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From Words to Value: The Relationship between CEO Letters and Financial Performance

Linder, Jacob LU and Gustafsson, William LU (2024) BUSN79 20241
Department of Business Administration
Abstract
Seminar Date: 2024-05-29

Course: BUSN79 - Degree Project in Accounting and Finance

Authors: William Gustafsson and Jacob Linder

Examiner: Anna Glenngård

Five key words: CEO letters, sentiment analysis, agency theory, firm performance, Tobin's Q.

Purpose: Discern with the help of a new machine learning model whether the sentiment expressed in CEO letters can offer meaningful insights into the firm's performance.

Methodology: The new algorithm FinBERT was used to collect sentiment scores, which were used as the main independent variables in this study. OLS Regressions with fixed effects were used. The dependent variables were ROAt+1, Tobin's Qt+1, ΔROAt+1, and ΔTobin's Qt+1.

Theoretical perspectives: The study draws from... (More)
Seminar Date: 2024-05-29

Course: BUSN79 - Degree Project in Accounting and Finance

Authors: William Gustafsson and Jacob Linder

Examiner: Anna Glenngård

Five key words: CEO letters, sentiment analysis, agency theory, firm performance, Tobin's Q.

Purpose: Discern with the help of a new machine learning model whether the sentiment expressed in CEO letters can offer meaningful insights into the firm's performance.

Methodology: The new algorithm FinBERT was used to collect sentiment scores, which were used as the main independent variables in this study. OLS Regressions with fixed effects were used. The dependent variables were ROAt+1, Tobin's Qt+1, ΔROAt+1, and ΔTobin's Qt+1.

Theoretical perspectives: The study draws from agency theory, information asymmetry, signaling theory, and prospect theory.

Empirical foundation: The study focuses on ten years of data from the FTSE 100, 2013 to 2022. The final sample consists of around 700 observations in the different regressions. Financial firms and companies whose letters were exceedingly long were excluded.

Conclusions: Negative sentiment in the CEO letter appears to negatively affect next year's ROA and Tobin's Q. For ΔROAt+1 and ΔTobin's Qt+1, the Negative score has a positive relationship. (Less)
Please use this url to cite or link to this publication:
author
Linder, Jacob LU and Gustafsson, William LU
supervisor
organization
course
BUSN79 20241
year
type
H1 - Master's Degree (One Year)
subject
keywords
CEO letters, sentiment analysis, agency theory, firm performance, Tobin's Q
language
English
id
9167817
date added to LUP
2024-08-07 16:27:59
date last changed
2024-08-07 16:27:59
@misc{9167817,
  abstract     = {{Seminar Date: 2024-05-29

Course: BUSN79 - Degree Project in Accounting and Finance

Authors: William Gustafsson and Jacob Linder

Examiner: Anna Glenngård

Five key words: CEO letters, sentiment analysis, agency theory, firm performance, Tobin's Q.

Purpose: Discern with the help of a new machine learning model whether the sentiment expressed in CEO letters can offer meaningful insights into the firm's performance.

Methodology: The new algorithm FinBERT was used to collect sentiment scores, which were used as the main independent variables in this study. OLS Regressions with fixed effects were used. The dependent variables were ROAt+1, Tobin's Qt+1, ΔROAt+1, and ΔTobin's Qt+1.

Theoretical perspectives: The study draws from agency theory, information asymmetry, signaling theory, and prospect theory.

Empirical foundation: The study focuses on ten years of data from the FTSE 100, 2013 to 2022. The final sample consists of around 700 observations in the different regressions. Financial firms and companies whose letters were exceedingly long were excluded.

Conclusions: Negative sentiment in the CEO letter appears to negatively affect next year's ROA and Tobin's Q. For ΔROAt+1 and ΔTobin's Qt+1, the Negative score has a positive relationship.}},
  author       = {{Linder, Jacob and Gustafsson, William}},
  language     = {{eng}},
  note         = {{Student Paper}},
  title        = {{From Words to Value: The Relationship between CEO Letters and Financial Performance}},
  year         = {{2024}},
}