1{2 "validation_errors": [],3 "doc_id": "jof_12784",4 "ontology_version": "1.0",5 "prompt_version": "1.0",6 "model": "claude-opus-5-5",7 "effort": "medium",8 "annotated_at": "2026-11-03T23:09:30+00:00",9 "source_sha256": "50340a5bb4f1fffa5d370d9ba2d5fb3990c373d87b8146486189d717a67ed9d9",10 "parser": "pymupdf-jof-heuristics-1.3",11 "payload_chars": 12790,12 "usage": {13 "input": 4705,14 "output": 1858,15 "cache_read": 3968,16 "cache_write": 017 },18 "cost_usd": 0.056774,19 "request_id": "req_011CggqWrPF5w93NWWWPqFq8",20 "annotation": {21 "genre": "replication_or_correction",22 "subfield": "asset_pricing",23 "subfield_secondary": "financial_econometrics",24 "primary_method": "calibration_simulation",25 "identification": {26 "estimand": "Bias and coverage of FDR estimates of the proportions of zero-, negative- and positive-alpha mutual funds, compared with known true proportions",27 "strategy": "Monte Carlo simulation of fund returns from a factor model with data-informed DGPs for alpha; the FDR estimator is applied to each sample and its estimates are compared with the true proportions",28 "key_assumptions": [29 "Simulated DGPs (alpha distributions, sample sizes, error correlation) are representative of real fund data",30 "Linear factor model of returns as in BSW"31 ],32 "threats_addressed": [33 "Discrete alpha distribution with point masses far from zero",34 "Sample size, both number of funds and observations per fund",35 "Unbalanced panel",36 "Cross-sectional error correlation"37 ],38 "causal_language_strength": 2,39 "uses_causal_claim": false40 },41 "abstract_moves": {42 "question": {43 "present": true,44 "sentence_index": 045 },46 "gap": {47 "present": false,48 "sentence_index": -149 },50 "method": {51 "present": true,52 "sentence_index": 153 },54 "results": {55 "present": true,56 "sentence_index": 157 },58 "magnitude": {59 "present": true,60 "sentence_index": 261 },62 "contribution": {63 "present": true,64 "sentence_index": 465 }66 },67 "introduction": {68 "moves": [69 {70 "paragraph_index": 0,71 "move": "motivation"72 },73 {74 "paragraph_index": 0,75 "move": "related_literature_positioning"76 },77 {78 "paragraph_index": 0,79 "move": "preview_of_approach"80 },81 {82 "paragraph_index": 0,83 "move": "preview_of_results"84 },85 {86 "paragraph_index": 1,87 "move": "mechanism_or_theory_sketch"88 },89 {90 "paragraph_index": 2,91 "move": "tension_or_puzzle"92 },93 {94 "paragraph_index": 3,95 "move": "mechanism_or_theory_sketch"96 },97 {98 "paragraph_index": 3,99 "move": "preview_of_approach"100 }101 ],102 "contribution_paragraph_index": 0,103 "contribution_types": [104 "replication_or_correction",105 "new_evidence"106 ],107 "roadmap_present": false,108 "literature_positioning_location": "inside_introduction"109 },110 "section_roles": [111 {112 "idx": 0,113 "role": "introduction"114 },115 {116 "idx": 1,117 "role": "theory"118 },119 {120 "idx": 2,121 "role": "results"122 },123 {124 "idx": 3,125 "role": "conclusion"126 }127 ],128 "results_presentation": {129 "economic_significance_discussed": true,130 "statistical_significance_language": "confidence_intervals",131 "magnitude_statements_in_intro": true132 },133 "robustness": {134 "location": "within_results",135 "types": [136 "sensitivity_to_parameters",137 "alternative_specification"138 ]139 },140 "tables": {141 "convention_notes": "Each table reports simulated FDR estimates against true proportions. Rows vary the true group proportions and columns vary the alpha distance or dispersion. Alphas are given as annualized percentages. Results are averaged across 1,000 simulations, and one table reports actual coverage of 95% confidence intervals.",142 "units_stated_in_notes": true,143 "standard_errors_description": "none"144 },145 "figures": {146 "uncertainty_shown": "unclear"147 },148 "conclusion": {149 "bounded_claims": true,150 "policy_implications": false,151 "open_questions": false,152 "restates_contribution": true153 },154 "hedging": {155 "level": "moderate",156 "typical_devices": [157 "'can materially change' phrasing",158 "'potentially unrealistic' qualifiers",159 "'under certain conditions' scoping",160 "'question applicability' framing"161 ]162 },163 "claim_evidence": [164 {165 "claim": "The FDR estimator overestimates the proportion of zero-alpha funds and underestimates nonzero-alpha funds under data-informed DGPs",166 "evidence_type": "table",167 "evidence_ref": "Tables I, III"168 },169 {170 "claim": "FDR 95% confidence intervals almost never contain the true proportions",171 "evidence_type": "table",172 "evidence_ref": "Table II"173 },174 {175 "claim": "Accuracy does not improve with more funds; bias stems from low signal-to-noise ratio and low test power",176 "evidence_type": "table",177 "evidence_ref": "Table IV"178 },179 {180 "claim": "Low-power tests spread alternative p-values across [0,1], so the null proportion is overestimated",181 "evidence_type": "figure",182 "evidence_ref": "Figure 1"183 },184 {185 "claim": "Bias persists in unbalanced panels and with correlated errors",186 "evidence_type": "table",187 "evidence_ref": "Tables V, VI"188 },189 {190 "claim": "FDR and 'no-luck' approaches compared across true alphas and proportions",191 "evidence_type": "figure",192 "evidence_ref": "Figure 2"193 }194 ],195 "structural_summary": "Short comment on an influential prior method. The introduction summarizes the original findings and their wide adoption, then explains intuitively how the method's assumption of high test power can fail in fund data, and previews the expanded simulations. Section I sets out the FDR mechanics. Section II runs simulations that vary the alpha distribution, sample size and error correlation, documenting bias and poor interval coverage. The conclusion attributes the original method's accuracy to unrealistic simulation assumptions and questions its use in low-power settings.",196 "writing_profile_keywords": [197 "comment",198 "simulation-based critique",199 "statistical power",200 "false discovery rate",201 "mutual fund alpha",202 "replication"203 ],204 "confidence": 0.85,205 "notes": "Labelled as a corrigendum/replication-type comment. No empirical identification; the evidence is entirely Monte Carlo. The original BSW results are cited from that paper rather than re-estimated."206 },207 "deterministic_checks": {208 "roadmap_regex": false,209 "contribution_regex_in_intro": true,210 "magnitude_in_abstract": true,211 "abstract_n_sentences": 6,212 "intro_n_paragraphs": 4,213 "intro_n_words": 599,214 "causal_words_in_abstract": 0,215 "hedge_words_in_abstract": 0,216 "stars_mentioned": false,217 "clustered_se_mentioned": false,218 "internet_appendix_mentioned": false,219 "section_roles_rule": {220 "0": "introduction",221 "1": "other",222 "2": "other",223 "3": "conclusion"224 }225 },226 "schema_valid": true,227 "code_version": "87c73cd-dirty"228}