The majority of electronic data today is in textual form. Financial data such as articles in the Wall Street Journal are written as texts. These electronic documents contain a wealth of information but require human interpretation. For financial analysis, rapid up-to-date information is critical. Most software tools currently require data which are better structured than text (such as data in r...

Quantitative tools have been widely adopted in order to extract the massive information from a variety of financial data. Mathematics, statistics and computers algorithms have never been so important to financial practitioners in history. Investment banks develop equilibrium models to evaluate financial instruments; mutual funds applied time series to identify the risks in their portfolio; and ...

In recent times, Hadoop based on the MapReduce model has gained considerable attention because the features of the data preprocessing techniques are not timeconsuming and are suitable for processing large-scale data. In particular, MapReduce is emerging as an important programming model for developing distributed dataprocessing applications such as web indexing, data mining, log file analysis, ...

Financial engineering and electrical engineering are seemingly different areas that share strong underlying connections. Both areas rely on statistical analysis and modeling of systems; either modeling the financial markets or modeling, say, wireless communication channels. Having a model of reality allows us to make predictions and to optimize the strategies. It is as important to optimize our...

eXtensible Business Reporting Language (XBRL) has the potential to influence users’ processing of financial information and their judgments and decisions. XBRL is an eXtensible Markup Language (XML)-based language, developed specifically for financial reporting. XBRL, as a search-facilitating technology, contributes to direct searches and simultaneous presentation of related financial statement...

In finance and healthcare, event processing systems handle sensitive data on behalf of many clients. Guaranteeing information security in such systems is challenging because of their strict performance requirements in terms of high event throughput and low processing latency. We describe DEFCON, an event processing system that enforces constraints on event flows between event processing units. ...

In finance and healthcare, event processing systems handle sensitive data on behalf of many clients. Guaranteeing information security in such systems is challenging because of their strict performance requirements in terms of high event throughput and low processing latency. We describe DEFCON, an event processing system that enforces constraints on event flows between event processing units. ...

In the last decade, high profile financial frauds committed by large companies in both developed and developing countries were discovered and reported. This study compares the performance of five popular statistical and machine learning models in detecting financial statement fraud. The research objects are companies which experienced both fraudulent and non-fraudulent financial statements betw...