the underlying volatility, and dt is the time between monitoring instants. The correction is justified both theoretically and experimentally.