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Results appear as propositions, with proofs in the appendix and fuller versions in an Internet Appendix. Comparative statics and dynamics are shown in figures whose captions state parameter values and time units.",156 "units_stated_in_notes": false,157 "standard_errors_description": "none"158 },159 "figures": {160 "uncertainty_shown": "no"161 },162 "conclusion": {163 "bounded_claims": false,164 "policy_implications": false,165 "open_questions": false,166 "restates_contribution": true167 },168 "hedging": {169 "level": "low",170 "typical_devices": [171 "first to my knowledge",172 "explicit acknowledgment that the model is stylized, with listed limitations in the extensions section",173 "conditional comparative-statics phrasing (holding price variability constant)"174 ]175 },176 "claim_evidence": [177 {178 "claim": "More frequent news raises the adverse selection cost of limit orders, which lowers market depth.",179 "evidence_type": "equation_or_proof",180 "evidence_ref": "Section II; Appendix proofs; Figure 5"181 },182 {183 "claim": "News arrival causes order flow and book imbalances and a volume spike, giving a positive covariance between volatility and volume.",184 "evidence_type": "figure",185 "evidence_ref": "Figure 6; Section III.E-F"186 },187 {188 "claim": "Holding unconditional price variability fixed, news frequency reduces the variability-volume covariance.",189 "evidence_type": "figure",190 "evidence_ref": "Figure 5; Section III.F"191 },192 {193 "claim": "Higher news frequency shortens the transition phase and raises the trades' share of order outflow.",194 "evidence_type": "figure",195 "evidence_ref": "Figure 5; Sections III.C-D"196 }197 ],198 "structural_summary": "A theory paper. The introduction motivates the question with electronic limit order books and the winner's curse that unscheduled news creates. It then sketches the equilibrium mechanism across several paragraphs and closes with a contribution claim and literature positioning relative to DGP and earlier limit order models. The body sets up a model in a Poisson framework and solves the equilibrium phases backward (steady state, convergence, transition phase). It then derives cross-sectional and time-series empirical predictions through comparative statics in news frequency, discusses extensions and limitations, and gives a short summary conclusion. Proofs are in the appendix, with fuller versions in an Internet Appendix.",199 "writing_profile_keywords": [200 "equilibrium model",201 "limit order book",202 "comparative statics",203 "testable predictions",204 "mechanism-driven intro",205 "proofs in appendix",206 "stylized model caveats"207 ],208 "confidence": 0.85,209 "notes": "The empirical implications section contains model-derived predictions, not data analysis. 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