Projects per year
The hidden nature of causality is a puzzling, yet critical notion for effective decision-making. Financial markets are characterized by fluctuating interdependencies which seldom give rise to emergent phenomena such as bubbles or crashes. In this paper, we propose a method based on symbolic dynamics, which probes beneath the surface of abstract causality and unveils the nature of causal interactions. Our method allows distinction between positive and negative interdependencies as well as a hybrid form that we refer to as "dark causality." We propose an algorithm which is validated by models of a priori defined causal interaction. Then, we test our method on asset pairs and on a network of sovereign credit default swaps (CDS). Our findings suggest that dark causality dominates the sovereign CDS network, indicating interdependencies which require caution from an investor's perspective.
|Number of pages||6|
|Journal||Proceedings of the National Academy of Sciences of the United States of America|
|Publication status||Published - 1 Jan 2019|
- Complex systems
- Financial markets
- Pairs trading
- Pattern causality
- Sovereign CDS networks
- 1 Active
EPSRC and ESRC Centre for Doctoral Training in Quantification and Management of Risk & Uncertainty in Complex Systems & Environments.
Ferson, S., Pantelous, A. & Patelli, E.
1/10/14 → 31/03/23