書籍詳細

書籍詳細




洋書

金融におけるエキスパート・システム

Expert Systems in Finance : Smart Financial Applications in Big Data Environments

(Banking, Money and International Finance)

Metawa, Noura (EDT)   Elhoseny, Mohamed (EDT)   Hassanien, Aboul Ella (EDT)

Taylor & Francis 2019/05
246 p. 24 cm   
装丁: Hrd    装丁について
テキストの言語: ENG    出版国: GB
ISBN: 9780367109523
KCN: 1034331268
紀伊國屋書店 選定タイトル
標準価格:¥25,212(本体 ¥22,920)   
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納期について
DDC: 332.0285
KDC: E210 金融理論
E235 経営情報
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Full Description

Throughout the industry, financial institutions seek to eliminate cumbersome authentication methods, such as PINs, passwords, and security questions, as these antiquated tactics prove increasingly weak. Thus, many organizations now aim to implement emerging technologies in an effort to validate identities with greater certainty. The near instantaneous nature of online banking, purchases, transactions, and payments puts tremendous pressure on banks to secure their operations and procedures. In order to reduce the risk of human error in financial domains, expert systems are seen to offer a great advantage in big data environments. Besides their efficiency in quantitative analysis such as profitability, banking management, and strategic financial planning, expert systems have successfully treated qualitative issues including financial analysis, investment advisories, and knowledge-based decision support systems. Due to the increase in financial applications' size, complexity, and number of components, it is no longer practical to anticipate and model all possible interactions and data processing in these applications using the traditional data processing model. The emergence of new research areas is clear evidence of the rise of new demands and requirements of modern real-life applications to be more intelligent. This book provides an exhaustive review of the roles of expert systems within the financial sector, with particular reference to big data environments. In addition, it offers a collection of high-quality research that addresses broad challenges in both theoretical and application aspects of intelligent and expert systems in finance. The book serves to aid the continued efforts of the application of intelligent systems that respond to the problem of big data processing in a smart banking and financial environment.

Table of Contents

List of figures. List of tables. List of contributors. 1 Theoretical and practical foundations of liquidity-adjusted value-at-risk (LVaR): optimization algorithms for portfolio selection and management. Mazin A. M. Al Janabi 2 Financial analysis for mobile and cloud applications. Jennifer Brodmann and Makeen Huda 3 Eye movement study of customers on video advertising marketing. Xiaolong Liu, Ruoqi Liang 4 An optimization algorithm and smart model for periodic capacitated arc routing problem considering mobile disposal sites. Erfan Babaee Tirkolaee, Ali Asghar Rahmani Hosseinabadi 5 Opinion mining analysis of e-commerce sites using fuzzy clustering with whale optimization techniques. K. Shankar, M. Ilayaraja, P. Deepalakshmi, S. Ramkumar, K. Sathesh Kumar, S. K. Lakshmanaprabu and Andino Maseleno 6 Big data text mining in the financial sector. Mirjana Pejic Bach, Zivko Krstic,, Sanja Seljan 7 CEL: citizen economic level using SAW. Andino Maseleno, K. Shankar, Prayugo Khoir, Muhammad Muslihudin 8 The investment opportunities for building smartphone applications for tourist cities in Saudi Arabia: the case of Abha City. Saeed Q. Al-Khalidi Al-Maliki and Mohammed A. Al-Ghobiri 9 An applied credit scoring model. Esther Castro, M. Kabir Hassan and Mark Rosa 10 Intelligent distributed applications in e-commerce and e-banking. Jennifer Brodmann and Phuvadon Wuthisatian 11 Feature selection-based data classification for stock price prediction using ant-miner algorithm. Saravanan Ramalingam and Pothula Sujatha 12 The value of simulations characterizing classes of symbiosis: ABCs of formulation design. K. Basaid, B. Chebli, J.N. Furze, E.H. Mayad and R. Bouharroud 13 Application of project scheduling in production process for paddy cleaning machine by using PERT & CPM techniques: case study. S. Bangphan, P.Bangphan and S. Phanphet 14 The management of deep learning algorithms to enhance momentum trading strategies during the time frame to quick detect market of smart money. Khalid Abouloula, Ali Ou-Yassine and Salah-ddine Krit 15 Pattern to build a robust trend indicator for automated trading. Khalid Abouloula, Ali Ou-Yassine and Salah-ddine Krit Index