Special issue on intelligent information systems for financial engineering

摘要

Financial engineering is a multidisciplinary research area that draws from a wide range of quantitative analysis disciplines (e.g. statistics, data mining, machine learning, artificial intelligence, neurocomputing, fuzzy and genetic methods, etc.) to optimize and facilitate various kinds of financial decisions related to, e.g. risk and investment management, financial planning, trading, hedging, pricing and asset valuation, and fraud detection. Undoubtedly, the introduction of several recent international financial and accounting standards (such as Basel II, Sarbanes-Oxley, IFRS) is having a significant impact on this field. For example, by allowing banks and financial institutions to use their internal risk assessment models as inputs to the minimum regulatory capital calculations, the Basel II framework is providing financial institutions with additional incentives to develop new or further refine existing financial engineering models. Hence, there has been a growing interest throughout the financial world in research on techniques to support the implementation of these guidelines.