This paper provides evidence that network complexity limits investors' ability to process non-local information, through the lens of return cross predictability. Using firm-to-firm citation networks, we find that the non-local indirectly-linked firms can well predict the return of the focal...

This article addresses decision-making parameters in machine-learning algorithms, and more specifically, critiques the mathematical explanation for the Hipster Effect (a group of evolutionary processes), and discusses implications for portfolio management and corporate bankruptcy prediction (two...

The growing complexity of many real world problems is one of the biggest challenges of our time. The area of international finance is one prominent example where decision making is often fraud to mistakes, and tasks such as forecasting, trading and hedging exchange rates seem to be too difficult...