FIRC0002-LITE-01/02/03/05/06/07/08/09/10/13 EDIT-14 (L11), ADVE-05 AI_C-04 EDIT-09 ECON-13 THEO-13 AI_C-13 ADVE-16 (L8), EDIT-04 DATA-03 (L6 inputs): DOI-verified bib additions, SPID sampling frame, IWV holdings manifest, FinData price check

references.bib: 19 entries appended (17 DOIs resolved via doi.org/Crossref incl. Eisfeldt et al. JF 2026, Hassan et al. QJE 2019,
Cao et al. RFS 2023, Hong-Lim-Stein JF 2000, Bloom et al. NBER w28999 'The Diffusion of New Technologies'; 2 self WP entries);
Xia et al. / Ofir not added (no identifier). SPID: 200 stratified mentions with source-text excerpts, no labels (AR-3 not granted).
IWV: 17 dated Wayback captures (2006-09, 2019-05..2025-08). FinData raw closes: 2,487/2,499 tickers, 98.9% within 2% of Yahoo-implied.

Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>

Simon-Pierre Boucher committed 3 days ago (Nov 5, 2026) parent f3cae18 Browse files

12 changed files +3,876 −0

modified paper/references.bib +193 −0

+   year        = {2024},
+   doi         = {10.3386/w32161}
+ }
++
++% ---- Stage D review additions (FIRC-0002, 2026-11-05): DOIs resolved through doi.org / Crossref by scripts/r3k_21_bib_crossref.py; cite from Stage E ----
++@techreport{basu2026aiexposure,
++  author = {Basu, Sakshi and Thapa, Chandra and Neupane, Biwesh and Basu, Amlan},
++  title = {{Firm-level AI Exposure: Measurement, Determinants, and Pricing Implications}},
++  year = {2026},
++  doi = {10.2139/ssrn.7575518},
++  institution = {Elsevier BV},
++  type = {Working paper},
++  note = {Elsevier BV, DOI 10.2139/ssrn.7575518}
++}
++
++@techreport{borri2026aifactor,
++  author = {Borri, Nicola and Liu, Yukun and Tsyvinski, Aleh},
++  title = {{The Cross-Section of Stock Returns and AI Exposure}},
++  year = {2026},
++  doi = {10.48550/arXiv.2606.30583},
++  institution = {arXiv},
++  type = {Working paper},
++  note = {arXiv, DOI 10.48550/arXiv.2606.30583}
++}
++
++@techreport{wulam2026genai,
++  author = {Institute for Monetary and Financial Research, Hong Kong},
++  title = {{Do Firms' Stock Prices Respond to AI-related Discussions? Evidence from Earnings Calls}},
++  year = {2026},
++  doi = {10.2139/ssrn.7482259},
++  institution = {Elsevier BV},
++  type = {Working paper},
++  note = {Elsevier BV, DOI 10.2139/ssrn.7482259}
++}
++
++@article{eisfeldt2026generative,
++  author = {EISFELDT, ANDREA L. and SCHUBERT, GREGOR and ZHANG, MIAO BEN and TASKA, BLEDI},
++  title = {{Generative AI and Firm Values}},
++  year = {2026},
++  doi = {10.1111/jofi.70089},
++  journal = {The Journal of Finance}
++}
++
++@techreport{song2026productexposure,
++  author = {Song, Tianhao},
++  title = {{What Firms Sell: Product Exposure to Generative AI *}},
++  year = {2026},
++  doi = {10.2139/ssrn.7527158},
++  institution = {Elsevier BV},
++  type = {Working paper},
++  note = {Elsevier BV, DOI 10.2139/ssrn.7527158}
++}
++
++@techreport{erdogan2026aiwashing,
++  author = {Erdogan, Sedat and Coskun Erdogan, Dilek and Li, Yanbing},
++  title = {{SEC Regulatory Intervention and Artificial Intelligence (AI) Washing: Widening the Disclosure Gap Between Transparent and Opaque Firms}},
++  year = {2026},
++  doi = {10.2139/ssrn.6749213},
++  institution = {Elsevier BV},
++  type = {Working paper},
++  note = {Elsevier BV, DOI 10.2139/ssrn.6749213}
++}
++
++@article{wang2026aiwashing,
++  author = {Wang, Shan and Wang, Yanze and Gao, Yue and Lyu, Xinran},
++  title = {{Talk is cheap, green is hard: The effect of AI-washing on corporate energy transition}},
++  year = {2026},
++  doi = {10.1016/j.iref.2026.105756},
++  journal = {International Review of Economics &amp; Finance},
++  volume = {111},
++  pages = {105756}
++}
++
++@techreport{celenymarechal2024cyber,
++  author = {Celeny, Daniel and Maréchal, Loïc},
++  title = {{Cyber risk and the cross-section of stock returns}},
++  year = {2023},
++  doi = {10.2139/ssrn.4587993},
++  institution = {Elsevier BV},
++  type = {Working paper},
++  note = {Elsevier BV, DOI 10.2139/ssrn.4587993}
++}
++
++@techreport{kearney2025cyberchatgpt,
++  author = {Kearney, Fearghal and Ma, Tren and Movaghari, Hadi and Sermpinis, Georgios},
++  title = {{Cyber Risk, ChatGPT and Firm Value}},
++  year = {2025},
++  doi = {10.2139/ssrn.5068625},
++  institution = {Elsevier BV},
++  type = {Working paper},
++  note = {Elsevier BV, DOI 10.2139/ssrn.5068625}
++}
++
++@article{hassan2019firmlevel,
++  author = {Hassan, Tarek A and Hollander, Stephan and van Lent, Laurence and Tahoun, Ahmed},
++  title = {{Firm-Level Political Risk: Measurement and Effects*}},
++  year = {2019},
++  doi = {10.1093/qje/qjz021},
++  journal = {The Quarterly Journal of Economics},
++  volume = {134},
++  number = {4},
++  pages = {2135-2202}
++}
++
++@techreport{davis2020exposures,
++  author = {Davis, Steven and Hansen, Stephen and Seminario-Amez, Cristhian},
++  title = {{Firm-Level Risk Exposures and Stock Returns in the Wake of COVID-19}},
++  year = {2020},
++  doi = {10.3386/w27867},
++  institution = {National Bureau of Economic Research},
++  type = {Working paper},
++  note = {National Bureau of Economic Research, DOI 10.3386/w27867}
++}
++
++@techreport{kim2023llmrisks,
++  author = {Kim, Alex G. and Muhn, Maximilian and Nikolaev, Valeri V.},
++  title = {{From Transcripts to Insights: Uncovering Corporate Risks Using Generative AI}},
++  year = {2023},
++  doi = {10.2139/ssrn.4593660},
++  institution = {Elsevier BV},
++  type = {Working paper},
++  note = {Elsevier BV, DOI 10.2139/ssrn.4593660}
++}
++
++@article{cao2023machinelistening,
++  author = {Cao, Sean and Jiang, Wei and Yang, Baozhong and Zhang, Alan L},
++  title = {{How to Talk When a Machine Is Listening: Corporate Disclosure in the Age of AI}},
++  year = {2023},
++  doi = {10.1093/rfs/hhad021},
++  journal = {The Review of Financial Studies},
++  volume = {36},
++  number = {9},
++  pages = {3603-3642}
++}
++
++@article{honglimstein2000,
++  author = {Hong, Harrison and Lim, Terence and Stein, Jeremy C.},
++  title = {{Bad News Travels Slowly: Size, Analyst Coverage, and the Profitability of Momentum Strategies}},
++  year = {2000},
++  doi = {10.1111/0022-1082.00206},
++  journal = {The Journal of Finance},
++  volume = {55},
++  number = {1},
++  pages = {265-295}
++}
++
++@article{yilmazkuday2026chatgpt,
++  author = {Yilmazkuday, Hakan},
++  title = {{ChatGPT and stock returns}},
++  year = {2026},
++  doi = {10.1007/s12197-026-09767-9},
++  journal = {Journal of Economics and Finance},
++  volume = {50},
++  number = {1}
++}
++
++@techreport{uqowp0001,
++  author = {Boucher, Simon-Pierre and Kammoun, Manel and Tandjambianda, Djerrycharli},
++  title = {{From Corporate Disclosures to a Russell 3000 Strategic Project Database}},
++  institution = {Universit\'e du Qu\'ebec en Outaouais, FIRC},
++  type = {UQO/FIRC Working Paper},
++  number = {0001},
++  year = {2026},
++  note = {Strategic Project Intelligence Database (SPID); EDGAR Research Database}
++}
++
++@techreport{kammoun2026v11,
++  author = {Kammoun, Manel and Tandjambianda, Djerrycharli and Boucher, Simon-Pierre},
++  title = {{Does the Language of Artificial Intelligence Move Markets? A Semantic Analysis of S\&P 500 SEC Filings and the Cross-Section of Stock Returns, 2010--2026}},
++  institution = {Universit\'e du Qu\'ebec en Outaouais, FIRC},
++  type = {UQO Working Paper (version 1.1, S\&P 500)},
++  number = {17},
++  year = {2026},
++  note = {Archived in docs/paper\_v1.1\_sp500\_20261026/ of the replication repository}
++}
++
++% ---- Stage D review additions (FIRC-0002, 2026-11-05): DOIs resolved through doi.org / Crossref by scripts/r3k_21_bib_crossref.py; cite from Stage E ----
++@techreport{hampole2025ai,
++  author = {Hampole, Menaka and Papanikolaou, Dimitris and Schmidt, Lawrence and Seegmiller, Bryan},
++  title = {{Artificial Intelligence and the Labor Market}},
++  year = {2025},
++  doi = {10.3386/w33509},
++  institution = {National Bureau of Economic Research},
++  type = {Working paper},
++  note = {National Bureau of Economic Research, DOI 10.3386/w33509}
++}
++
++@techreport{bloom2021diffusion,
++  author = {Kalyani, Aakash and Bloom, Nicholas and Carvalho, Marcela and Hassan, Tarek Alexander and Lerner, Josh and Tahoun, Ahmed},
++  title = {{The Diffusion of New Technologies}},
++  year = {2021},
++  doi = {10.3386/w28999},
++  institution = {National Bureau of Economic Research},
++  type = {Working paper},
++  note = {National Bureau of Economic Research, DOI 10.3386/w28999}
++}

added results/r3k_v2/bib_additions.json +252 −0

++{
++  "resolved": [
++    {
++      "key": "basu2026aiexposure",
++      "doi": "10.2139/ssrn.7575518",
++      "title": "Firm-level AI Exposure: Measurement, Determinants, and Pricing Implications",
++      "year": 2026,
++      "container": "Elsevier BV",
++      "n_authors": 4,
++      "first_author": "Basu",
++      "anchor": "LITE-01 competitor (SSRN 7575518)",
++      "title_matches_expectation": true
++    },
++    {
++      "key": "borri2026aifactor",
++      "doi": "10.48550/arXiv.2606.30583",
++      "title": "The Cross-Section of Stock Returns and AI Exposure",
++      "year": 2026,
++      "container": "arXiv",
++      "n_authors": 3,
++      "first_author": "Borri",
++      "anchor": "LITE-08 (arXiv 2606.30583)",
++      "title_matches_expectation": true
++    },
++    {
++      "key": "wulam2026genai",
++      "doi": "10.2139/ssrn.7482259",
++      "title": "Do Firms' Stock Prices Respond to AI-related Discussions? Evidence from Earnings Calls",
++      "year": 2026,
++      "container": "Elsevier BV",
++      "n_authors": 1,
++      "first_author": "Institute for Monetary and Financial Research",
++      "anchor": "LITE-08 (SSRN 7482259)",
++      "title_matches_expectation": true
++    },
++    {
++      "key": "eisfeldt2026generative",
++      "doi": "10.1111/jofi.70089",
++      "title": "Generative AI and Firm Values",
++      "year": 2026,
++      "container": "The Journal of Finance",
++      "n_authors": 4,
++      "first_author": "EISFELDT",
++      "anchor": "LITE-02 / EDIT-14: JF 2026 version replacing eisfeldt2023generative",
++      "title_matches_expectation": true
++    },
++    {
++      "key": "song2026productexposure",
++      "doi": "10.2139/ssrn.7527158",
++      "title": "What Firms Sell: Product Exposure to Generative AI *",
++      "year": 2026,
++      "container": "Elsevier BV",
++      "n_authors": 1,
++      "first_author": "Song",
++      "anchor": "LITE-02 (SSRN 7527158)",
++      "title_matches_expectation": true
++    },
++    {
++      "key": "erdogan2026aiwashing",
++      "doi": "10.2139/ssrn.6749213",
++      "title": "SEC Regulatory Intervention and Artificial Intelligence (AI) Washing: Widening the Disclosure Gap Between Transparent and Opaque Firms",
++      "year": 2026,
++      "container": "Elsevier BV",
++      "n_authors": 3,
++      "first_author": "Erdogan",
++      "anchor": "LITE-03 AI washing (SSRN 6749213)",
++      "title_matches_expectation": true
++    },
++    {
++      "key": "wang2026aiwashing",
++      "doi": "10.1016/j.iref.2026.105756",
++      "title": "Talk is cheap, green is hard: The effect of AI-washing on corporate energy transition",
++      "year": 2026,
++      "container": "International Review of Economics &amp; Finance",
++      "n_authors": 4,
++      "first_author": "Wang",
++      "anchor": "LITE-03 AI washing (IREF 2026)",
++      "title_matches_expectation": true
++    },
++    {
++      "key": "celenymarechal2024cyber",
++      "doi": "10.2139/ssrn.4587993",
++      "title": "Cyber risk and the cross-section of stock returns",
++      "year": 2023,
++      "container": "Elsevier BV",
++      "n_authors": 2,
++      "first_author": "Celeny",
++      "anchor": "LITE-05 / LITE-09 (SSRN 4587993)",
++      "title_matches_expectation": true
++    },
++    {
++      "key": "kearney2025cyberchatgpt",
++      "doi": "10.2139/ssrn.5068625",
++      "title": "Cyber Risk, ChatGPT and Firm Value",
++      "year": 2025,
++      "container": "Elsevier BV",
++      "n_authors": 4,
++      "first_author": "Kearney",
++      "anchor": "LITE-05 (SSRN 5068625)",
++      "title_matches_expectation": true
++    },
++    {
++      "key": "hassan2019firmlevel",
++      "doi": "10.1093/qje/qjz021",
++      "title": "Firm-Level Political Risk: Measurement and Effects*",
++      "year": 2019,
++      "container": "The Quarterly Journal of Economics",
++      "n_authors": 4,
++      "first_author": "Hassan",
++      "anchor": "LITE-09 / EDIT-14 (QJE 2019)",
++      "title_matches_expectation": true
++    },
++    {
++      "key": "davis2020exposures",
++      "doi": "10.3386/w27867",
++      "title": "Firm-Level Risk Exposures and Stock Returns in the Wake of COVID-19",
++      "year": 2020,
++      "container": "National Bureau of Economic Research",
++      "n_authors": 3,
++      "first_author": "Davis",
++      "anchor": "LITE-09 (NBER w27867)",
++      "title_matches_expectation": true
++    },
++    {
++      "key": "kim2023llmrisks",
++      "doi": "10.2139/ssrn.4593660",
++      "title": "From Transcripts to Insights: Uncovering Corporate Risks Using Generative AI",
++      "year": 2023,
++      "container": "Elsevier BV",
++      "n_authors": 3,
++      "first_author": "Kim",
++      "anchor": "LITE-09 (SSRN 4593660)",
++      "title_matches_expectation": true
++    },
++    {
++      "key": "cao2023machinelistening",
++      "doi": "10.1093/rfs/hhad021",
++      "title": "How to Talk When a Machine Is Listening: Corporate Disclosure in the Age of AI",
++      "year": 2023,
++      "container": "The Review of Financial Studies",
++      "n_authors": 4,
++      "first_author": "Cao",
++      "anchor": "LITE-09 / EDIT-14 (RFS 2023)",
++      "title_matches_expectation": true
++    },
++    {
++      "key": "honglimstein2000",
++      "doi": "10.1111/0022-1082.00206",
++      "title": "Bad News Travels Slowly: Size, Analyst Coverage, and the Profitability of Momentum Strategies",
++      "year": 2000,
++      "container": "The Journal of Finance",
++      "n_authors": 3,
++      "first_author": "Hong",
++      "anchor": "LITE-07 (JF 2000)",
++      "title_matches_expectation": true
++    },
++    {
++      "key": "yilmazkuday2026chatgpt",
++      "doi": "10.1007/s12197-026-09767-9",
++      "title": "ChatGPT and stock returns",
++      "year": 2026,
++      "container": "Journal of Economics and Finance",
++      "n_authors": 1,
++      "first_author": "Yilmazkuday",
++      "anchor": "LITE-08 (J. Econ. Finance 2026)",
++      "title_matches_expectation": true
++    },
++    {
++      "key": "hampole2025ai",
++      "doi": "10.3386/w33509",
++      "title": "Artificial Intelligence and the Labor Market",
++      "year": 2025,
++      "container": "National Bureau of Economic Research",
++      "n_authors": 4,
++      "first_author": "Hampole",
++      "anchor": "plan L11 (NBER w33509: Hampole, Papanikolaou, Schmidt, Seegmiller)",
++      "title_matches_expectation": true
++    },
++    {
++      "key": "bloom2021diffusion",
++      "doi": "10.3386/w28999",
++      "title": "The Diffusion of New Technologies",
++      "year": 2021,
++      "container": "National Bureau of Economic Research",
++      "n_authors": 6,
++      "first_author": "Kalyani",
++      "anchor": "EDIT-14: Bloom et al. NBER 28999 = The Diffusion of New Technologies (Bloom, Hassan, Kalyani, Lerner, Tahoun), DOI verified",
++      "title_matches_expectation": true
++    }
++  ],
++  "not_added": [
++    {
++      "key": "xia2026aiwashingindex",
++      "anchor": "LITE-03 Xia et al., Systems 2026 (no identifier given)",
++      "reason": "no identifier given by the referee; Crossref candidates listed for the author to confirm (not added)",
++      "candidates": [
++        {
++          "doi": "10.22541/au.177187613.38652471/v1",
++          "title": "Cognitive Integrity Security: Securing Human-AI Interaction in Large Language Model Systems",
++          "year": 2026,
++          "container": "",
++          "score": 33.896973
++        },
++        {
++          "doi": "10.22541/au.177437389.95026495/v1",
++          "title": "Cognitive Integrity Security: Securing Human-AI Interaction in Large Language Model Systems",
++          "year": 2026,
++          "container": "",
++          "score": 33.87944
++        },
++        {
++          "doi": "10.2139/ssrn.6298899",
++          "title": "AI Washing: Strategic Disclosure and Backlash",
++          "year": 2026,
++          "container": "",
++          "score": 33.102043
++        }
++      ]
++    },
++    {
++      "key": "ofir2026aiwashinglaw",
++      "anchor": "LITE-03 Ofir, ABLJ 2026 (no identifier given)",
++      "reason": "no identifier given by the referee; Crossref candidates listed for the author to confirm (not added)",
++      "candidates": [
++        {
++          "doi": "10.1111/ablj.70020",
++          "title": "<scp>AI</scp>\n                    washing",
++          "year": 2026,
++          "container": "American Business Law Journal",
++          "score": 55.419296
++        },
++        {
++          "doi": "10.1111/ablj.70025",
++          "title": "The law of\n                    <scp>AI</scp>\n                    knowledge distillation",
++          "year": 2026,
++          "container": "American Business Law Journal",
++          "score": 31.04866
++        },
++        {
++          "doi": "10.1111/ablj.70024",
++          "title": "Copyright and\n                    <scp>AI</scp>\n                    : The building blocks",
++          "year": 2026,
++          "container": "American Business Law Journal",
++          "score": 29.898045
++        }
++      ]
++    }
++  ],
++  "when": "2026-11-05T15:12:25.813372",
++  "n_entries_appended": 2,
++  "note_eisfeldt": "eisfeldt2023generative is kept (cited in the text); eisfeldt2026generative is the JF version to substitute at Stage E"
++}
+ \ No newline at end of file

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spb/wp17_uqo

FIRC0002-LITE-01/02/03/05/06/07/08/09/10/13 EDIT-14 (L11), ADVE-05 AI_C-04 EDIT-09 ECON-13 THEO-13 AI_C-13 ADVE-16 (L8), EDIT-04 DATA-03 (L6 inputs): DOI-verified bib additions, SPID sampling frame, IWV holdings manifest, FinData price check

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