Discovering Bayesian Market Views for Intelligent Asset Allocation? Frank Z. Xing1, Erik Cambria1, Lorenzo Malandri2, and Carlo Vercellis2 1 School of Computer Science and Engineering, Nanyang Technological University 2 Data Mining and Optimization Research Group, Politecnico di Milano {zxing001,cambria}@ntu.edu.sg {lorenzo.malandri,carlo.vercellis}@polimi.it Abstract. Along with the advance of opinion mining techniques, public mood has been found to be a key element for stock market prediction. However, how market participants’ behavior is affected by public mood has been rarely discussed. Consequently, there has been little progress in leveraging public mood for the asset allocation problem, which is pre- ferred in a trusted and interpretable way. In order to address the issue of incorporating public mood analyzed from social media, we propose to formalize public mood into market views, because market views can be integrated into the modern portfolio theory. In our fra
