On the Three Demons in Causality in Finance: Time Resolution, Nonstationarity, and Latent Factors

TL;DR

This paper explores three fundamental issues in financial time series—time resolution mismatch, nonstationarity, and unobserved causal factors—using a causal perspective to offer systematic solutions and new insights.

Contribution

It introduces a causal framework to address time resolution, nonstationarity, and latent factors in financial data, providing systematic solutions and foundational understanding.

Findings

Reexamines issues through causality perspective

Proposes systematic solutions for each issue

Lays groundwork for future research in financial causality

Abstract

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.