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20201003_吕漫妮_论文展示1
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1. Preprocessing 2. Model train 1. Other corporate 2. Other disclosures to 3. Se
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Measuring Corporate Culture Using
Machine Learning
Kai Li, Feng Mai, Rui Shen, Xinyan Yan
Review of Financial Studies, 2020.7
吕漫妮
2020.10.3
Contents
• Data, Preprocessing and Parsing, and Learning
Phrases
• Word Embedding, word2vec, and Model Training
• Measuring Corporate Culture Using word2vec
• Validating Our Measure of Corporate Culture
• Implications of Corporate Culture
• Conclusion
2020/10/11
Lv Manni
2
Backgrounds & Motivation
• Corporate culture matters because employees will
inevitably face choices that cannot be properly regulated
ex ante.
• Ample extant literature about culture - performance link
is focus on survey/interview evidence, but has limited
large sample evidence.
• The notion of corporate culture is somewhat nebulous
and thus raises numerous measurement issues in
empirical research.
2020/10/11 3
Lv Manni
Research Problem
• Can we propose a more appropriate approach to measure corporate
culture with large sample evidence?
Ø We propose a semi-supervised machine learning approach to
measuring corporate culture.
• If yes, can we validate some existing findings base on our new
measure?
Ø We show that corporate culture correlates with all aspects of
business outcomes and the culture-performance link is more
pronounced in bad times.
• Can we find out some other evidence about corporate culture?
Ø We show that corporate culture plays an important role in deal
incidence and merger pairing, and corporate culture is shaped by
major corporate events.
2020/10/11 4
Lv Manni
Contribution
• Our paper puts forward a new measure of corporate
culture which is easily applied to a large sample of firms
over time, extending earlier literature on corporate
culture.
• We introduce the word embedding model to quantify
meaning of expressions in finance and accounting text,
provides an effective way to quantify the semantics,
rather than merely the syntactic, at the expression level.
• Our paper is the first to apply neural network language
models to the analysis of qualitative corporate
disclosures.
2020/10/11 5
Lv Manni
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