Market Reaction to Cyber Strategy Disclosure: Word Embedding Derived Approach

Date
2023-01-03
Authors
Cao, Rui
Kafaee, Özüm
Aziz, Arslan
Cavusoglu, Hasan
Contributor
Advisor
Department
Instructor
Depositor
Speaker
Researcher
Consultant
Interviewer
Annotator
Journal Title
Journal ISSN
Volume Title
Publisher
Volume
Number/Issue
Starting Page
6078
Ending Page
Alternative Title
Abstract
In this study, we use a semi-supervised natural language processing (NLP) methodology to assess cybersecurity strategy of firms based on their 10-K filings. Adapted from the Cybersecurity Framework developed by the National Institute of Standards and Technology (NIST), five distinct cybersecurity strategies, namely identification, protection, detection, response, and recovery, are measured annually. We find evidence that cybersecurity identification strategy is positively and significantly associated with firm market value. For those firms experienced a cyberattack in the past, disclosing cybersecurity protection strategy is not positively assessed by the market. This paper makes contribution to the literature on cybersecurity by identifying the cyber strategies disclosed in 10-K reports using textual analysis, which can be used in future cyber studies. We further show empirical evidence of how market reacts to different strategies, which have valuable implications for industry as to how to better manage cyber risk.
Description
Keywords
Organizational Cybersecurity: Advanced Cyber Defense, Cyber Analytics, and Security Operations, cyberattacks, cybersecurity strategy, disclosure
Citation
Extent
10
Format
Geographic Location
Time Period
Related To
Proceedings of the 56th Hawaii International Conference on System Sciences
Table of Contents
Rights
Attribution-NonCommercial-NoDerivatives 4.0 International
Rights Holder
Local Contexts
Email libraryada-l@lists.hawaii.edu if you need this content in ADA-compliant format.