A parsimonious model to forecast financial distress,based on audit evidence

This paper provides evidence that audit reports convey relevant evidence for inferring the existence of underlying, unrevealed, financial imbalances. Unlike previous works, which studied US listed-firms bankruptcy, our research deals with Spanish non-financial SMEs under financial stress. Our results indicate that the audit of distressed SMEs has several distinctive features: higher auditor rotation, more qualified reports, and non-compliance with deadlines to approve and file the annual financial statements. We use this evidence to build and test a parsimonious and reliable forecast model. Several implications for auditors’ independence, information quality, and failure forecast are discussed.     

2种风电功率预测模型的比较

采用ARMA模型对风电功率进行了预测,并由ARMA方程推导出卡尔曼滤波状态方程和测量方程,从而将预测问题转化到状态空间,并利用卡尔曼滤波法预测了风电功率,比较了2种方法的预测效果。实例表明,卡尔曼滤波法能够提高风电功率的预测精度,并在一定程度上解决了时间序列分析法的预测时延问题,对电力系统的安全、稳定、经济运行以及提高运行效益具有重要意义。     

2030年世界能源与电力发展展望

在系统分析世界能源与电力发展最新动态的基础上,对2030年世界及主要国家的能源与电力发展趋势以及能源与电力投资增长的趋势进行了分析预测。该分析预测结果可为研究和制定我国的能源及电力发展战略提供参考。     

上市公司盈利预测信息自愿性披露实证研究--来自1090家中国上市公司中期报告的证据

文章以探寻上市公司自愿性信息披露的行为特征和影响因素为研究目标，选取1090家2004年深沪上市公司为样本，对其中期盈利预测信息披露进行了实证检验。结果表明：（1）与国外研究结论相似，我国公司盈利预测自愿性披露水平与公司规模、公司盈利能力正相关，这说明盈利预测自愿披露正成为我国优质公司消除资本市场“柠檬”问题、展示自身价值的有效手段；（2）与国外研究结论相悖，我国公司盈利预测自愿性披露水平与公司股权集中度正相关，原因是我国股权集中度高的公司多是规模大、盈利能力强的国有控股公司和民营控股公司，这些公司披露盈利预测的动机较强。     

关于我国建立节水高效农业的对策和建议

21世纪我国农业水资源供需矛盾进一步加剧,农业水资源严重短缺,要解决我国粮食安全问题,走可持续发展之路,必须采取强有效的措施走节水高效之路,从而才能从根本上缓解农业水资源的短缺状况。首先论述了我国农业水资源的现状及存在的主要问题——节水设备不配套,灌溉水利用率低;然后,对其前景进行了预测;最后,重点提出了节水的对策和建议,指出发展农业节水不仅是技术问题,更主要的是管理体制和政策问题。通过这些对策的实施以期能对我国经济及社会发展有所助益。     

面向售后服务的汽车备品需求预测研究

根据面向售后服务的汽车备品需求特点的差异,本文将其分为专用配件和通用配件并分别选用不同的预测模型.对专用配件,采用基于时间序列相关的线性回归模型,并运用加权最小二乘法（WLS）估计参数.对通用配件,选用GM（1,1）模型进行需求预测.     

耕地保有量分析和保护对策研究——以山东青岛市为例

在社会经济快速发展的形势下,保持耕地面积基本稳定,质量有所提高,是保障我国粮食安全、社会安全、生态安全和经济安全的根本所在。该文以山东青岛市为例,探讨了确定规划期耕地保有量的方法,进行了基于粮食生产能力的耕地需求量预测;结合国民经济发展及各用地部门需求,考虑规划期间耕地减少和耕地增加的各种可能性,估算了耕地的可供给量,最终确定了2010年和2020年的耕地保有量;然后从行政、法律、经济和科技4个方面提出了耕地保护对策。     

On the Predictability of the Stock Market Volatility: Does History Matter?

This study compares the performance of the ISD, the GARCH (1,1) , the historical volatility estimates and of two lagged trading volume measures for predicting the Swiss Stock Market Index's (SMI) volatility. The ISD has a superior daily informational content than the GARCH (1,1) estimate and retains unbiased but decreasing explanatory power over up to 20 days ahead horizons. Mean and spread daily volume measures play a significant correcting role when forecasting stock market volatility over daily and longer intervals respectively and clearly dominate the GARCH (1,1) forecasts. Their significance emphasises heterogeneous horizon traders' influence on the SMI volatility time series properties     

Futures Trading Activity and Commodity Cash Price Volatility

Abstract:   This paper examines the lead‐lag relationship between futures trading activity (volume and open interest) and cash price volatility for major agricultural commodities. Granger causality tests and generalized forecast error variance decompositions show that an unexpected increase in futures trading volume unidirectionally causes an increase in cash price volatility for most commodities. Likewise, there is a weak causal feedback between open interest and cash price volatility. These findings are generally consistent with the destabilizing effect of futures trading on agricultural commodity markets.     

Information flows within and across sectors in Chinese stock markets

We examine the patterns of information flows within and across sectors of the two Chinese stock exchanges in Shanghai and Shenzhen during 1994–2001. Using the generalized forecast error variance decomposition, we find a high degree of interdependence, indicating that the sectors are highly integrated and sector prices reflect information from other sectors. Industry is the most influential sector in both exchanges, while Finance in Shenzhen is the least integrated with other sectors. Implications of the findings for investors and policymakers are also discussed.