Machine learning for financial transaction classification across companies using character-level word embeddings of text fields

An important initial step in accounting is mapping financial transfers to the corresponding accounts. We devised machine-learning-based systems that automate this process. They use word embeddings with character-level features to process transaction texts. When considering 473 companies independently, our approach achieved an average top-1 accuracy of 80.50%, outperforming baselines that exclude the transaction texts or rely on a lexical bag-of-words text representation. We extended the approach to generalizes across companies and even across different corporate sectors. After standardization of the account structures and careful feature engineering, a single classifier trained on 44 companies from 28 sectors achieved a test accuracy of more than 80%. When trained on 43 companies and tested on the remaining one, the system achieved an average performance of 64.62%. This rate increased to nearly 70% when considering only the largest sector.     

Financial scandals: a historical overview

I examine the incidence of fraud from c.1720 to 2009 and relate it to the occurrence of significant financial scandals. Focusing on the UK, and US prior to Enron, and using a detailed dataset of significant events and news content, underpinned by examination of specific watershed scandals, the paper highlights the regulatory response to scandals and the implications for accounting and financial reporting. The evidence reveals the incidence of fraud and financial scandal to be historically contingent and skewed towards certain sectors, particularly banking and finance, facilitated by complex group structures and international capital mobility, and mediated by managerial incentives and ownership concentration. Financial reporting and auditing can mitigate fraud opportunities in all sectors and businesses without complex group structures, and the accounting profession achieved some success in this respect up to the mid-1970s. Since then, the profession has been increasingly challenged by, and to some degree implicated in, the development of interconnected and international business networks, which, combined with wider financial deregulation, has led to a resurgence of fraud and financial scandal not previously experienced since the mid-nineteenth century.     

Cross-border exchanges and volatility forecasting

We test for the performance of a series of volatility forecasting models (GARCH 1,1; EGARCH 1,1; CGARCH) in the context of several indices from the two oldest cross-border exchanges (Euronext; OMX). Our findings overall indicate that the EGARCH (1,1) model outperforms the other two, both before and after the outbreak of the global financial crisis. Controlling for the presence of feedback traders, the accuracy of the EGARCH (1,1) model is not affected, something further confirmed for both the pre and post crisis periods. Overall, ARCH effects can be found in the Euronext and OMX indices, with our results further indicating the presence of significant positive feedback trading in several of our tests.     

对齐齐哈尔市奶牛产业可持续发展的思考与建议

齐齐哈尔是农业大市,有发展奶牛产业的极大优势,奶牛产业化工作成绩突出,但与发达国家和地区相比,还存在许多不足,因此,做大做强齐齐哈尔市的奶牛产业还有很多事情要做.     

公司业绩与财务杠杆

本文从实证角度分析了我国上市公司的财务杠杆对公司业绩的影响。结果表明,往年财务杠杆和当年财务杠杆对当年公司业绩的影响截然相反。财务杠杆对公司的息税后收益和息税前收益均有影响。长期负债率和长期借款率对公司业绩的影响分别比同年的流动负债率和短期借款率对公司业     

美国调节区域经济差异的财政措施及启示

美国的地理位置和历史文化决定了美国区域经济的发展严重不平衡.本文分析了美国政府对落后地区经济的财政调节措施,这对我国在市场经济条件下调节区域经济,推进西部大开发,一定具有深刻的启示.     

高校财务实行内部会计控制的几点思考

分析了高校实施内部会计控制的背景和存在的主要问题,表述了对高校内部会计控制的方法和关键控制点,提出了解决目前高校内部会计控制存在问题的解决方法和主要对策.