, a stock correlation network is built to find the intracommunity and inter-community relationship. Design …/methodology/approach: The stock correlation network is built taking the vertices as stocks and edges as correlation coefficients of logarithm … after transferring the network into un-weighted with different thresholds. Findings: The result of the network community …

network attention proxy, network degree, provides a robust and significant cross-sectional predictability of the monthly stock …

level shocks through the network. Using earnings surprises as a proxy for firm shocks, we find that our model's aggregation … is significantly correlated with the aggregate market return. Also, the network structure estimated by our model can …

structure of price interdependencies across stocks. For correct empirical network determination of such dynamic liquidity price … bootstrap procedure. We document the importance of LOB liquidity network spillovers even for a small blue-chip NASDAQ portfolio. …