The Pessimism Factor: SEC EDGAR Form 10-K Textual Analysis and Stock Returns

Chouliaras, Andreas

doi:10.2139/ssrn.2627037

Cited by 7 publications

(5 citation statements)

References 36 publications

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“…During the two recessions (grey bars) that happened in the period from 2000 to 2018, the GDP (upper panel) dropped significantly and the unemployment rate increased (central panel). 19 Correlated with these overall macroeconomic developments, the share of negative words in 10-K reports (lower panel) increased in these periods. In periods of economic recovery (lowering unemployment rates in 2004 to 2008 and in 2010 to 2012), the overall text negativity decreased.…”

Section: Comparing 10-k and 10-q Reportsmentioning

confidence: 91%

“…These reports are imperative to comply with legal and insurance requirements and therefore contain reliable risk evaluations. Prior work has underlined the forward-looking nature of SEC filings, as they allow for an effective prediction of volatility on stock market returns and other financial metrics [17][18][19] .…”

Section: Introductionmentioning

confidence: 99%

“…https://sraf.nd.edu/crsp-flat-file/18 The macroeconomic data has been collected from: https://research.stlouisfed.org/econ/mccracken/ fred-databases/ 19. Recession periods from https://www.nber.org/cycles.html.…”

mentioning

confidence: 99%

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The CoRisk-Index: Measuring economic risks related to COVID-19 in real time

Braesemann

Stephany

Neuhäuser

et al. 2021

Preprint

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The global spread of Covid-19 has caused major economic disruptions. Governments around the world provide considerable financial support to mitigate the economic downturn. However, effective policy responses require reliable data on the economic consequences of the corona pandemic. We propose the CoRisk-Index: a real-time economic indicator of Covid-19 related risk assessments by industry. Using data mining, we analyse all reports from US companies filed since January 2020, representing more than a third of all US employees. We construct two measures - the number of 'corona' words in each report and the average text negativity of the sentences mentioning corona in each industry - that are aggregated in the CoRisk-Index. The index correlates with U.S. unemployment data and preempts stock market losses of February 2020. Moreover, thanks to topic modelling and natural language processing techniques, the CoRisk data provides unique granularity with regards to the particular contexts of the crisis and the concerns of individual industries about them. The data presented here help researchers and decision makers to measure, the previously unobserved, risk awareness of industries with regard to Covid-19, bridging the quantification gap between highly volatile stock market dynamics and long-term macro-economic figures. For immediate access to the data, we provide all findings and raw data on an interactive online dashboard in real time.

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Section: Comparing 10-k and 10-q Reportsmentioning

confidence: 91%

Section: Introductionmentioning

confidence: 99%

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The CoRisk-Index: Measuring economic risks related to COVID-19 in real time

Braesemann

Stephany

Neuhäuser

et al. 2021

Preprint

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“…Loughran and McDonald (2011) develop financeoriented word lists by fine-tuning the Harvard dictionary, and correlate textual analysis variables with 10-Ks filing returns, trading volume, volatility and other characteristics. Chouliaras (2015a) finds that monthly portfolios based on the product of annual pessimism change and the previous period returns generate returns in excess of previous winners/losers. Other studies report evidence of predictive power of stock message boards and major financial columns on volatility, returns and volume (?…”

Section: Textual Analysis Literaturementioning

confidence: 99%

“…To the best of my knowledge, this is the first paper to study the institutional trading behavior along with content analysis performed on corporate annual filings. The previous literature studies the very short term effects of Form 10-K content on stock prices a few days before and after the filing (Loughran and McDonald (2011)), or how previous prices and 10-K textual analysis pessimism affects stock prices in the months after the filing (Chouliaras (2015a)). There exists no previous paper to examine how institutional investing affects (and is affected) by the tone that firms use in their annual reports.…”

Section: Introductionmentioning

confidence: 99%

Institutional Investors, Annual Reports, Textual Analysis and Stock Returns: Evidence from SEC EDGAR 10-K and 13-F Forms

Chouliaras¹

2015

SSRN Journal

Self Cite

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I analyze 18510 SEC EDGAR Form 10-K (annual reports), for NASDAQ, NYSE and AMEX (NYSE MKT) stocks, from 1999 until 2015, along with 176565 SEC EDGAR Form 13-F (quarterly reports of institutional investors holdings). I find that (i) 10-K pessimism negatively affects stock holdings after the filing (ii) institutions do not appear to have forecasting power as to how pessimistic the annual report will be, as they do not adjust their holdings in the pessimistic stocks before the 10-K filing takes place, (iii) an increase in the number of institutional investors that hold a stock leads to an increase in stock prices after the 10-K filing (iv) institutions increase their positions in stocks that had positive returns one (1) to twelve (12) months before the 10-K filing.JEL classification: G10, G14, G23.

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The CoRisk-Index: a data-mining approach to identify industry-specific risk perceptions related to Covid-19

Stephany

Neuhäuser

Stoehr

et al. 2022

Humanit Soc Sci Commun

View full text Add to dashboard Cite

The global spread of Covid-19 has caused major economic disruptions. Governments around the world provide considerable financial support to mitigate the economic downturn. However, effective policy responses require reliable data on the economic consequences of the corona pandemic. We propose the CoRisk-Index: a real-time economic indicator of corporate risk perceptions related to Covid-19. Using data mining, we analyse all reports from US companies filed since January 2020, representing more than a third of the US workforce. We construct two measures—the number of ‘corona’ words in each report and the average text negativity of the sentences mentioning corona in each industry—that are aggregated in the CoRisk-Index. The index correlates with U.S. unemployment rates across industries and with an established market volatility measure, and it preempts stock market losses of February 2020. Moreover, thanks to topic modelling and natural language processing techniques, the CoRisk data provides highly granular data on different dimensions of the crisis and the concerns of individual industries. The index presented here helps researchers and decision makers to measure risk perceptions of industries with regard to Covid-19, bridging the quantification gap between highly volatile stock market dynamics and long-term macroeconomic figures. For immediate access to the data, we provide all findings and raw data on an interactive online dashboard.

show abstract

The Pessimism Factor: SEC EDGAR Form 10-K Textual Analysis and Stock Returns

Cited by 7 publications

References 36 publications

The CoRisk-Index: Measuring economic risks related to COVID-19 in real time

The CoRisk-Index: Measuring economic risks related to COVID-19 in real time

Institutional Investors, Annual Reports, Textual Analysis and Stock Returns: Evidence from SEC EDGAR 10-K and 13-F Forms

The CoRisk-Index: a data-mining approach to identify industry-specific risk perceptions related to Covid-19

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