Towards Automated Optimal Equity Portfolios Discovery in a Financial Knowledge Management System

We propose a knowledge discovery and knowledge management process for equity management institutions. We realize the process with a financial knowledge management system, FKMS, that is a system platform being able to convert various sources of data into the data warehouse, to retrieve data cubes based on different power users’ commands for subsequent valuation modeling or data mining applications. We then introduced a data mining solution for equity portfolio construction using the simulated annealing algorithm. Two data sets consist of small stocks ranging from 11/86 to 10/91 and from 6/93 to 5/96 are used. The corresponding rates of return of Russell 2000 index are collected as benchmarks for evaluation based on the Sharpe ratios and the turnover ratios. The result of the simulated annealing algorithm has shown to outperform the market index as well as the gradient maximization method.