Disclosure Sentiment: Machine Learning vs. Dictionary Methods

References

• Allee K, DeAngelis M (2015) The structure of voluntary disclosure narratives: Evidence from tone dispersion. J. Accounting Res. 53(2):241–274.Crossref, Google Scholar
• Bajari P, Nekipelov D, Ryan S, Yang M (2015) Machine learning methods for demand estimation. Amer. Econom. Rev. 105(5):481–485.Crossref, Google Scholar
• Ball R, Brown P (1968) An empirical evaluation of accounting income numbers. J. Accounting Res. 6(2):159–178.Crossref, Google Scholar
• Bao Y, Datta A (2014) Simultaneously discovering and quantifying risk types from textual risk disclosures. Management Sci. 60(6):1371–1391.Link, Google Scholar
• Beyer A, Cohen DA, Lys TZ, Walther BR (2010) The financial reporting environment: Review of the recent literature. J. Accounting Econom. 50(2-3):296–343.Crossref, Google Scholar
• Blau BM, DeLisle JR, Price SM (2015) Do sophisticated investors interpret earnings conference call tone differently than investors at large? Evidence from short sales. J. Corporate Finance 31:203–219.Crossref, Google Scholar
• Blei D, McAuliffe J (2007) Supervised topic models. Platt JC, Koller D, Singer Y, Roweis ST, eds. Proc. 20th Internat. Conf. Neural Inform. Processing Systems (Curran Associates, Red Hook, NY), 121–128.Google Scholar
• Blei D, Ng A, Jordan M (2003) Latent Dirichlet allocation. J. Machine Learn. Res. 3:993–1022.Google Scholar
• Bochkay K, Hales J, Chava S (2020) Hyperbole or reality? Investor response to extreme language in earnings conference calls. Accounting Rev. 95(2):31–60.Crossref, Google Scholar
• Bonsall S, Leone A, Miller B, Rennekamp K (2017) A plain English measure of financial reporting readability. J. Accounting Econom. 63(2):329–357.Crossref, Google Scholar
• Botosan C (1997) Disclosure level and the cost of equity capital. Accounting Rev. 72(3):323–349.Google Scholar
• Breiman L (2001) Random forests. Machine Learn. 45:5–32.Crossref, Google Scholar
• Brockman P, Li X, Price SM (2015) Differences in conference call tones: Managers vs. analysts. Financial Anal. J. 71(4):24–42.Crossref, Google Scholar
• Brown S, Tucker J (2011) Large-sample evidence on firms’ year-over-year MD&A modifications. J. Accounting Res. 49(2):309–346.Crossref, Google Scholar
• Brown N, Crowley R, Elliott B (2020) What are you saying? Using topic to detect financial misreporting. J. Accounting Res. 58(1):237–291.Crossref, Google Scholar
• Bryan S (1997) Incremental information content of required disclosures contained in management discussion and analysis. Accounting Rev. 72(2):285–301.Google Scholar
• Callahan C, Smith R (2004) Firm performance and management’s discussion and analysis disclosures: An industry approach. Working paper, University of Louisville, Louisville, KY.Google Scholar
• Campbell J, Chen H, Dhaliwal D, Lu H, Steele L (2014) The information content of mandatory risk factor disclosures in corporate filings. Rev. Accounting Stud. 19:396–455.Crossref, Google Scholar
• Cao S, Jiang W, Yang B, Zhang A (2021) How to talk when a machine is listening: Corporate disclosure in the age of AI. Working paper, Georgia State University, Atlanta.Google Scholar
• Chen J, Demers E, Lev B (2018a) Oh what a beautiful morning! Diurnal influences on executives and analysts: Evidence from conference calls. Management Sci. 64(12):5899–5924.Link, Google Scholar
• Chen JV, Nagar V, Schoenfeld J (2018b) Manager-analyst conversations in earnings conference calls. Rev. Accounting Stud. 23(4):1315–1354.Crossref, Google Scholar
• Core J (2001) A review of the empirical literature. [Discussion] J. Accounting Econom. 31:441–456.Crossref, Google Scholar
• D’Augusta C, DeAngelis MD (2020) Does accounting conservatism discipline qualitative disclosure? Evidence from tone management in the MD&A. Contemporary Accounting Res. 37(4):2287–2318.Crossref, Google Scholar
• Davis AK, Tama‐Sweet I (2012) Managers’ use of language across alternative disclosure outlets: Earnings press releases vs. MD&A. Contemporary Accounting Res. 29(3):804–837.Crossref, Google Scholar
• Davis A, Piger J, Sedor L (2012) Beyond the numbers: Measuring the information content of earnings press release language. Contemporary Accounting Res. 29(3):845–868.Crossref, Google Scholar
• Davis AK, Ge W, Matsumoto D, Zhang JL (2015) The effect of manager-specific optimism on the tone of earnings conference calls. Rev. Accounting Stud. 20(2):639–673.Crossref, Google Scholar
• DeLong JB, Shleifer A, Summers LH, Waldmann RJ (1990) Noise trader risk in financial markets. J. Political Econom. 98(4):703–738.Crossref, Google Scholar
• Donovan J, Koharki K, Jennings J, Lee J (2021) Measuring credit risk using qualitative disclosure. Rev. Accounting Stud. 26:815–863.Crossref, Google Scholar
• Dyer T, Lang M, Stice-Lawrence L (2017) The evolution of 10-K textual disclosure: Evidence from latent Dirichlet allocation. J. Accounting Econom. 64(2-3):221–245.Crossref, Google Scholar
• Feldman R, Govindaraj S, Livnat J, Segal B (2010) Management’s tone change, post earnings announcement drift and accruals. Rev. Accounting Stud. 15(4):915–953.Crossref, Google Scholar
• Frankel R, Jennings J, Lee J (2016) Using unstructured and qualitative disclosures to explain accruals. J. Accounting Econom. 45(2):209–227.Crossref, Google Scholar
• Gentzkow M, Kelly B, Taddy M (2019) Text as data. J. Econom. Literature 57(3):535–574.Crossref, Google Scholar
• Hoberg G, Lewis C (2017) Do fraudulent firms produce abnormal disclosure? J. Corporate Finance 43:58–85.Crossref, Google Scholar
• Hobson J, Mayew B, Venkatachalam M (2012) Analyzing speech to detect financial misreporting. J. Accounting Res. 50(2):349–392.Crossref, Google Scholar
• Hooks K, Moon J (1993) A classification scheme to examine management discussion and analysis compliance. Accounting Horizons 7(2):41–59.Google Scholar
• Huang A, Zang A, Zheng R (2014) Evidence on the information content of text in analyst reports. Accounting Rev. 89(6):2151–2180.Crossref, Google Scholar
• Huang A, Lehavy R, Zang A, Zheng R (2018) Analyst information discovery and interpretation roles: A topic modeling approach. Management Sci. 64(6):2833–2855.Link, Google Scholar
• Jennings JN, Kim JM, Lee JA, Taylor DJ (2021) Measurement error and bias in causal models in accounting research. Preprint, submitted January 8, https://dx.doi.org/10.2139/ssrn.3731197.Google Scholar
• Kothari SP, Li X, Short J (2009) The effect of disclosures by management, analysts, and financial press on the equity cost of capital: A study using content analysis. Accounting Rev. 84(5):1639–1670.Crossref, Google Scholar
• Kravet T, Muslu V (2013) Textual risk disclosures and investors’ risk perceptions. Rev. Accounting Stud. 18:1088–1122.Crossref, Google Scholar
• Law KK, Mills LF (2015) Taxes and financial constraints: Evidence from linguistic cues. J. Accounting Res. 53(4):777–819.Crossref, Google Scholar
• Lang M, Stice-Lawrence L (2015) Textual analysis and international financial reporting: Large sample evidence. J. Accounting Econom. 60:110–135.Crossref, Google Scholar
• Larcker D, Zakolyukina A (2012) Detecting deceptive discussions in conference calls. J. Accounting Res. 50:495–540.Crossref, Google Scholar
• Lehavy R, Li F, Merkley K (2011) The effect of annual report readability on analyst following and the properties of their earnings forecasts. Accounting Rev. 86(3):1087–1115.Crossref, Google Scholar
• Li F (2008) Annual report readability, current earnings, and earnings persistence. J. Accounting Econom. 45:221–247.Crossref, Google Scholar
• Li F (2010) The information content of forward-looking statements in corporate filings–A naïve Bayesian machine learning approach. J. Accounting Res. 48(5):1049–1102.Crossref, Google Scholar
• Li F, Lundholm R, Minnis M (2013) A measure of competition based on 10-K filings. J. Accounting Res. 51(2):399–436.Crossref, Google Scholar
• Li E, Ramesh K (2009) Market reaction surrounding the filing of periodic SEC reports. Accounting Rev. 84(4):1171–1208.Crossref, Google Scholar
• Loughran T, McDonald B (2011) When is a liability not a liability? Textual analysis, dictionaries, and 10-Ks. J. Finance 66(1):35–65.Crossref, Google Scholar
• Loughran T, McDonald B (2014) Measuring readability in financial disclosures. J. Finance 69(4):1643–1671.Crossref, Google Scholar
• Loughran T, McDonald B (2016) Textual analysis in accounting and finance: A survey. J. Accounting Res. 54(4):1187–1230.Google Scholar
• Manela A, Moreira A (2017) News implied volatility and disaster concerns. J. Financial Econom. 123(1):137–162.Crossref, Google Scholar
• Matsumoto D, Pronk M, Roelofsen E (2011) What makes conference calls useful? The information content of managers’ presentations and analysts’ discussion sessions. Accounting Rev. 86(4):1384–1414.Crossref, Google Scholar
• Peterson K, Schmardebeck R, Wilks J (2015) The earnings quality and information processing effects of accounting consistency. Accounting Rev. 90(6):2483–2514.Crossref, Google Scholar
• Price SM, Doran JS, Peterson DR, Bliss BA (2012) Earnings conference calls and stock returns: The incremental informativeness of textual tone. J. Banking Finance 36(4):992–1011.Crossref, Google Scholar
• Rogers J, Van Buskirk A, Zechman S (2011) Disclosure tone and shareholder litigation. Accounting Rev. 86:2155–2183.Crossref, Google Scholar
• Sun Y (2010) Do MD&A disclosures help users interpret disproportionate inventory increases? Accounting Rev. 85(4):1411–1440.Crossref, Google Scholar
• Suslava K (2021) “Stiff business headwinds and uncharted economic waters”: The use of euphemisms in earnings conference calls. Management Sci., ePub ahead of print, https://doi.org/10.1287/mnsc.2020.3826.Link, Google Scholar
• Tetlock PC (2007) Giving content to investor sentiment: The role of media in the stock market. J. Finance 62(3):1139–1168.Crossref, Google Scholar
• Tetlock PC, Saar-Tsechansky M, Macskassy S (2008) More than words: Quantifying language to measure firms’ fundamentals. J. Finance 63(3):1437–1467.Crossref, Google Scholar