Complex Information Environments,Asset Pricing And Financial Decision Making

The increasing volumes of big data reflecting various aspects of investor activities represent a vital new opportunity for financial economist to address fundamental questions about the potential causes and pricing mechanism.The descriptive account of the media industry recognizes that media outlets do not just report plain facts.The collision of big data and media bias gives rise to “Complex Information Environments”,which is promising to revolutionize the processes of asset pricing and financial decision-making.This dissertation mainly consists of two parts.The first part is the empirical works on asset pricing.Generally speaking,the results show that information is spread more efficiently under the complex information environments.To characterize the financial decision making behavior as well as to interpret the findings in the first part,an agent-based computational financial(ACF)model is proposed.By populating the ACF model with various proportions of media bias(both ideology and spin)and introducing the competition mechanism,the numerical simulation shows that media competition is closed linked with the degree of dependency of agent's financial decision making based on media information.And both the media bias and media competition have a significant impact on asset pricing.This theoretical model explains the findings in the first part;meanwhile the empirical findings uphold the simulation results.