In mathematics, a time series is a series of data points indexed in time order. Most commonly, a time series is a sequence taken at successive equally spaced points in time. Thus it is a sequence of discrete-time data. Examples of time series are heights of ocean tides, counts of sunspots, and the daily closing value of the Dow Jones Industrial Average.
Collaborative filtering (CF) is a technique used by recommender systems. Collaborative filtering has two senses, a narrow one and a more general one.
In corporate finance, capital structure refers to the mix of various forms of external funds, known as capital, used to finance a business. It consists of shareholders' equity, debt, and preferred stock, and is detailed in the company's balance sheet. The larger the debt component is in relation to the other sources of capital, the greater financial leverage the firm is said to have. Too much debt can increase the risk of the company and reduce its financial flexibility, which at some point creates concern among investors and results in a greater cost of capital. Company management is responsible for establishing a capital structure for the corporation that makes optimal use of financial leverage and holds the cost of capital as low as possible.
Articles in economics journals are usually classified according to JEL classification codes, which derive from the Journal of Economic Literature. The JEL is published quarterly by the American Economic Association (AEA) and contains survey articles and information on recently published books and dissertations. The AEA maintains EconLit, a searchable data base of citations for articles, books, reviews, dissertations, and working papers classified by JEL codes for the years from 1969. A recent addition to EconLit is indexing of economics journal articles from 1886 to 1968 parallel to the print series Index of Economic Articles.
Vasant G. Honavar is an Indian-American computer scientist, and artificial intelligence, machine learning, big data, data science, causal inference, knowledge representation, bioinformatics and health informatics researcher and professor.
Predictive analytics is a form of business analytics applying machine learning to generate a predictive model for certain business applications. As such, it encompasses a variety of statistical techniques from predictive modeling and machine learning that analyze current and historical facts to make predictions about future or otherwise unknown events. It represents a major subset of machine learning applications; in some contexts, it is synonymous with machine learning.
Sentiment analysis is the use of natural language processing, text analysis, computational linguistics, and biometrics to systematically identify, extract, quantify, and study affective states and subjective information. Sentiment analysis is widely applied to voice of the customer materials such as reviews and survey responses, online and social media, and healthcare materials for applications that range from marketing to customer service to clinical medicine. With the rise of deep language models, such as RoBERTa, also more difficult data domains can be analyzed, e.g., news texts where authors typically express their opinion/sentiment less explicitly.
In data analysis, anomaly detection is generally understood to be the identification of rare items, events or observations which deviate significantly from the majority of the data and do not conform to a well defined notion of normal behavior. Such examples may arouse suspicions of being generated by a different mechanism, or appear inconsistent with the remainder of that set of data.
The trade-off theory of capital structure is the idea that a company chooses how much debt finance and how much equity finance to use by balancing the costs and benefits. The classical version of the hypothesis goes back to Kraus and Litzenberger who considered a balance between the dead-weight costs of bankruptcy and the tax saving benefits of debt. Often agency costs are also included in the balance. This theory is often set up as a competitor theory to the pecking order theory of capital structure. A review of the trade-off theory and its supporting evidence is provided by Ai, Frank, and Sanati.
The Z-score formula for predicting bankruptcy was published in 1968 by Edward I. Altman, who was, at the time, an Assistant Professor of Finance at New York University. The formula may be used to predict the probability that a firm will go into bankruptcy within two years. Z-scores are used to predict corporate defaults and an easy-to-calculate control measure for the financial distress status of companies in academic studies. The Z-score uses multiple corporate income and balance sheet values to measure the financial health of a company.
Bankruptcy prediction is the art of predicting bankruptcy and various measures of financial distress of public firms. It is a vast area of finance and accounting research. The importance of the area is due in part to the relevance for creditors and investors in evaluating the likelihood that a firm may go bankrupt.
Richard Andreas Werner is a German banking and development economist who is a university professor at University of Winchester.
ELKI is a data mining software framework developed for use in research and teaching. It was originally at the database systems research unit of Professor Hans-Peter Kriegel at the Ludwig Maximilian University of Munich, Germany, and now continued at the Technical University of Dortmund, Germany. It aims at allowing the development and evaluation of advanced data mining algorithms and their interaction with database index structures.
Colm Kearney (1954–2018) was an Irish economist and academic, who was dean of the Faculty of Business and Economics at Monash University, Melbourne, Australia, until 2017, shortly before his death on 28 March 2018.
Software analytics is the analytics specific to the domain of software systems taking into account source code, static and dynamic characteristics as well as related processes of their development and evolution. It aims at describing, monitoring, predicting, and improving the efficiency and effectiveness of software engineering throughout the software lifecycle, in particular during software development and software maintenance. The data collection is typically done by mining software repositories, but can also be achieved by collecting user actions or production data.
Social media mining is the process of obtaining big data from user-generated content on social media sites and mobile apps in order to extract actionable patterns, form conclusions about users, and act upon the information, often for the purpose of advertising to users or conducting research. The term is an analogy to the resource extraction process of mining for rare minerals. Resource extraction mining requires mining companies to shift through vast quantities of raw ore to find the precious minerals; likewise, social media mining requires human data analysts and automated software programs to shift through massive amounts of raw social media data in order to discern patterns and trends relating to social media usage, online behaviours, sharing of content, connections between individuals, online buying behaviour, and more. These patterns and trends are of interest to companies, governments and not-for-profit organizations, as these organizations can use these patterns and trends to design their strategies or introduce new programs, new products, processes or services.
Yutaka Tsujinaka is a professor of political science and the Graduate School of Humanities and Social Sciences at the University of Tsukuba. He is now teaching at the College of Social Sciences and the doctoral program in International and Advanced Japanese Studies. He is also the president of Japan Political Science Association, a member of the International Association of Universities (2012–2016), the director of Internationalization Subcommittee of IAU (2013–), the executive assistant to the President at University of Tsukuba (2013–) and the director of Institute for Comparative Research in Human and Social Sciences (ICR) (2014–). Youji Inaba professor of economy at Nippon University said in a newspaper column that Professor Tsujinaka talks in friendly Kansai dialect and always gives everyone warm smile as if he has "Tender-Heated DNA" in his body. (Nikkei: July 8, 2015)
Michael Timothy Dugan is an accounting academic, currently serving as Professor of Accounting at Augusta University. He is noted for research contributions in the area of predictive ability and market-based archival research. Peers external to his home institution have recognized Dugan for teaching excellence.
Networked-loan, also known as networked-guarantee loan, is a popular economic phenomenon in some Asia countries. In these countries, if the borrowers do not meet the loan criteria of commercial banks, they are allowed to find guarantors to back their applicants. If the borrowers default on their loans, their guarantors take the legal obligation to repay the loan, which is called guaranteed-loan, or networked-guarantee loan. The guarantee interdependencies can be naturally represented as networks, where each node represents a firm, and each directed edge represents the guarantee relationship between the two corresponding firms.
Ahmed Rashad Abdel-khalik is an American scholar who was born in Egypt. He is the V. K. Zimmerman Professor of International Accounting, Professor of Accountancy, and Director of the V. K. Zimmerman Center for International Education and Research in Accounting at University of Illinois at Urbana–Champaign.
