Environmental, Social and Governance
Machine Learning and Textual analysis
Corporate Innovation
Factor Investing
Corporate innovation
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A song to share with my students
A song shared by Prof. Bruce Grundy to me when I was a PhD student -
Lecture notes
Empirical Methods in Corporate Finance by Todd A. GormleyRegression Discontinuity Design by Caroline Flammer -
Dissertation examples
Cohesiveness of value and quality anomalies by Saieswari Vedula -
Guide and sources
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Meeting arrangements
The first group meeting: Introduction, Resources and ExpectationsTask 1: Identify three key papers and submit through the link by Saturday 26 June
Task 2: Present one key paper in the second group meeting
The second group meeting: Literature ReviewTask: Submit a 3000-word litearture review by Monday 12 July 2021
Individual-based meeting to offer feedbacks on research topicThe third group meeting: Empirical AnalysisIndividual-based meeting: By appointments -
Presentations
Ewart Adams: The ESG-Innovation Disconnect -
Papers
Hsu, Po-Hsuan. 2009. Technological innovations and aggregate risk premiums. Journal of Financial Economics 94, 264-279.Kogan, Leonid, and Dimitris Papanikolaou. 2010. Growth opportunities and technology shocks. American Economic Review 100, 532–536.Cohen, Lauran, Karl Diether, and Christopher Malloy. 2013. Misvaluing innovation. Review of Financial Studies 26, 635–66.Hirshleifer,David, Po-Hsuan Hsu, and Dongmei Li. 2013. Innovative efficiency and stock returns. Journal of Financial Economics 107, 632–54.Kogan, Leonid, Dimitris Papanikolaou, Amit Seru, and Noah Stoffman. 2017. Technological innovation, resource allocation, and growth.” The Quarterly Journal of Economics 132, 665-712.Balsmeier, Benjamin, Lee Fleming, and Gustavo Manso. 2017. Independent boards and innovation.” Journal of Financial Economics 123, 536-557.Hirshleifer,David, Po-Hsuan Hsu, and Dongmei Li. 2018. Innovative originality, profitability, and stock returns. Review of Financial Studies 31, 2553–2605. -
Reseachers on patents
Tristan Fitzgerald from Texas A&MDeepak Hegde from NYU SternSabrina T. Howell from NYU SternPo-Hsuan (Paul) Hsu from NTHUDongmei Li from USCBryan Kelly Yale School of ManagementgmLeonid Kogan MIT SloanTom Nicholas HBSDimitris Papanikolaou Northwestern KelloggAmit Seru Stanford GSBNoah Stoffman from Indiana KelleyJohn Van Reenen from MIT -
Patent data
PATSTAT collection of patent documents worldwide, curated by EPO and OECDEPO bulk data sets, bulk extractions from EPO-internal patent databases made available to external users for further processing. They are structured and standardised collections of data.Match of US Patents to CRSP 1926-2010 by Leonid Kogan, Dimitris Papanikolaou, Amit Seru, and Noah StoffmanMatch of EPO (European Patent Office) patent data to European firm data (including R&D data) by Grid ThomaMatch of Chinese patent data to firm names by Zilin He, Tony Tong, and Yuchen ZhangPatent Information and Databases by Bronwyn H. HallPatents data by Michael Woeppel -
Journal links
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Stata links
Propensity Score Matching by Ani KatchovaInstrumental Variables by Ani KatchovaUseful output command suite: estout
Master dissertation: ESG
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A song to share with my students
A song shared by Prof. Bruce Grundy to me when I was a PhD student -
Lecture materials
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Dissertation examples
Cohesiveness of value and quality anomalies by Saieswari Vedula -
Guide and sources
Climate Finance by Stefano Giglio, Bryan T. Kelly, and Johannes Stroebel. -
Reseachers on ESG
Caroline Flammer Boston UniversityMarcin T. Kacperczyk Imperial CollegePhilipp Krueger Swiss Finance InstitutePedro Matos Virginia DardenZacharias Sautner Frankfurt School of Finance & ManagementLaura T. Starks UTexas Austin -
Meeting arrangements
The first group meeting: Introduction, Resources and ExpectationsTask 1: Identify three key papers and submit through the link by Saturday 26 June
Task 2: Present one key paper in the second group meeting
The second group meeting: Literature ReviewTask: Submit a 3000-word litearture review by Monday 12 July 2021
Individual-based meeting to offer feedbacks on research topicThe third group meeting: Empirical AnalysisIndividual-based meeting: By appointments -
Presentations
Ewart Adams: The ESG-Innovation DisconnectHamza Khan: Do green mutual funds perform wellZhengyan Ou: Corporate green bondsFrida Zhang: Resiliency of Environmental and Social StocksYvonne Zhang : Corporate social responsibility and access to finance -
Data sources
Refinitiv ESG ratings available thourgh Datastream Eikon -
ESG links
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Talks
Which Capitalism? by Luigi Zingales -
Journal links
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Stata links
Propensity Score Matching by Ani KatchovaInstrumental Variables by Ani KatchovaUseful output command suite: estout
Machine Learning
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A song to share with my students
A song shared by Prof. Bruce Grundy to me when I was a PhD student -
Self-learning resources
Natural Language Processing with Dan Jurafsky and Chris ManningNatural Language Processing with Deep Learning with Christopher Manning and Abi SeeText as Data by Matthew Gentzkow, Bryan Kelly and Matt TaddyTextual Analysis in Finance by Tim Loughran and Bill McDonaldText and Context: Language Analytics in Finance by Sanjiv Ranjan Das -
10-K/Q fillings
Li, Feng, 2008. Annual report readability, current earnings, and earnings persistence. Journal of Accounting and Economics 2008, 221-247.Li, Feng, 2010. The Information Content of Forward‐Looking Statements in Corporate Filings—A Naïve Bayesian Machine Learning Approach. Journal of Accounting Research 48,1049-1102Loughran, Tim, Bill McDonald, 2011. When Is a Liability Not a Liability? Textual Analysis, Dictionaries, and 10‐Ks. Journal of Finance 66, 35-65Jegadeesha, Narasimhan, Di Wu, 2013.Word power: A new approach for content analysis. Journal of Financial Economics 110, 712-729.Bao, Yang, Anindya Datta, 2014. Simultaneously Discovering and Quantifying Risk Types from Textual Risk Disclosures Management Science 60, 1371–1391.Bodnaruk, Andriy, Tim Loughran, Bill McDonald, 2015. Using 10-K text to gauge financial constraints. Journal of Financial and Quantitative Analysis 50, 623-646.Dyera, Travis, Mark Langa, LorienStice-Lawrence, 2017. The evolution of 10-K textual disclosure: Evidence from Latent Dirichlet Allocation Journal of Accounting and Economics 64, 221-245.Buehlmaier, Matthias M M, Toni M Whited, 2018. Are Financial Constraints Priced? Evidence from Textual Analysis. Review of Financial Studies 31, 2693–2728.Cohen, Lauren, Christopher Malloy, Quoc Nguyen, 2020. Lazy Prices. Journal of Finance 75, 1371-1415.Frésard, Laurent, Gerard Hoberg, Gordon M Phillips, 2020. Innovation Activities and Integration through Vertical Acquisitions. Review of Financial Studies 33, 2937–2976.Lopez-Liza, Alejandro, 2020. Risk factors that matter: Textual analysis of risk disclosures for the cross-section of returns. Working Paper.Grundy, Bruce, Stefan Petry, 2020. LDA quantification of 10-K risk-factors and the information content of textual reporting. Working Paper.Hoberg, Gerard, Vojislav Maksimovic, 2020. Product life cycles in corporate finance. Working paper.Huang, Allen, Hui Wang, Yi Wang 2021.FinBERT—A Deep Learning Approach to Extracting Textual Information. Working paper. -
8-K fillings
Carter, Mary Ellen, Billy S. Soo, 1999. The relevance of form 8-K reports. Journal of Accounting Research 37, 119-132.Lerman, Alinda, Joshua Livnat, 2010. The new form 8-K disclosures. Review of Accounting Studies 15, 752-778.Bird, Andrew, Stephen A. Karolyi, 2016. Do institutional investors demand public disclosure? Review of Financial Studies 29, 3245-3277.Zhao, Xiaofei, 2017. Does information intensity matter for stock returns? Evidence from form 8-K filings. Management Science 63, 1271-1656.Ben-Rephael, Azi, Zhi Da, Peter D. Easton, Ryan D. Isralsen, 2017. Who pays attention to SEC form 8-K? Working Paper.Cheng, Stephanie, F., Gus De Franco, Haibo Jiang, Pengkai Lin, 2019. Riding the blockchain mania: Public firms’ speculative 8-K disclosures. Management Science 65, 5901-5913.He, Jing, Marlene Plumlee, 2020. Measure disclosure using 8-K fillings. Working paper. -
Conference call
Mayew, William, Mohan Venkatachalam, 2012. Firm-Level Political Risk: Measurement and Effects. Jounrnal of Finance 67,1-43.Lee, Joshua, 2016. Can Investors Detect Managers' Lack of Spontaneity? Adherence to Predetermined Scripts during Earnings Conference Calls. The Accounting Review 91, 229–250.Bushee, Brian J., Ian D. Gow, Daniel J. Taylor, 2019. Linguistic Complexity in Firm Disclosures: Obfuscation or Information? Journal of Accounting Research 56, 85-121.Hassan, Tarek A, Stephan Hollander, Laurence van Lent, Ahmed Tahoun, 2019. Firm-Level Political Risk: Measurement and Effects. Quarterly Journal of Economics 134, 2135–2202.Clifton, Green, T., Russell Jame, Brandon Lock, 2019. Executive Extraversion: Career and Firm Outcomes. The Accounting Review 94(3), 177–204.Li, Qing, Hongyu Shan, Yuehua Tang, Vincent Yao, 2020. Corporate Climate Risk: Measurements and Responses. Working paper. -
IPO prospectuses
Hanley, Kathleen Weiss, Gerard Hoberg, 2010. The Information Content of IPO Prospectuses Review of financial studies 23, 2821-2864.Loughran, Tim, Bill McDonald, 2013. IPO first-day returns, offer price revisions, volatility, and form S-1 language. Journal of Financial Economics 109, 307–326. -
Funds
Abis, Simona, Anton Lines, 2020. Text-Based Mutual Fund Peer Groups. Working paper.Krakow, Jonathan, Timo Schäfer, 2020. Mutual Funds and Risk Disclosure: Information Content of Fund Prospectuses. Working paper.Huang, Alan Guoming, Hongping Tan, Russ Wermers, 2020. Institutional Trading around Corporate News: Evidence from Textual Analysis. Review of Financial Studies 33, 4627–4675. -
Twitter
Blankespoor,Elizabeth, Gregory S. Miller,Hal D. White, 2013. The role of dissemination in market liquidity: Evidence from firms' use of Twitter The Accounting Review 89 (1): 79–112. .Elliott, W. Brooke, Stephanie M. Grant, Frank D. Hodge, 2018. Negative news and investor trust: The role of $Firm and #CEO Twitter use The Accounting Research 56 (5),1483-1519.Cao, Shun Seen, Vivian W.Fang, Lijun(Gillian) Lei, 2020. Negative peer disclosure Journal of Financial Economics forthcoming. -
Machine learning
Bai, Yang, Kuntara Pukthuanthong, 2020. Machine Learning Classification Methods and Portfolio Allocation: An Examination of Market Efficiency. Working paper.Avramov,Doron, Si Cheng, Lior Metzker, 2020. Machine Learning versus Economic Restrictions: Evidence from Stock Return Predictability. Working paper.Hu, Allen, Song Ma, 2020. Persuading Investors: A Video-Based Study. Working paper.Gu, Shihao, Bryan Kelly, Dacheng Xiu, 2020. Empirical Asset Pricing via Machine Learning. Review of Financial Studies 33, 2223–2273.Ke, Tracy Zheng, Bryan Kelly, Dacheng Xiu, 2020. Predicting Returns with Text Data. Working paper.Rossi, Alberto, Stephen Utkus, 2020. Who Benefits from Robo-advising? Evidence from Machine Learning Working paper.Rytchkov, Oleg, Xun Zhong, 2020.Macroeconomic Content of Characteristics-Based Asset Pricing Models: A Machine Learning Analysis. Working paper.van Binsbergen, Jules H., Xiao Han, Alejandro Lopez-Lira, 2020. Man vs. Machine Learning: The Term Structure of Earnings Expectations and Conditional Biases. Working paper.Bandiera, Oriana, Andrea Prat, Stephen Hansen, Raffaella Sadun, 2020. CEO Behavior and Firm Performance. Journal of Political Economy 128 (4),1325-1369.Wu, Wenbo, Jiaqi Chen, Zhibin (Ben) Yang, Michael L. Tindall, 2021. A Cross-Sectional Machine Learning Approach for Hedge Fund Return Prediction and Selection. Management Science forthcoming. -
Video
Blankespoor, Elizabeth, Bradley E. Hendricks, Gregory S. Miller, 2017. Perceptions and Price: Evidence from CEO Presentations at IPO Roadshows. Journal of Accounting Research 55, 275-327.Hu, Allen, Song Ma, 2020. Persuading Investors: A Video-Based Study. Working paper. -
Others
Antweiler, Werner, Murray Z. Frank, 2004. Is all that talk just noise? The Information content of internet stock message boards. Journal of Finance 59, 1259-1294.Das, Sanjiv R., Mike Y. Chen, 2007. Yahoo! for Amazon: Sentiment extraction from small talk on the Web. Management Science 53, 1375-1388.Hoberg, Gerard, Gordon Phillips, 2016. Text-based network industries and endogenous product differentiation. Journal of Political Economy 124, 1423-1465.Kelly, Bryan, Dimitris Papanikolaou, Amit Seru, Matt Taddy, 2020. Measuring Technological Innovation Over the Long Run. American Economic Review, Insights, Forthcoming. -
Online seminars
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Research links
The Economist’s Craft by Michael S. WeisbachWriting Tips for Ph. D. Students by John H. CochraneHow to succeed in Academia by Lasse H. PedersenJob market guide by John CawleySAS for Finance PhDs by André de Souza -
Useful links
Stop wordsBog Index Data for 10-K Filings by Brian P. MillerText-based industry classification by Gerard Hoberg and Gordon PhillipsText similarity by Joshua A. LeeGood libraries for NLPParts of speechTransformersGood overview of these architectures
Transformer Types
Factor Investing
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Lecture materials
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Dissertation examples
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Guide and sources
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Meeting arrangements
The first group meeting: Introduction, Resources and ExpectationsTask 1: Submit three papers by June 28
Task 2: Present a paper on July 5
The second group meeting: Literature ReviewTask: Submit a 3000-word litearture review (the final version) by July 19
Individual-based meeting to offer feedbacks on research topicTask: Submit a three-page research proposal by July 11
The third group meeting: Empirical Analysis on August 16Task: Submit a document as well as codings by August 8
Individual-based meeting: By appointments -
Presentations
Sixiang Zhang: An Augmented q-Factor Model with Expected Growth |SlidesZiyi Xi: Replicating Anomalies|SlidesXiaoyu Zhou: Earnings, retained earnings, and book-to-market in the cross section of expected returns|Slides