News-Implied Linkages and Local Dependency in the Equity Market
34 Pages Posted: 19 Apr 2021 Last revised: 3 May 2021
Date Written: April 16, 2021
This paper studies a heterogeneous coefficient spatial factor model that separately addresses both common factor risks (strong cross-sectional dependence) and local dependency (weak cross-sectional dependence) in the equity returns. For a high-dimensional panel of equity returns, it is challenging to measure firm-to-firm connectivity. We use extensive business news to construct firms’ links via which local shocks transmit, and we use those news-implied linkages as a proxy for the connectivity among firms. We document a considerable degree of local dependency amongS&P500 stocks. From the asset pricing perspective, we derive the theoretical implications of no asymptotic arbitrage for the heterogeneous spatial factor model. Empirically, we show that adding spatial interactions to factor models significantly reduces mispricing and estimation errors. We also show that our news-implied linkages provide a comprehensive and integrated proxy for firm-to-firm connectivity, and it out-performs other existing networks in the literature.
Keywords: Spatial asset pricing model, weak and strong cross-sectional dependence, local dependency, networks, textual analysis, big data, large heterogeneous panel
JEL Classification: C33, C58, G10, G12
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