Hierarchical Fuzzy Case Based Reasoning with Multi-criteria Decision Making for Financial Applications Shanu Sushmita and Santanu Chaudhury Electrical Engineering Department, Indian Institute of Technology Delhi, New Delhi, India - 110016 {schaudhury,shanusushmita}@gmail.com Abstract. This paper presents a framework for using a case-based reasoning system for stock analysis in financial market. The unique aspect of this paper is the use of a hierarchical structure for case representation. The system further incorporates a multi-criteria decision-making algorithm which furnishes the most suitable solution with respect to the current market scenario. Two important as- pects of financial market are addressed in this paper: stock evaluation and investment planning. CBR and multi-criteria when used in conjunction offer an effective tool for evaluating goodness of a particular stock based on certain fac- tors. The system also suggests a suitable investment plan based on the current assets of a particular investor. Stock evaluation maps to a flat case structure, but investment planning offers a scenario more suited for structuring the case into successive detailed layers of information related to different facets. This natu- rally leads to a hierarchical case structure. 1 Introduction In this paper, we propose an application framework involving a fuzzy case based reasoning system with a hierarchical case structure and a multi-criteria decision mak- ing. So far, case structures used in majority of CBR applications have had a flat case structure which, to some extent, manages to incorporate example applications that can be mapped to flat case structures. Many of the complex real world problems require a framework capable of handling non-summarized information where one component’s value is dependent on several other relevant factors. Investment planning is an example application having non-summarised information, which requires classification of case features, based on different aspects, into successive layers. This segregation of informa- tion into layers leads to a hierarchical case structure. Also, combining hierarchical CBR with multi-criteria is all together a new approach towards decision making systems tai- lored for applications having a dynamic and complex nature. Past did witness some of the evolving research work, which looked into the financial areas and suggested how CBR can be efficiently used as a tool to produce a suitable de- cision making system. Some of the work like [1] addressed the movement of the stock market and its prediction. [2] proposed the daily financial condition indicator (DFCI) monitoring financial market built on CBR, [3], in their work proposed a new learning A. Ghosh, R.K. De, and S.K. Pal (Eds.): PReMI 2007, LNCS 4815, pp. 226–234, 2007. c  Springer-Verlag Berlin Heidelberg 2007