Object oriented analysis and programming for a working capital management system

Paper presented at the IEEE/IAFE 1995 computational intelligence for financial engineering, CIFEr, New York, NY.The main purpose of this paper is to present an Object Oriented Analysis (OOA) of a firm and its accounting and financial environments for the implementation of a working capital management system. The object oriented analysis has been designed so that it can be used by different types and sizes of companies, (e.g., industrial, commercial or service). This versatility is a consequence of an important feature of the object oriented paradigm: the reusability of code. This OOA includes firm’s regular operations as well as tools and reports used in the management of working capital such as cash flows and estimated balance sheets. In order to demonstrate the functionality of the OOA, we discuss parts of the analysis that we have implemented successfully in the C++ object oriented programming language

Artificial intelligence techniques for modeling financial analysis

Tese (doutorado) - Universidade Federal de Santa Catarina, Centro Tecnologico, Programa de Pós-Graduação em Engenharia de Produção, Florianópolis, 1996Although monitoring financial health of small firms is decisive to their success, these firms commonly present difficulty when analysing their operational financial condition. In order to overcome this fact, the present thesis proposes a financial knowledge representation that is capable of proposing alternative actions whenever a deviation is detected. The knowledge representation developed recognizes the existence of different phases of analysis: one that looks for some clues about possible financial problems and another one that focuses on with more detail the potential problems detected by the prior phase.The vagueness present in many semantic rules was implemented by using the Theory of Fuzzy Sets. The uncertainty about the future behavior of some key financial variables is incorporated by means of managers perceptions about trends and events. A practical formulation of this proposal is done considering the retail bus sector

A Hybrid intelligent system for diagnosing and solving financial problems

Tese (doutorado) - Universidade Federal de Santa Catarina, Centro Tecnologico. Programa de Pós-Graduação em Engenharia de Produção2012-10-16T09:55:39

NEW ARTIFACTS FOR THE KNOWLEDGE DISCOVERY VIA DATA ANALYTICS (KDDA) PROCESS

Recently, the interest in the business application of analytics and data science has increased significantly. The popularity of data analytics and data science comes from the clear articulation of business problem solving as an end goal. To address limitations in existing literature, this dissertation provides four novel design artifacts for Knowledge Discovery via Data Analytics (KDDA). The first artifact is a Snail Shell KDDA process model that extends existing knowledge discovery process models, but addresses many existing limitations. At the top level, the KDDA Process model highlights the iterative nature of KDDA projects and adds two new phases, namely Problem Formulation and Maintenance. At the second level, generic tasks of the KDDA process model are presented in a comparative manner, highlighting the differences between the new KDDA process model and the traditional knowledge discovery process models. Two case studies are used to demonstrate how to use KDDA process model to guide real world KDDA projects. The second artifact, a methodology for theory building based on quantitative data is a novel application of KDDA process model. The methodology is evaluated using a theory building case from the public health domain. It is not only an instantiation of the Snail Shell KDDA process model, but also makes theoretical contributions to theory building. It demonstrates how analytical techniques can be used as quantitative gauges to assess important construct relationships during the formative phase of theory building. The third artifact is a data mining ontology, the DM3 ontology, to bridge the semantic gap between business users and KDDA expert and facilitate analytical model maintenance and reuse. The DM3 ontology is evaluated using both criteria-based approach and task-based approach. The fourth artifact is a decision support framework for MCDA software selection. The framework enables users choose relevant MCDA software based on a specific decision making situation (DMS). A DMS modeling framework is developed to structure the DMS based on the decision problem and the users\u27 decision preferences and. The framework is implemented into a decision support system and evaluated using application examples from the real-estate domain