On the Three Demons in Causality in Finance: Time Resolution, Nonstationarity, and Latent Factors
This work addresses critical challenges in finance for researchers and practitioners, though it appears incremental as it builds on existing causal frameworks without introducing a new paradigm.
The paper tackles three fundamental issues in financial time series data—time resolution mismatch, nonstationarity, and latent causal factors—by reexamining them from a causal perspective, providing systematic solutions that aim to serve as a foundation for future research.
Financial data is generally time series in essence and thus suffers from three fundamental issues: the mismatch in time resolution, the time-varying property of the distribution - nonstationarity, and causal factors that are important but unknown/unobserved. In this paper, we follow a causal perspective to systematically look into these three demons in finance. Specifically, we reexamine these issues in the context of causality, which gives rise to a novel and inspiring understanding of how the issues can be addressed. Following this perspective, we provide systematic solutions to these problems, which hopefully would serve as a foundation for future research in the area.