Financial Modelling with Forward-looking Information

This book focuses on modelling financial information flows and information-based asset pricing framework. After introducing the fundamental properties of the framework, it presents a short information-theoretic perspective with a view to quantifying the information content of financial signals, and links the present framework with the literature on asymmetric information and market microstructure by means of a dynamic, bipartite, heterogeneous agent network. Numerical and explicit analyses shed light on the effects of differential information and information acquisition on the allocation of profit and loss as well as the pace of fundamental price discovery. The dynamic programming method is used to seek an optimal strategy for utilizing superior information. Lastly, the book features an implementation of the present framework using real-world financial data.

Presents a novel, intuitive and more fundamental approach to financial asset pricing Includes numerical and explicit analyses as well as graphical illustrations to facilitate understanding Explores the implications for market efficiency, high-frequency trading, and market shut-downs Features implementation on the basis of real-world financial data

Autorentext
Dr. Nadi Serhan Aydn, FRM, is a graduate of the Institute of Applied Mathematics at Middle East Technical University and a lecturer at TED University in Ankara, Turkey. Formerly, he was a research fellow at Imperial College London and served as a senior research economist in an intergovernmental organization. His research interest lies in financial mathematics, risk management, stochastic & digital filtering, market microstructure, and frequency-domain analysis.

Inhalt
Introduction.- The Signal-based Framework.- A Signal-based Heterogeneous Agent Network.- Putting Signal-based Model to Work.- Conclusion.