Are Oil Price News Headlines Statistically and Economically Significant for Investors?

While much has been written about the effects of oil price on stock returns, surprisingly nothing is known about the effect of oil price news on stock returns. This article is a response to this research gap. For a large number of stocks on the New York Stock Exchange, the authors find that while oil price news does predict market returns it only predicts returns of some sectors and not all. They find that sorting stocks based on oil price news generates a significant return differential in the cross-section, which holds consistently across a range of models allowing for the well-known risk factors. Their findings suggest that information contained in oil price news affects stock returns.     

Improving the predictability of the oil–US stock nexus: The role of macroeconomic variables

In this study, we revisit the oil–stock nexus by accounting for the role of macroeconomic variables and testing their in-sample and out-of-sample predictive powers. We follow the approaches of Lewellen (2004) and Westerlund and Narayan (2015), which were formulated into a linear multi-predictive form by Makin et al. (2014) and Salisu et al. (2018) and a nonlinear multi-predictive model by Salisu and Isah (2018). Thereafter, we extend the multi-predictive model to account for structural breaks and asymmetries. Our analyses are conducted on aggregate and sectoral stock price indexes for the US stock market. Our proposed predictive model, which accounts for macroeconomic variables, outperforms the oil-based single-factor variant as well as the constant returns (historical average) model for both in-sample and out-of-sample forecasts. We find that it is important to account for structural breaks in our proposed predictive model, although asymmetries do not seem to improve predictability. In addition, we show that it is important to pre-test the predictors for persistence, endogeneity, and conditional heteroscedasticity, particularly when modeling with high-frequency series. Our results are robust to different forecast measures and forecast horizons and are useful for making effective hedging decisions in the US stock market.     

基金\"重仓股\"特征及可预测性研究

基于对1999-2004年我国封闭式基金重仓持有股票的收益结构特征、财务和非财务特征以及重仓股的可预测性研究,结果表明:重仓股在季度末基金持股信息披露前后的累积超常收益(CAR)分化显著,在信息披露之前[-75,-15]内有显著正的CAR,而在信息披露之后[15,75]内有显著负的CAR;重仓股具有明显的可识别特征,基金表现出一定的择股能力;重仓股具有较强的可预测性,Logit模型的预测结果总正确率达到92.9%,通过预测的股票组合可以获得显著正的CAR。     

冲击世界未来的能源问题：油价低迷走势及其对国际关系的影响

本文介绍了非政府机构美国外交关系委员会亚洲能源和安全研究项目组关于世界未来2 0年石油供应将持续保持低价的论点 ,这对世界石油供应短缺的预测提出了挑战。该项研究认为 ,这对美国对外关系政策和国家安全政策也构成了严峻的挑战     

近期汇率体制改革后股价与汇率的联动效应及其检验

在全球外部失衡的宏观背景下，伴随着中国经济体制市场化和金融深化进程的加快，股票价格同汇率波动的相关性日益增强。根据从理论层面阐释二者相互作用的潜在机制和渠道，并采用中国的数据利用协整分析，发现在汇率体制改革（2005年7月21日）之后，二者的波动存在稳定的协整关系和双向的因果关系。因此，应理顺二者的互动机制需要推进各方面的综合改革，理顺这两个核心变量的互动机制，保持经济高效和健康发展。     

股票市场能量体系研究

本文借鉴物理学研究物体运动规律的思想,提出以成交量为基础的标的资产交易速度定义。根据近代物理学相对论质速关系及质能方程的数学模型,提出以价格为基础的标的资产惯性价格以及其动量和能量假说。在此基础上,本文推导出股票市场量能方程,并结合金融市场的动量现象以及动量生命周期假说,构建了股票市场的资产动量和能量体系框架。通过对30只不同股本股票的能量谱进行实证研究,发现当股票能量值大于某一常数时,随后的一段时间里股价将会出现较大的变化,用此能量值可以揭示股票价格是处于稳态还是非稳态。研究30只股票的资产动量与能量之间的数量关系,发现要达到同一能级,大盘股需要较大的动量,而小盘股需要较小的动量。     

Stock options and managerial optimal contracts

Summary. In this paper we are concerned with the performance of stock option contracts in the provision of managerial incentives. In our simple framework, we restrict the space of contracts available to the principal to those conformed by a fixed payment and a call option on the firms stock. As compared to the fixed payment and the option grant, we find that the strike price plays an intermediate role in the provision of insurance and incentives. We also develop some methods for the calibration of a standard principal-agent model based upon observed CEO earnings schedules and the volatility of the firms value in the stock market. These methods are useful to address some important issues such as the performance of stock option contracts, the degree of risk aversion compatible with current earnings profiles and the sensitivity of compensation to changes in firms characteristics.Received: 9 April 2003, Revised: 13 September 2004, JEL Classification Numbers: C6, D83. Correspondence to: Manuel S. SantosWe have benefitted from helpful discussions with Marco Celentani, Hector Chade, Alejandro Manelli and Ed Schlee. We are especially grateful to an anonymous referee for very detailed comments.     

Growth and inflation forecasts for Germany a panel-based assessment of accuracy and efficiency

We analyse forecasts of professional forecasters for Germany regarding the time span from 1970 to 2004. This novel panel data set renders it possible to assess the accuracy and efficiency of growth and inflation forecasts more efficiently than in previous studies. We argue that the forecasts are, on average, unbiased and weakly—but not strongly—efficient. Using model confidence sets suggested by Hansen et al. (2004), we find that, besides the effect of diverging forecasting dates, no other substantial differences in forecasting quality among forecasters exist. Nevertheless, on the basis of a direction-of-change analysis we argue that it is not always advisable to listen to the majority of forecasters.

信息不对称、机构投资者与股价波动率——基于扩展CAPM的理论与实证分析

针对现有文献对于机构投资者与股价波动率研究结果的差异,我们认为不管是羊群效应模型,还是Fama-MacBeth截面回归方法,均由于无法考虑二者之间的相关性问题而使股价波动率的估计有所偏误。因此,基于李勇、王满仓等（2010）所提出的扩展CAPM,本文将影响股价波动率的因素定义为机构投资者的逆向选择效应和道德风险效应,从而可以将羊群效应模型和Fama-MacBeth截面回归方法统一到相同的框架来分析股价波动率的影响因素。在此基础上,本文运用2005年1月至2009年12月的相关数据,选择反映机构投资者逆向选择效应和道德风险效应的相应指标,利用固定效应模型和TSLS模型等方法对上述结论进行实证检验,并给出了相应的政策建议。     

Comparing linear and nonlinear forecasts for stock returns

We compare the out-of-sample performance of monthly returns forecasts for two indices, namely the Dow Jones (DJ) and the Financial Times (FT) indices. A linear and a nonlinear artificial neural network (ANN) model are used to generate the out-of-sample competing forecasts for monthly returns. Stationary transformations of dividends and trading volume are considered as fundamental explanatory variables in the linear model and the input variables in the ANN model. The comparison of out-of-sample forecasts is done on the basis of forecast accuracy, using the Diebold and Mariano test [J. Bus. Econ. Stat. 13 (1995) 253.], and forecast encompassing, using the Clements and Hendry approach [J. Forecast. 5 (1998) 559.]. The results suggest that the out-of-sample ANN forecasts are significantly more accurate than linear forecasts of both indices. Furthermore, the ANN forecasts can explain the forecast errors of the linear model for both indices, while the linear model cannot explain the forecast errors of the ANN in either of the two indices. Overall, the results indicate that the inclusion of nonlinear terms in the relation between stock returns and fundamentals is important in out-of-sample forecasting. This conclusion is consistent with the view that the relation between stock returns and fundamentals is nonlinear.     

特征价格模型的发展应用研究

特征价格模型因为其完美的理论思想而成为国际上普遍使用的分析异质品价格和特征关系的主要方法.本文通过对国外核心期刊上一百五十二篇特征价格法相关文献的检阅,梳理了国内外特征价格模型及指数编制的研究现状,对特征价格模型的功能进行了总结性定位,认为特征价格模型的功能主要在于:异质品价格指数的编制,异质品价格预测、价值评估或产品定价,异质品价格影响因素分析,非市场因素的经济效应的检验及对传统经济学模型的改进五方面.文章最后以住宅为例,归纳总结了特征价格法在研究应用中存在的主要问题:一是市场细分;二是特征变量选择和量化;三是模型形式选择;四是模型估计方法的研究;五是指数编制中的问题.这些研究对象为未来特征价格的研究提供了可行参考.     

A Social-Psychological Perspective on Herding in Stock Markets

A social-psychological perspective conceives of herding in stock markets as informative social influence resulting from heuristic or systematic information processing. In three laboratory experiments employing undergraduates we apply this perspective to investigate factors that prevent herd influence that would lead to inaccurate predictions of stock prices. In Experiment 1, we show that an economic reward for making the same predictions as the herd increases the influence of a majority but not the influence of a minority, and that an individual economic reward for making accurate predictions reduces the influence of the majority. In Experiment 2, we show a reduced influence of a majority herd's inaccurate predictions when requiring assessments of the accuracy of the majority herd´s predictions as compared to requiring judgments of their consistency. Experiment 3 shows that a lower volatility of stock prices reduces the influence of a majority herd´s inaccurate predictions.     

Long-run waves or short-run fluctuations – what establishes the correlation between oil and food prices?

The strong correlation between food prices and energy prices has gained much attention in the public debate. In this article, we focus on the so-called excess co-movement, which is the correlation between crude oil price and the prices of food commodities after controlling for economic activity. We use a frequency domain Granger causality test to analyse short-run and long-run relationships between crude oil prices and prices of food commodities. For important biofuel inputs like maize, soybeans, rapeseed and EU sugar, we find evidence for long-run Granger causality in particular for the period after 2007. This supports the hypothesis that the increasing biofuel production creates the link between the prices of crude oil and food commodities. However, we also find short-run Granger causality for various food commodities. This result is more in line with herd behaviour or speculation in commodity markets.     

Profitability and supply price in the US domestic oil industry: implications for the political economy of oil in the twenty-first century

In May 2001, the US Government's National Energy Policy DevelopmentGroup proposed to increase investment in domestic oil resourcesand to diversify further the sourcing of US oil imports by increasingproduction in new petroleum provinces. The paper argues thatboth strands of this policy are dependent upon a third, unstated,objective—to ensure that OPEC retains sufficient marketpower to prevent the sort of collapse in world oil prices thatoccurred in 1998–99. The consequences of that collapse,when the real price of US oil fell to its lowest level in 53years, are explored. Finally, it is argued that the outcomeof the crisis was a rapprochement between OPEC and the US. Itis suggested that the consensus between the US and OPEC as tothe desired range within which the world oil price should moveis likely to survive any temporary political disturbances.     

Do Chinese executives reward for luck?

This paper examines the sensitivity of executive compensation to luck based on Chinese listed companies. To identify the causal effect, we rely on companies’ market performances driven by exogenous oil prices. We document a positive relationship between executive compensation and market performance driven by oil prices, which support the story of pay for luck. Moreover, by introducing a natural experiment China in 2015, i.e., the policy of “CEO compensation limit” in state-owned firms, we show that the shock of CEO compensation limit significantly weakens the effect of pay-for-luck. We further show that there is asymmetry in pay for luck. Specifically, when oil prices rise, executive compensation is more sensitive to good luck. In addition, the sensitivity of executives to pay-for-luck is more pronounced in firms with state-owned, higher equity concentration, and related party transaction.