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1{2 "validation_errors": [],3 "doc_id": "jof_12705",4 "ontology_version": "1.0",5 "prompt_version": "1.0",6 "model": "claude-opus-5-5",7 "effort": "medium",8 "annotated_at": "2026-11-03T23:03:56+00:00",9 "source_sha256": "7b321cc72bce45285903db0b5a312635229141a7ab9922f2200b0a1aecb358b6",10 "parser": "pymupdf-jof-heuristics-1.3",11 "payload_chars": 19907,12 "usage": {13  "input": 6793,14  "output": 2217,15  "cache_read": 3968,16  "cache_write": 017 },18 "cost_usd": 0.072306,19 "request_id": "req_011Cggq5yonQUcEbrsPLyUME",20 "annotation": {21  "genre": "mixed_theory_empirical",22  "subfield": "asset_pricing",23  "subfield_secondary": "credit derivatives / rare disasters",24  "primary_method": "calibration_simulation",25  "identification": {26   "estimand": "Model-implied CDX and CDX tranche spreads (levels and time series) compared with observed spreads",27   "strategy": "Calibrate an equilibrium rare-disaster model to consumption data and the equity premium. Extract latent state variables from index option implied volatilities. Compare predicted tranche spreads with data and run comparative statics.",28   "key_assumptions": [29    "Representative agent with complete markets in an endowment economy",30    "Time-varying disaster probability governed by square-root processes",31    "Firm cash flows load on aggregate disasters, sector shocks and idiosyncratic shocks",32    "Preference and consumption parameters taken from prior studies without reference to CDX data"33   ],34   "threats_addressed": [35    "Model is not fit directly to CDX data",36    "Disaster risk is linked tightly to the equity premium, so a low-equity-premium recalibration fails",37    "Removing idiosyncratic risk or sector shocks changes the fit",38    "Physical default probabilities are matched to Moody's data"39   ],40   "causal_language_strength": 2,41   "uses_causal_claim": false42  },43  "abstract_moves": {44   "question": {45    "present": true,46    "sentence_index": 047   },48   "gap": {49    "present": false,50    "sentence_index": -151   },52   "method": {53    "present": true,54    "sentence_index": 355   },56   "results": {57    "present": true,58    "sentence_index": 359   },60   "magnitude": {61    "present": false,62    "sentence_index": -163   },64   "contribution": {65    "present": false,66    "sentence_index": -167   }68  },69  "introduction": {70   "moves": [71    {72     "paragraph_index": 0,73     "move": "motivation"74    },75    {76     "paragraph_index": 1,77     "move": "motivation"78    },79    {80     "paragraph_index": 1,81     "move": "literature_gap"82    },83    {84     "paragraph_index": 1,85     "move": "preview_of_approach"86    },87    {88     "paragraph_index": 2,89     "move": "related_literature_positioning"90    },91    {92     "paragraph_index": 2,93     "move": "tension_or_puzzle"94    },95    {96     "paragraph_index": 3,97     "move": "mechanism_or_theory_sketch"98    },99    {100     "paragraph_index": 3,101     "move": "preview_of_results"102    },103    {104     "paragraph_index": 4,105     "move": "preview_of_results"106    },107    {108     "paragraph_index": 4,109     "move": "contribution_statement"110    },111    {112     "paragraph_index": 4,113     "move": "policy_or_broader_implication"114    }115   ],116   "contribution_paragraph_index": 4,117   "contribution_types": [118    "new_theory_or_model",119    "new_evidence",120    "resolution_of_puzzle"121   ],122   "roadmap_present": false,123   "literature_positioning_location": "inside_introduction"124  },125  "section_roles": [126   {127    "idx": 0,128    "role": "introduction"129   },130   {131    "idx": 1,132    "role": "theory"133   },134   {135    "idx": 2,136    "role": "data"137   },138   {139    "idx": 3,140    "role": "empirical_design"141   },142   {143    "idx": 4,144    "role": "results"145   },146   {147    "idx": 5,148    "role": "results"149   },150   {151    "idx": 6,152    "role": "conclusion"153   }154  ],155  "results_presentation": {156   "economic_significance_discussed": true,157   "statistical_significance_language": "unclear",158   "magnitude_statements_in_intro": true159  },160  "robustness": {161   "location": "within_results",162   "types": [163    "sensitivity_to_parameters",164    "alternative_specification"165   ]166  },167  "tables": {168   "convention_notes": "Tables report calibrated parameters and data-versus-model moments. Simulated small-sample percentiles (5th, 50th, 95th) are shown alongside population moments. Tranche spreads are given in basis points per year, with the equity tranche reported as an upfront payment. Pre-crisis and crisis subsamples are reported separately.",169   "units_stated_in_notes": true,170   "standard_errors_description": "none"171  },172  "figures": {173   "uncertainty_shown": "unclear"174  },175  "conclusion": {176   "bounded_claims": true,177   "policy_implications": false,178   "open_questions": true,179   "restates_contribution": true180  },181  "hedging": {182   "level": "moderate",183   "typical_devices": [184    "framing as 'can explain' or 'is possible to account for'",185    "'at least some of the pricing behavior'",186    "explicit acknowledgment of model failures as challenges for future work"187   ]188  },189  "claim_evidence": [190   {191    "claim": "Calibrated disaster model matches average five- and three-year CDX tranche spreads before and during the crisis",192    "evidence_type": "table",193    "evidence_ref": "Tables V, VI, VII"194   },195   {196    "claim": "Model reproduces the time series of tranche spreads using option-implied state variables",197    "evidence_type": "figure",198    "evidence_ref": "Figures 5, 6"199   },200   {201    "claim": "Lower equity premium calibration produces senior tranche spreads far below the data",202    "evidence_type": "figure",203    "evidence_ref": "Figure 9"204   },205   {206    "claim": "Model matches physical default probabilities across horizons",207    "evidence_type": "figure",208    "evidence_ref": "Figure 1"209   },210   {211    "claim": "Model cannot reconcile low implied-volatility autocorrelation with a persistent price-dividend ratio",212    "evidence_type": "figure",213    "evidence_ref": "Figure 10, Table IV"214   },215   {216    "claim": "Model predicts counterfactually low long-term real bond yields",217    "evidence_type": "figure",218    "evidence_ref": "Figure 11"219   },220   {221    "claim": "Model matches equity premium and bill rate moments",222    "evidence_type": "table",223    "evidence_ref": "Table II"224   }225  ],226  "structural_summary": "The paper motivates the question with dramatic crisis-era senior tranche pricing and a gap: few quantitative models link structured products to fundamentals. It then positions itself against no-arbitrage models, whose limitation is incomplete markets, and turns to an equilibrium model. Next it sketches the mechanism tying the equity premium to tranche prices. A theory section presents a continuous-time disaster model, followed by data, calibration (including option-based extraction of state variables), and an evaluation of averages, time series and comparative statics. It then examines implications for options, the price-dividend ratio and bonds, honestly reporting where the model fails. The conclusion restates the fit and lists remaining puzzles.",227  "writing_profile_keywords": [228   "rare disasters",229   "equilibrium calibration",230   "model-versus-data comparison",231   "credit derivatives",232   "comparative statics",233   "acknowledged model limitations",234   "2008 crisis"235  ],236  "confidence": 0.82,237  "notes": "Calibration and evaluation sections are labeled 'other' in the source and were mapped here to empirical_design and results. No regression-based inference appears. Uncertainty is reported via simulated percentiles in Table II. The introduction excerpt is truncated, so a roadmap may exist but is not visible."238 },239 "deterministic_checks": {240  "roadmap_regex": false,241  "contribution_regex_in_intro": false,242  "magnitude_in_abstract": false,243  "abstract_n_sentences": 4,244  "intro_n_paragraphs": 5,245  "intro_n_words": 869,246  "causal_words_in_abstract": 0,247  "hedge_words_in_abstract": 0,248  "stars_mentioned": false,249  "clustered_se_mentioned": false,250  "internet_appendix_mentioned": false,251  "section_roles_rule": {252   "0": "introduction",253   "1": "theory",254   "2": "data",255   "3": "other",256   "4": "other",257   "5": "other",258   "6": "conclusion"259  }260 },261 "schema_valid": true,262 "code_version": "feb6c9e-dirty"263}
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