Supplier concentration and analyst forecast bias

This study examines the relationship between analyst forecast dispersion or accuracy and supplier concentration of listed firms in China from 2008 to 2019.Our findings suggest that higher supplier concentration is associated with lower analyst forecast dispersion,which can be attributed to the increased attention from analysts.Moreover,this effect is more pronounced when firms have less bargaining power and higher institutional ownership,indicating a greater reliance on the supply chain.Our study highlights the importance of disclosing supply chain information,which provides insights beyond those of traditional financial information.

Analyst Coverage,Forecasting Bias,and Corporate Innovation:Evidence from China

Due to information asymmetry and strategic innovation,firms often encounter challenges related to insufficient driving forces and low-quality innovation outcomes.Analysts always act as information intermediaries who help foster the advancement of corporate innovation activities and the conversion of innovation output.This study examines the impact of analyst coverage and forecasting bias on corporate innovation,employing data from China A-shared listed firms spanning the period 2007 to 2019.We measure corporate innovation from two perspectives:Input and output.Specifically,we use the ratio of research and development(R&D)expenditure to sales as a proxy for the innovation input and the number of patent citations excluding self-citations to measure innovation output.We find that analyst coverage promotes corporate innovation,which is consistent with the“bright”side of analyst coverage.However,the positive effect of analyst coverage hinges on effectively transmitting and disclosing accurate information to investors in the capital market.Based on this,analysts'forecasting bias includes forecasting dispersion and optimism bias.We find evidence that an increase in analysts'forecast dispersion leads to a decrease in corporate innovation quality.Moreover,this paper presents a novel approach by employing the regression discontinuity method to examine the effect of analyst optimistic bias on firm innovation.The empirical findings reveal that overly optimistic forecasts by analysts exacerbate innovation quality.These analyses enrich the research on analyst coverage and corporate innovation,providing an empirical basis for improving the capital market with the help of analysts.

基于有偏小波网络的非线性时间序列分析

针对小波网络计算过程中出现大量冗余的特点,提出一种有偏小波网络模型。该模型在网络中添加一个偏倚层,通过自适应调整参数,增加自由度,减少计算冗余,同时采用基于多分辨率的初始化框架,加快了收敛速度,提高了计算精度。仿真计算表明,有偏小波网络能够反映非线性时间序列的内在特性,得到较好的径流预报结果,是一种有效的非线性建模方法。

特质正念对初中生学业情绪预测偏差的影响

基于真实考试和实验室模拟情境,考察特质正念对初中生学业情绪预测偏差的影响及其机制。结果表明:(1)学业领域存在情绪预测偏差;(2)特质正念影响情绪预测偏差,特质正念水平高的初中生情绪预测偏差相对更小,反之则更大;(3)注意聚焦在特质正念影响情绪预测偏差中存在中介作用。本研究初步提出正念的“扩大−联结”解释模型,推进了学业领域情绪预测的研究,具有良好的生态学效度和切实的教育实践价值。

基于有偏最小最大概率回归的短期负荷预测

针对电力负荷的一些特性,提出了使用非线性数据分类学习机的理论来解决短期负荷预测问题。利用有偏最小最大概率机进行数据学习分类,对采集到的信息进行分类、特征提取,形成归一的数据类型;用得到的分类数据作为有偏最小最大概率回归模型的输入进行训练预测。该方法通过核函数将输入向量从低维空间映射到高维空间,在高维空间实现了基于高阶统计信息的负荷影响因数的特征提取,既全面考虑了影响负荷预测的历史时间序列、气象等各种因素,又避免了由于输入变量过多而导致模型结构复杂、训练时间长等不足。计算实例表明,文中提出的方法用于短期负荷预测,其预测精度较高,且训练时间较短,方法可行且有效。

Impact of GNSS radio occultation bending angle data assimilation in YH4DVAR system

Global Navigation Satellite System （GNSS） radio occultation measurements have been assimilated into the four- dimensional variational data assimilation system （YH4DVAR） using a one-dimensional bending angle operator （GBAO） as a new type of observation. For the sake of verifying the impact of GNSS radio occultation （RO） measurements to the data assimilation system, three experiments have been conducted. The statistical results of the analysis error experiment and forecast skill experiment show that the GNSS RO measurements have an impact on the analysis system. The typhoon forecast experiment shows the impact on the important weather process. They all have a positive impact on the weather forecast. Lastly, we look forward to future work on the observation system simulation experiment （OSSE） to investigate the impact of GNSS RO measurements as a function of observation number, which is an effective method to estimate the saturation of the observation number.

凯恩斯选美竞赛与分析师预测偏差行为——基于高阶预期的研究视角

现实中,分析师一方面难以坚持已见,往往随行就市改变自己之前给出的预测数字,即所谓的"变脸行为";另一方面常常盲从因袭,呈现出明显的羊群特征。本文在凯恩斯经典的选美竞赛理论框架下对此展开讨论,提供有别于已有研究的新解释,以期拓展我们对分析师预测偏差行为根源的认识。基于2004-2010年中国A股上市公司的数据,本文研究发现:(1)分析师行为存在选美竞赛现象,他们在预测时会倚重于市场上其他参与者的平均看法(高阶预期),而这也导致了变脸行为的发生;(2)分析师选美竞赛效应与其预测趋同行为密切相关,即分析师越倚重于高阶预期,其做出勇敢预测的可能性越小,羊群特征也越明显;(3)与一般分析师相比,明星分析师对高阶预期的依赖程度有所减轻,表现出的选美竞赛效应和羊群行为特征都有所减弱。

经济政策不确定性与分析师盈余预测偏差——来自分析师行为特征与个人特质的经验证据

本文以宏观经济政策不确定性为视角,以分析师针对上市公司当年度的每股收益预测为研究对象,采用分析师个体层面数据,探寻经济政策不确定性对分析师盈余预测偏差的影响及机理,并考察分析师个人行为与特质在其中发挥的作用。研究结果表明:经济政策不确定性会显著降低分析师盈余预测精确度,使其做出悲观预测;分析师所在券商与被跟踪公司在同一省(或市)内的本地优势,以及持续三年以上跟踪同一家公司的行为,能有效缓解经济政策不确定性对分析师盈余预测质量的负面影响。上述结论在进行一系列稳健性检验与内生性检验后依然成立。本文进一步检验分析师从业资深度与行业名声的调节作用,发现分析师丰富的从业经验能有效削弱经济政策不确定性对盈余预测精确度的负面影响,分析师行业声誉则不具有调节作用。