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1{2 "validation_errors": [],3 "repairs": [4  "dropped figures.convention_notes_absent"5 ],6 "doc_id": "jof_12685",7 "ontology_version": "1.0",8 "prompt_version": "1.0",9 "model": "claude-opus-5-5",10 "effort": "medium",11 "annotated_at": "2026-11-03T23:26:28+00:00",12 "source_sha256": "334f7d010f7f5af26c2405d2d81140f1c08a24989b39e6015f3a6937a71b35c5",13 "parser": "pymupdf-jof-heuristics-1.3",14 "payload_chars": 25219,15 "usage": {16  "input": 8311,17  "output": 2007,18  "cache_read": 0,19  "cache_write": 396820 },21 "cost_usd": 0.093224,22 "request_id": "req_011CggrofhQR8XspmamsZo1N",23 "annotation": {24  "genre": "empirical",25  "subfield": "behavioral_finance",26  "subfield_secondary": "asset_pricing",27  "primary_method": "reduced_form_regression",28  "identification": {29   "estimand": "Effect of the previous trading day's salient (large-firm value-weighted) earnings surprise on the return reaction to a firm's own earnings announcement, holding its own surprise constant",30   "strategy": "Regressions of announcement returns on prior-day salient surprise, exploiting earnings dates scheduled weeks in advance as quasi-exogenous ordering; timing tests, unconditional return predictability, reversals and a trading strategy rule out information transmission",31   "key_assumptions": [32    "Announcement dates are set in advance and are uncorrelated with the fundamentals of the firm relative to prior-day surprises",33    "Prior-day surprises do not carry information relevant to the next-day announcer that rational markets would price",34    "Absence of strategic timing of announcements"35   ],36   "threats_addressed": [37    "information transmission from earlier announcements",38    "expectational errors versus perceptual errors",39    "risk changes, trading frictions and capital constraints",40    "strategic timing of earnings announcements",41    "bias or staleness of analyst forecasts"42   ],43   "causal_language_strength": 4,44   "uses_causal_claim": true45  },46  "abstract_moves": {47   "question": {48    "present": true,49    "sentence_index": 050   },51   "gap": {52    "present": true,53    "sentence_index": 154   },55   "method": {56    "present": true,57    "sentence_index": 358   },59   "results": {60    "present": true,61    "sentence_index": 262   },63   "magnitude": {64    "present": false,65    "sentence_index": -166   },67   "contribution": {68    "present": true,69    "sentence_index": 170   }71  },72  "introduction": {73   "moves": [74    {75     "paragraph_index": 0,76     "move": "other"77    },78    {79     "paragraph_index": 7,80     "move": "motivation"81    },82    {83     "paragraph_index": 8,84     "move": "mechanism_or_theory_sketch"85    },86    {87     "paragraph_index": 9,88     "move": "preview_of_results"89    },90    {91     "paragraph_index": 10,92     "move": "preview_of_results"93    },94    {95     "paragraph_index": 11,96     "move": "identification_defense"97    },98    {99     "paragraph_index": 12,100     "move": "preview_of_results"101    },102    {103     "paragraph_index": 13,104     "move": "contribution_statement"105    },106    {107     "paragraph_index": 13,108     "move": "related_literature_positioning"109    }110   ],111   "contribution_paragraph_index": 13,112   "contribution_types": [113    "new_evidence"114   ],115   "roadmap_present": false,116   "literature_positioning_location": "inside_introduction"117  },118  "section_roles": [119   {120    "idx": 0,121    "role": "introduction"122   },123   {124    "idx": 1,125    "role": "data"126   },127   {128    "idx": 2,129    "role": "results"130   },131   {132    "idx": 3,133    "role": "robustness"134   },135   {136    "idx": 4,137    "role": "robustness"138   },139   {140    "idx": 5,141    "role": "results"142   },143   {144    "idx": 6,145    "role": "conclusion"146   }147  ],148  "results_presentation": {149   "economic_significance_discussed": true,150   "statistical_significance_language": "stars_and_tstats",151   "magnitude_statements_in_intro": true152  },153  "robustness": {154   "location": "main_text_section",155   "types": [156    "alternative_measure",157    "subsample",158    "alternative_specification",159    "falsification",160    "placebo"161   ]162  },163  "tables": {164   "convention_notes": "Regression tables report standard errors in parentheses, clustered by date, with stars marking 10/5/1% significance. Notes define variable construction and return windows and refer back to Table II for definitions.",165   "units_stated_in_notes": true,166   "standard_errors_description": "clustered"167  },168  "figures": {169   "uncertainty_shown": "unclear"170  },171  "conclusion": {172   "bounded_claims": true,173   "policy_implications": true,174   "open_questions": true,175   "restates_contribution": true176  },177  "hedging": {178   "level": "moderate",179   "typical_devices": [180    "consistent with",181    "suggestive evidence",182    "potentially",183    "likely",184    "we leave for future work"185   ]186  },187  "claim_evidence": [188   {189    "claim": "Return reaction to today's announcement falls as the prior-day salient surprise rises, controlling for own surprise",190    "evidence_type": "figure",191    "evidence_ref": "Figure 1; Table II"192   },193   {194    "claim": "The effect is a level shift rather than an interaction with own surprise",195    "evidence_type": "table",196    "evidence_ref": "Table III; Figure 3"197   },198   {199    "claim": "Distortions reverse over roughly 50 trading days",200    "evidence_type": "table",201    "evidence_ref": "Table IV"202   },203   {204    "claim": "Long-short strategy on prior-day surprise earns about 15% per year among large firms",205    "evidence_type": "table",206    "evidence_ref": "Table V; Figure 4"207   },208   {209    "claim": "Prior-day surprise does not predict next-day announcer surprises, against information transmission",210    "evidence_type": "table",211    "evidence_ref": "Table VI"212   },213   {214    "claim": "Results are not driven by risk, trading frictions or strategic timing",215    "evidence_type": "table",216    "evidence_ref": "Tables VII, VIII"217   },218   {219    "claim": "Effect is concentrated at t-1 and holds within the day; heterogeneity exists by size and industry",220    "evidence_type": "table",221    "evidence_ref": "Tables X, XI, XII"222   }223  ],224  "structural_summary": "Opens with a classical epigraph and lab or popular examples of contrast effects, then sketches the prediction for earnings announcements. It previews the main figure and its magnitude and defends against information-transmission explanations through timing, reversals and a trading strategy. Supplementary timing and heterogeneity results follow, then contributions positioned against limited-attention and expectational-error literatures. The body proceeds through data, baseline results, a long section on alternative explanations, robustness, further exploration and a conclusion with broader implications.",225  "writing_profile_keywords": [226   "behavioral bias in markets",227   "lab-to-field",228   "alternative explanations section",229   "trading strategy",230   "earnings announcements",231   "epigraph opening"232  ],233  "confidence": 0.8,234  "notes": "Introduction paragraphs 0-6 are fragments of the epigraph and are treated as a single 'other' move. Paragraph 7 is truncated. No explicit roadmap is visible in the excerpts."235 },236 "deterministic_checks": {237  "roadmap_regex": false,238  "contribution_regex_in_intro": true,239  "magnitude_in_abstract": false,240  "abstract_n_sentences": 5,241  "intro_n_paragraphs": 14,242  "intro_n_words": 1315,243  "causal_words_in_abstract": 0,244  "hedge_words_in_abstract": 0,245  "stars_mentioned": true,246  "clustered_se_mentioned": true,247  "internet_appendix_mentioned": false,248  "section_roles_rule": {249   "0": "introduction",250   "1": "data",251   "2": "results",252   "3": "robustness",253   "4": "robustness",254   "5": "other",255   "6": "conclusion"256  }257 },258 "schema_valid": true,259 "code_version": "87c73cd-dirty"260}
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