Stochastic Discount Factors with Cross-Asset Spillovers

2026-02-24

AI Summary

This study proposes a unified framework that explicitly models the intrinsic relationships among firm-level predictive signals, cross-asset information spillovers, and the stochastic discount factor (SDF). By jointly estimating predictive signals and spillover effects through Sharpe ratio maximization, the approach yields an economically interpretable SDF that not only identifies feature importance but also reveals the directional nature of predictive influences across assets. Innovatively integrating cross-asset information spillovers with firm characteristics into SDF estimation, the analysis uncovers that large-cap, low-turnover stocks act as net information transmitters, thereby enabling the construction of a well-structured information network. Out-of-sample tests demonstrate that the resulting SDF significantly outperforms both autoregressive and expected-return benchmark models across diverse portfolios and market regimes.

Technology Category

• Machine Learning: Information Theory
• Natural Language Processing: Information Extraction
• Game Theory and Economic Paradigms: Imperfect Information

Application Category

• Social Networks and Social Media: Influence propagation, information diffusion, and the prediction on networks
• Graph Algorithms and Modeling for the Web: Representation, reconstruction, and subgraph or motif discovery in Web-related graphs
• Web Mining and Content Analysis: Content-based information diffusion

Abstract

This paper develops a unified framework that links firm-level predictive signals, cross-asset spillovers, and the stochastic discount factor (SDF). Signals and spillovers are jointly estimated by maximizing the Sharpe ratio, yielding an interpretable SDF that both ranks characteristic relevance and uncovers the direction of predictive influence across assets. Out-of-sample, the SDF consistently outperforms self-predictive and expected-return benchmarks across investment universes and market states. The inferred information network highlights large, low-turnover firms as net transmitters. The framework offers a clear, economically grounded view of the informational architecture underlying cross-sectional return dynamics.

Problem

• Stochastic Discount Factor
• Cross-Asset Spillovers
• Predictive Signals
• Return Dynamics
• Information Network

Innovation

• Stochastic Discount Factor
• Cross-Asset Spillovers
• Predictive Signals
• Sharpe Ratio Maximization
• Information Network