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postgraduate thesis: Technical vocabulary in finance : a corpus-based study of annual reports and earnings calls

TitleTechnical vocabulary in finance : a corpus-based study of annual reports and earnings calls
Authors
Issue Date2015
PublisherThe University of Hong Kong (Pokfulam, Hong Kong)
Citation
Ha, Y. [夏映荷]. (2015). Technical vocabulary in finance : a corpus-based study of annual reports and earnings calls. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b5570790
AbstractThe study investigated the technical vocabulary in finance based on a self-built Financial Corpus (FC) of 6,753,212 words of written annual reports and spoken earnings calls collected from 146 world’s largest companies in four financial sectors. Being the most important genres in corporate communication, annual reports and earnings calls provide considerable insights into the technical vocabulary of the financial sectors. The main aims of the study are to show differences among modes especially impromptu speech, examine differences among financial sectors, identify discipline-specific words, and propose a method to assess the technicality of words and categorise technical words. Corpus evidence justified using the word type as the unit of analysis. Results for the impromptu speech from earnings calls, in line with expectations, always fell between those for writing and those for scripted speech and a list of words specific to impromptu speech were identified. Although vocabulary distribution patterns based on reference word lists and other descriptive data do not reveal any striking differences among financial sectors, each sector is characterised by its own financial-sector-specific words. To identify finance-specific words in the FC, keywords analyses were performed using a written academic corpus as a reference corpus. Results show that 1,361 words were specific to finance and they constituted as much as 30.93% of the FC, providing corpus evidence to the notion of disciplinary specificity. Keywords analyses identified 837 financial-sector-specific words out of the finance-specific vocabulary and the majority of which were nouns. According to the degree of technicality, each financial-sector-specific word was then categorised into one of the five groups, namely least technical, slightly technical, moderately technical, very technical, and most technical. Categorisation criteria in the technicality analysis involve the banding of a word in reference word lists and the general sense(s) and specialised sense(s) of a word. Results indicate that a specific word is not necessarily technical, suggesting that specificity and technicality are distinct. Interdisciplinary ties between finance and law were also observed. Adapting the categorisation method for single-word units, the degrees of technicality of 539 selected multi-word units (MWUs) were preliminarily assessed. A MWU was then categorised into least technical MWUs, visible technical MWUs, or synergistic technical MWUs by assessing its senses. The sense exhibited by the MWU as a whole was compared with the sense combined from the literal senses of its constituents. If the two senses differ, a MWU will be deemed a synergistic technical MWU and its degree of technicality of the MWU will be escalated to at least moderately technical accordingly. Findings suggest that the more technical a MWU is, the more sector-specific it tends to be. The construct of synergistic technical MWUs was then further explored by identifying synergistic technical MWUs in another self-built corpus of journal articles in Software. This corpus-based study yielded meaningful findings which show that a principled and systematic method to assess the technicality of single-word units and multiword units can shed light on the understanding of technical vocabulary. The findings have implications for teaching students of finance and accounting subjects.
DegreeDoctor of Philosophy
SubjectCorporation reports
Financial statements
Corpora (Linguistics)
Dept/ProgramApplied English Studies
Persistent Identifierhttp://hdl.handle.net/10722/220001

 

DC FieldValueLanguage
dc.contributor.authorHa, Ying-ho-
dc.contributor.author夏映荷-
dc.date.accessioned2015-10-08T23:12:19Z-
dc.date.available2015-10-08T23:12:19Z-
dc.date.issued2015-
dc.identifier.citationHa, Y. [夏映荷]. (2015). Technical vocabulary in finance : a corpus-based study of annual reports and earnings calls. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b5570790-
dc.identifier.urihttp://hdl.handle.net/10722/220001-
dc.description.abstractThe study investigated the technical vocabulary in finance based on a self-built Financial Corpus (FC) of 6,753,212 words of written annual reports and spoken earnings calls collected from 146 world’s largest companies in four financial sectors. Being the most important genres in corporate communication, annual reports and earnings calls provide considerable insights into the technical vocabulary of the financial sectors. The main aims of the study are to show differences among modes especially impromptu speech, examine differences among financial sectors, identify discipline-specific words, and propose a method to assess the technicality of words and categorise technical words. Corpus evidence justified using the word type as the unit of analysis. Results for the impromptu speech from earnings calls, in line with expectations, always fell between those for writing and those for scripted speech and a list of words specific to impromptu speech were identified. Although vocabulary distribution patterns based on reference word lists and other descriptive data do not reveal any striking differences among financial sectors, each sector is characterised by its own financial-sector-specific words. To identify finance-specific words in the FC, keywords analyses were performed using a written academic corpus as a reference corpus. Results show that 1,361 words were specific to finance and they constituted as much as 30.93% of the FC, providing corpus evidence to the notion of disciplinary specificity. Keywords analyses identified 837 financial-sector-specific words out of the finance-specific vocabulary and the majority of which were nouns. According to the degree of technicality, each financial-sector-specific word was then categorised into one of the five groups, namely least technical, slightly technical, moderately technical, very technical, and most technical. Categorisation criteria in the technicality analysis involve the banding of a word in reference word lists and the general sense(s) and specialised sense(s) of a word. Results indicate that a specific word is not necessarily technical, suggesting that specificity and technicality are distinct. Interdisciplinary ties between finance and law were also observed. Adapting the categorisation method for single-word units, the degrees of technicality of 539 selected multi-word units (MWUs) were preliminarily assessed. A MWU was then categorised into least technical MWUs, visible technical MWUs, or synergistic technical MWUs by assessing its senses. The sense exhibited by the MWU as a whole was compared with the sense combined from the literal senses of its constituents. If the two senses differ, a MWU will be deemed a synergistic technical MWU and its degree of technicality of the MWU will be escalated to at least moderately technical accordingly. Findings suggest that the more technical a MWU is, the more sector-specific it tends to be. The construct of synergistic technical MWUs was then further explored by identifying synergistic technical MWUs in another self-built corpus of journal articles in Software. This corpus-based study yielded meaningful findings which show that a principled and systematic method to assess the technicality of single-word units and multiword units can shed light on the understanding of technical vocabulary. The findings have implications for teaching students of finance and accounting subjects.-
dc.languageeng-
dc.publisherThe University of Hong Kong (Pokfulam, Hong Kong)-
dc.relation.ispartofHKU Theses Online (HKUTO)-
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.rightsThe author retains all proprietary rights, (such as patent rights) and the right to use in future works.-
dc.subject.lcshCorporation reports-
dc.subject.lcshFinancial statements-
dc.subject.lcshCorpora (Linguistics)-
dc.titleTechnical vocabulary in finance : a corpus-based study of annual reports and earnings calls-
dc.typePG_Thesis-
dc.identifier.hkulb5570790-
dc.description.thesisnameDoctor of Philosophy-
dc.description.thesislevelDoctoral-
dc.description.thesisdisciplineApplied English Studies-
dc.description.naturepublished_or_final_version-

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