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Ramji Balakrishnan Xin Ying Qiu Padmini Srinivasan 《European Journal of Operational Research》2010,202(3):789-801
We investigate whether narrative disclosures in 10-K and 10K-405 filings contain value-relevant information for predicting market performance. We apply text classification techniques from computer science to machine code text disclosures in a sample of 4280 filings by 1236 firms over five years. Our methodology develops a model using documents and actual performance for a training sample. This model, when applied to documents from a test set, leads to performance prediction. We find that a portfolio based on model predictions earns significantly positive size-adjusted returns, indicating that narrative disclosures contain value-relevant information. Supplementary analyses show that the text classification model captures information not contained in document-level features of clarity, tone and risk sentiment considered in prior research. However, we find that the narrative score is not providing information incremental to traditional predictors such as size, market-to-book and momentum, but rather affects investors’ use of price momentum as a factor that predicts excess returns. 相似文献
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Revenue management (RM) enhances the revenues of a company by means of demand-management decisions. An RM system must take into account the possibility that a booking may be canceled, or that a booked customer may fail to show up at the time of service (no-show). We review the Passenger Name Record data mining based cancellation rate forecasting models proposed in the literature, which mainly address the no-show case. Using a real-world dataset, we illustrate how the set of relevant variables to describe cancellation behavior is very different in different stages of the booking horizon, which not only confirms the dynamic aspect of this problem, but will also help revenue managers better understand the drivers of cancellation. Finally, we examine the performance of the state-of-the-art data mining methods when applied to Passenger Name Record based cancellation rate forecasting. 相似文献
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Given a sample of binary random vectors with i.i.d. Bernoulli(p) components, that is equal to 1 (resp. 0) with probability p (resp. 1−p), we first establish a formula for the mean of the size of the random Galois lattice built from this sample, and a more complex one for its variance. Then, noticing that closed α-frequent itemsets are in bijection with closed α-winning coalitions, we establish similar formulas for the mean and the variance of the number of closed α-frequent itemsets. This can be interesting for the study of the complexity of some data mining problems such as association rule mining, sequential pattern mining and classification. 相似文献
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电子政务系统中面向公众的个性化信息服务模型 总被引:6,自引:0,他引:6
电子政务作为Internet的主要应用领域,已受到世界各国的普遍关注。面对公众各种服务需求日趋个性化,如何打破政府职能机构的条块分割,构建一个一体化的虚拟政府,集成各类信息资源,为公众提供“一站式”的、个性化的服务,是当前电子政务理论和实践的热点课题。本文首先提出一个面向公众的“一站式”服务总体框架;其次,将个性化信息服务的概念引入到电子政务系统中,构建一个个性化信息服务模型;最后,运用数据挖掘技术对模型中的关键技术加以实现。 相似文献